A database containing more than 17,700 discharge values and ancillary hydraulic properties was assembled from summaries of discharge measurement records for 424 U.S. Geological Survey streamflow-gauging stations (stream gauges) in Texas. Each discharge exceeds the 90th-percentile daily mean streamflow as determined by period-of-record, stream-gauge-specific, flow-duration curves. Each discharge therefore is assumed to represent discharge measurement made during direct-runoff conditions. The hydraulic properties of each discharge measurement included concomitant cross-sectional flow area, water-surface top width, and reported mean velocity. Systematic and statewide investigation of these data in pursuit of regional models for the estimation of discharge and mean velocity has not been previously attempted. Generalized additive regression modeling is used to develop readily implemented procedures by end-users for estimation of discharge and mean velocity from select predictor variables at ungauged stream locations. The discharge model uses predictor variables of cross-sectional flow area, top width, stream location, mean annual precipitation, and a generalized terrain and climate index (OmegaEM) derived for a previous flood-frequency regionalization study. The mean velocity model uses predictor variables of discharge, top width, stream location, mean annual precipitation, and OmegaEM. The discharge model has an adjusted R-squared value of about 0.95 and a residual standard error (RSE) of about 0.22 base-10 logarithm (cubic meters per second); the mean velocity model has an adjusted R-squared value of about 0.67 and an RSE of about 0.063 fifth root (meters per second). Example applications and computations using both regression models are provided. - See more at: http://ascelibrary.org/doi/abs/10.1061/%28ASCE%29HE.1943-5584.0000635#sthash.jhGyPxgZ.dpuf
","publisher":"American Society of Civil Engineers","doi":"10.1061/(ASCE)HE.1943-5584.0000635","usgsCitation":"Asquith, W.H., Herrmann, G.R., and Cleveland, T., 2013, Generalized additive regression models of discharge and mean velocity associated with direct-runoff conditions in Texas: Utility of the U.S. Geological Survey discharge measurement database: Journal of Hydrologic Engineering, v. 18, no. 10, p. 1331-1348, https://doi.org/10.1061/(ASCE)HE.1943-5584.0000635.","productDescription":"18 p.","startPage":"1331","endPage":"1348","ipdsId":"IP-039500","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":340267,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"18","issue":"10","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59006066e4b0e85db3a5de0b","contributors":{"authors":[{"text":"Asquith, William H. 0000-0002-7400-1861 wasquith@usgs.gov","orcid":"https://orcid.org/0000-0002-7400-1861","contributorId":1007,"corporation":false,"usgs":true,"family":"Asquith","given":"William","email":"wasquith@usgs.gov","middleInitial":"H.","affiliations":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":518200,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Herrmann, George R.","contributorId":191361,"corporation":false,"usgs":false,"family":"Herrmann","given":"George","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":692815,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cleveland, Theodore G.","contributorId":88029,"corporation":false,"usgs":true,"family":"Cleveland","given":"Theodore G.","affiliations":[],"preferred":false,"id":692816,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70136386,"text":"70136386 - 2013 - Assessing winter cover crop nutrient uptake efficiency using a water quality simulation model","interactions":[],"lastModifiedDate":"2015-01-05T09:46:02","indexId":"70136386","displayToPublicDate":"2013-01-01T00:00:00","publicationYear":"2013","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":"Assessing winter cover crop nutrient uptake efficiency using a water quality simulation model","docAbstract":"Winter cover crops are an effective conservation management practice with potential to improve water quality. Throughout the Chesapeake Bay Watershed (CBW), which is located in the Mid-Atlantic US, winter cover crop use has been emphasized and federal and state cost-share programs are available to farmers to subsidize the cost of winter cover crop establishment. The objective of this study was to assess the long-term effect of planting winter cover crops at the watershed scale and to identify critical source areas of high nitrate export. A physically-based watershed simulation model, Soil and Water Assessment Tool (SWAT), was calibrated and validated using water quality monitoring data and satellite-based estimates of winter cover crop species performance to simulate hydrological processes and nutrient cycling over the period of 1991–2000. Multiple scenarios were developed to obtain baseline information on nitrate loading without winter cover crops planted and to investigate how nitrate loading could change with different winter cover crop planting scenarios, including different species, planting times, and implementation areas. The results indicate that winter cover crops had a negligible impact on water budget, but significantly reduced nitrate leaching to groundwater and delivery to the waterways. Without winter cover crops, annual nitrate loading was approximately 14 kg ha−1, but it decreased to 4.6–10.1 kg ha−1 with winter cover crops resulting in a reduction rate of 27–67% at the watershed scale. Rye was most effective, with a potential to reduce nitrate leaching by up to 93% with early planting at the field scale. Early planting of winter cover crops (~30 days of additional growing days) was crucial, as it lowered nitrate export by an additional ~2 kg ha−1 when compared to late planting scenarios. The effectiveness of cover cropping increased with increasing extent of winter cover crop implementation. Agricultural fields with well-drained soils and those that were more frequently used to grow corn had a higher potential for nitrate leaching and export to the waterways. This study supports the effective implement of winter cover crop programs, in part by helping to target critical pollution source areas for winter cover crop implementation.
","language":"English","publisher":"European Geosciences Union","doi":"10.5194/hessd-10-14229-2013","collaboration":"Department of Geographical Sciences, University of Maryland, College Park, MD; USDA-ARS, Hydrology and Remote Sensing Laboratory, Beltsville, MD; Dream it Do it Western New York, Jamestown, NY; USDA Forest Service, Northern Research Station, Beltsville, MD","usgsCitation":"Yeo, I., Lee, S., Sadeghi, A.M., Beeson, P.C., Hively, W., McCarty, G.W., and Lang, M.W., 2013, Assessing winter cover crop nutrient uptake efficiency using a water quality simulation model: Hydrology and Earth System Sciences, v. 10, no. 11, p. 14229-14263, https://doi.org/10.5194/hessd-10-14229-2013.","productDescription":"35 p.","startPage":"14229","endPage":"14263","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056041","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"links":[{"id":474018,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/hessd-10-14229-2013","text":"Publisher Index Page"},{"id":296981,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Chesapeake Bay Watershed","volume":"10","issue":"11","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2b3ce4b08de9379b32bf","contributors":{"authors":[{"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":537473,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lee, Sangchui","contributorId":131146,"corporation":false,"usgs":false,"family":"Lee","given":"Sangchui","email":"","affiliations":[{"id":7261,"text":"Department of Geographical Sciences, University of Maryland, College Park, MD, 20742","active":true,"usgs":false}],"preferred":false,"id":537474,"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":537475,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Beeson, Peter C.","contributorId":131148,"corporation":false,"usgs":false,"family":"Beeson","given":"Peter","email":"","middleInitial":"C.","affiliations":[{"id":7263,"text":"Dream it Do it Western New York, Jamestown, NY 14701","active":true,"usgs":false}],"preferred":false,"id":537476,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hively, W. Dean whively@usgs.gov","contributorId":4919,"corporation":false,"usgs":true,"family":"Hively","given":"W. 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It was named an Estuary of National Significance in 1995 under the U.S. Environmental Protection Agency’s (EPA) National Estuary Program (NEP), and its Comprehensive Conservation Management Plan was completed in 2002. Mobile Bay is 1,070 km2 (413 miles2) in area and 51 km (32 miles) long, making it the sixth largest estuary in the continental United States (Mobile Bay NEP, 2008). Its ecosystem provides habitat for more than 300 species of birds, 310 species of fish, 68 species of reptiles, 57 species of mammals, 40 species of amphibians, and 15 species of shrimp (Mobile Bay NEP, 1997). Mobile Bay lies between the Mississippi and Atlantic Flyways (Mobile Bay NEP, 2003). Commercial and residential development and industrial use is heavy in the Mobile Bay area. Although local growth and industrial markets support the Mobile Bay area economy, the resulting environmental damage to the very ecosystem upon which they depend remains a threat to the environment, economy, and population.
The Mobile Bay ecosystem boasts high biological diversity and productivity and supports many freshwater and saltwater species of recreational and commercial importance. The great diversity of Mobile Bay reflects the diversity of Alabama, which is home to the largest number of different plant and animal species of all states east of the Mississippi River (Stein, 2002), and is bolstered by the unique climate and geographic conditions surrounding the bay. Freshwater inflow from the Mobile-Tensaw River Delta, ranging from 60,000 to 3,700,000 gallons per second (Wallace, 1996), mixes with saltwater from the Gulf of Mexico, which enters Mobile Bay via wind and tides (Burgan and Engle, 2006). Because of the unique conditions surrounding Mobile Bay, including shallow waters, a dynamic climate, and artificial hydrologic modifications—such as the construction of the Mobile Bay Causeway in the 1920s, which serves as an unintentional barrier between Delta waters north of the Causeway and saline waters south of the Causeway, the salinity of Mobile Bay is highly variable. Mobile Bay receives an average of 165 cm (65 inches) of rain per year from tropical storms, summer thunderstorms, and winter cold fronts (Stout et al., 1998).
The climate and geography that have made Mobile Bay so rich in resources have also contributed to the threats surrounding its ecosystem. The extensive amount of rain in Mobile Bay creates large amounts of runoff, polluting the waters with fertilizers, chemicals, sediment, oil, trash, and sewage (Mobile Bay NEP, 1997). Tourism, ecotourism, recreational and commercial fishing, recreational boating, shipping, and chemical, pulp, and paper production are significant industries in Mobile Bay and the surrounding areas. Despite the approximate \\$3 billion and 55,000 jobs these industries bring into the community (Alabama Tourism Department, 2010), the growth, development, and environmental stress they create are major threats to the Mobile Bay ecosystem.
Among the nation’s states, Alabama ranks fifth in number of different species (144 endemic species), second in number of extinctions that have already occurred (90 extinct species) and fourth in number of species at risk for extinction (14.8% at risk out of 4,533 total species; Stein, 2002). Twenty-one of these threatened and endangered species are found in Mobile Bay, whose brackish waters provide a nursery area for many species of vertebrates and invertebrates. Some of these species include the Alabama sturgeon, Gulf sturgeon, heavy pigtoe mussel, inflated heel-splitter mussel, West Indian manatee, Alabama beach mouse, Perdido beach mouse, Alabama red-bellied turtle, gopher tortoise, Kemp’s ridley sea turtle, green sea turtle, loggerhead sea turtle, eastern indigo snake, flatwoods salamander, piping plover, red-cockaded woodpecker, and wood stork. Habitat loss underlies the decline of some bird species in Mobile Bay, and large mammals such as the red wolf, Florida panther, and Florida black bear are no longer found in the area. However, some rare species, such as the swallow-tailed kite, sandhill crane, and gopher tortoise can still be found (Duke and Kruczynski, 1992). The value of wetlands in Mobile Bay and the rest of the Gulf of Mexico is still being investigated. Although various monetary valuations of wetlands exist, critics remark that undervaluation of wetlands is inevitable (Mobile Bay NEP, 2008) and that estimates often do not place appropriate value on ecological services (Mitsch and Gosselink, 2000). Additionally, many estimates account only for anthropogenic values. One estimate concludes that one acre of wetlands performs \\$3,000 worth of water purification each year (Mobile Bay NEP, 1997). With more than 76,890 hectares (190,000 acres) of wetlands in the Mobile Bay area, that equates to a value exceeding one-half billion dollars every year. Tourism, fishing, boating, production, and shipping are significant industries in the Mobile Bay area. More than 90% of fish landed in recreational and commercial fishing in the bay depend on bay habitat, including wetlands, for life requirements (Mobile Bay NEP, 1997). The Port of Mobile is Alabama’s only ocean-ship port (Mobile Bay NEP, 2008). Baldwin County, on the eastern side of the bay, experienced a population increase of 75% from 1990 to 2007, with an 89% increase in housing units (Mobile Bay NEP, 2008). Development and industry support the Mobile Bay economy, but they depend on the continued health, sustainability, and production of the water and living resources of the Mobile Bay ecosystem. Wetland loss, along with other forms of environmental degradation, remains a threat to the Mobile Bay ecosystem and Mobile Bay’s socioeconomic foundation.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Emergent wetlands status and trends in the northern Gulf of Mexico: 1950-2010","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"conferenceTitle":"2013 Gulf of Mexico Alliance (GOMA) All Hands Meeting","conferenceDate":"June 25-27, 2013","conferenceLocation":"Tampa, FL","language":"English","publisher":"U.S. Geological Survey and U.S. Environmental Protection Agency","usgsCitation":"Handley, L.R., Spear, K.A., Jones, S., and Thatcher, C.A., 2013, Mobile Bay, 22 p.","productDescription":"22 p.","ipdsId":"IP-037809","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":344098,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":344097,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://gom.usgs.gov/web/Site/EmWetStatusTrends"}],"country":"United States","state":"Alabama","otherGeospatial":"Mobile Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.85,\n 30.5\n ],\n [\n -87.85,\n 30.9\n ],\n [\n -88.15,\n 30.9\n ],\n [\n -88.15,\n 30.7\n ],\n [\n -88.24,\n 30.7\n ],\n [\n -88.24,\n 30.3\n ],\n [\n -88.24,\n 30.25\n ],\n [\n -88.15,\n 30.25\n ],\n [\n -88.15,\n 30.1\n ],\n [\n -87.76,\n 30.1\n ],\n [\n -87.76,\n 30.5\n ],\n [\n -87.85,\n 30.5\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59706fdee4b0d1f9f065ab03","contributors":{"authors":[{"text":"Handley, Lawrence R. handleyl@usgs.gov","contributorId":3459,"corporation":false,"usgs":true,"family":"Handley","given":"Lawrence","email":"handleyl@usgs.gov","middleInitial":"R.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":743021,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Spear, Kathryn A. 0000-0001-8942-2856 speark@usgs.gov","orcid":"https://orcid.org/0000-0001-8942-2856","contributorId":1949,"corporation":false,"usgs":true,"family":"Spear","given":"Kathryn","email":"speark@usgs.gov","middleInitial":"A.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":705778,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jones, Stephen","contributorId":118160,"corporation":false,"usgs":true,"family":"Jones","given":"Stephen","email":"","affiliations":[],"preferred":false,"id":705779,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thatcher, Cindy A. 0000-0003-0331-071X thatcherc@usgs.gov","orcid":"https://orcid.org/0000-0003-0331-071X","contributorId":2868,"corporation":false,"usgs":true,"family":"Thatcher","given":"Cindy","email":"thatcherc@usgs.gov","middleInitial":"A.","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":423,"text":"National Geospatial Program","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":false,"id":705780,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70174138,"text":"70174138 - 2013 - Management of wetlands for wildlife","interactions":[],"lastModifiedDate":"2016-06-28T16:08:37","indexId":"70174138","displayToPublicDate":"2013-01-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Management of wetlands for wildlife","docAbstract":"Wetlands are highly productive ecosystems that provide habitat for a diversity of wildlife species and afford various ecosystem services. Managing wetlands effectively requires an understanding of basic ecosystem processes, animal and plant life history strategies, and principles of wildlife management. Management techniques that are used differ depending on target species, coastal versus interior wetlands, and available infrastructure, resources, and management objectives. Ideally, wetlands are managed as a complex, with many successional stages and hydroperiods represented in close proximity. Managing wetland wildlife typically involves manipulating water levels and vegetation in the wetland, and providing an upland buffer. Commonly, levees and water control structures are used to manipulate wetland hydrology in combination with other management techniques (e.g., disking, burning, herbicide application) to create desired plant and wildlife responses. In the United States, several conservation programs are available to assist landowners in developing wetland management infrastructure on their property. Managing wetlands to increase habitat quality for wildlife is critical, considering this ecosystem is one of the most imperiled in the world.
","language":"English","publisher":"Springer Netherlands","doi":"10.1007/978-94-007-6907-6_4","usgsCitation":"Gray, M.J., Hagy, H.M., J. Andrew Nyman, and Stafford, J.D., 2013, Management of wetlands for wildlife, p. 121-180, https://doi.org/10.1007/978-94-007-6907-6_4.","productDescription":"60 p.","startPage":"121","endPage":"180","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-038465","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":324562,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2013-08-03","publicationStatus":"PW","scienceBaseUri":"57739fb2e4b07657d1a90ce2","contributors":{"authors":[{"text":"Gray, Matthew J.","contributorId":172498,"corporation":false,"usgs":false,"family":"Gray","given":"Matthew","email":"","middleInitial":"J.","affiliations":[{"id":16989,"text":"University of Tennessee, Knoxville, TN","active":true,"usgs":false}],"preferred":false,"id":640984,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hagy, Heath M.","contributorId":172496,"corporation":false,"usgs":false,"family":"Hagy","given":"Heath","email":"","middleInitial":"M.","affiliations":[{"id":27056,"text":"Illinois Natural History Survey, Havana, IL","active":true,"usgs":false}],"preferred":false,"id":640982,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"J. Andrew Nyman","contributorId":172497,"corporation":false,"usgs":false,"family":"J. Andrew Nyman","affiliations":[{"id":16756,"text":"Louisiana State University, Baton Rouge, LA","active":true,"usgs":false}],"preferred":false,"id":640983,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stafford, Joshua D. jstafford@usgs.gov","contributorId":4267,"corporation":false,"usgs":true,"family":"Stafford","given":"Joshua","email":"jstafford@usgs.gov","middleInitial":"D.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":640981,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70178263,"text":"70178263 - 2013 - Characterization and remediation of iron(III) oxide-rich scale in a pipeline carrying acid mine drainage at Iron Mountain Mine, California, USA","interactions":[],"lastModifiedDate":"2018-08-06T12:41:56","indexId":"70178263","displayToPublicDate":"2013-01-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Characterization and remediation of iron(III) oxide-rich scale in a pipeline carrying acid mine drainage at Iron Mountain Mine, California, USA","docAbstract":"http://imwa.info/docs/imwa_2013/IMWA2013_Campbell_481.pdf
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Reliable mine water technology: Proceedings of the International Mine Water Association Annual Conference 2013, August 6-9, 2013, Golden, Colorado, USA","largerWorkSubtype":{"id":15,"text":"Monograph"},"conferenceTitle":"International Mine Water Association Annual Conference 2013","conferenceDate":"August 6-9, 2013","conferenceLocation":"Golden, CO","language":"English","publisher":"International Mine Water Association","usgsCitation":"Campbell, K.M., Alpers, C.N., Nordstrom, D.K., Blum, A.E., and Williams, A., 2013, Characterization and remediation of iron(III) oxide-rich scale in a pipeline carrying acid mine drainage at Iron Mountain Mine, California, USA, in Reliable mine water technology: Proceedings of the International Mine Water Association Annual Conference 2013, August 6-9, 2013, Golden, Colorado, USA, Golden, CO, August 6-9, 2013, p. 287-294.","productDescription":"8 p.","startPage":"287","endPage":"294","ipdsId":"IP-045300","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":331116,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"582ecff0e4b04d580bd4353a","contributors":{"editors":[{"text":"Brown, A.","contributorId":27825,"corporation":false,"usgs":true,"family":"Brown","given":"A.","affiliations":[],"preferred":false,"id":654053,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Figueroa, L.","contributorId":176780,"corporation":false,"usgs":false,"family":"Figueroa","given":"L.","affiliations":[],"preferred":false,"id":654054,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Wolkersdorfer, C.","contributorId":176947,"corporation":false,"usgs":false,"family":"Wolkersdorfer","given":"C.","affiliations":[],"preferred":false,"id":654055,"contributorType":{"id":2,"text":"Editors"},"rank":3}],"authors":[{"text":"Campbell, Kate M. 0000-0002-8715-5544 kcampbell@usgs.gov","orcid":"https://orcid.org/0000-0002-8715-5544","contributorId":1441,"corporation":false,"usgs":true,"family":"Campbell","given":"Kate","email":"kcampbell@usgs.gov","middleInitial":"M.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":653444,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Alpers, Charles N. 0000-0001-6945-7365 cnalpers@usgs.gov","orcid":"https://orcid.org/0000-0001-6945-7365","contributorId":411,"corporation":false,"usgs":true,"family":"Alpers","given":"Charles","email":"cnalpers@usgs.gov","middleInitial":"N.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":653442,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nordstrom, D. Kirk 0000-0003-3283-5136 dkn@usgs.gov","orcid":"https://orcid.org/0000-0003-3283-5136","contributorId":749,"corporation":false,"usgs":true,"family":"Nordstrom","given":"D.","email":"dkn@usgs.gov","middleInitial":"Kirk","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":false,"id":653443,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Blum, Alex E. aeblum@usgs.gov","contributorId":2845,"corporation":false,"usgs":true,"family":"Blum","given":"Alex","email":"aeblum@usgs.gov","middleInitial":"E.","affiliations":[],"preferred":true,"id":653441,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Williams, Amy","contributorId":176785,"corporation":false,"usgs":false,"family":"Williams","given":"Amy","affiliations":[],"preferred":false,"id":653445,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70138190,"text":"70138190 - 2013 - Towards a publicly available, map-based regional software tool to estimate unregulated daily streamflow at ungauged rivers","interactions":[],"lastModifiedDate":"2015-01-15T11:58:35","indexId":"70138190","displayToPublicDate":"2013-01-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1818,"text":"Geoscientific Model Development","active":true,"publicationSubtype":{"id":10}},"title":"Towards a publicly available, map-based regional software tool to estimate unregulated daily streamflow at ungauged rivers","docAbstract":"Streamflow information is critical for addressing any number of hydrologic problems. Often, streamflow information is needed at locations that are ungauged and, therefore, have no observations on which to base water management decisions. Furthermore, there has been increasing need for daily streamflow time series to manage rivers for both human and ecological functions. To facilitate negotiation between human and ecological demands for water, this paper presents the first publicly available, map-based, regional software tool to estimate historical, unregulated, daily streamflow time series (streamflow not affected by human alteration such as dams or water withdrawals) at any user-selected ungauged river location. The map interface allows users to locate and click on a river location, which then links to a spreadsheet-based program that computes estimates of daily streamflow for the river location selected. For a demonstration region in the northeast United States, daily streamflow was, in general, shown to be reliably estimated by the software tool. Estimating the highest and lowest streamflows that occurred in the demonstration region over the period from 1960 through 2004 also was accomplished but with more difficulty and limitations. The software tool provides a general framework that can be applied to other regions for which daily streamflow estimates are needed.
In the United States, estimation of flood frequency quantiles at ungauged locations has been largely based on regional regression techniques that relate measurable catchment descriptors to flood quantiles. More recently, spatial interpolation techniques of point data have been shown to be effective for predicting streamflow statistics (i.e., flood flows and low-flow indices) in ungauged catchments. Literature reports successful applications of two techniques, canonical kriging, CK (or physiographical-space-based interpolation, PSBI), and topological kriging, TK (or top-kriging). CK performs the spatial interpolation of the streamflow statistic of interest in the two-dimensional space of catchment descriptors. TK predicts the streamflow statistic along river networks taking both the catchment area and nested nature of catchments into account. It is of interest to understand how these spatial interpolation methods compare with generalized least squares (GLS) regression, one of the most common approaches to estimate flood quantiles at ungauged locations. By means of a leave-one-out cross-validation procedure, the performance of CK and TK was compared to GLS regression equations developed for the prediction of 10, 50, 100 and 500 yr floods for 61 streamgauges in the southeast United States. TK substantially outperforms GLS and CK for the study area, particularly for large catchments. The performance of TK over GLS highlights an important distinction between the treatments of spatial correlation when using regression-based or spatial interpolation methods to estimate flood quantiles at ungauged locations. The analysis also shows that coupling TK with CK slightly improves the performance of TK; however, the improvement is marginal when compared to the improvement in performance over GLS.
Research Strategies for Addressing Uncertainties builds on descriptions of research needs presented elsewhere in the book; describes current research efforts and the challenges and opportunities to reduce the uncertainties of climate change; explores ways to improve the understanding of changes in climate and hydrology; and emphasizes the use of research to inform decision making.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Assessment of climate change in southwest United States: a report prepared for the National Climate Assessment","language":"English","publisher":"Island Press","publisherLocation":"Washington, DC","usgsCitation":"Busch, D.E., Brekke, L., Averyt, K., Jardine, A., and Welling, L., 2013, Research strategies for addressing uncertainties, chap. of Assessment of climate change in southwest United States: a report prepared for the National Climate Assessment, p. 462-478.","productDescription":"17 p.","startPage":"462","endPage":"478","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true}],"links":[{"id":308340,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56012a96e4b03bc34f544426","contributors":{"editors":[{"text":"Garfin, Gregg","contributorId":97740,"corporation":false,"usgs":true,"family":"Garfin","given":"Gregg","affiliations":[],"preferred":false,"id":572847,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Jardine, Angela","contributorId":147833,"corporation":false,"usgs":false,"family":"Jardine","given":"Angela","email":"","affiliations":[],"preferred":false,"id":572848,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Merideth, Robert W.","contributorId":147834,"corporation":false,"usgs":false,"family":"Merideth","given":"Robert","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":572849,"contributorType":{"id":2,"text":"Editors"},"rank":3},{"text":"Black, Mary","contributorId":147835,"corporation":false,"usgs":false,"family":"Black","given":"Mary","email":"","affiliations":[],"preferred":false,"id":572850,"contributorType":{"id":2,"text":"Editors"},"rank":4},{"text":"LeRoy, Sarah","contributorId":147836,"corporation":false,"usgs":false,"family":"LeRoy","given":"Sarah","email":"","affiliations":[],"preferred":false,"id":572851,"contributorType":{"id":2,"text":"Editors"},"rank":5}],"authors":[{"text":"Busch, David E. dave_busch@usgs.gov","contributorId":3392,"corporation":false,"usgs":true,"family":"Busch","given":"David","email":"dave_busch@usgs.gov","middleInitial":"E.","affiliations":[],"preferred":true,"id":572842,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brekke, Levi D.","contributorId":35847,"corporation":false,"usgs":true,"family":"Brekke","given":"Levi D.","affiliations":[],"preferred":false,"id":572843,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Averyt, Kristen","contributorId":63331,"corporation":false,"usgs":true,"family":"Averyt","given":"Kristen","email":"","affiliations":[],"preferred":false,"id":572844,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jardine, Angela","contributorId":147833,"corporation":false,"usgs":false,"family":"Jardine","given":"Angela","email":"","affiliations":[],"preferred":false,"id":572845,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Welling, Leigh","contributorId":77864,"corporation":false,"usgs":true,"family":"Welling","given":"Leigh","email":"","affiliations":[],"preferred":false,"id":572846,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70156873,"text":"70156873 - 2013 - Managing the impacts of endocrine disrupting chemicals in wastewater-impacted streams","interactions":[],"lastModifiedDate":"2016-11-30T14:48:14","indexId":"70156873","displayToPublicDate":"2013-01-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Managing the impacts of endocrine disrupting chemicals in wastewater-impacted streams","docAbstract":"A revolution in analytical instrumentation circa 1920 greatly improved the ability to characterize chemical substances [1]. This analytical foundation resulted in an unprecedented explosion in the design and production of synthetic chemicals during and post-World War II. What is now often referred to as the 2nd Chemical Revolution has provided substantial societal benefits; with modern chemical design and manufacturing supporting dramatic advances in medicine, increased food production, and expanding gross domestic products at the national and global scales as well as improved health, longevity, and lifestyle convenience at the individual scale [1, 2]. Presently, the chemical industry is the largest manufacturing sector in the United States (U.S.) and the second largest in Europe and Japan, representing approximately 5% of the Gross Domestic Product (GDP) in each of these countries [2]. At the turn of the 21st century, the chemical industry was estimated to be worth more than $1.6 trillion and to employ over 10 million people, globally [2]. During the first half of the 20th century, the chemical sector expanded rapidly, the chemical industry enjoyed a generally positive status in society, and chemicals were widely appreciated as fundamental to individual and societal quality of life. Starting in the 1960s, however, the environmental costs associated with the chemical industry increasingly became the focus, due in part to the impact of books like “Silent Spring” [3] and “Our Stolen Future” [4] and to a number of highly publicized environmental disasters. Galvanizing chemical industry disasters included the 1976 dioxin leak north of Milan, Italy, the Love Canal evacuations in Niagara, New York beginning in 1978, and the Union Carbide leak in Bhopal, India in 1984 [2]. Understanding the environmental impact of synthetic compounds is essential to any informed assessment of net societal benefit, for the simple reason that any chemical substance that is in commercial production or use will eventually find its way to the environment [5]. Not surprisingly given the direct link to profits, manufacturers intensely investigate and routinely document the potential benefits of new chemicals and chemical products. In contrast, the environmental risks associated with chemical production and uses are often investigated less intensely and are poorly communicated. An imbalance in the risk-benefit analysis of any synthetic chemical substance or naturally occurring chemical, which presence and concentration in the environment largely reflects human activities and management, is a particular concern owing to the fundamental link between chemistry and biology. Biological organisms are intrinsically a homeostatic balance of innumerable internal and external chemical interactions and, thus, inherently sensitive to changes in the external chemical environment.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Current perspectives in contaminant hydrology and water resources sustainability","language":"English","publisher":"InTech","doi":"10.5772/54337","usgsCitation":"Journey, C.A., Bradley, P.M., and Kolpin, D.W., 2013, Managing the impacts of endocrine disrupting chemicals in wastewater-impacted streams, chap. of Current perspectives in contaminant hydrology and water resources sustainability, p. 3-26, https://doi.org/10.5772/54337.","productDescription":"24 p.","startPage":"3","endPage":"26","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":474020,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5772/54337","text":"Publisher Index Page"},{"id":307763,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationDate":"2013-02-27","publicationStatus":"PW","scienceBaseUri":"560bb6c6e4b058f706e53d4b","contributors":{"editors":[{"text":"Bradley, Paul M. 0000-0001-7522-8606 pbradley@usgs.gov","orcid":"https://orcid.org/0000-0001-7522-8606","contributorId":361,"corporation":false,"usgs":true,"family":"Bradley","given":"Paul","email":"pbradley@usgs.gov","middleInitial":"M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":570913,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Journey, Celeste A. 0000-0002-2284-5851 cjourney@usgs.gov","orcid":"https://orcid.org/0000-0002-2284-5851","contributorId":2617,"corporation":false,"usgs":true,"family":"Journey","given":"Celeste","email":"cjourney@usgs.gov","middleInitial":"A.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":false,"id":570910,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bradley, Paul M. 0000-0001-7522-8606 pbradley@usgs.gov","orcid":"https://orcid.org/0000-0001-7522-8606","contributorId":361,"corporation":false,"usgs":true,"family":"Bradley","given":"Paul","email":"pbradley@usgs.gov","middleInitial":"M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":570911,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kolpin, Dana W. 0000-0002-3529-6505 dwkolpin@usgs.gov","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":1239,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana","email":"dwkolpin@usgs.gov","middleInitial":"W.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":570912,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70156522,"text":"70156522 - 2013 - Interactions among hydrogeomorphology, vegetation, and nutrient biogeochemistry in floodplain ecosystems","interactions":[],"lastModifiedDate":"2020-10-16T14:53:06.263227","indexId":"70156522","displayToPublicDate":"2013-01-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"subseriesTitle":"Treatise on Geomorphology","title":"Interactions among hydrogeomorphology, vegetation, and nutrient biogeochemistry in floodplain ecosystems","docAbstract":"Hydrogeomorphic, vegetative, and biogeochemical processes interact in floodplains resulting in great complexity that provides opportunities to better understand linkages among physical and biological processes in ecosystems. Floodplains and their associated river systems are structured by four-dimensional gradients of hydrogeomorphology: longitudinal, lateral, vertical, and temporal components. These four dimensions create dynamic hydrologic and geomorphologic mosaics that have a large imprint on the vegetation and nutrient biogeochemistry of floodplains. Plant physiology, population dynamics, community structure, and productivity are all very responsive to floodplain hydrogeomorphology. The strength of this relationship between vegetation and hydrogeomorphology is evident in the use of vegetation as an indicator of hydrogeomorphic processes. However, vegetation also influences hydrogeomorphology by modifying hydraulics and sediment entrainment and deposition that typically stabilize geomorphic patterns. Nitrogen and phosphorus biogeochemistry commonly influence plant productivity and community composition, although productivity is not limited by nutrient availability in all floodplains. Conversely, vegetation influences nutrient biogeochemistry through direct uptake and storage as well as production of organic matter that regulates microbial biogeochemical processes. The biogeochemistries of nitrogen and phosphorus cycling are very sensitive to spatial and temporal variation in hydrogeomorphology, in particular floodplain wetness and sedimentation. The least-studied interaction is the direct effect of biogeochemistry on hydrogeomorphology, but the control of nutrient availability over organic matter decomposition and thus soil permeability and elevation is likely important. Biogeochemistry also has the more documented but indirect control of hydrogeomorphology through regulation of plant biomass. In summary, the defining characteristics of floodplain ecosystems are determined by the many interactions among physical and biological processes. Conservation and restoration of the valuable ecosystem services that floodplains provide depend on improved understanding and predictive models of interactive system controls and behavior.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Treatise on geomorphology","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Elselvier","doi":"10.1016/B978-0-12-374739-6.00338-9","usgsCitation":"Noe, G.B., 2013, Interactions among hydrogeomorphology, vegetation, and nutrient biogeochemistry in floodplain ecosystems, chap. of Treatise on geomorphology, v. 12, p. 307-321, https://doi.org/10.1016/B978-0-12-374739-6.00338-9.","productDescription":"15 p.","startPage":"307","endPage":"321","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":307238,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55dc402fe4b0518e354d110b","contributors":{"editors":[{"text":"Shroder, John F.","contributorId":113549,"corporation":false,"usgs":true,"family":"Shroder","given":"John F.","affiliations":[],"preferred":false,"id":569384,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Noe, G. B.","contributorId":146903,"corporation":false,"usgs":true,"family":"Noe","given":"G.","email":"","middleInitial":"B.","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":569382,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70154975,"text":"70154975 - 2013 - Valley plugs, land use, and phytogeomorphic response: Chapter 14","interactions":[],"lastModifiedDate":"2015-07-22T11:31:24","indexId":"70154975","displayToPublicDate":"2013-01-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"14","title":"Valley plugs, land use, and phytogeomorphic response: Chapter 14","docAbstract":"Anthropogenic alteration of fluvial systems can disrupt functional processes that provide valuable ecosystem services. Channelization alters fluvial parameters and the connectivity of river channels to their floodplains which is critical for productivity, nutrient cycling, flood control, and biodiversity. The effects of channelization can be exacerbated by local geology and land-use activities, resulting in dramatic geomorphic readjustments including the formation of valley plugs. Considerable variation in the response of abiotic processes, including surface hydrology, subsurface hydrology, and sedimentation dynamics, to channelization and the formation of valley plugs. Altered abiotic processes associated with these geomorphic features and readjustments influence biotic processes including species composition, abundance, and successional processes. Considerable interest exists for restoring altered fluvial systems and their floodplains because of their social and ecological importance. Understanding abiotic and biotic responses of channelization and valley-plug formation within the context of the watershed is essential to successful restoration. This chapter focuses on the primary causes of valley-plug formation, resulting fluvial-geomorphic responses, vegetation responses, and restoration and research needs for these systems.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Treatise on Geomorphology: Ecogeomorphology","language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-12-374739-6.00330-4","usgsCitation":"Pierce, A.R., and King, S.L., 2013, Valley plugs, land use, and phytogeomorphic response: Chapter 14, chap. 14 of Treatise on Geomorphology: Ecogeomorphology, v. 12, p. 221-235, https://doi.org/10.1016/B978-0-12-374739-6.00330-4.","productDescription":"15 p.","startPage":"221","endPage":"235","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-025579","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":305892,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55b0beafe4b09a3b01b530ab","contributors":{"editors":[{"text":"Shroder, John F.","contributorId":145788,"corporation":false,"usgs":false,"family":"Shroder","given":"John","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":565302,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Pierce, Aaron R.","contributorId":94421,"corporation":false,"usgs":false,"family":"Pierce","given":"Aaron","email":"","middleInitial":"R.","affiliations":[{"id":33463,"text":"Nicholls State University, Thibodaux, LA","active":true,"usgs":false}],"preferred":false,"id":565301,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"King, Sammy L. 0000-0002-5364-6361 sking@usgs.gov","orcid":"https://orcid.org/0000-0002-5364-6361","contributorId":557,"corporation":false,"usgs":true,"family":"King","given":"Sammy","email":"sking@usgs.gov","middleInitial":"L.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":564454,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70178333,"text":"70178333 - 2013 - Assessing and measuring wetland hydrology","interactions":[],"lastModifiedDate":"2016-11-17T12:52:40","indexId":"70178333","displayToPublicDate":"2013-01-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Assessing and measuring wetland hydrology","docAbstract":"Virtually all ecological processes that occur in wetlands are influenced by the water that flows to, from, and within these wetlands. This chapter provides the “how-to” information for quantifying the various source and loss terms associated with wetland hydrology. The chapter is organized from a water-budget perspective, with sections associated with each of the water-budget components that are common in most wetland settings. Methods for quantifying the water contained within the wetland are presented first, followed by discussion of each separate component. Measurement accuracy and sources of error are discussed for each of the methods presented, and a separate section discusses the cumulative error associated with determining a water budget for a wetland. Exercises and field activities will provide hands-on experience that will facilitate greater understanding of these processes.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Wetland techniques, Volume 1 Foundations","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Springer","doi":"10.1007/978-94-007-6860-4_3","usgsCitation":"Rosenberry, D.O., and Hayashi, M., 2013, Assessing and measuring wetland hydrology, chap. of Wetland techniques, Volume 1 Foundations, p. 87-225, https://doi.org/10.1007/978-94-007-6860-4_3.","productDescription":"138 p.","startPage":"87","endPage":"225","ipdsId":"IP-042489","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":331098,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2013-08-04","publicationStatus":"PW","scienceBaseUri":"582ecff0e4b04d580bd43538","contributors":{"editors":[{"text":"Anderson, James T.","contributorId":28071,"corporation":false,"usgs":false,"family":"Anderson","given":"James","email":"","middleInitial":"T.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":654020,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Davis, Craig A.","contributorId":171490,"corporation":false,"usgs":false,"family":"Davis","given":"Craig","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":654021,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"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":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":653621,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hayashi, Masaki","contributorId":176832,"corporation":false,"usgs":false,"family":"Hayashi","given":"Masaki","affiliations":[],"preferred":false,"id":653622,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70188335,"text":"70188335 - 2013 - Establishing an operational waterhole monitoring system using satellite data and hydrologic modelling: Application in the pastoral regions of East Africa","interactions":[],"lastModifiedDate":"2017-06-06T13:38:58","indexId":"70188335","displayToPublicDate":"2013-01-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5413,"text":"Pastoralism: Research, Policy and Practice","active":true,"publicationSubtype":{"id":10}},"title":"Establishing an operational waterhole monitoring system using satellite data and hydrologic modelling: Application in the pastoral regions of East Africa","docAbstract":"Timely information on the availability of water and forage is important for the sustainable development of pastoral regions. The lack of such information increases the dependence of pastoral communities on perennial sources, which often leads to competition and conflicts. The provision of timely information is a challenging task, especially due to the scarcity or non-existence of conventional station-based hydrometeorological networks in the remote pastoral regions. A multi-source water balance modelling approach driven by satellite data was used to operationally monitor daily water level fluctuations across the pastoral regions of northern Kenya and southern Ethiopia. Advanced Spaceborne Thermal Emission and Reflection Radiometer data were used for mapping and estimating the surface area of the waterholes. Satellite-based rainfall, modelled run-off and evapotranspiration data were used to model daily water level fluctuations. Mapping of waterholes was achieved with 97% accuracy. Validation of modelled water levels with field-installed gauge data demonstrated the ability of the model to capture the seasonal patterns and variations. Validation results indicate that the model explained 60% of the observed variability in water levels, with an average root-mean-squared error of 22%. Up-to-date information on rainfall, evaporation, scaled water depth and condition of the waterholes is made available daily in near-real time via the Internet (http://watermon.tamu.edu). Such information can be used by non-governmental organizations, governmental organizations and other stakeholders for early warning and decision making. This study demonstrated an integrated approach for establishing an operational waterhole monitoring system using multi-source satellite data and hydrologic modelling.
","language":"English","publisher":"Springer","doi":"10.1186/2041-7136-3-20","usgsCitation":"Senay, G., Velpuri, N.M., Alemu, H., Pervez, S., Asante, K.O., Karuki, G., Taa, A., and Angerer, J., 2013, Establishing an operational waterhole monitoring system using satellite data and hydrologic modelling: Application in the pastoral regions of East Africa: Pastoralism: Research, Policy and Practice, v. 3, p. 1-16, https://doi.org/10.1186/2041-7136-3-20.","productDescription":"Article 20; 16 p.","startPage":"1","endPage":"16","ipdsId":"IP-049147","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":474022,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/2041-7136-3-20","text":"Publisher Index Page"},{"id":342154,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Africa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 33,\n -0\n ],\n [\n 42.0556640625,\n -0\n ],\n [\n 42.0556640625,\n 9\n ],\n [\n 33,\n 9\n ],\n [\n 33,\n -0\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"3","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5937bf30e4b0f6c2d0d9c7a0","contributors":{"authors":[{"text":"Senay, Gabriel B. 0000-0002-8810-8539 senay@usgs.gov","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":152206,"corporation":false,"usgs":true,"family":"Senay","given":"Gabriel B.","email":"senay@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":697260,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Velpuri, Naga Manohar 0000-0002-6370-1926 nvelpuri@usgs.gov","orcid":"https://orcid.org/0000-0002-6370-1926","contributorId":166813,"corporation":false,"usgs":true,"family":"Velpuri","given":"Naga","email":"nvelpuri@usgs.gov","middleInitial":"Manohar","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":697261,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Alemu, Henok","contributorId":124527,"corporation":false,"usgs":false,"family":"Alemu","given":"Henok","email":"","affiliations":[{"id":5087,"text":"Geographic Information Science Center of Excellence (GIScCE), South Dakota State University, Brookings, USA","active":true,"usgs":false}],"preferred":false,"id":697262,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pervez, Shahriar Md 0000-0003-3417-1871 shahriar.pervez.ctr@usgs.gov","orcid":"https://orcid.org/0000-0003-3417-1871","contributorId":192362,"corporation":false,"usgs":true,"family":"Pervez","given":"Shahriar Md","email":"shahriar.pervez.ctr@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":697263,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Asante, Kwabena O 0000-0001-5408-1852","orcid":"https://orcid.org/0000-0001-5408-1852","contributorId":192649,"corporation":false,"usgs":true,"family":"Asante","given":"Kwabena","email":"","middleInitial":"O","affiliations":[],"preferred":true,"id":697264,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Karuki, Gatarwa","contributorId":192650,"corporation":false,"usgs":false,"family":"Karuki","given":"Gatarwa","email":"","affiliations":[],"preferred":false,"id":697265,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Taa, Asefa","contributorId":192651,"corporation":false,"usgs":false,"family":"Taa","given":"Asefa","email":"","affiliations":[],"preferred":false,"id":697266,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Angerer, Jay","contributorId":172794,"corporation":false,"usgs":false,"family":"Angerer","given":"Jay","email":"","affiliations":[],"preferred":false,"id":697267,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70189198,"text":"70189198 - 2013 - Use of gene-expression programming to estimate Manning’s roughness coefficient for high gradient streams","interactions":[],"lastModifiedDate":"2017-07-05T17:08:05","indexId":"70189198","displayToPublicDate":"2013-01-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3721,"text":"Water Resources Management","onlineIssn":"1573-1650","printIssn":"0920-4741","active":true,"publicationSubtype":{"id":10}},"title":"Use of gene-expression programming to estimate Manning’s roughness coefficient for high gradient streams","docAbstract":"Manning’s roughness coefficient (n) has been widely used in the estimation of flood discharges or depths of flow in natural channels. Therefore, the selection of appropriate Manning’s nvalues is of paramount importance for hydraulic engineers and hydrologists and requires considerable experience, although extensive guidelines are available. Generally, the largest source of error in post-flood estimates (termed indirect measurements) is due to estimates of Manning’s n values, particularly when there has been minimal field verification of flow resistance. This emphasizes the need to improve methods for estimating n values. The objective of this study was to develop a soft computing model in the estimation of the Manning’s n values using 75 discharge measurements on 21 high gradient streams in Colorado, USA. The data are from high gradient (S > 0.002 m/m), cobble- and boulder-bed streams for within bank flows. This study presents Gene-Expression Programming (GEP), an extension of Genetic Programming (GP), as an improved approach to estimate Manning’s roughness coefficient for high gradient streams. This study uses field data and assessed the potential of gene-expression programming (GEP) to estimate Manning’s n values. GEP is a search technique that automatically simplifies genetic programs during an evolutionary processes (or evolves) to obtain the most robust computer program (e.g., simplify mathematical expressions, decision trees, polynomial constructs, and logical expressions). Field measurements collected by Jarrett (J Hydraulic Eng ASCE 110: 1519–1539, 1984) were used to train the GEP network and evolve programs. The developed network and evolved programs were validated by using observations that were not involved in training. GEP and ANN-RBF (artificial neural network-radial basis function) models were found to be substantially more effective (e.g., R2 for testing/validation of GEP and RBF-ANN is 0.745 and 0.65, respectively) than Jarrett’s (J Hydraulic Eng ASCE 110: 1519–1539, 1984) equation (R2 for testing/validation equals 0.58) in predicting the Manning’s n.
","language":"English","publisher":"Springer","doi":"10.1007/s11269-012-0211-1","usgsCitation":"Azamathulla, H., and Jarrett, R.D., 2013, Use of gene-expression programming to estimate Manning’s roughness coefficient for high gradient streams: Water Resources Management, v. 27, no. 3, p. 715-729, https://doi.org/10.1007/s11269-012-0211-1.","productDescription":"15 p.","startPage":"715","endPage":"729","ipdsId":"IP-023452","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":343376,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2012-11-27","publicationStatus":"PW","scienceBaseUri":"595dfab8e4b0d1f9f056a7b2","contributors":{"authors":[{"text":"Azamathulla, H.","contributorId":194211,"corporation":false,"usgs":false,"family":"Azamathulla","given":"H.","email":"","affiliations":[],"preferred":false,"id":703509,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jarrett, Robert D. rjarrett@usgs.gov","contributorId":2260,"corporation":false,"usgs":true,"family":"Jarrett","given":"Robert","email":"rjarrett@usgs.gov","middleInitial":"D.","affiliations":[],"preferred":true,"id":703510,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70178489,"text":"70178489 - 2013 - Integrated hydrologic modeling of a transboundary aquifer system —Lower Rio Grande","interactions":[],"lastModifiedDate":"2017-01-20T10:47:07","indexId":"70178489","displayToPublicDate":"2013-01-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Integrated hydrologic modeling of a transboundary aquifer system —Lower Rio Grande","docAbstract":"For more than 30 years the agreements developed for the aquifer systems of the lower Rio Grande and related river compacts of the Rio Grande River have evolved into a complex setting of transboundary conjunctive use. The conjunctive use now includes many facets of water rights, water use, and emerging demands between the states of New Mexico and Texas, the United States and Mexico, and various water-supply agencies. The analysis of the complex relations between irrigation and streamflow supplyand-demand components and the effects of surface-water and groundwater use requires an integrated hydrologic model to track all of the use and movement of water. MODFLOW with the Farm Process (MFFMP) provides the integrated approach needed to assess the stream-aquifer interactions that are dynamically affected by irrigation demands on streamflow allotments that are supplemented with groundwater pumpage. As a first step to the ongoing full implementation of MF-FMP by the USGS, the existing model (LRG_2007) was modified to include some FMP features, demonstrating the ability to simulate the existing streamflow-diversion relations known as the D2 and D3 curves, departure of downstream deliveries from these curves during low allocation years and with increasing efficiency upstream, and the dynamic relation between surface-water conveyance and estimates of pumpage and recharge. This new MF-FMP modeling framework can now internally analyze complex relations within the Lower Rio Grande Hydrologic Model (LRGHM_2011) that previous techniques had limited ability to assess.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"MODFLOW and more 2013--Translating science into practice","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Colorado School of Mines, Integrated Groundwater Modeling Center","publisherLocation":"Golden, CO","usgsCitation":"Hanson, R.T., Schmid, W., Knight, J.E., and Maddock, T., 2013, Integrated hydrologic modeling of a transboundary aquifer system —Lower Rio Grande, in MODFLOW and more 2013--Translating science into practice, p. 57-61.","productDescription":"5 p.","startPage":"57","endPage":"61","ipdsId":"IP-042752","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":333539,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58833023e4b0d0023163779a","contributors":{"authors":[{"text":"Hanson, Randall T. 0000-0002-9819-7141 rthanson@usgs.gov","orcid":"https://orcid.org/0000-0002-9819-7141","contributorId":801,"corporation":false,"usgs":true,"family":"Hanson","given":"Randall","email":"rthanson@usgs.gov","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":654190,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schmid, Wolfgang","contributorId":140408,"corporation":false,"usgs":false,"family":"Schmid","given":"Wolfgang","email":"","affiliations":[{"id":6624,"text":"University of Arizona, Laboratory of Tree-Ring Research","active":true,"usgs":false}],"preferred":false,"id":654192,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Knight, Jacob E. 0000-0003-0271-9011 jknight@usgs.gov","orcid":"https://orcid.org/0000-0003-0271-9011","contributorId":5143,"corporation":false,"usgs":true,"family":"Knight","given":"Jacob","email":"jknight@usgs.gov","middleInitial":"E.","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":654189,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Maddock, Thomas III","contributorId":32983,"corporation":false,"usgs":true,"family":"Maddock","given":"Thomas","suffix":"III","affiliations":[],"preferred":false,"id":654191,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70188073,"text":"70188073 - 2013 - Simulating the water budget of a Prairie Potholes complex from LiDAR and hydrological models in North Dakota, USA","interactions":[],"lastModifiedDate":"2017-05-30T12:51:09","indexId":"70188073","displayToPublicDate":"2013-01-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1927,"text":"Hydrological Sciences Journal","active":true,"publicationSubtype":{"id":10}},"title":"Simulating the water budget of a Prairie Potholes complex from LiDAR and hydrological models in North Dakota, USA","docAbstract":"Hydrological processes of the wetland complex in the Prairie Pothole Region (PPR) are difficult to model, partly due to a lack of wetland morphology data. We used Light Detection And Ranging (LiDAR) data sets to derive wetland features; we then modelled rainfall, snowfall, snowmelt, runoff, evaporation, the “fill-and-spill” mechanism, shallow groundwater loss, and the effect of wet and dry conditions. For large wetlands with a volume greater than thousands of cubic metres (e.g. about 3000 m3), the modelled water volume agreed fairly well with observations; however, it did not succeed for small wetlands (e.g. volume less than 450 m3). Despite the failure for small wetlands, the modelled water area of the wetland complex coincided well with interpretation of aerial photographs, showing a linear regression with R2 of around 0.80 and a mean average error of around 0.55 km2. The next step is to improve the water budget modelling for small wetlands.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/02626667.2013.831419","usgsCitation":"Huang, S., Young, C., Abdul-Aziz, O.I., Dahal, D., Feng, M., and Liu, S., 2013, Simulating the water budget of a Prairie Potholes complex from LiDAR and hydrological models in North Dakota, USA: Hydrological Sciences Journal, v. 58, no. 7, p. 1434-1444, https://doi.org/10.1080/02626667.2013.831419.","productDescription":"11 p.","startPage":"1434","endPage":"1444","ipdsId":"IP-043188","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":474025,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/02626667.2013.831419","text":"Publisher Index Page"},{"id":341846,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Dakota","volume":"58","issue":"7","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"592e84c9e4b092b266f10dc8","contributors":{"authors":[{"text":"Huang, Shengli shuang@usgs.gov","contributorId":1926,"corporation":false,"usgs":true,"family":"Huang","given":"Shengli","email":"shuang@usgs.gov","affiliations":[],"preferred":true,"id":696403,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Young, Claudia 0000-0002-0859-7206 claudia.young.ctr@usgs.gov","orcid":"https://orcid.org/0000-0002-0859-7206","contributorId":191382,"corporation":false,"usgs":true,"family":"Young","given":"Claudia","email":"claudia.young.ctr@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":696401,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Abdul-Aziz, Omar I.","contributorId":192386,"corporation":false,"usgs":false,"family":"Abdul-Aziz","given":"Omar","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":696402,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dahal, Devendra 0000-0001-9594-1249 ddahal@usgs.gov","orcid":"https://orcid.org/0000-0001-9594-1249","contributorId":5622,"corporation":false,"usgs":true,"family":"Dahal","given":"Devendra","email":"ddahal@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":696405,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Feng, Min","contributorId":75370,"corporation":false,"usgs":true,"family":"Feng","given":"Min","email":"","affiliations":[],"preferred":false,"id":696406,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Liu, Shuguang 0000-0002-6027-3479 sliu@usgs.gov","orcid":"https://orcid.org/0000-0002-6027-3479","contributorId":147403,"corporation":false,"usgs":true,"family":"Liu","given":"Shuguang","email":"sliu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":696404,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70189675,"text":"70189675 - 2013 - Persistence and potential effects of complex organic contaminant mixtures in wastewater-impacted streams","interactions":[],"lastModifiedDate":"2021-05-28T14:54:00.795953","indexId":"70189675","displayToPublicDate":"2013-01-01T00:00:00","publicationYear":"2013","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":"Persistence and potential effects of complex organic contaminant mixtures in wastewater-impacted streams","docAbstract":"Natural and synthetic organic contaminants in municipal wastewater treatment plant (WWTP) effluents can cause ecosystem impacts, raising concerns about their persistence in receiving streams. In this study, Lagrangian sampling, in which the same approximate parcel of water is tracked as it moves downstream, was conducted at Boulder Creek, Colorado and Fourmile Creek, Iowa to determine in-stream transport and attenuation of organic contaminants discharged from two secondary WWTPs. Similar stream reaches were evaluated, and samples were collected at multiple sites during summer and spring hydrologic conditions. Travel times to the most downstream (7.4 km) site in Boulder Creek were 6.2 h during the summer and 9.3 h during the spring, and to the Fourmile Creek 8.4 km downstream site times were 18 and 8.8 h, respectively. Discharge was measured at each site, and integrated composite samples were collected and analyzed for >200 organic contaminants including metal complexing agents, nonionic surfactant degradates, personal care products, pharmaceuticals, steroidal hormones, and pesticides. The highest concentration (>100 μg L–1) compounds detected in both WWTP effluents were ethylenediaminetetraacetic acid and 4-nonylphenolethoxycarboxylate oligomers, both of which persisted for at least 7 km downstream from the WWTPs. Concentrations of pharmaceuticals were lower (<1 μg L–1), and several compounds, including carbamazepine and sulfamethoxazole, were detected throughout the study reaches. After accounting for in-stream dilution, a complex mixture of contaminants showed little attenuation and was persistent in the receiving streams at concentrations with potential ecosystem implications.
","language":"English","publisher":"ACS","doi":"10.1021/es303720g","usgsCitation":"Barber, L.B., Keefe, S.H., Brown, G.K., Furlong, E.T., Gray, J.L., Kolpin, D.W., Meyer, M.T., Sandstrom, M.W., and Zaugg, S.D., 2013, Persistence and potential effects of complex organic contaminant mixtures in wastewater-impacted streams: Environmental Science & Technology, v. 47, no. 5, p. 2177-2188, https://doi.org/10.1021/es303720g.","productDescription":"12 p.","startPage":"2177","endPage":"2188","ipdsId":"IP-042619","costCenters":[{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":344082,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Iowa","otherGeospatial":"Boulder Creek, Fourmile Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.625,\n 41.75\n ],\n [\n -93.5,\n 41.75\n ],\n [\n -93.5,\n 41.625\n ],\n [\n -93.625,\n 41.625\n ],\n [\n -93.625,\n 41.75\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.191667,\n 40.09166\n ],\n [\n -105.075,\n 40.09166\n ],\n [\n -105.075,\n 40.01667\n ],\n [\n -105.191667,\n 40.01667\n ],\n [\n -105.191667,\n 40.09166\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"47","issue":"5","noUsgsAuthors":false,"publicationDate":"2013-02-11","publicationStatus":"PW","scienceBaseUri":"59706fbde4b0d1f9f065a918","contributors":{"authors":[{"text":"Barber, Larry B. 0000-0002-0561-0831 lbbarber@usgs.gov","orcid":"https://orcid.org/0000-0002-0561-0831","contributorId":921,"corporation":false,"usgs":true,"family":"Barber","given":"Larry","email":"lbbarber@usgs.gov","middleInitial":"B.","affiliations":[{"id":5044,"text":"National Research Program - 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Eastern Branch","active":true,"usgs":true},{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true}],"preferred":true,"id":705736,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kolpin, Dana W. 0000-0002-3529-6505 dwkolpin@usgs.gov","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":1239,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana","email":"dwkolpin@usgs.gov","middleInitial":"W.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":705737,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Meyer, Michael T. 0000-0001-6006-7985 mmeyer@usgs.gov","orcid":"https://orcid.org/0000-0001-6006-7985","contributorId":866,"corporation":false,"usgs":true,"family":"Meyer","given":"Michael","email":"mmeyer@usgs.gov","middleInitial":"T.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":705738,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sandstrom, Mark W. 0000-0003-0006-5675 sandstro@usgs.gov","orcid":"https://orcid.org/0000-0003-0006-5675","contributorId":706,"corporation":false,"usgs":true,"family":"Sandstrom","given":"Mark","email":"sandstro@usgs.gov","middleInitial":"W.","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true},{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true}],"preferred":true,"id":705739,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Zaugg, Steven D. sdzaugg@usgs.gov","contributorId":768,"corporation":false,"usgs":true,"family":"Zaugg","given":"Steven","email":"sdzaugg@usgs.gov","middleInitial":"D.","affiliations":[],"preferred":true,"id":705740,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70195369,"text":"70195369 - 2013 - An evaluation of automated GIS tools for delineating karst sinkholes and closed depressions from 1-meter LIDAR-derived digital elevation data","interactions":[],"lastModifiedDate":"2018-02-12T12:41:08","indexId":"70195369","displayToPublicDate":"2013-01-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"An evaluation of automated GIS tools for delineating karst sinkholes and closed depressions from 1-meter LIDAR-derived digital elevation data","docAbstract":"LiDAR (Light Detection and Ranging) surveys of karst terrains provide high-resolution digital elevation models (DEMs) that are particularly useful for mapping sinkholes. In this study, we used automated processing tools within ArcGIS (v. 10.0) operating on a 1.0 m resolution LiDAR DEM in order to delineate sinkholes and closed depressions in the Boyce 7.5 minute quadrangle located in the northern Shenandoah Valley of Virginia. The results derived from the use of the automated tools were then compared with depressions manually delineated by a geologist. Manual delineation of closed depressions was conducted using a combination of 1.0 m DEM hillshade, slopeshade, aerial imagery, and Topographic Position Index (TPI) rasters. The most effective means of visualizing depressions in the GIS was using an overlay of the partially transparent TPI raster atop the slopeshade raster at 1.0 m resolution. Manually identified depressions were subsequently checked using aerial imagery to screen for false positives, and targeted ground-truthing was undertaken in the field. The automated tools that were utilized include the routines in ArcHydro Tools (v. 2.0) for prescreening, evaluating, and selecting sinks and depressions as well as thresholding, grouping, and assessing depressions from the TPI raster. Results showed that the automated delineation of sinks and depressions within the ArcHydro tools was highly dependent upon pre-conditioning of the DEM to produce \"hydrologically correct\" surface flow routes. Using stream vectors obtained from the National Hydrologic Dataset alone to condition the flow routing was not sufficient to produce a suitable drainage network, and numerous artificial depressions were generated where roads, railways, or other manmade structures acted as flow barriers in the elevation model. Additional conditioning of the DEM with drainage paths across these barriers was required prior to automated 2delineation of sinks and depressions. In regions where the DEM had been properly conditioned, the tools for automated delineation performed reasonably well as compared to the manually delineated depressions, but generally overestimated the number of depressions thus necessitating manual filtering of the final results. Results from the TPI thresholding analysis were not dependent on DEM pre-conditioning, but the ability to extract meaningful depressions depended on careful assessment of analysis scale and TPI thresholding.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Sinkholes and the Engineering and Environmental Impacts of Karst: Proceedings of the Thirteenth Multidisciplinary Conference","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"National Cave and Karst Research Insititute","doi":"10.5038/9780979542275.1156","usgsCitation":"Doctor, D.H., and Young, J.A., 2013, An evaluation of automated GIS tools for delineating karst sinkholes and closed depressions from 1-meter LIDAR-derived digital elevation data, in Sinkholes and the Engineering and Environmental Impacts of Karst: Proceedings of the Thirteenth Multidisciplinary Conference, p. 449-458, https://doi.org/10.5038/9780979542275.1156.","productDescription":"9 p.","startPage":"449","endPage":"458","ipdsId":"IP-044120","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":488751,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://digitalcommons.usf.edu/sinkhole_2013/Proceedings/Mapping_Management/8","text":"External Repository"},{"id":351475,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afef06de4b0da30c1bfc7e6","contributors":{"authors":[{"text":"Doctor, Daniel H. 0000-0002-8338-9722 dhdoctor@usgs.gov","orcid":"https://orcid.org/0000-0002-8338-9722","contributorId":2037,"corporation":false,"usgs":true,"family":"Doctor","given":"Daniel","email":"dhdoctor@usgs.gov","middleInitial":"H.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":728192,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Young, John A. 0000-0002-4500-3673 jyoung@usgs.gov","orcid":"https://orcid.org/0000-0002-4500-3673","contributorId":3777,"corporation":false,"usgs":true,"family":"Young","given":"John","email":"jyoung@usgs.gov","middleInitial":"A.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":728193,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70187702,"text":"70187702 - 2013 - Projecting the land cover change and its environmental impacts in the Cedar River Basin in the Midwestern United States","interactions":[],"lastModifiedDate":"2017-05-31T16:13:52","indexId":"70187702","displayToPublicDate":"2013-01-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1562,"text":"Environmental Research Letters","active":true,"publicationSubtype":{"id":10}},"title":"Projecting the land cover change and its environmental impacts in the Cedar River Basin in the Midwestern United States","docAbstract":"The physical surface of the Earth is in constant change due to climate forcing and human activities. In the Midwestern United States, urban area, farmland, and dedicated energy crop (e.g., switchgrass) cultivation are predicted to expand in the coming decades, which will lead to changes in hydrological processes. This study is designed to (1) project the land use and land cover (LULC) by mid-century using the FORecasting SCEnarios of future land-use (FORE-SCE) model under the A1B greenhouse gas emission scenario (future condition) and (2) assess its potential impacts on the water cycle and water quality against the 2001 baseline condition in the Cedar River Basin using the physically based soil and water assessment tool (SWAT). We compared the baseline LULC (National Land Cover data 2001) and 2050 projection, indicating substantial expansions of urban area and pastureland (including the cultivation of bioenergy crops) and a decrease in rangeland. We then used the above two LULC maps as the input data to drive the SWAT model, keeping other input data (e.g., climate) unchanged to isolate the LULC change impacts. The modeling results indicate that quick-response surface runoff would increase significantly (about 10.5%) due to the projected urban expansion (i.e., increase in impervious areas), and the baseflow would decrease substantially (about 7.3%) because of the reduced infiltration. Although the net effect may cause an increase in water yield, the increased variability may impede its use for public supply. Additionally, the cultivation of bioenergy crops such as switchgrass in the newly added pasture lands may further reduce the soil water content and lead to an increase in nitrogen loading (about 2.5% increase) due to intensified fertilizer application. These study results will be informative to decision makers for sustainable water resource management when facing LULC change and an increasing demand for biofuel production in this area.
","language":"English","publisher":"IOP Science","doi":"10.1088/1748-9326/8/2/024025","usgsCitation":"Wu, Y., Liu, S., Sohl, T.L., and Young, C., 2013, Projecting the land cover change and its environmental impacts in the Cedar River Basin in the Midwestern United States: Environmental Research Letters, v. 8, p. 1-13, https://doi.org/10.1088/1748-9326/8/2/024025.","productDescription":"Article 024025; 13 p.","startPage":"1","endPage":"13","ipdsId":"IP-045247","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":474037,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1088/1748-9326/8/2/024025","text":"Publisher Index Page"},{"id":341313,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2013-05-20","publicationStatus":"PW","scienceBaseUri":"591abe3ae4b0a7fdb43c8c05","contributors":{"authors":[{"text":"Wu, Yiping ywu@usgs.gov","contributorId":987,"corporation":false,"usgs":true,"family":"Wu","given":"Yiping","email":"ywu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":695177,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liu, Shuguang 0000-0002-6027-3479 sliu@usgs.gov","orcid":"https://orcid.org/0000-0002-6027-3479","contributorId":147403,"corporation":false,"usgs":true,"family":"Liu","given":"Shuguang","email":"sliu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":695175,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sohl, Terry L. 0000-0002-9771-4231 sohl@usgs.gov","orcid":"https://orcid.org/0000-0002-9771-4231","contributorId":648,"corporation":false,"usgs":true,"family":"Sohl","given":"Terry","email":"sohl@usgs.gov","middleInitial":"L.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":695176,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Young, Claudia 0000-0002-0859-7206 claudia.young.ctr@usgs.gov","orcid":"https://orcid.org/0000-0002-0859-7206","contributorId":192026,"corporation":false,"usgs":true,"family":"Young","given":"Claudia","email":"claudia.young.ctr@usgs.gov","affiliations":[],"preferred":false,"id":695174,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70189935,"text":"70189935 - 2013 - Rethinking infiltration in wildfire-affected soils","interactions":[],"lastModifiedDate":"2017-08-01T08:25:29","indexId":"70189935","displayToPublicDate":"2013-01-01T00:00:00","publicationYear":"2013","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":"Rethinking infiltration in wildfire-affected soils","docAbstract":"Wildfires frequently result in natural hazards such as flash floods (Yates et al., 2001) and debris flows (Cannon et al., 2001a,b; Gabet and Sternberg, 2008). One of the principal causes of the increased risk of post-wildfire hydrologically driven hazards is reduced in filtration rates (e.g. Scott and van Wyk, 1990; Cerdà, 1998; Robichaud, 2000; Martin and Moody, 2001). Beyond the reduction in peak infiltration rate, there is mounting evidence that the fundamental physics of infiltration in wild fire-affected soils is different from unburned soils (e.g. Imeson et al., 1992; Moody et al., 2009; Moody and Ebel, 2012).
Understanding post-wildfire hydrology is critical given the increasing wildfire incidence in the western USA (Westerling et al., 2006) and elsewhere in the world (Kasischke and Turetsky, 2006; Holz and Veblen, 2011; Pausas and Fernández-Muñoz, 2012). Wildfire is a disturbance event with global distribution (Bowman et al., 2009; Krawchuk et al., 2009; Pechony and Shindell, 2010; Moritz et al., 2012), and with increasing populations moving into fire-prone areas, understanding post-wildfire infiltration is of increasing importance for predicting post-wildfire consequences. Runoff is generally controlled by the infiltration-excess mechanism in fire-affected soils (e.g. Mayor et al., 2007; Onda et al., 2008; Kinner and Moody, 2010). It is essential that the fire community have conceptual models, physical equations and tools (i.e. numerical models) to predict infiltration and thus excess rainfall (after Horton, 1933), which can provide estimates of peak discharge, start of runoff, time to peak and total runoff for hydroclimatic scenarios after wildfires. Reductions in saturated hydraulic conductivity Ksat [LT-1] are common for fire-affected soils, and the relatively low values observed explain the elevated flash flood hazards (e.g. Ksat of 1–100 mm h-1 , Robichaud, 2000; Yates et al., 2000; Martin and Moody, 2001; Robichaud et al., 2007; Moody et al., 2009; Neary, 2011; Nyman et al., 2011).
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.9696","usgsCitation":"Ebel, B.A., and Moody, J.A., 2013, Rethinking infiltration in wildfire-affected soils: Hydrological Processes, v. 27, no. 10, p. 1510-1514, https://doi.org/10.1002/hyp.9696.","productDescription":"5 p.","startPage":"1510","endPage":"1514","ipdsId":"IP-042674","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":344488,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"27","issue":"10","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2013-01-21","publicationStatus":"PW","scienceBaseUri":"59819316e4b0e2f5d463b7a7","contributors":{"authors":[{"text":"Ebel, Brian A. 0000-0002-5413-3963 bebel@usgs.gov","orcid":"https://orcid.org/0000-0002-5413-3963","contributorId":2557,"corporation":false,"usgs":true,"family":"Ebel","given":"Brian","email":"bebel@usgs.gov","middleInitial":"A.","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":707008,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moody, John A. 0000-0003-2609-364X jamoody@usgs.gov","orcid":"https://orcid.org/0000-0003-2609-364X","contributorId":771,"corporation":false,"usgs":true,"family":"Moody","given":"John","email":"jamoody@usgs.gov","middleInitial":"A.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":707009,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70182180,"text":"70182180 - 2013 - Wildfire and aspect effects on hydrologic states after the 2010 Fourmile Canyon Fire","interactions":[],"lastModifiedDate":"2017-02-20T11:40:17","indexId":"70182180","displayToPublicDate":"2013-01-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3674,"text":"Vadose Zone Journal","active":true,"publicationSubtype":{"id":10}},"title":"Wildfire and aspect effects on hydrologic states after the 2010 Fourmile Canyon Fire","docAbstract":"Wildfire can change how soils take in, store, and release water. This study examined differences in how burned and unburned plots on north versus south-facing slope aspects respond to rainfall. The largest wildfire impacts were litter/duff combustion on burned north-facing slopes versus soil-water retention reduction on burned south-facing slopes.
Wildfire is one of the most significant disturbances in mountainous landscapes, affecting water supply and ecologic function and setting the stage for natural hazards such as flash floods. The impacts of wildfire can affect the entire hydrologic cycle. Measurements of soil-water content and matric potential in the near surface (top 30 cm) captured the hydrologic state in both burned and unburned hillslopes during the first spring through fall period (1 June–1 Oct. 2011) after the 2010 Fourmile Canyon Fire near Boulder, CO. This time span included different hydrologic periods characterized by cyclonic frontal storms (low-intensity, long duration), convective storms (high-intensity, short duration), and dry periods. In mountainous environments, aspect can also control hydrologic states, so north- vs. south-facing slopes were compared. Wildfire tended to homogenize soil-water contents across aspects and with depth in the soil, yet it also may have introduced an aspect control on matric potential that was not observed in unburned soils. Post-wildfire changes in hydrologic state were observed in south-facing soils, probably reflecting decreased soil-water retention after wildfire. North-facing soils were impacted the most, in terms of hydrologic state, by the loss of water storage in the combusted litter–duff layer and forest canopy, which had provided a large “hydrologic buffering” capacity when unburned. Unsaturated zone measurements showed increased variability in hydrologic states and more rapid state transitions in wildfire-impacted soils. A simple, qualitative analysis suggested that the range of unsaturated-zone processes along the gravity–capillarity–adsorption continuum was expanded by wildfire for a given soil. The small number of experimental plots in this study suggests that further work is needed before these conclusions can be generalized to other geographic areas.
","language":"English","publisher":"Soil Science Society of America","doi":"10.2136/vzj2012.0089","usgsCitation":"Ebel, B.A., 2013, Wildfire and aspect effects on hydrologic states after the 2010 Fourmile Canyon Fire: Vadose Zone Journal, v. 12, no. 1, https://doi.org/10.2136/vzj2012.0089.","ipdsId":"IP-038010","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":335829,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2013-02-04","publicationStatus":"PW","scienceBaseUri":"58ac0e31e4b0ce4410e7d60a","contributors":{"authors":[{"text":"Ebel, Brian A. 0000-0002-5413-3963 bebel@usgs.gov","orcid":"https://orcid.org/0000-0002-5413-3963","contributorId":2557,"corporation":false,"usgs":true,"family":"Ebel","given":"Brian","email":"bebel@usgs.gov","middleInitial":"A.","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":669908,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70187113,"text":"70187113 - 2013 - Hydrologic connectivity to streams increases nitrogen and phosphorus inputs and cycling in soils of created and natural floodplain wetlands","interactions":[],"lastModifiedDate":"2017-04-24T11:28:32","indexId":"70187113","displayToPublicDate":"2013-01-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2262,"text":"Journal of Environmental Quality","active":true,"publicationSubtype":{"id":10}},"title":"Hydrologic connectivity to streams increases nitrogen and phosphorus inputs and cycling in soils of created and natural floodplain wetlands","docAbstract":"Greater connectivity to stream surface water may result in greater inputs of allochthonous nutrients that could stimulate internal nitrogen (N) and phosphorus (P) cycling in natural, restored, and created riparian wetlands. This study investigated the effects of hydrologic connectivity to stream water on soil nutrient fluxes in plots (n = 20) located among four created and two natural freshwater wetlands of varying hydrology in the Piedmont physiographic province of Virginia. Surface water was slightly deeper; hydrologic inputs of sediment, sediment-N, and ammonium were greater; and soil net ammonification, N mineralization, and N turnover were greater in plots with stream water classified as their primary water source compared with plots with precipitation or groundwater as their primary water source. Soil water-filled pore space, inputs of nitrate, and soil net nitrification, P mineralization, and denitrification enzyme activity (DEA) were similar among plots. Soil ammonification, N mineralization, and N turnover rates increased with the loading rate of ammonium to the soil surface. Phosphorus mineralization and ammonification also increased with sedimentation and sediment-N loading rate. Nitrification flux and DEA were positively associated in these wetlands. In conclusion, hydrologic connectivity to stream water increased allochthonous inputs that stimulated soil N and P cycling and that likely led to greater retention of sediment and nutrients in created and natural wetlands. Our findings suggest that wetland creation and restoration projects should be designed to allow connectivity with stream water if the goal is to optimize the function of water quality improvement in a watershed.
","language":"English","publisher":"American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America","doi":"10.2134/jeq2012.0466","usgsCitation":"Wolf, K.L., Noe, G.E., and Ahn, C., 2013, Hydrologic connectivity to streams increases nitrogen and phosphorus inputs and cycling in soils of created and natural floodplain wetlands: Journal of Environmental Quality, v. 42, no. 4, p. 1245-1255, https://doi.org/10.2134/jeq2012.0466.","productDescription":"11 p.","startPage":"1245","endPage":"1255","ipdsId":"IP-024681","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":340177,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"42","issue":"4","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2013-07-01","publicationStatus":"PW","scienceBaseUri":"58ff0ea7e4b006455f2d61f6","contributors":{"authors":[{"text":"Wolf, Kristin L.","contributorId":92151,"corporation":false,"usgs":true,"family":"Wolf","given":"Kristin","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":692517,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Noe, Gregory E. 0000-0002-6661-2646 gnoe@usgs.gov","orcid":"https://orcid.org/0000-0002-6661-2646","contributorId":139100,"corporation":false,"usgs":true,"family":"Noe","given":"Gregory","email":"gnoe@usgs.gov","middleInitial":"E.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true}],"preferred":true,"id":692518,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ahn, Changwoo","contributorId":38047,"corporation":false,"usgs":true,"family":"Ahn","given":"Changwoo","affiliations":[],"preferred":false,"id":692519,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70006283,"text":"70006283 - 2013 - Tamarix, hydrology and fluvial geomorphology","interactions":[],"lastModifiedDate":"2022-12-20T15:02:14.764881","indexId":"70006283","displayToPublicDate":"2013-01-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"7","displayTitle":"Tamarix, hydrology and fluvial geomorphology","title":"Tamarix, hydrology and fluvial geomorphology","docAbstract":"This chapter explores the impact of hydrology and fluvial geomorphology on the distribution and abundance of Tamarix as well as the reciprocal effects of Tamarix on hydrologic and geomorphic conditions. It examines whether flow-regime alteration favors Tamarix establishment over native species, and how Tamarix stands modify processes involved in the narrowing of river channels and the formation of floodplains. It begins with an overview of the basic geomorphic and hydrologic character of rivers in the western United States before analyzing how this setting has contributed to the regional success of Tamarix. It then considers the influence of Tamarix on the hydrogeomorphic form and function of rivers and concludes by discussing how a changing climate, vegetation management, and continued water-resource development affect the future role of Tamarix in these ecosystems.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Tamarix: A case study of ecological change in the American West","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Oxford University Press","doi":"10.1093/acprof:osobl/9780199898206.003.0007","usgsCitation":"Auerbach, D., Merritt, D.M., and Shafroth, P.B., 2013, Tamarix, hydrology and fluvial geomorphology, chap. 7 of Tamarix: A case study of ecological change in the American West, p. 99-122, https://doi.org/10.1093/acprof:osobl/9780199898206.003.0007.","productDescription":"24 p.","startPage":"99","endPage":"122","ipdsId":"IP-034390","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":331328,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"583ff351e4b04fc80e43726e","contributors":{"editors":[{"text":"Sher, Anna A","contributorId":146314,"corporation":false,"usgs":false,"family":"Sher","given":"Anna","email":"","middleInitial":"A","affiliations":[{"id":12651,"text":"University of Denver","active":true,"usgs":false}],"preferred":false,"id":654507,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Quigley, Martin F.","contributorId":112538,"corporation":false,"usgs":true,"family":"Quigley","given":"Martin","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":654508,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Auerbach, Daniel A.","contributorId":147716,"corporation":false,"usgs":false,"family":"Auerbach","given":"Daniel A.","affiliations":[],"preferred":false,"id":654504,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Merritt, David M.","contributorId":95976,"corporation":false,"usgs":true,"family":"Merritt","given":"David","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":654505,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shafroth, Patrick B. 0000-0002-6064-871X shafrothp@usgs.gov","orcid":"https://orcid.org/0000-0002-6064-871X","contributorId":2000,"corporation":false,"usgs":true,"family":"Shafroth","given":"Patrick","email":"shafrothp@usgs.gov","middleInitial":"B.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":654506,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}