Hydrologic variables such as evapotranspiration (ET) and soil water storage are difficult to observe across spatial scales in complex terrain. Streamflow and lidar‐derived snow observations provide information about distributed hydrologic processes such as snowmelt, infiltration, and storage. We use a distributed streamflow data set across eight basins in the upper Tuolumne River region of Yosemite National Park in the Sierra Nevada mountain range, and the NASA Airborne Snow Observatory (ASO) lidar‐derived snow data set over 3 years (2013–2015) during a prolonged drought in California, to estimate basin‐scale water balance components. We compare snowmelt and cumulative precipitation over periods from the ASO flight to the end of the water year against cumulative streamflow observations. The basin water balance residual term (snow melt plus precipitation minus streamflow) is calculated for each basin and year. Using soil moisture observations and hydrologic model simulations, we show that the residual term represents short‐term changes in basin water storage over the snowmelt season, but that over the period from peak snow water equivalent (SWE) to the end of summer, it represents cumulative basin‐mean ET. Warm‐season ET estimated from this approach is 168 (85–252 at 95% confidence), 162 (0–326) and 191 (48–334) mm averaged across the basins in 2013, 2014, and 2015, respectively. These values are lower than previous full‐year and point ET estimates in the Sierra Nevada, potentially reflecting reduced ET during drought, the effects of spatial variability, and the part‐year time period. Using streamflow and ASO snow observations, we quantify spatially‐distributed hydrologic processes otherwise difficult to observe.
","language":"English","publisher":"AGU","doi":"10.1002/2017WR020473","usgsCitation":"Henn, B., Painter, T.H., Bormann, K.J., McGurk, B., Flint, A.L., Flint, L.E., White, V., and Lundquist, J., 2018, High‐elevation evapotranspiration estimates during drought: Using streamflow and NASA Airborne Snow Observatory SWE observations to vlose the upper Tuolumne River Basin eater balance: Water Resources Research, v. 54, no. 2, p. 746-766, https://doi.org/10.1002/2017WR020473.","productDescription":"21 p.","startPage":"746","endPage":"766","ipdsId":"IP-083705","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":469044,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017wr020473","text":"Publisher Index Page"},{"id":357979,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Tuolumne River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120,\n 37.5\n ],\n [\n -119,\n 37.5\n ],\n [\n -119,\n 38.25\n ],\n [\n -120,\n 38.25\n ],\n [\n -120,\n 37.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"54","issue":"2","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-03","publicationStatus":"PW","scienceBaseUri":"5bc03033e4b0fc368eb539dc","contributors":{"authors":[{"text":"Henn, Brian","contributorId":139777,"corporation":false,"usgs":false,"family":"Henn","given":"Brian","email":"","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":746954,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Painter, Thomas H.","contributorId":12378,"corporation":false,"usgs":true,"family":"Painter","given":"Thomas","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":746955,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bormann, Kathryn J.","contributorId":208401,"corporation":false,"usgs":false,"family":"Bormann","given":"Kathryn","email":"","middleInitial":"J.","affiliations":[{"id":37796,"text":"Jet Propulsion Laboratory, California Institute of Technology, Pasadena","active":true,"usgs":false}],"preferred":false,"id":746960,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McGurk, Bruce","contributorId":74457,"corporation":false,"usgs":true,"family":"McGurk","given":"Bruce","affiliations":[],"preferred":false,"id":746956,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Flint, Alan L. 0000-0002-5118-751X aflint@usgs.gov","orcid":"https://orcid.org/0000-0002-5118-751X","contributorId":1492,"corporation":false,"usgs":true,"family":"Flint","given":"Alan","email":"aflint@usgs.gov","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":746953,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Flint, Lorraine E. 0000-0002-7868-441X lflint@usgs.gov","orcid":"https://orcid.org/0000-0002-7868-441X","contributorId":1184,"corporation":false,"usgs":true,"family":"Flint","given":"Lorraine","email":"lflint@usgs.gov","middleInitial":"E.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":746957,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"White, Vince","contributorId":208399,"corporation":false,"usgs":false,"family":"White","given":"Vince","email":"","affiliations":[{"id":37795,"text":"Southern California Edison","active":true,"usgs":false}],"preferred":false,"id":746958,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lundquist, Jessica D.","contributorId":12792,"corporation":false,"usgs":true,"family":"Lundquist","given":"Jessica D.","affiliations":[],"preferred":false,"id":746959,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70202267,"text":"70202267 - 2018 - Wind River Subbasin Restoration, Annual report of U.S. Geological Survey activities, January 2016 through December 2016","interactions":[],"lastModifiedDate":"2019-02-20T11:24:57","indexId":"70202267","displayToPublicDate":"2018-02-01T11:24:50","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"title":"Wind River Subbasin Restoration, Annual report of U.S. Geological Survey activities, January 2016 through December 2016","docAbstract":"We used Passive Integrated Transponder (PIT)-tagging and a series of instream PIT-tag interrogation systems (PTISs) to investigate life-histories, populations, and efficacy of habitat restoration actions for steelhead Oncorhynchus mykiss in the Wind River subbasin, WA. Our tagging focused on parr in headwaters areas of the subbasin and our instream readers provided information on movement of these parr and other life-stages of tagged steelhead. The Wind River subbasin in southwest Washington State provides habitat for a population of wild Lower Columbia River steelhead and is an excellent watershed for long-term studies of population dynamics and responses to restoration of this wild population. No hatchery steelhead have been planted in the Wind River subbasin since 1994, and hatchery adults are estimated to be less than one percent of adults in any year (pers comm. Thomas Buehrens, Washington Department of Fish and Wildlife). Numerous restoration actions have been implemented in the subbasin, including the removal of Hemlock Dam on Trout Creek in 2009. Data from our study, and companion work by Washington Department of Fish and Wildlife (WDFW), will contribute to Bonneville Power Administration’s (BPA) Research Monitoring and Evaluation (RM&E) Program Strategy of Fish Population Status Monitoring (www.cbfish.org/ProgramStrategy.mvc/ViewProgramStrategySummary/1), specifically the substrategies of: 1) Assessing the Status and Trends of Diversity of Natural Origin Fish Populations and to Uncertainties Research regarding differing life histories of a wild steelhead population, 2) Assessing the Status and Trend of Adult Natural Origin Fish Populations, and 3) Monitoring and Evaluating the Effectiveness of Tributary Habitat Actions Relative to Environmental, Physical, or Biological Performance Objectives.
During summer 2016, we sampled and PIT-tagged age-0 and age-1 steelhead parr in headwater areas of the Wind River subbasin to characterize population traits and investigate variable life-histories, including growth and parr movement downstream prior to smolting. Repeat sampling and smolt traps provide opportunities for recapture, and instream PTISs and Columbia River infrastructure provide opportunity for detection of PIT-tagged fish.
Throughout the year, we maintained a series of instream PTISs to monitor movement of tagged steelhead parr, smolts, and adults. During 2016, we repaired or replaced much of our instream PTIS infrastructure that had been damaged or destroyed during a large flood event in December 2015. This included moving our upper Wind River detection site (WRU) about a kilometer downstream to a location we hope to be less susceptible to damage in high flows and that will allow grid power connection for more reliable winter operations.
Detections at the instream PTISs showed trends of parr emigration during summer and fall, in addition to the expected movement of parr and smolts in spring. These data are increasing our understanding of varied life histories of juvenile steelhead; paired with other steelhead population work in the subbasin we hope to begin to understand some of the factors which may influence parr movements. Long-term monitoring of PIT-tagged fish over multiple years is providing information on contribution of various life-history strategies to smolt production and adult returns, as well as helping to identify factors influencing parr movement.
Movements of PIT-tagged adult steelhead were also tracked with our instream PTISs. These data have provided information on timing of adult movements to various parts of the watershed, which is allowing us to assess adult returns to tributary watersheds within the Wind River subbasin. Determination of adult use of tributary watersheds is providing data to contribute to evaluation of the efficacy of the removal of Hemlock Dam on Trout Creek. Hemlock Dam, located at rkm 2.0 of Trout Creek was removed in summer 2009 and had contributed to hydrologic impairment of Trout Creek
Evaluating restoration efforts is of interest to many managers and agencies so that funding and time are allocated for best results. The evaluation of various life-histories of Lower Columbia River steelhead within the Wind River subbasin will provide information to better track populations, and to direct habitat restoration and water allocation planning. Increasingly detailed Viable Salmonid Population information, such as that provided by PIT-tagging and instream PTISs networks like those we are building and operating in the Wind River subbasin, will provide data to inform policy and management, as life-history strategies and production bottlenecks are identified and understood.
","language":"English","publisher":"Bonneville Power Administration","usgsCitation":"Jezorek, I.G., and Connolly, P., 2018, Wind River Subbasin Restoration, Annual report of U.S. Geological Survey activities, January 2016 through December 2016, 54 p.","productDescription":"54 p.","ipdsId":"IP-093844","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":361385,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":361346,"type":{"id":15,"text":"Index Page"},"url":"https://www.cbfish.org/Document.mvc/DocumentViewer/P161233/77688-1.pdf"}],"publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Jezorek, Ian G. 0000-0002-3842-3485 ijezorek@usgs.gov","orcid":"https://orcid.org/0000-0002-3842-3485","contributorId":3572,"corporation":false,"usgs":true,"family":"Jezorek","given":"Ian","email":"ijezorek@usgs.gov","middleInitial":"G.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":757561,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Connolly, Patrick J. 0000-0001-7365-7618 pconnolly@usgs.gov","orcid":"https://orcid.org/0000-0001-7365-7618","contributorId":2920,"corporation":false,"usgs":true,"family":"Connolly","given":"Patrick J.","email":"pconnolly@usgs.gov","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":757562,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70195193,"text":"70195193 - 2018 - The suitability of using dissolved gases to determine groundwater discharge to high gradient streams","interactions":[],"lastModifiedDate":"2018-02-07T13:08:28","indexId":"70195193","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"The suitability of using dissolved gases to determine groundwater discharge to high gradient streams","docAbstract":"Determining groundwater discharge to streams using dissolved gases is known to be useful over a wide range of streamflow rates but the suitability of dissolved gas methods to determine discharge rates in high gradient mountain streams has not been sufficiently tested, even though headwater streams are critical as ecological habitats and water resources. The aim of this study is to test the suitability of using dissolved gases to determine groundwater discharge rates to high gradient streams by field experiments in a well-characterized, high gradient mountain stream and a literature review. At a reach scale (550 m) we combined stream and groundwater radon activity measurements with an in-stream SF6 tracer test. By means of numerical modeling we determined gas exchange velocities and derived very low groundwater discharge rates (∼15% of streamflow). These groundwater discharge rates are below the uncertainty range of physical streamflow measurements and consistent with temperature, specific conductance and streamflow measured at multiple locations along the reach. At a watershed-scale (4 km), we measured CFC-12 and δ18O concentrations and determined gas exchange velocities and groundwater discharge rates with the same numerical model. The groundwater discharge rates along the 4 km stream reach were highly variable, but were consistent with the values derived in the detailed study reach. Additionally, we synthesized literature values of gas exchange velocities for different stream gradients which show an empirical relationship that will be valuable in planning future dissolved gas studies on streams with various gradients. In sum, we show that multiple dissolved gas tracers can be used to determine groundwater discharge to high gradient mountain streams from reach to watershed scales.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2017.12.022","usgsCitation":"Gleeson, T., Manning, A.H., Popp, A., Zane, M., and Clark, J.F., 2018, The suitability of using dissolved gases to determine groundwater discharge to high gradient streams: Journal of Hydrology, v. 557, p. 561-572, https://doi.org/10.1016/j.jhydrol.2017.12.022.","productDescription":"12 p.","startPage":"561","endPage":"572","ipdsId":"IP-071701","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":469056,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://escholarship.org/uc/item/82x8s2wg","text":"External Repository"},{"id":351246,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.3167,\n 39.4\n ],\n [\n -120.2167,\n 39.4\n ],\n [\n -120.2167,\n 39.4667\n ],\n [\n -120.3167,\n 39.4667\n ],\n [\n -120.3167,\n 39.4\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"557","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a7c1e73e4b00f54eb2292dc","contributors":{"authors":[{"text":"Gleeson, Tom","contributorId":42694,"corporation":false,"usgs":false,"family":"Gleeson","given":"Tom","affiliations":[{"id":6646,"text":"McGill University","active":true,"usgs":false}],"preferred":false,"id":727373,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Manning, Andrew H. 0000-0002-6404-1237 amanning@usgs.gov","orcid":"https://orcid.org/0000-0002-6404-1237","contributorId":1305,"corporation":false,"usgs":true,"family":"Manning","given":"Andrew","email":"amanning@usgs.gov","middleInitial":"H.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":727372,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Popp, Andrea","contributorId":202011,"corporation":false,"usgs":false,"family":"Popp","given":"Andrea","email":"","affiliations":[{"id":35133,"text":"University of Freiburg, Freiburg, Germany","active":true,"usgs":false}],"preferred":false,"id":727374,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zane, Mathew","contributorId":202012,"corporation":false,"usgs":false,"family":"Zane","given":"Mathew","email":"","affiliations":[{"id":36321,"text":"Department of Geological Sciences, University of California, Santa Barbara, California","active":true,"usgs":false}],"preferred":false,"id":727375,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Clark, Jordan F.","contributorId":202013,"corporation":false,"usgs":false,"family":"Clark","given":"Jordan","email":"","middleInitial":"F.","affiliations":[{"id":36321,"text":"Department of Geological Sciences, University of California, Santa Barbara, California","active":true,"usgs":false}],"preferred":false,"id":727376,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70196466,"text":"70196466 - 2018 - Groundwater connectivity of upland-embedded wetlands in the Prairie Pothole Region","interactions":[],"lastModifiedDate":"2018-04-10T10:41:52","indexId":"70196466","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","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":"Groundwater connectivity of upland-embedded wetlands in the Prairie Pothole Region","docAbstract":"Groundwater connections from upland-embedded wetlands to downstream waterbodies remain poorly understood. In principle, water from upland-embedded wetlands situated high in a landscape should flow via groundwater to waterbodies situated lower in the landscape. However, the degree of groundwater connectivity varies across systems due to factors such as geologic setting, hydrologic conditions, and topography. We use numerical models to evaluate the conditions suitable for groundwater connectivity between upland-embedded wetlands and downstream waterbodies in the prairie pothole region of North Dakota (USA). Results show groundwater connectivity between upland-embedded wetlands and other waterbodies is restricted when these wetlands are surrounded by a mounding water table. However, connectivity exists among adjacent upland-embedded wetlands where water–table mounds do not form. In addition, the presence of sand layers greatly facilitates groundwater connectivity of upland-embedded wetlands. Anisotropy can facilitate connectivity via groundwater flow, but only if it becomes unrealistically large. These findings help consolidate previously divergent views on the significance of local and regional groundwater flow in the prairie pothole region.
","language":"English","publisher":"Springer","doi":"10.1007/s13157-017-0956-7","usgsCitation":"Neff, B., and Rosenberry, D.O., 2018, Groundwater connectivity of upland-embedded wetlands in the Prairie Pothole Region: Wetlands, v. 38, no. 1, p. 51-63, https://doi.org/10.1007/s13157-017-0956-7.","productDescription":"13 p.","startPage":"51","endPage":"63","ipdsId":"IP-080137","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":353281,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Dakota","volume":"38","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-10-07","publicationStatus":"PW","scienceBaseUri":"5afee741e4b0da30c1bfc1e1","contributors":{"authors":[{"text":"Neff, Brian 0000-0003-3718-7350 bneff@usgs.gov","orcid":"https://orcid.org/0000-0003-3718-7350","contributorId":198885,"corporation":false,"usgs":true,"family":"Neff","given":"Brian","email":"bneff@usgs.gov","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":733016,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rosenberry, Donald O. 0000-0003-0681-5641 rosenber@usgs.gov","orcid":"https://orcid.org/0000-0003-0681-5641","contributorId":1312,"corporation":false,"usgs":true,"family":"Rosenberry","given":"Donald","email":"rosenber@usgs.gov","middleInitial":"O.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":733017,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70194959,"text":"70194959 - 2018 - How could a freshwater swamp produce a chemical signature characteristic of a saltmarsh?","interactions":[],"lastModifiedDate":"2025-05-13T16:25:12.462135","indexId":"70194959","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5615,"text":"ACS Earth and Space Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"How could a freshwater swamp produce a chemical signature characteristic of a saltmarsh?","docAbstract":"Reduction–oxidation (redox) reaction conditions, which are of great importance for the soil chemistry of coastal marshes, can be temporally dynamic. We present a transect of cores from northwest Florida wherein radical postdepositional changes in the redox regime has created atypical geochemical profiles at the bottom of the sedimentary column. The stratigraphy is consistent along the transect, consisting of, from the bottom upward, carbonate bedrock, a gray clay, an organic mud section, a dense clay layer, and an upper organic mud unit representing the current saltwater marsh. However, the geochemical signature of the lower organic mud unit suggests pervasive redox reactions, although the interval has been identified as representing a freshwater marsh, an unlikely environment for such conditions. Analyses indicate that this discrepancy results from postdepositional diagenesis driven by millennial-scale environmental parameters. Rising sea level that led to the deposition of the capping clay layer, created anaerobic conditions in the freshwater swamp interval, and isolated it hydrologically from the rest of the sediment column. The subsequent infiltration of marine water into this organic material led to sulfate reduction, the buildup of H2S and FeS, and anoxic conditions. Continued sulfidation eventually resulted in euxinic conditions, as evidenced by elevated levels of Fe, S, and especially Mo, the diagnostic marker of euxinia. Because this chemical transformation occurred long after the original deposition the geochemical signature does not reflect soil chemistry at the time of deposition and cannot be used to infer syn-depositional environmental conditions, emphasizing the importance of recognizing diagenetic processes in paleoenvironmental studies.
","language":"English","publisher":"ACS","doi":"10.1021/acsearthspacechem.7b00098","usgsCitation":"McCloskey, T.A., Smith, C.G., Liu, K., Marot, M.E., and Haller, C., 2018, How could a freshwater swamp produce a chemical signature characteristic of a saltmarsh?: ACS Earth and Space Chemistry, v. 2, no. 1, p. 9-20, https://doi.org/10.1021/acsearthspacechem.7b00098.","productDescription":"12 p.","startPage":"9","endPage":"20","ipdsId":"IP-092624","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":350892,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.78,\n 29.19\n ],\n [\n -82.87,\n 29.19\n ],\n [\n -82.87,\n 29.14\n ],\n [\n -82.78,\n 29.14\n ],\n [\n -82.78,\n 29.19\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"2","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-12-11","publicationStatus":"PW","scienceBaseUri":"5a743582e4b0a9a2e9e25c90","contributors":{"authors":[{"text":"McCloskey, Terrence A. 0000-0003-3979-3821 tmccloskey@usgs.gov","orcid":"https://orcid.org/0000-0003-3979-3821","contributorId":200684,"corporation":false,"usgs":true,"family":"McCloskey","given":"Terrence","email":"tmccloskey@usgs.gov","middleInitial":"A.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":726296,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":726297,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Liu, Kam-biu","contributorId":201527,"corporation":false,"usgs":false,"family":"Liu","given":"Kam-biu","affiliations":[{"id":13050,"text":"Department of Oceanography and Coastal Sciences, Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":726298,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Marot, Marci E. 0000-0003-0504-315X mmarot@usgs.gov","orcid":"https://orcid.org/0000-0003-0504-315X","contributorId":2078,"corporation":false,"usgs":true,"family":"Marot","given":"Marci","email":"mmarot@usgs.gov","middleInitial":"E.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":726299,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Haller, Christian","contributorId":200685,"corporation":false,"usgs":false,"family":"Haller","given":"Christian","affiliations":[],"preferred":false,"id":726300,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70196503,"text":"70196503 - 2018 - Comparison of the chemical composition of dissolved organic matter in three lakes in Minnesota","interactions":[],"lastModifiedDate":"2018-04-13T11:10:39","indexId":"70196503","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"Comparison of the chemical composition of dissolved organic matter in three lakes in Minnesota","docAbstract":"New information on the chemical composition of dissolved organic matter (DOM) in three lakes in Minnesota has been gained from spectral editing and two-dimensional nuclear magnetic resonance (NMR) methods, indicating the effects of lake hydrological settings on DOM composition. Williams Lake (WL), Shingobee Lake (SL), and Manganika Lake (ML) had different source inputs, and the lake water residence time (WRT) of WL was markedly longer than that of SL and ML. The hydrophobic organic acid (HPOA) and transphilic organic acid (TPIA) fractions combined comprised >50% of total DOM in these lakes, and contained carboxyl-rich alicyclic molecules (CRAM), aromatics, carbohydrates, and N-containing compounds. The previously understudied TPIA fractions contained fewer aromatics, more oxygen-rich CRAM, and more N-containing compounds compared to the corresponding HPOA. CRAM represented the predominant component in DOM from all lakes studied, and more so in WL than in SL and ML. Aromatics including lignin residues and phenols decreased in relative abundances from ML to SL and WL. Carbohydrates and N-containing compounds were minor components in both HPOA and TPIA and did not show large variations among the three lakes. The increased relative abundances of CRAM in DOM from ML, SL to WL suggested the selective preservation of CRAM with increased residence time.
","language":"English","publisher":"ACS","doi":"10.1021/acs.est.7b04076","usgsCitation":"Cao, X., Aiken, G.R., Butler, K.D., Mao, J., and Schmidt-Rohr, K., 2018, Comparison of the chemical composition of dissolved organic matter in three lakes in Minnesota: Environmental Science & Technology, v. 52, no. 4, p. 1747-1755, https://doi.org/10.1021/acs.est.7b04076.","productDescription":"9 p.","startPage":"1747","endPage":"1755","ipdsId":"IP-090645","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":438033,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F77M06VP","text":"USGS data release","linkHelpText":"Organic Carbon Data in Water Samples from Minnesota Lakes, 2012 to 2013"},{"id":353407,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","volume":"52","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-07","publicationStatus":"PW","scienceBaseUri":"5afee740e4b0da30c1bfc1db","contributors":{"authors":[{"text":"Cao, Xiaoyan","contributorId":204169,"corporation":false,"usgs":false,"family":"Cao","given":"Xiaoyan","email":"","affiliations":[{"id":36869,"text":"Old Dominion University; Brandeis University","active":true,"usgs":false}],"preferred":false,"id":733289,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aiken, George R. 0000-0001-8454-0984 graiken@usgs.gov","orcid":"https://orcid.org/0000-0001-8454-0984","contributorId":1322,"corporation":false,"usgs":true,"family":"Aiken","given":"George","email":"graiken@usgs.gov","middleInitial":"R.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":733290,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Butler, Kenna D. 0000-0001-9604-4603 kebutler@usgs.gov","orcid":"https://orcid.org/0000-0001-9604-4603","contributorId":178885,"corporation":false,"usgs":true,"family":"Butler","given":"Kenna","email":"kebutler@usgs.gov","middleInitial":"D.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":733288,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mao, Jingdong","contributorId":204171,"corporation":false,"usgs":false,"family":"Mao","given":"Jingdong","email":"","affiliations":[{"id":36518,"text":"Old Dominion University","active":true,"usgs":false}],"preferred":false,"id":733291,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schmidt-Rohr, Klaus","contributorId":173865,"corporation":false,"usgs":false,"family":"Schmidt-Rohr","given":"Klaus","email":"","affiliations":[{"id":27307,"text":"Dept. of Chemistry, Brandeis University, Waltham, MA","active":true,"usgs":false}],"preferred":false,"id":733292,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70194989,"text":"70194989 - 2018 - Comparative analyses of hydrological responses of two adjacent watersheds to climate variability and change using the SWAT model","interactions":[],"lastModifiedDate":"2018-02-02T10:29:37","indexId":"70194989","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","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":"Comparative analyses of hydrological responses of two adjacent watersheds to climate variability and change using the SWAT model","docAbstract":"Water quality problems in the Chesapeake Bay Watershed (CBW) are expected to be exacerbated by climate variability and change. However, climate impacts on agricultural lands and resultant nutrient loads into surface water resources are largely unknown. This study evaluated the impacts of climate variability and change on two adjacent watersheds in the Coastal Plain of the CBW, using the Soil and Water Assessment Tool (SWAT) model. We prepared six climate sensitivity scenarios to assess the individual impacts of variations in CO2concentration (590 and 850 ppm), precipitation increase (11 and 21 %), and temperature increase (2.9 and 5.0 °C), based on regional general circulation model (GCM) projections. Further, we considered the ensemble of five GCM projections (2085–2098) under the Representative Concentration Pathway (RCP) 8.5 scenario to evaluate simultaneous changes in CO2, precipitation, and temperature. Using SWAT model simulations from 2001 to 2014 as a baseline scenario, predicted hydrologic outputs (water and nitrate budgets) and crop growth were analyzed. Compared to the baseline scenario, a precipitation increase of 21 % and elevated CO2 concentration of 850 ppm significantly increased streamflow and nitrate loads by 50 and 52 %, respectively, while a temperature increase of 5.0 °C reduced streamflow and nitrate loads by 12 and 13 %, respectively. Crop biomass increased with elevated CO2 concentrations due to enhanced radiation- and water-use efficiency, while it decreased with precipitation and temperature increases. Over the GCM ensemble mean, annual streamflow and nitrate loads showed an increase of ∼ 70 % relative to the baseline scenario, due to elevated CO2 concentrations and precipitation increase. Different hydrological responses to climate change were observed from the two watersheds, due to contrasting land use and soil characteristics. The watershed with a larger percent of croplands demonstrated a greater increased rate of 5.2 kg N ha−1 in nitrate yield relative to the watershed with a lower percent of croplands as a result of increased export of nitrate derived from fertilizer. The watershed dominated by poorly drained soils showed increased nitrate removal due do enhanced denitrification compared to the watershed dominated by well-drained soils. Our findings suggest that increased implementation of conservation practices would be necessary for this region to mitigate increased nitrate loads associated with predicted changes in future climate.
","language":"English","publisher":"European Geosciences Union","doi":"10.5194/hess-22-689-2018","usgsCitation":"Lee, S., Yeo, I., Sadeghi, A.M., McCarty, G.W., Hively, W., Lang, M.W., and Sharifi, A., 2018, Comparative analyses of hydrological responses of two adjacent watersheds to climate variability and change using the SWAT model: Hydrology and Earth System Sciences, v. 22, p. 689-708, https://doi.org/10.5194/hess-22-689-2018.","productDescription":"10 p.","startPage":"689","endPage":"708","ipdsId":"IP-090233","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"links":[{"id":469071,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/hess-22-689-2018","text":"Publisher Index Page"},{"id":350956,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Greensboro Watershed, Tuckahoe Creek Watershed","volume":"22","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-25","publicationStatus":"PW","scienceBaseUri":"5a7586d6e4b00f54eb1d81d4","contributors":{"authors":[{"text":"Lee, Sangchul","contributorId":201237,"corporation":false,"usgs":false,"family":"Lee","given":"Sangchul","email":"","affiliations":[],"preferred":false,"id":726400,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yeo, In-Young","contributorId":131145,"corporation":false,"usgs":false,"family":"Yeo","given":"In-Young","email":"","affiliations":[{"id":7261,"text":"Department of Geographical Sciences, University of Maryland, College Park, MD, 20742","active":true,"usgs":false}],"preferred":false,"id":726402,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sadeghi, Ali M.","contributorId":131147,"corporation":false,"usgs":false,"family":"Sadeghi","given":"Ali","email":"","middleInitial":"M.","affiliations":[{"id":7262,"text":"USDA-ARS, Hydrology and Remote Sensing Laboratory, Beltsville, MD 20705","active":true,"usgs":false}],"preferred":false,"id":726401,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McCarty, Gregory W.","contributorId":192367,"corporation":false,"usgs":false,"family":"McCarty","given":"Gregory","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":726403,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hively, Wells whively@usgs.gov","contributorId":201563,"corporation":false,"usgs":true,"family":"Hively","given":"Wells","email":"whively@usgs.gov","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":726399,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lang, Megan W.","contributorId":196284,"corporation":false,"usgs":false,"family":"Lang","given":"Megan","email":"","middleInitial":"W.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":726404,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sharifi, Amir","contributorId":201564,"corporation":false,"usgs":false,"family":"Sharifi","given":"Amir","email":"","affiliations":[{"id":18168,"text":"USDA ARS","active":true,"usgs":false}],"preferred":false,"id":726405,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70196845,"text":"70196845 - 2018 - Estimating wetland connectivity to streams in the Prairie Pothole Region: An isotopic and remote sensing approach","interactions":[],"lastModifiedDate":"2018-05-04T10:36:11","indexId":"70196845","displayToPublicDate":"2018-02-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Estimating wetland connectivity to streams in the Prairie Pothole Region: An isotopic and remote sensing approach","docAbstract":"Understanding hydrologic connectivity between wetlands and perennial streams is critical to understanding the reliance of stream flow on inputs from wetlands. We used the isotopic evaporation signal in water and remote sensing to examine wetland‐stream hydrologic connectivity within the Pipestem Creek watershed, North Dakota, a watershed dominated by prairie‐pothole wetlands. Pipestem Creek exhibited an evaporated‐water signal that had approximately half the isotopic‐enrichment signal found in most evaporatively enriched prairie‐pothole wetlands. Groundwater adjacent to Pipestem Creek had isotopic values that indicated recharge from winter precipitation and had no significant evaporative enrichment, indicating that enriched surface water did not contribute significantly to groundwater discharging into Pipestem Creek. The estimated surface water area necessary to generate the evaporation signal within Pipestem Creek was highly dynamic, varied primarily with the amount of discharge, and was typically greater than the immediate Pipestem Creek surface water area, indicating that surficial flow from wetlands contributed to stream flow throughout the summer. We propose a dynamic range of spilling thresholds for prairie‐pothole wetlands across the watershed allowing for wetland inputs even during low‐flow periods. Combining Landsat estimates with the isotopic approach allowed determination of potential (Landsat) and actual (isotope) contributing areas in wetland‐dominated systems. This combined approach can give insights into the changes in location and magnitude of surface water and groundwater pathways over time. This approach can be used in other areas where evaporation from wetlands results in a sufficient evaporative isotopic signal.
","language":"English","publisher":"AGU","doi":"10.1002/2017WR021016","usgsCitation":"Brooks, J.R., Mushet, D.M., Vanderhoof, M.K., Leibowitz, S.G., Christensen, J.R., Neff, B., Rosenberry, D.O., Rugh, W.D., and Alexander, L., 2018, Estimating wetland connectivity to streams in the Prairie Pothole Region: An isotopic and remote sensing approach: Water Resources Research, v. 54, no. 2, p. 955-977, https://doi.org/10.1002/2017WR021016.","productDescription":"23 p.","startPage":"955","endPage":"977","ipdsId":"IP-086197","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":469082,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/5903587","text":"Publisher Index Page"},{"id":353957,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Dakota","volume":"54","issue":"2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-09","publicationStatus":"PW","scienceBaseUri":"5afee740e4b0da30c1bfc1cb","contributors":{"authors":[{"text":"Brooks, J. R.","contributorId":204685,"corporation":false,"usgs":false,"family":"Brooks","given":"J.","email":"","middleInitial":"R.","affiliations":[{"id":36973,"text":"U.S. EPA, National Health and Environmental Effects Res Lab, Western Ecology Division, Corvallis, OR","active":true,"usgs":false}],"preferred":false,"id":734681,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mushet, David M. 0000-0002-5910-2744 dmushet@usgs.gov","orcid":"https://orcid.org/0000-0002-5910-2744","contributorId":1299,"corporation":false,"usgs":true,"family":"Mushet","given":"David","email":"dmushet@usgs.gov","middleInitial":"M.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":734680,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Vanderhoof, Melanie K. 0000-0002-0101-5533 mvanderhoof@usgs.gov","orcid":"https://orcid.org/0000-0002-0101-5533","contributorId":168395,"corporation":false,"usgs":true,"family":"Vanderhoof","given":"Melanie","email":"mvanderhoof@usgs.gov","middleInitial":"K.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":734682,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Leibowitz, Scott G.","contributorId":156432,"corporation":false,"usgs":false,"family":"Leibowitz","given":"Scott","email":"","middleInitial":"G.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":734686,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Christensen, J. R.","contributorId":204686,"corporation":false,"usgs":false,"family":"Christensen","given":"J.","email":"","middleInitial":"R.","affiliations":[{"id":36974,"text":"U.S. Environmental Protection Agency, National Exposure Research Laboratory, Las Vegas, NV","active":true,"usgs":false}],"preferred":false,"id":734684,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Neff, Brian 0000-0003-3718-7350 bneff@usgs.gov","orcid":"https://orcid.org/0000-0003-3718-7350","contributorId":198885,"corporation":false,"usgs":true,"family":"Neff","given":"Brian","email":"bneff@usgs.gov","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":734685,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rosenberry, Donald O. 0000-0003-0681-5641 rosenber@usgs.gov","orcid":"https://orcid.org/0000-0003-0681-5641","contributorId":1312,"corporation":false,"usgs":true,"family":"Rosenberry","given":"Donald","email":"rosenber@usgs.gov","middleInitial":"O.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":734687,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Rugh, W. D.","contributorId":204687,"corporation":false,"usgs":false,"family":"Rugh","given":"W.","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":734688,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Alexander, L.C.","contributorId":204056,"corporation":false,"usgs":false,"family":"Alexander","given":"L.C.","email":"","affiliations":[{"id":36812,"text":"U.S. EPA, Office of Research and Development","active":true,"usgs":false}],"preferred":false,"id":734689,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70194887,"text":"sir20185011 - 2018 - Flood-inundation maps for the Withlacoochee River From Skipper Bridge Road to St. Augustine Road, within the City of Valdosta, Georgia, and Lowndes County, Georgia","interactions":[],"lastModifiedDate":"2018-06-11T09:26:02","indexId":"sir20185011","displayToPublicDate":"2018-01-31T10:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-5011","title":"Flood-inundation maps for the Withlacoochee River From Skipper Bridge Road to St. Augustine Road, within the City of Valdosta, Georgia, and Lowndes County, Georgia","docAbstract":"Digital flood-inundation maps for a 12.6-mile reach of the Withlacoochee River from Skipper Bridge Road to St. Augustine Road (Georgia State Route 133) were developed to depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the U.S. Geological Survey (USGS) streamgage at Withlacoochee River at Skipper Bridge Road, near Bemiss, Ga. (023177483). Real-time stage information from this streamgage can be used with these maps to estimate near real-time areas of inundation. The forecasted peak-stage information for the USGS streamgage at Withlacoochee River at Skipper Bridge Road, near Bemiss, Ga. (023177483), can be used in conjunction with the maps developed for this study to show predicted areas of flood inundation.
A one-dimensional step-backwater model was developed using the U.S. Army Corps of Engineers Hydrologic Engineer-ing Center’s River Analysis System (HEC–RAS) software for the Withlacoochee River and was used to compute flood profiles for a 12.6-mile reach of the Withlacoochee River. The hydraulic model was then used to simulate 23 water-surface profiles at 1.0-foot (ft) intervals at the Withlacoochee River near the Bemiss streamgage. The profiles ranged from the National Weather Service action stage of 10.7 ft, which is 131.0 ft above the North American Vertical Datum of 1988 (NAVD 88), to a stage of 32.7 ft, which is 153.0 ft above NAVD 88. The simulated water-surface profiles were then combined with a geographic information system digital elevation model—derived from light detection and ranging (lidar) data having a 4.0-ft horizontal resolution—to delineate the area flooded at each 1.0-ft interval of stream stage.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185011","collaboration":"Prepared in cooperation with the City of Valdosta, Georgia, and Lowndes County, Georgia","usgsCitation":"Musser, J.W., 2018, Flood-inundation maps for the Withlacoochee River from Skipper Bridge Road to St. Augustine Road, within the City of Valdosta, Georgia, and Lowndes County, Georgia: U.S. Geological Survey Scientific Investigations Report 2018–5011, 15 p., https://doi.org/10.3133/sir20185011.","productDescription":"Report: viii, 18 p.; Data release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-087876","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":350785,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5011/coverthb.jpg"},{"id":350787,"rank":3,"type":{"id":30,"text":"Data 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South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Columbia, SC 29210
Two identical Radar Stage Sensors from Forest Technology Systems were evaluated to determine if they are suitable for U.S. Geological Survey (USGS) hydrologic data collection. The sensors were evaluated in laboratory conditions to evaluate the distance accuracy of the sensor over the manufacturer’s specified operating temperatures and distance to water ranges. Laboratory results were compared to the manufacturer’s accuracy specification of ±0.007 foot (ft) and the USGS Office of Surface Water (OSW) policy requirement that water-level sensors have a measurement uncertainty of no more than 0.01 ft or 0.20 percent of the indicated reading. Both of the sensors tested were within the OSW policy requirement in both laboratory tests and within the manufacturer’s specification in the distance to water test over tested distances from 3 to 15 ft. In the temperature chamber test, both sensors were within the manufacturer’s specification for more than 90 percent of the data points collected over a temperature range of –40 to +60 degrees Celsius at a fixed distance of 8 ft. One sensor was subjected to an SDI-12 communication test, which it passed. A field test was conducted on one sensor at a USGS field site near Landon, Mississippi, from February 5 to March 29, 2016. Water-level measurements made by the radar during the field test were in agreement with those made by the Sutron Accubar Constant Flow Bubble Gauge.
Upon the manufacturer’s release of updated firmware version 1.09, additional SDI-12 and temperature testing was performed to evaluate added SDI-12 functions and verify that performance was unaffected by the update. At this time, an Axiom data logger is required to perform a firmware update on this sensor. The data confirmed the results of the original test. Based on the test results, the Radar Stage Sensor is a suitable choice for USGS hydrologic data collection.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171085","usgsCitation":"Kunkle, G.A., 2018, Evaluation of the Radar Stage Sensor manufactured by Forest Technology Systems—Results of laboratory and field testing: U.S. Geological Survey Open-File Report 2017–1085, 12 p., https://doi.org/10.3133/ofr20171085.","productDescription":"Report: iv, 12 p.; Data Release","numberOfPages":"20","onlineOnly":"Y","ipdsId":"IP-083860","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":350803,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F71C1VSR","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Evaluation of the Radar Stage Sensor Manufactured by Forest Technology Systems, Incorporated—Results of Laboratory and Field Testing"},{"id":350800,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1085/ofr20171085.pdf","text":"Report","size":"918 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017–1085"},{"id":350799,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1085/coverthb.jpg"}],"contact":"Chief, Hydrologic Instrumentation Facility
U.S. Geological Survey
Building 2101
Stennis Space Center, MS 39529
A calibrated conceptual glacio-hydrological monthly water balance model (MWBMglacier) was used to evaluate future changes in water partitioning in a high-latitude glacierized watershed in Southcentral Alaska under future climate conditions. The MWBMglacier was previously calibrated and evaluated against streamflow measurements, literature values of glacier mass balance change, and satellite-based observations of snow covered area, evapotranspiration, and total water storage. Output from five global climate models representing two future climate scenarios (RCP 4.5 and RCP 8.5) was used with the previously calibrated parameters to drive the MWBMglacier at 2 km spatial resolution. Relative to the historical period 1949–2009, precipitation will increase and air temperature in the mountains will be above freezing for an additional two months per year by mid-century which significantly impacts snow/rain partitioning and the generation of meltwater from snow and glaciers. Analysis of the period 1949–2099 reveals that numerous hydrologic regime shifts already occurred or are projected to occur in the study area including glacier accumulation area, snow covered area, and forest vulnerability. By the end of the century, Copper River discharge is projected to increase by 48%, driven by 21% more precipitation and 53% more glacial melt water (RCP 8.5) relative to the historical period (1949–2009).
","language":"English","publisher":"MDPI","doi":"10.3390/w10020128","usgsCitation":"Valentin, M., Hogue, T.S., and Hay, L., 2018, Hydrologic regime changes in a high-latitude glacierized watershed under future climate conditions: Water, v. 10, no. 2, 128, 24 p., https://doi.org/10.3390/w10020128.","productDescription":"128, 24 p.","ipdsId":"IP-088012","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":469085,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w10020128","text":"Publisher Index Page"},{"id":429864,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Copper River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -148,\n 63.4\n ],\n [\n -148,\n 60.5\n ],\n [\n -140,\n 60.5\n ],\n [\n -140,\n 63.4\n ],\n [\n -148,\n 63.4\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"10","issue":"2","noUsgsAuthors":false,"publicationDate":"2018-01-30","publicationStatus":"PW","contributors":{"authors":[{"text":"Valentin, Melissa","contributorId":202218,"corporation":false,"usgs":false,"family":"Valentin","given":"Melissa","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":902997,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hogue, Terri S.","contributorId":205175,"corporation":false,"usgs":false,"family":"Hogue","given":"Terri","email":"","middleInitial":"S.","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":902998,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hay, Lauren 0000-0003-3763-4595","orcid":"https://orcid.org/0000-0003-3763-4595","contributorId":205020,"corporation":false,"usgs":true,"family":"Hay","given":"Lauren","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":902999,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70194835,"text":"ofr20181002 - 2018 - Using a food web model to inform the design of river restoration—An example at the Barkley Bear Segment, Methow River, north-central Washington","interactions":[],"lastModifiedDate":"2018-06-06T14:13:05","indexId":"ofr20181002","displayToPublicDate":"2018-01-29T00:00:00","publicationYear":"2018","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":"2018-1002","title":"Using a food web model to inform the design of river restoration—An example at the Barkley Bear Segment, Methow River, north-central Washington","docAbstract":"With the decline of Chinook salmon (Oncorhynchus tshawytscha) and steelhead (O. mykiss), habitat restoration actions in freshwater tributaries have been implemented to improve conditions for juveniles. Typically, physical (for example, hydrologic and engineering) based models are used to design restoration alternatives with the assumption that biological responses will be improved with changes to the physical habitat. Biological models rarely are used. Here, we describe simulations of a food web model, the Aquatic Trophic Productivity (ATP) model, to aid in the design of a restoration project in the Methow River, north-central Washington. The ATP model mechanistically links environmental conditions of the stream to the dynamics of river food webs, and can be used to simulate how alternative river restoration designs influence the potential for river reaches to sustain fish production. Four restoration design alternatives were identified that encompassed varying levels of side channel and floodplain reconnection and large wood addition. Our model simulations suggest that design alternatives focused on reconnecting side channels and the adjacent floodplain may provide the greatest increase in fish capacity. These results were robust to a range of discharge and thermal regimes that naturally occur in the Methow River. Our results suggest that biological models, such as the ATP model, can be used during the restoration planning phase to increase the effectiveness of restoration actions. Moreover, the use of multiple modeling efforts, both physical and biological, when evaluating restoration design alternatives provides a better understanding of the potential outcome of restoration actions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181002","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Benjamin, J.R., Bellmore, J.R., and Dombroski, Daniel, 2018, Using a food web model to inform the design of river restoration—An example at the Barkley Bear Segment, Methow River, north-central Washington: U.S. Geological Survey Open-File Report 2018–1002, 24 p., https://doi.org/10.3133/ofr20181002.","productDescription":"iv, 24 p.","numberOfPages":"32","onlineOnly":"Y","ipdsId":"IP-092102","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":350751,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1002/ofr20181002.pdf","text":"Report","size":"4.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1002"},{"id":350750,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1002/coverthb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Methow River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.497802734375,\n 47.646886969413\n ],\n [\n -119.02587890624999,\n 47.646886969413\n ],\n [\n -119.02587890624999,\n 49.15296965617042\n ],\n [\n -121.497802734375,\n 49.15296965617042\n ],\n [\n -121.497802734375,\n 47.646886969413\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Forest and Rangeland Ecosystem Science Center
U.S. Geological Survey
777 NW 9th St., Suite 400
Corvallis, Oregon 97330
The U.S. Geological Survey, in cooperation with the New Hampshire Department of Environmental Services and the Department of Health and Human Services, has developed a hydrologic model to assess the effects of short- and long-term climate change on hydrology in New Hampshire. This report documents the model and datasets developed by using the model to predict how climate change will affect the hydrologic cycle and provide data that can be used by State and local agencies to identify locations that are vulnerable to the effects of climate change in areas across New Hampshire.
Future hydrologic projections were developed from the output of five general circulation models for two future climate scenarios. The scenarios are based on projected future greenhouse gas emissions and estimates of land-use and land-cover change within a projected global economic framework. An evaluation of the possible effect of projected future temperature on modeling of evapotranspiration is summarized to address concerns regarding the implications of the future climate on model parameters that are based on climate variables. The results of the model simulations are hydrologic projections indicating increasing streamflow across the State with large increases in streamflow during winter and early spring and general decreases during late spring and summer. Wide spatial variability in changes to groundwater recharge is projected, with general decreases in the Connecticut River Valley and at high elevations in the northern part of the State and general increases in coastal and lowland areas of the State. In general, total winter snowfall is projected to decrease across the State, but there is a possibility of increasing snow in some locations, particularly during November, February, and March. The simulated future changes in recharge and snowfall vary by watershed across the State. This means that each area of the State could experience very different changes, depending on topography or other factors. Therefore, planning for infrastructure and public safety needs to be flexible in order to address the range of possible outcomes indicated by the various model simulations. The absolute magnitude and timing of the daily streamflows, especially the larger floods, are not considered to be reliably simulated compared to changes in frequency and duration of daily streamflows and changes in accumulated monthly and seasonal streamflow volumes.
Simulated current and future streamflow, groundwater recharge, and snowfall datasets include simulated data derived from the five general circulation models used in this study for a current reference time period and two future time periods. Average monthly streamflow time series datasets are provided for 27 streamgages in New Hampshire. Fourteen of the 27 streamgages associated with daily streamflow time series showed a good calibration. Average monthly groundwater recharge and snowfall time series for the same reference time period and two future time periods are also provided for each of the 467 hydrologic response units that compose the model.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175143","collaboration":"Prepared in cooperation with the New Hampshire Department of Environmental Services and Department of Health and Human Services","usgsCitation":"Bjerklie, D.M., and Sturtevant, Luke, 2018, Simulated hydrologic response to climate change during the 21st century in New Hampshire: U.S. Geological Survey Scientific Investigations Report 2017–5143, 53 p., https://doi.org/10.3133/sir20175143.","productDescription":"Report: viii, 53 p.; 4 Tables; Data release","numberOfPages":"66","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-074537","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":395616,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F76T0KJZ","text":"USGS data release","description":"USGS data release","linkHelpText":"Thirty- and ninety-year data sets of streamflow, groundwater recharge, and snowfall simulating potential hydrologic response to climate change in the 21st century in New Hampshire"},{"id":350514,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5143/tables/sir20175143_table4.csv","text":"Table 4","size":"10.8 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"- Streamflow percent change"},{"id":350513,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5143/tables/sir20175143_table3.csv","text":"Table 3","size":"6 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"- Streamgages in New Hampshire"},{"id":350512,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5143/sir20175143.pdf","text":"Report","size":"14.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5143"},{"id":350511,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5143/coverthb.jpg"},{"id":350515,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5143/tables/sir20175143_table5.csv","text":"Table 5","size":"10 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"- Mean monthly streamflow percent change"},{"id":350516,"rank":6,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5143/tables/sir20175143_table6.csv","text":"Table 6","size":"10.3 KB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"- Mean monthly streamflow percent change standard deviation"}],"country":"United States","state":"New 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Hampshire\",\"nation\":\"USA \"}}]}","contact":"Director, New England Water Science Center
U.S. Geological Survey
101 Pitkin Street
East Hartford, CT 06108
Digital flood-inundation maps for a 9.5-mile reach of the Patoka River in and near the city of Jasper, southwestern Indiana (Ind.), from the streamgage near County Road North 175 East, downstream to State Road 162, 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 web site 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 USGS streamgage Patoka River at Jasper, Ind. (station number 03375500). The Patoka streamgage is located at the upstream end of the 9.5-mile river reach. Near-real-time stages at this streamgage may be obtained from the USGS National Water Information System at https://waterdata.usgs.gov/ or the National Weather Service Advanced Hydrologic Prediction Service at http://water.weather.gov/ahps/, although flood forecasts and stages for action and minor, moderate, and major flood stages are not currently (2017) available at this site (JPRI3).
Flood profiles were computed for the stream reach by means of a one-dimensional step-backwater model. The hydraulic model was calibrated by using the most current stage-discharge relation at the Patoka River at Jasper, Ind., streamgage and the documented high-water marks from the flood of April 30, 2017. The calibrated hydraulic model was then used to compute five water-surface profiles for flood stages referenced to the streamgage datum ranging from 15 feet (ft), or near bankfull, to 19 ft. The simulated water-surface profiles were then combined with a geographic information system digital elevation model (derived from light detection and ranging [lidar] data having a 0.98 ft vertical accuracy and 4.9 ft horizontal resolution) to delineate the area flooded at each water level.
The availability of these flood-inundation maps, along with real-time stage from the USGS streamgage at the Patoka River at Jasper, Ind., 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/sir20175138","collaboration":"Prepared in cooperation with the Indiana Department of Transportation","usgsCitation":"Fowler, K.K., 2018, Flood-inundation maps for the Patoka River in and near Jasper, southwestern Indiana: U.S. Geological Survey Scientific Investigations Report 2017–5138, 11 p., https://doi.org/10.3133/sir20175138.","productDescription":"Report: vii, 11 p.; Data Release","numberOfPages":"23","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-086512","costCenters":[{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true}],"links":[{"id":350479,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5138/coverthb.jpg"},{"id":350480,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5138/sir20175138.pdf","text":"Report","size":"34.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5138"},{"id":350481,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7862DX0","text":"USGS data release","description":"USGS data release","linkHelpText":"Geospatial Datasets and Surface-Water Hydraulic Model for the Patoka River in and near Jasper, Southwest Indiana, Flood-inundation Study"}],"country":"United States","state":"Indiana","city":"Jasper","otherGeospatial":"Patoka River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -86.95,\n 38.360839624761944\n ],\n [\n -86.875,\n 38.360839624761944\n ],\n [\n -86.875,\n 38.425\n ],\n [\n -86.95,\n 38.425\n ],\n [\n -86.95,\n 38.360839624761944\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Indiana Water Science Center
U.S. Geological Survey
5957 Lakeside Blvd
Indianapolis, IN 46278
Interannual differences in the water quality of Anvil Lake, Wisconsin, were examined to determine how water level and climate affect the hydrodynamics and trophic state of shallow lakes, and their importance compared to anthropogenic changes in the watershed. Anvil Lake is a relatively pristine seepage lake with hydrology dominated by precipitation, evaporation, and groundwater exchange enabling the typically subtle effects of water level and climate to be evaluated. Groundwater and hydrodynamic models were used to describe lake water and phosphorus budgets and how its hydrodynamics are affected by water level and air temperature. Decreases in water level are expected to cause Anvil Lake and other shallow lakes to stratify fewer days, and have warmer bottom temperatures and more deep-mixing events. Increasing air temperatures should cause these lakes to have shorter ice cover, longer summer stratification periods, and warmer bottom temperatures. How water level affects water quality depends on how nutrient loading and lake volume vary: during drier, low-water years, lakes with large interannual changes in loading should have better water quality, whereas lakes with small changes in loading should degrade slightly. Anthropogenic changes in Anvil Lake's watershed over the past ∼100 yr were about 1.5 times the effects of changes in water level when levels were low, but the effects were similar when levels were high. Climate warming is expected to increase productivity in shallow lakes because warmer air temperatures will likely increase bottom temperatures increasing sediment phosphorus release and deep-mixing events enabling this phosphorus to reach the epilimnion.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/10402381.2017.1412374","usgsCitation":"Robertson, D.M., Juckem, P.F., Dantoin, E.D., and Winslow, L., 2018, Effects of water level and climate on the hydrodynamics and water quality of Anvil Lake, Wisconsin, a shallow seepage lake: Lake and Reservoir Management, v. 34, no. 3, p. 211-231, https://doi.org/10.1080/10402381.2017.1412374.","productDescription":"21 p.","startPage":"211","endPage":"231","ipdsId":"IP-082880","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":438051,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7F18WXW","text":"USGS data release","linkHelpText":"MODFLOW-NWT model data sets used to evaluate the changes in hydrodynamics of Anvil Lake, Wisconsin"},{"id":361735,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Anvil Lake","volume":"34","issue":"3","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Robertson, Dale M. 0000-0001-6799-0596","orcid":"https://orcid.org/0000-0001-6799-0596","contributorId":204668,"corporation":false,"usgs":true,"family":"Robertson","given":"Dale","email":"","middleInitial":"M.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":758737,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Juckem, Paul F. 0000-0002-3613-1761 pfjuckem@usgs.gov","orcid":"https://orcid.org/0000-0002-3613-1761","contributorId":1905,"corporation":false,"usgs":true,"family":"Juckem","given":"Paul","email":"pfjuckem@usgs.gov","middleInitial":"F.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":758738,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dantoin, Eric D. 0000-0002-8561-2924 edantoin@usgs.gov","orcid":"https://orcid.org/0000-0002-8561-2924","contributorId":2278,"corporation":false,"usgs":true,"family":"Dantoin","given":"Eric","email":"edantoin@usgs.gov","middleInitial":"D.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":758739,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Winslow, Luke A. 0000-0002-8602-5510","orcid":"https://orcid.org/0000-0002-8602-5510","contributorId":211187,"corporation":false,"usgs":false,"family":"Winslow","given":"Luke A.","affiliations":[{"id":12656,"text":"Rensselaer Polytechnic Institute","active":true,"usgs":false}],"preferred":false,"id":758740,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70194509,"text":"sir20175140 - 2018 - Development of a hydraulic model and flood-inundation maps for the Wabash River near the Interstate 64 Bridge near Grayville, Illinois","interactions":[],"lastModifiedDate":"2018-07-25T10:40:07","indexId":"sir20175140","displayToPublicDate":"2018-01-16T11:30:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5140","title":"Development of a hydraulic model and flood-inundation maps for the Wabash River near the Interstate 64 Bridge near Grayville, Illinois","docAbstract":"A two-dimensional hydraulic model and digital flood‑inundation maps were developed for a 30-mile reach of the Wabash River near the Interstate 64 Bridge near Grayville, Illinois. The flood-inundation maps, which can be accessed through the U.S. Geological Survey (USGS) Flood Inundation Mapping Science web site at http://water.usgs.gov/osw/flood_inundation/, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage on the Wabash River at Mount Carmel, Ill (USGS station number 03377500). Near-real-time stages at this streamgage may be obtained on the internet from the USGS National Water Information System at http://waterdata.usgs.gov/ or the National Weather Service (NWS) Advanced Hydrologic Prediction Service (AHPS) at http://water.weather.gov/ahps/, which also forecasts flood hydrographs at this site (NWS AHPS site MCRI2). The NWS AHPS forecasts peak stage information that may be used with the maps developed in this study to show predicted areas of flood inundation.
Flood elevations were computed for the Wabash River reach by means of a two-dimensional, finite-volume numerical modeling application for river hydraulics. The hydraulic model was calibrated by using global positioning system measurements of water-surface elevation and the current stage-discharge relation at both USGS streamgage 03377500, Wabash River at Mount Carmel, Ill., and USGS streamgage 03378500, Wabash River at New Harmony, Indiana. The calibrated hydraulic model was then used to compute 27 water-surface elevations for flood stages at 1-foot (ft) intervals referenced to the streamgage datum and ranging from less than the action stage (9 ft) to the highest stage (35 ft) of the current stage-discharge rating curve. The simulated water‑surface elevations were then combined with a geographic information system digital elevation model, derived from light detection and ranging data, to delineate the area flooded at each water level.
The availability of these maps, along with information on the internet regarding current stage from the USGS streamgage at Mount Carmel, Ill., and forecasted stream stages from the NWS AHPS, provides 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/sir20175140","collaboration":"Prepared in cooperation with the Indiana Department of Transportation; Illinois Department of Transportation","usgsCitation":"Boldt, J.A., 2018, Development of a hydraulic model and flood-inundation maps for the Wabash River near the Interstate 64 Bridge near Grayville, Illinois: U.S. Geological Survey Scientific Investigations Report 2017–5140, 13 p., https://doi.org/10.3133/sir20175140.","productDescription":"vi, 13 p.","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-087699","costCenters":[{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true}],"links":[{"id":355963,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F78P5ZCD","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Geospatial datasets and model for the flood-inundation study of the Wabash River near the Interstate 64 Bridge near Grayville, Illinois"},{"id":350289,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/publication/sir20175117","text":"Scientific Investigations Report 2017–5117","linkHelpText":"- River Meander Modeling of the Wabash River near the Interstate 64 Bridge near Grayville, Illinois"},{"id":350288,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5140/sir20175140.pdf","text":"Report","size":"3.06 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5140"},{"id":350287,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5140/coverthb.jpg"}],"country":"United States","state":"Illinois","city":"Grayville","otherGeospatial":"Wabash River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.01456451416016,\n 38.153727245014004\n ],\n [\n -87.77870178222656,\n 38.153727245014004\n ],\n [\n -87.77870178222656,\n 38.338694087313534\n ],\n [\n -88.01456451416016,\n 38.338694087313534\n ],\n [\n -88.01456451416016,\n 38.153727245014004\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Ohio-Kentucky-Indiana Water Science Center
U.S. Geological Survey
9818 Bluegrass Parkway
Louisville, KY 40299
Globally, hydrologic modifications such as ditching and subsurface drainage have significantly reduced wetland water storage capacity (i.e., volume of surface water a wetland can retain) and consequent wetland functions. While wetland area has been well documented across many landscapes and used to guide restoration efforts, few studies have directly quantified the associated wetland storage capacity. Here, we present a novel raster-based approach to quantify both contemporary and potential (i.e., restorable) storage capacities of individual depressional basins across landscapes. We demonstrate the utility of this method by applying it to the Delmarva Peninsula, a region punctuated by both depressional wetlands and drainage ditches. Across the entire peninsula, we estimated that restoration (i.e., plugging ditches) could increase storage capacity by 80%. Focusing on an individual watershed, we found that over 59% of restorable storage capacity occurs within 20 m of the drainage network, and that 93% occurs within 1 m elevation of the drainage network. Our demonstration highlights widespread ditching in this landscape, spatial patterns of both contemporary and potential storage capacities, and clear opportunities for hydrologic restoration. In Delmarva and more broadly, our novel approach can inform targeted landscape-scale conservation and restoration efforts to optimize hydrologically mediated wetland functions.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.11405","usgsCitation":"Jones, C.N., Evenson, G.R., McLaughlin, D.L., Vanderhoof, M.K., Lang, M.W., McCarty, G.W., Golden, H.E., Lane, C., and Alexander, L., 2018, Estimating restorable wetland water storage at landscape scales: Hydrological Processes, v. 32, no. 2, p. 305-313, https://doi.org/10.1002/hyp.11405.","productDescription":"9 p.","startPage":"305","endPage":"313","ipdsId":"IP-088286","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":29789,"text":"John Wesley Powell Center for Analysis and Synthesis","active":true,"usgs":true}],"links":[{"id":461079,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/5907502","text":"External Repository"},{"id":351516,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"32","issue":"2","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-12-13","publicationStatus":"PW","scienceBaseUri":"5afee751e4b0da30c1bfc22a","contributors":{"authors":[{"text":"Jones, Charles Nathan","contributorId":202421,"corporation":false,"usgs":false,"family":"Jones","given":"Charles","email":"","middleInitial":"Nathan","affiliations":[{"id":36428,"text":"The National Socio-Environmental Synthesis Center, University of Maryland","active":true,"usgs":false}],"preferred":false,"id":728374,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Evenson, Grey R.","contributorId":202422,"corporation":false,"usgs":false,"family":"Evenson","given":"Grey","email":"","middleInitial":"R.","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":728375,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McLaughlin, Daniel L.","contributorId":156435,"corporation":false,"usgs":false,"family":"McLaughlin","given":"Daniel","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":728376,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vanderhoof, Melanie K. 0000-0002-0101-5533 mvanderhoof@usgs.gov","orcid":"https://orcid.org/0000-0002-0101-5533","contributorId":168395,"corporation":false,"usgs":true,"family":"Vanderhoof","given":"Melanie","email":"mvanderhoof@usgs.gov","middleInitial":"K.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":728373,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lang, Megan W.","contributorId":196284,"corporation":false,"usgs":false,"family":"Lang","given":"Megan","email":"","middleInitial":"W.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":728377,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McCarty, Greg W.","contributorId":143675,"corporation":false,"usgs":false,"family":"McCarty","given":"Greg","email":"","middleInitial":"W.","affiliations":[{"id":15298,"text":"USDA-ARS Hydrology and Remote Sensing Laboratory, Bldg 007, BARC-W, 10300 Baltimore Avenue, Beltsville, Maryland 20705, United States","active":true,"usgs":false}],"preferred":false,"id":728378,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Golden, Heather E.","contributorId":202423,"corporation":false,"usgs":false,"family":"Golden","given":"Heather","email":"","middleInitial":"E.","affiliations":[{"id":36429,"text":"USEPA ORD","active":true,"usgs":false}],"preferred":false,"id":728379,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Lane, Charles R.","contributorId":138991,"corporation":false,"usgs":false,"family":"Lane","given":"Charles R.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":728380,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Alexander, Laurie C.","contributorId":138989,"corporation":false,"usgs":false,"family":"Alexander","given":"Laurie C.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":728381,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70194647,"text":"ofr20171159 - 2018 - Processing of next generation weather radar-multisensor precipitation estimates and quantitative precipitation forecast data for the DuPage County streamflow simulation system","interactions":[],"lastModifiedDate":"2018-01-25T15:19:19","indexId":"ofr20171159","displayToPublicDate":"2018-01-12T13:45:00","publicationYear":"2018","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":"2017-1159","title":"Processing of next generation weather radar-multisensor precipitation estimates and quantitative precipitation forecast data for the DuPage County streamflow simulation system","docAbstract":"The U.S. Geological Survey, in cooperation with DuPage County Stormwater Management Department, is testing a near real-time streamflow simulation system that assists in the management and operation of reservoirs and other flood-control structures in the Salt Creek and West Branch DuPage River drainage basins in DuPage County, Illinois. As part of this effort, the U.S. Geological Survey maintains a database of hourly meteorological and hydrologic data for use in this near real-time streamflow simulation system. Among these data are next generation weather radar-multisensor precipitation estimates and quantitative precipitation forecast data, which are retrieved from the North Central River Forecasting Center of the National Weather Service. The DuPage County streamflow simulation system uses these quantitative precipitation forecast data to create streamflow predictions for the two simulated drainage basins. This report discusses in detail how these data are processed for inclusion in the Watershed Data Management files used in the streamflow simulation system for the Salt Creek and West Branch DuPage River drainage basins.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171159","collaboration":"Prepared in cooperation with the DuPage County Stormwater Management Department","usgsCitation":"Bera, Maitreyee, and Ortel, T.W., 2018, Processing of next generation weather radar-multisensor precipitation estimates and quantitative precipitation forecast data for the DuPage County streamflow simulation system: \nU.S. Geological Survey Open-File Report 2017–1159, 16 p., https://doi.org/10.3133/ofr20171159.","productDescription":"iv, 15 p.","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-087229","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":350409,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1159/coverthb.jpg"},{"id":350410,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1159/ofr20171159.pdf","text":"Report","size":"3.64 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1159"}],"country":"United States","state":"Illinois","county":"DuPage County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-88.2634,41.9876],[-88.1473,41.9883],[-88.0342,41.9925],[-87.9175,41.9938],[-87.9188,41.9076],[-87.9178,41.8185],[-87.9142,41.7318],[-87.9139,41.7172],[-87.9438,41.7017],[-87.9482,41.694],[-87.9674,41.6879],[-87.9883,41.6877],[-88.0013,41.6874],[-88.0308,41.6868],[-88.0317,41.7295],[-88.1499,41.7272],[-88.2625,41.7251],[-88.2628,41.811],[-88.2632,41.8623],[-88.2631,41.9],[-88.2634,41.9876]]]},\"properties\":{\"name\":\"Dupage\",\"state\":\"IL\"}}]}","contact":"Director, Illinois-Iowa Water Science Center
U.S. Geological Survey
405 North Goodwin Avenue
Urbana, IL 61801
Agricultural activities can affect water quality and the health of aquatic ecosystems; many water-quality issues originate with the movement of water, agricultural chemicals, and eroded soil from agricultural areas to streams and groundwater. Most agricultural activities are designed to sustain or increase crop production, while some are designed to protect soil and water resources. Numerous soil- and water-protection practices are designed to reduce the volume and velocity of runoff and increase infiltration. This report presents a conceptual framework that combines generalized concepts on the movement of water, the environmental behavior of chemicals and eroded soil, and the designed functions of various agricultural activities, as they relate to hydrology, to create attainable expectations for the protection of—with the goal of improving—water quality through changes in an agricultural activity.
The framework presented uses two types of decision trees to guide decision making toward attainable expectations regarding the effectiveness of changing agricultural activities to protect and improve water quality in streams. One decision tree organizes decision making by considering the hydrologic setting and chemical behaviors, largely at the field scale. This decision tree can help determine which agricultural activities could effectively protect and improve water quality in a stream from the movement of chemicals, or sediment, from a field. The second decision tree is a chemical fate accounting tree. This decision tree helps set attainable expectations for the permanent removal of sediment, elements, and organic chemicals—such as herbicides and insecticides—through trapping or conservation tillage practices. Collectively, this conceptual framework consolidates diverse hydrologic settings, chemicals, and agricultural activities into a single, broad context that can be used to set attainable expectations for agricultural activities. This framework also enables better decision making for future agricultural activities as a means to reduce current, and prevent new, water-quality issues.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175095","usgsCitation":"Capel, P.D., Wolock, D.M., Coupe, R.H., and Roth, J.L., 2018, A conceptual framework for effectively anticipating water-quality changes resulting from changes in agricultural activities: U.S. Geological Survey Scientific Investigations Report 2017–5095, 35 p., https://doi.org/10.3133/sir20175095.","productDescription":"Report: viii, 35 p.; Data release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-071052","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"links":[{"id":350408,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F75T3HN9","text":"USGS data release","description":"USGS data release","linkHelpText":"Data set used to develop a conceptual framework for effectively anticipating water-quality changes resulting from changes in agricultural activities"},{"id":349840,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5095/coverthb.jpg"},{"id":349841,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5095/sir20175095.pdf","text":"Report","size":"2.14 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5095"}],"contact":"National Water-Quality Program
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
This report documents several components of the U.S. Geological Survey National Hydrologic Model of the conterminous United States for use with the Precipitation-Runoff Modeling System (PRMS). It provides descriptions of the (1) National Hydrologic Model, (2) Geospatial Fabric for National Hydrologic Modeling, (3) PRMS hydrologic simulation code, (4) parameters and estimation methods used to compute spatially and temporally distributed default values as required by PRMS, (5) National Hydrologic Model Parameter Database, and (6) model extraction tool named Bandit. The National Hydrologic Model Parameter Database contains values for all PRMS parameters used in the National Hydrologic Model. The methods and national datasets used to estimate all the PRMS parameters are described. Some parameter values are derived from characteristics of topography, land cover, soils, geology, and hydrography using traditional Geographic Information System methods. Other parameters are set to long-established default values and computation of initial values. Additionally, methods (statistical, sensitivity, calibration, and algebraic) were developed to compute parameter values on the basis of a variety of nationally-consistent datasets. Values in the National Hydrologic Model Parameter Database can periodically be updated on the basis of new parameter estimation methods and as additional national datasets become available. A companion ScienceBase resource provides a set of static parameter values as well as images of spatially-distributed parameters associated with PRMS states and fluxes for each Hydrologic Response Unit across the conterminuous United States.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section B: Surface water in Book 6: Modeling techniques","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm6B9","usgsCitation":"Regan, R.S., Markstrom, S.L., Hay, L.E., Viger, R.J., Norton, P.A., Driscoll, J.M., LaFontaine, J.H., 2018, Description of the National Hydrologic Model for use with the Precipitation-Runoff Modeling System (PRMS): U.S. Geological Survey Techniques and Methods, book 6, chap B9, 38 p., https://doi.org/10.3133/tm6B9.","productDescription":"vii, 38 p.","onlineOnly":"Y","ipdsId":"IP-084916","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":438059,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TYOJKN","text":"USGS data release","linkHelpText":"National Hydrologic Model v1.0 water budget components aggregated to 10 and 12-digit Hydrologic Unit Code boundaries"},{"id":350326,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/06/b09/coverthb.jpg"},{"id":350327,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/06/b09/tm6b9.pdf","text":"Report","size":"5.96 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM 6-B9"}],"publicComments":"This report is Chapter 9 of Section B: Surface Water in Book 6 Modeling Techniques.","contact":"Director, Integrated Modeling and Prediction Division
U.S. Geological Survey
Mail Stop 415
12201 Sunrise Valley Drive
Reston, VA 20192
Thaw lakes are ubiquitous on arctic coastal plains (ACPs). While many thaw lakes have steep banks, stable water levels, and static surface areas, others only partially fill their basins and vary in area over the summer. These partially drained lakes (PDLs) are hydrologically connected to the wetlands immediately surrounding them. Heat and nutrient availability limit aquatic productivity on ACPs, and we hypothesized that shallow shorelines and greater hydrologic connectivity with the landscape should result in greater nutrient concentrations and biogeochemical cycling in PDLs. We tested this by monitoring water chemistry in lakes with varying levels of seasonal drainage in sandy and silty peaty lowland sites on the ACP of Alaska. One highly drained lake (N1) was significantly warmer than minimally drained lakes (minDLs) related to earlier ice off, reaching temperatures as high as 16 °C in June when minDLs still contained ice. Ammonia, total dissolved phosphorus, and dissolved organic carbon and nitrogen concentrations were higher in lakes with greater drainage, and concentrations in N1 rivaled those in the small, biologically productive ponds. Many PDLs displayed a midsummer decrease in nutrients consistent with assimilation by the aquatic ecosystem, and a late‐summer increase most likely related to runoff from drained lake margins following precipitation. N1 exported kilograms of ammonium and total dissolved phosphorus to the stream network over the summer. Given increased warming and drying in the arctic, the proportion of PDLs may be changing, which in turn may affect nutrient and organic matter availability in arctic lakes and export to downstream environments.
","language":"English","publisher":"Wiley","doi":"10.1002/2017JG004187","usgsCitation":"Koch, J.C., Fondell, T.F., Schmutz, J.A., and Laske, S.M., 2018, Nutrient dynamics in partially drained arctic thaw lakes: Journal of Geophysical Research: Biogeosciences, v. 123, no. 2, p. 440-452, https://doi.org/10.1002/2017JG004187.","productDescription":"13 p.","startPage":"440","endPage":"452","ipdsId":"IP-085121","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":469103,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2017jg004187","text":"Publisher Index Page"},{"id":438061,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7BC3XHJ","text":"USGS data release","linkHelpText":"Arctic Coastal Plain Seasonal Lake Drainage, Water Temperature, and Solute and Nutrient Concentrations, 2011 - 2014"},{"id":356006,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"123","issue":"2","noUsgsAuthors":false,"publicationDate":"2018-02-17","publicationStatus":"PW","scienceBaseUri":"5b6fc4cbe4b0f5d57878eacc","contributors":{"authors":[{"text":"Koch, Joshua C. 0000-0001-7180-6982 jkoch@usgs.gov","orcid":"https://orcid.org/0000-0001-7180-6982","contributorId":202532,"corporation":false,"usgs":true,"family":"Koch","given":"Joshua","email":"jkoch@usgs.gov","middleInitial":"C.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":741071,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fondell, Tom F. tfondell@usgs.gov","contributorId":3563,"corporation":false,"usgs":true,"family":"Fondell","given":"Tom","email":"tfondell@usgs.gov","middleInitial":"F.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":false,"id":741072,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schmutz, Joel A. 0000-0002-6516-0836 jschmutz@usgs.gov","orcid":"https://orcid.org/0000-0002-6516-0836","contributorId":1805,"corporation":false,"usgs":true,"family":"Schmutz","given":"Joel","email":"jschmutz@usgs.gov","middleInitial":"A.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"preferred":true,"id":741073,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Laske, Sarah M. 0000-0002-6096-0420 slaske@usgs.gov","orcid":"https://orcid.org/0000-0002-6096-0420","contributorId":204872,"corporation":false,"usgs":true,"family":"Laske","given":"Sarah","email":"slaske@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":741074,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70202537,"text":"70202537 - 2018 - Comparison of time nonlocal transport models for characterizing non-Fickian transport: From mathematical interpretation to laboratory application","interactions":[],"lastModifiedDate":"2019-03-07T16:38:39","indexId":"70202537","displayToPublicDate":"2018-01-01T16:38:26","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"Comparison of time nonlocal transport models for characterizing non-Fickian transport: From mathematical interpretation to laboratory application","docAbstract":"Non-Fickian diffusion has been increasingly documented in hydrology and modeled by promising time nonlocal transport models. While previous studies showed that most of the time nonlocal models are identical with correlated parameters, fundamental challenges remain in real-world applications regarding model selection and parameter definition. This study compared three popular time nonlocal transport models, including the multi-rate mass transfer (MRMT) model, the continuous time random walk (CTRW) framework, and the tempered time fractional advection–dispersion equation (tt-fADE), by focusing on their physical interpretation and feasibility in capturing non-Fickian transport. Mathematical comparison showed that these models have both related parameters defining the memory function and other basic-transport parameters (i.e., velocity v and dispersion coefficient D) with different hydrogeologic interpretations. Laboratory column transport experiments and field tracer tests were then conducted, providing data for model applicability evaluation. Laboratory and field experiments exhibited breakthrough curves with non-Fickian characteristics, which were better represented by the tt-fADE and CTRW models than the traditional advection–dispersion equation. The best-fit velocity and dispersion coefficient, however, differ significantly between the tt-fADE and CTRW. Fitting exercises further revealed that the observed late-time breakthrough curves were heavier than the MRMT solutions with no more than two mass-exchange rates and lighter than the MRMT solutions with power-law distributed mass-exchange rates. Therefore, the time nonlocal models, where some parameters are correlated and exchangeable and the others have different values, differ mainly in their quantification of pre-asymptotic transport dynamics. In all models tested above, the tt-fADE model is attractive, considering its small fitting error and the reasonable velocity close to the measured flow rate.
","language":"English","publisher":"MDPI","doi":"10.3390/w10060778","usgsCitation":"Lu, B., Zhang, Y., Zheng, C., Green, C.T., O’Neill, C., Sun, H., and Qian, J., 2018, Comparison of time nonlocal transport models for characterizing non-Fickian transport: From mathematical interpretation to laboratory application: Water, v. 10, no. 6, p. 1-28, https://doi.org/10.3390/w10060778.","productDescription":"Article 778; 28 p.","startPage":"1","endPage":"28","ipdsId":"IP-086405","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":469107,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w10060778","text":"Publisher Index Page"},{"id":361861,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"6","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Lu, Bingqing","contributorId":214039,"corporation":false,"usgs":false,"family":"Lu","given":"Bingqing","email":"","affiliations":[{"id":16675,"text":"U Alabama","active":true,"usgs":false}],"preferred":false,"id":758998,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Zhang, Yong","contributorId":214040,"corporation":false,"usgs":false,"family":"Zhang","given":"Yong","email":"","affiliations":[{"id":16675,"text":"U Alabama","active":true,"usgs":false}],"preferred":false,"id":758999,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zheng, Chunmiao","contributorId":214041,"corporation":false,"usgs":false,"family":"Zheng","given":"Chunmiao","email":"","affiliations":[{"id":16675,"text":"U Alabama","active":true,"usgs":false}],"preferred":false,"id":759000,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Green, Christopher T. 0000-0002-6480-8194 ctgreen@usgs.gov","orcid":"https://orcid.org/0000-0002-6480-8194","contributorId":1343,"corporation":false,"usgs":true,"family":"Green","given":"Christopher","email":"ctgreen@usgs.gov","middleInitial":"T.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":758997,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"O’Neill, Charles","contributorId":214042,"corporation":false,"usgs":false,"family":"O’Neill","given":"Charles","email":"","affiliations":[{"id":16675,"text":"U Alabama","active":true,"usgs":false}],"preferred":false,"id":759001,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sun, Hong-Guang 0000-0002-8422-3871","orcid":"https://orcid.org/0000-0002-8422-3871","contributorId":176581,"corporation":false,"usgs":false,"family":"Sun","given":"Hong-Guang","email":"","affiliations":[],"preferred":false,"id":759002,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Qian, Jiazhong","contributorId":214043,"corporation":false,"usgs":false,"family":"Qian","given":"Jiazhong","email":"","affiliations":[{"id":38964,"text":"Hefei University of Technology, Hefei","active":true,"usgs":false}],"preferred":false,"id":759003,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70199960,"text":"70199960 - 2018 - High resolution water body mapping for SWAT evaporative modelling in the Upper Oconee watershed of Georgia, USA","interactions":[],"lastModifiedDate":"2018-10-05T14:44:36","indexId":"70199960","displayToPublicDate":"2018-01-01T14:44:30","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"High resolution water body mapping for SWAT evaporative modelling in the Upper Oconee watershed of Georgia, USA","docAbstract":"Technological improvements in remote sensing and geographic information systems have demonstrated the abundance of artificially constructed water bodies across the landscape. Although research has shown the ubiquity of small ponds globally, and in the southeastern United States in particular, their cumulative impact in terms of evaporative alteration is less well quantified. The objectives of this study are to examine the hydrologic and evaporative importance of small artificial water bodies in the Upper Oconee watershed in the northern Georgia Piedmont, USA, by mapping their locations and modelling these small reservoirs using the Soil Water Assessment Tool. Comparative Soil Water Assessment Tool models were run with and without the inclusion of small reservoir surface area and volume. The models used meteorological inputs from 1990–2013 to represent years with drought, high precipitation, and moderate precipitation for both the calibration and evaluation periods. Statistical comparison of streamflow indicated that the calibration methodology produced results where the default model simulation without reservoirs fit observed flows more closely than the modified model with small reservoirs included (e.g., Nash–Sutcliffe efficiency of 0.72 vs. 0.64, r2 of 0.73 vs. 0.66, and percent bias of 11.4 vs. 21.6). In addition, Penman–Monteith, Hargreaves, and Priestley–Taylor evapotranspiration equations were used to estimate actual evaporation from 2,219 small water bodies identified throughout the 1,936.8 km2 watershed. Depending on the evaporation equation used, water bodies evaporated an average of 0.03–0.036 km3/year for the period 2003–2013. Using Penman–Monteith further, if the reservoirs were not considered and average actual evapotranspiration rates from the rest of the basin were applied, only 0.016 km3 of water would have left the basin as a result of evapotranspiration. This finding suggests construction of small reservoirs increased evaporation by an average of 0.017 km3 per year (approximately 46,500 m3/day). As the construction of small reservoirs continues and high resolution image data used to map these water bodies becomes increasingly available, watershed models that evolve to address the cumulative impacts of small water bodies on evaporation and other hydrologic processes will have greater potential to benefit the water resource management community.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.11398","usgsCitation":"Ignatius, A., and Jones, J., 2018, High resolution water body mapping for SWAT evaporative modelling in the Upper Oconee watershed of Georgia, USA: Hydrological Processes, v. 32, no. 1, p. 51-65, https://doi.org/10.1002/hyp.11398.","productDescription":"15 p.","startPage":"51","endPage":"65","ipdsId":"IP-073606","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"links":[{"id":469108,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/hyp.11398","text":"Publisher Index Page"},{"id":358190,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Georgia","otherGeospatial":"Upper Oconee watershed","volume":"32","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-12-18","publicationStatus":"PW","scienceBaseUri":"5bc0304de4b0fc368eb539ec","contributors":{"authors":[{"text":"Ignatius, Amber R. 0000-0002-2636-836X","orcid":"https://orcid.org/0000-0002-2636-836X","contributorId":193407,"corporation":false,"usgs":false,"family":"Ignatius","given":"Amber R.","affiliations":[],"preferred":false,"id":747475,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, John 0000-0001-6117-3691 jwjones@usgs.gov","orcid":"https://orcid.org/0000-0001-6117-3691","contributorId":2220,"corporation":false,"usgs":true,"family":"Jones","given":"John","email":"jwjones@usgs.gov","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"preferred":true,"id":747474,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70196378,"text":"70196378 - 2018 - Advances in drainage: Selected works from the Tenth International Drainage Symposium","interactions":[],"lastModifiedDate":"2018-04-04T13:59:51","indexId":"70196378","displayToPublicDate":"2018-01-01T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3619,"text":"Transactions of the ASABE","active":true,"publicationSubtype":{"id":10}},"title":"Advances in drainage: Selected works from the Tenth International Drainage Symposium","docAbstract":"This article introduces a special collection of fourteen articles accepted from among the 140 technical presentations, posters, and meeting papers presented at the 10th International ASABE Drainage Symposium. The symposium continued in the tradition of previous symposia that began in 1965 as a forum for presenting and assessing the progress of drainage research and implementation throughout the world. The articles in this collection address a wide range of topics grouped into five broad categories: (1) crop response, (2) design and management, (3) hydrology and scale, (4) modeling, and (5) water quality. The collection provides valuable information for scientists, engineers, planners, and others working on crop production, water quality, and water quantity issues affected by agricultural drainage. The collection also provides perspectives on the challenges of increasing agricultural production in a changing climate, with ever-greater attention to water quality and quantity concerns that will require integrated technical, economic, and social solutions.
","language":"English","publisher":"American Society of Agricultural and Biological Engineering (ASABE)","doi":"10.13031/trans.12668","usgsCitation":"Strock, J.S., Hay, C., Helmers, M., Nelson, K.A., Sands, G.R., Skaggs, R.W., and Douglas-Mankin, K.R., 2018, Advances in drainage: Selected works from the Tenth International Drainage Symposium: Transactions of the ASABE, v. 61, no. 1, p. 161-168, https://doi.org/10.13031/trans.12668.","productDescription":"8 p.","startPage":"161","endPage":"168","ipdsId":"IP-094677","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":469128,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.13031/trans.12668","text":"Publisher Index Page"},{"id":353154,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"61","issue":"1","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee752e4b0da30c1bfc247","contributors":{"authors":[{"text":"Strock, Jeffrey S.","contributorId":203928,"corporation":false,"usgs":false,"family":"Strock","given":"Jeffrey","email":"","middleInitial":"S.","affiliations":[{"id":36759,"text":"Southwest Research and Outreach Center, University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":732673,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hay, Christopher","contributorId":203929,"corporation":false,"usgs":false,"family":"Hay","given":"Christopher","email":"","affiliations":[{"id":36760,"text":"Iowa Soybean Association","active":true,"usgs":false}],"preferred":false,"id":732674,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Helmers, Matthew","contributorId":189905,"corporation":false,"usgs":false,"family":"Helmers","given":"Matthew","email":"","affiliations":[],"preferred":false,"id":732675,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nelson, Kelly A.","contributorId":203931,"corporation":false,"usgs":false,"family":"Nelson","given":"Kelly","email":"","middleInitial":"A.","affiliations":[{"id":36762,"text":"Greenley Research Center, University of Missouri","active":true,"usgs":false}],"preferred":false,"id":732676,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sands, Gary R.","contributorId":203932,"corporation":false,"usgs":false,"family":"Sands","given":"Gary","email":"","middleInitial":"R.","affiliations":[{"id":36763,"text":"Department of Biosystems and Agricultural Engineering, University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":732677,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Skaggs, R. Wayne","contributorId":203933,"corporation":false,"usgs":false,"family":"Skaggs","given":"R.","email":"","middleInitial":"Wayne","affiliations":[{"id":36764,"text":"Department of Biological and Agricultural Engineering, North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":732678,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Douglas-Mankin, Kyle R. 0000-0002-3155-3666","orcid":"https://orcid.org/0000-0002-3155-3666","contributorId":203927,"corporation":false,"usgs":true,"family":"Douglas-Mankin","given":"Kyle","email":"","middleInitial":"R.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":732672,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70216339,"text":"70216339 - 2018 - Managing the water-energy-food nexus: Opportunities in Central Asia","interactions":[],"lastModifiedDate":"2020-11-12T15:58:35.123594","indexId":"70216339","displayToPublicDate":"2017-12-19T09:54:26","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Managing the water-energy-food nexus: Opportunities in Central Asia","docAbstract":"This article examines impacts of infrastructure development and climate variability on economic outcomes for the Amu Darya Basin in Central Asia. It aims to identify the most economically productive mix of expanded reservoir storage for economic benefit sharing to occur, in which economic welfare of all riparians is improved. Policies examined include four combinations of storage infrastructure for each of two climate futures. An empirical optimization model is developed and applied to identify opportunities for improving the welfare of Tajikistan, Uzbekistan, Afghanistan, and Turkmenistan. The analysis 1) characterizes politically constrained and economically optimized water-use patterns for these combinations of expanded reservoir storage capacity, 2) describes Pareto-Improving packages of expanded storage capacity that could raise economic welfare for all four riparians, and accounts for impacts for each of two climate scenarios. Results indicate that a combination of targeted water storage infrastructure and efficient water allocation could produce outcomes for which the discounted net present value of benefits are favorable for each riparian. Results identify a framework to provide economic motivation for all riparians to cooperate through development of water storage infrastructure. Our findings illustrate the principle that development of water infrastructure can expand the negotiation space by which all communities can gain economic benefits in the face of limited water supply. Still, despite our optimistic findings, patient and deliberate negotiation will be required to transform potential improvements into actual gains.