Breton National Wildlife Refuge, the Chandeleur Islands chain in Louisiana, provides habitat and nesting areas for wildlife and is an initial barrier protecting New Orleans from storms. The U.S. Geological Survey (USGS) in partnership with the University of New Orleans Pontchartrain Institute for Environmental Sciences undertook an intensive study that included (1) an analysis of island change based on historical maps and remotely sensed shoreline and topographic data; (2) a series of lidar surveys at 3- to 4-month intervals after Hurricane Katrina to determine barrier island recovery potential; (3) a discussion of sea level rise and effects on the islands; (4) an analysis of sea floor evolution and sediment dynamics in the refuge over the past 150 years; (5) an assessment of the local sediment transport and sediment resource availability based on the bathymetric and subbottom data; (6) a carefully selected core collection effort to groundtruth the geophysical data and more fully characterize the sediments composing the islands and surrounds; (7) an additional survey of the St. Bernard Shoals to assess their potential as a sand resource; and (8) a modeling study to numerically simulate the potential response of the islands to the low-intensity, intermediate, and extreme events likely to affect the refuge over the next 50 years.
Results indicate that the islands have become fragmented and greatly diminished in subaerial extent over time: the southern islands retreating landward as they reorganize into subaerial features, the northern islands remaining in place. Breton Island, because maintenance of the Mississippi River-Gulf Outlet (MRGO) outer bar channel requires dredging, is deprived of sand sufficient to sustain itself. Regional sediment transport trends indicate that large storms are extremely effective in transporting sand and controlling the shoreline development and barrier island geometry. Sand is transported north and south from a divergent zone near Monkey Bayou at the southern end of the Chandeleur Islands. Numerical simulation of waves and sediment transport supports the geophysical results and indicates that vast areas of the lower shoreface are affected and are undergoing erosion during storm events, that there is little or no fair weather mechanism to rework material into the littoral system, and that as a result, there is a net loss of sediment from the system. Lidar surveys revealed that the island chain immediately after Hurricane Katrina lost about 84 percent of its area and about 92 percent of its prestorm volume. Marsh platforms that supported the islands’ sand prior to the storm were reduced in width by more than one-half. Repeated lidar surveys document that in places the shoreline has retreated about 100 m under the relatively low-energy waves since Hurricanes Katrina and Rita; however, this retreat is nonuniform.
Recent high-resolution geophysical surveys of the sea floor and subsurface within 5–6 km of the Chandeleur Islands during 2006 and 2007 show that, in addition to the sand that is rebuilding portions of the island chain, a large volume of sand is contained in Hewes Point, in an extensive subtidal spit platform that has formed at the northern end of the Chandeleur Islands. Hewes Point appears to be the depositional terminus of the alongshore transport system. In the southern Chandeleurs, sand is being deposited in a broad tabular deposit near Breton Island called the southern offshore sand sheet. These two depocenters account for approximately 70 percent of the estimated sediment volume located in potential borrow sites. An additional large potential source of sand for restoration lies in the St. Bernard Shoals, which are estimated to contain approximately 200 × 106 m3 of sand.
Successful restoration planning for the Breton National Wildlife Refuge should mimic the natural processes of early stages of barrier island evolution including lateral transport to the flanks of the island chain from a centralized sand source that will ultimately enhance the ability of the islands to naturally build backbarrier marsh, dunes, and a continuous sandy shoreline. Barrier island sediment nourishment should be executed with the understanding that gulf shoreline erosion is inevitable but that island area can be maintained and enhanced during retreat (thus significantly prolonging the life of the island chain) with strategic sand placement.
","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/sir20095252","collaboration":"In cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"2009, Sand resources, regional geology, and coastal processes of the Chandeleur Islands Coastal System: An evaluation of the Breton National Wildlife Refuge: U.S. Geological Survey Scientific Investigations Report 2009-5252, vii, 180 p., https://doi.org/10.3133/sir20095252.","productDescription":"vii, 180 p.","onlineOnly":"N","additionalOnlineFiles":"Y","costCenters":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"links":[{"id":117616,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2009_5252.jpg"},{"id":13491,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2009/5252/","linkFileType":{"id":5,"text":"html"}},{"id":463443,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_92027.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Louisiana","otherGeospatial":"Breton National Wildlife Refuge, Chandeleur Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -88.92327457015571,\n 30.053706780767456\n ],\n [\n -88.92327457015571,\n 29.75738626372666\n ],\n [\n -88.80295686921512,\n 29.75738626372666\n ],\n [\n -88.80295686921512,\n 30.053706780767456\n ],\n [\n -88.92327457015571,\n 30.053706780767456\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a0ee4b07f02db5fdd53","contributors":{"editors":[{"text":"Lavoie, Dawn","contributorId":43881,"corporation":false,"usgs":true,"family":"Lavoie","given":"Dawn","affiliations":[],"preferred":false,"id":505748,"contributorType":{"id":2,"text":"Editors"},"rank":1}]}} ,{"id":98249,"text":"ds449 - 2009 - ATM Coastal Topography-Texas, 2001: UTM Zone 15","interactions":[],"lastModifiedDate":"2023-12-07T15:45:03.118664","indexId":"ds449","displayToPublicDate":"2010-03-06T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"449","title":"ATM Coastal Topography-Texas, 2001: UTM Zone 15","docAbstract":"These remotely sensed, geographically referenced elevation measurements of lidar-derived first-surface (FS) topography were produced collaboratively by the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL, and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA.\r\n\r\nThis project provides highly detailed and accurate datasets of a portion of the Texas coastline within UTM zone 15, from Matagorda Peninsula to Galveston Island, acquired October 12-13, 2001. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative scanning lidar instrument originally developed by NASA, and known as the Airborne Topographic Mapper (ATM), was used during data acquisition. The ATM system is a scanning lidar system that measures high-resolution topography of the land surface and incorporates a green-wavelength laser operating at pulse rates of 2 to 10 kilohertz. Measurements from the laser-ranging device are coupled with data acquired from inertial navigation system (INS) attitude sensors and differentially corrected global positioning system (GPS) receivers to measure topography of the surface at accuracies of +/-15 centimeters. The nominal ATM platform is a Twin Otter or P-3 Orion aircraft, but the instrument may be deployed on a range of light aircraft.\r\n\r\nElevation measurements were collected over the survey area using the ATM system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or first-surface topography.","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/ds449","usgsCitation":"Klipp, E.S., Nayegandhi, A., Brock, J., Sallenger, A., Bonisteel, J.M., Yates, X., and Wright, C.W., 2009, ATM Coastal Topography-Texas, 2001: UTM Zone 15: U.S. Geological Survey Data Series 449, HTML Document; DVD, https://doi.org/10.3133/ds449.","productDescription":"HTML Document; DVD","onlineOnly":"N","additionalOnlineFiles":"Y","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"links":[{"id":423298,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_97225.htm","linkFileType":{"id":5,"text":"html"}},{"id":13502,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/449/","linkFileType":{"id":5,"text":"html"}},{"id":197469,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"}],"country":"United States","state":"Texas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.75,\n 28.5861\n ],\n [\n -94.75,\n 29.3228\n ],\n [\n -96,\n 29.3228\n ],\n [\n -96,\n 28.5861\n ],\n [\n -94.75,\n 28.5861\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b14e4b07f02db6a4779","contributors":{"authors":[{"text":"Klipp, Emily S. eklipp@usgs.gov","contributorId":2754,"corporation":false,"usgs":true,"family":"Klipp","given":"Emily","email":"eklipp@usgs.gov","middleInitial":"S.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":304795,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nayegandhi, Amar","contributorId":37292,"corporation":false,"usgs":true,"family":"Nayegandhi","given":"Amar","affiliations":[],"preferred":false,"id":304797,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brock, John 0000-0002-5289-9332 jbrock@usgs.gov","orcid":"https://orcid.org/0000-0002-5289-9332","contributorId":2261,"corporation":false,"usgs":true,"family":"Brock","given":"John","email":"jbrock@usgs.gov","affiliations":[{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true}],"preferred":true,"id":304794,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sallenger, A. H.","contributorId":78290,"corporation":false,"usgs":true,"family":"Sallenger","given":"A. H.","affiliations":[],"preferred":false,"id":304799,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bonisteel, Jamie M.","contributorId":12005,"corporation":false,"usgs":true,"family":"Bonisteel","given":"Jamie","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":304796,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Yates, Xan","contributorId":78291,"corporation":false,"usgs":true,"family":"Yates","given":"Xan","email":"","affiliations":[],"preferred":false,"id":304800,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wright, C. Wayne wwright@usgs.gov","contributorId":57422,"corporation":false,"usgs":true,"family":"Wright","given":"C.","email":"wwright@usgs.gov","middleInitial":"Wayne","affiliations":[],"preferred":false,"id":304798,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":98245,"text":"ds431 - 2009 - ATM Coastal Topography-Florida 2001: Eastern Panhandle","interactions":[],"lastModifiedDate":"2023-12-07T15:37:48.794291","indexId":"ds431","displayToPublicDate":"2010-03-06T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"431","title":"ATM Coastal Topography-Florida 2001: Eastern Panhandle","docAbstract":"These remotely sensed, geographically referenced elevation measurements of Lidar-derived first surface (FS) topography were produced collaboratively by the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL, and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA.\r\n\r\nThis project provides highly detailed and accurate datasets of the eastern Florida panhandle coastline, acquired October 2, 2001. The datasets are made available for use as a management tool to research scientists and natural resource managers. An innovative scanning Lidar instrument originally developed by NASA, and known as the Airborne Topographic Mapper (ATM), was used during data acquisition. The ATM system is a scanning Lidar system that measures high-resolution topography of the land surface and incorporates a green-wavelength laser operating at pulse rates of 2 to 10 kilohertz. Measurements from the laser-ranging device are coupled with data acquired from inertial navigation system (INS) attitude sensors and differentially corrected global positioning system (GPS) receivers to measure topography of the surface at accuracies of +/-15 centimeters. The nominal ATM platform is a Twin Otter or P-3 Orion aircraft, but the instrument may be deployed on a range of light aircraft.\r\n\r\nElevation measurements were collected over the survey area using the ATM system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of Lidar data in an interactive or batch mode. Modules for presurvey flight line definition, flight path plotting, Lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is routinely used to create maps that represent submerged or first surface topography.","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/ds431","usgsCitation":"Yates, X., Nayegandhi, A., Brock, J., Sallenger, A., Bonisteel, J.M., Klipp, E.S., and Wright, C.W., 2009, ATM Coastal Topography-Florida 2001: Eastern Panhandle: U.S. Geological Survey Data Series 431, HTML Document, https://doi.org/10.3133/ds431.","productDescription":"HTML Document","onlineOnly":"N","additionalOnlineFiles":"Y","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"links":[{"id":423297,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_97316.htm","linkFileType":{"id":5,"text":"html"}},{"id":13498,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/431/","linkFileType":{"id":5,"text":"html"}},{"id":196900,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"}],"country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -85.7389,\n 30.125\n ],\n [\n -85.7389,\n 29.5917\n ],\n [\n -84.3292,\n 29.5917\n ],\n [\n -84.3292,\n 30.125\n ],\n [\n -85.7389,\n 30.125\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b15e4b07f02db6a481a","contributors":{"authors":[{"text":"Yates, Xan","contributorId":78291,"corporation":false,"usgs":true,"family":"Yates","given":"Xan","email":"","affiliations":[],"preferred":false,"id":304772,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nayegandhi, Amar","contributorId":37292,"corporation":false,"usgs":true,"family":"Nayegandhi","given":"Amar","affiliations":[],"preferred":false,"id":304769,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brock, John 0000-0002-5289-9332 jbrock@usgs.gov","orcid":"https://orcid.org/0000-0002-5289-9332","contributorId":2261,"corporation":false,"usgs":true,"family":"Brock","given":"John","email":"jbrock@usgs.gov","affiliations":[{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true}],"preferred":true,"id":304766,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sallenger, A. H.","contributorId":78290,"corporation":false,"usgs":true,"family":"Sallenger","given":"A. H.","affiliations":[],"preferred":false,"id":304771,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bonisteel, Jamie M.","contributorId":12005,"corporation":false,"usgs":true,"family":"Bonisteel","given":"Jamie","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":304768,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Klipp, Emily S. eklipp@usgs.gov","contributorId":2754,"corporation":false,"usgs":true,"family":"Klipp","given":"Emily","email":"eklipp@usgs.gov","middleInitial":"S.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":304767,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Wright, C. Wayne wwright@usgs.gov","contributorId":57422,"corporation":false,"usgs":true,"family":"Wright","given":"C.","email":"wwright@usgs.gov","middleInitial":"Wayne","affiliations":[],"preferred":false,"id":304770,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":98209,"text":"ofr20091286 - 2009 - Benthic flux of nutrients and trace metals in the northern component of San Francisco Bay, California","interactions":[],"lastModifiedDate":"2019-08-13T13:00:18","indexId":"ofr20091286","displayToPublicDate":"2010-02-25T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2009-1286","title":"Benthic flux of nutrients and trace metals in the northern component of San Francisco Bay, California","docAbstract":"Two sets of sampling trips were coordinated in late summer 2008 (weeks of July 8 and August 6) to sample the interstitial and overlying bottom waters at 10 shallow locations (9 sites <3 meters in depth) within the northern component of the San Francisco Bay/Delta (herein referred to as North Bay). The work was performed to better understand sources of biologically reactive solutes (namely, dissolved macronutrients and trace metals) that may affect the base of the food web in this part of the estuary. A nonmetallic pore-water profiler was used to obtain the first centimeter-scale estimates of the vertical solute-concentration gradients for diffusive-flux determinations. This study, performed in collaboration with scientists from San Francisco State University?s Romberg Tiburon Center for Environmental Studies, provides information to assist in developing and refining management strategies for the Bay/Delta system and supports efforts to monitor changes in food-web structure associated with regional habitat modifications directed by the California Bay-Delta Authority. \r\n\r\nOn July 7, 2008, and August 5, 2008, pore-water profilers were successfully deployed at six North Bay sites per trip to measure the concentration gradient of dissolved macronutrients and trace metals near the sediment-water interface. Only two of the sites (433 and SSB009 within Honker Bay) were sampled in both series of profiler deployments. At each sampling site, profilers were deployed in triplicate, while discrete samples and dataloggers were used to collect ancillary data from both the water column and benthos to help interpret diffusive-flux measurements. \r\n\r\nBenthic flux of dissolved (0.2-micron filtered) inorganic phosphate (that is, soluble reactive phosphorus (SRP)) ranged from negligible levels (-0.003?0.005 millimole per square meter per day (mmole m-2d-1) at Site 4.1 outside Honker Bay) to 0.060?0.006 mmole m-2d-1 near the northern coast of Brown?s Island. Except for the elevated flux at Browns Island, the benthic flux of soluble reactive phosphorus (SRP) was consistently: (1) lower than previously reported for South Bay sites, (2) an order of magnitude lower than oligotrophic Coeur d?Alene Lake, (3) two orders of magnitude lower than determined for eutrophic Upper Klamath Lake, and (4) an order of magnitude or more lower than the estimated summer riverine inputs for SRP (900 to 1,300 kilograms of phosphorous per day (kg-P d-1)). \r\n\r\nIn contrast to fluxes reported for the South Bay, nitrate fluxes were consistently negative (that is, drawn from the water column into the sediment), except for one site with statistically insignificant nitrate fluxes (Site 409 within Suisun Bay). The most negative nitrate flux (-7.3?0.1 mmole m-2d-1) was observed within Grizzly Bay (Site 416). Observed nitrate fluxes bracketed the estimated summer fluvial flux of nitrate (3,500 to 5,000 kg-N d-1). With the exception of the two Grizzly Bay sites (416 and 417), the consistently positive benthic flux of ammonia generally counteracted the negative flux of nitrate to yield a net balance of dissolved inorganic nitrogen. Ammonia benthic fluxes extrapolated for Suisun Bay ranged from 320 kg-N d-1 (Site SSB009 near the entrance to Honker Bay) to 1,900 kg-N d-1 (Montezuma Island). These values represent a significant ammonia source to the water column relative to summer riverine inputs (approximately 400 to 600 kg-N d-1). \r\n\r\nDissolved silica also displayed a consistently positive benthic flux, except for Site 409 within Suisun Bay, which showed insignificant fluxes (also insignificant for nitrate and SRP). As with the nitrate fluxes, Grizzly Bay and Browns Island sites yielded the highest dissolved silica fluxes (1.3?1.2 to 2.5?0.6 mmole m-2d-1, respectively). These initial diffusive-flux estimates are greater than those measured in the South Bay using core-incubation experiments, which include bioturbation and bioirrigation effects, but they are nevertheless probably one to t","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20091286","collaboration":"Prepared in cooperation with the California Bay-Delta Authority and San Francisco State University","usgsCitation":"Kuwabara, J.S., Topping, B.R., Parcheso, F., Engelstad, A., and Greene, V.E., 2009, Benthic flux of nutrients and trace metals in the northern component of San Francisco Bay, California: U.S. Geological Survey Open-File Report 2009-1286, iv, 26 p., https://doi.org/10.3133/ofr20091286.","productDescription":"iv, 26 p.","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2008-07-08","temporalEnd":"2008-08-06","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":125954,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2009_1286.jpg"},{"id":13465,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2009/1286/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.16666666666667,38 ], [ -122.16666666666667,38.2 ], [ -121.86666666666666,38.2 ], [ -121.86666666666666,38 ], [ -122.16666666666667,38 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a53e4b07f02db62b58d","contributors":{"authors":[{"text":"Kuwabara, James S. 0000-0003-2502-1601 kuwabara@usgs.gov","orcid":"https://orcid.org/0000-0003-2502-1601","contributorId":3374,"corporation":false,"usgs":true,"family":"Kuwabara","given":"James","email":"kuwabara@usgs.gov","middleInitial":"S.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":304667,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Topping, Brent R. 0000-0002-7887-4221 btopping@usgs.gov","orcid":"https://orcid.org/0000-0002-7887-4221","contributorId":1484,"corporation":false,"usgs":true,"family":"Topping","given":"Brent","email":"btopping@usgs.gov","middleInitial":"R.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":304665,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Parcheso, Francis 0000-0002-9471-7787 parchaso@usgs.gov","orcid":"https://orcid.org/0000-0002-9471-7787","contributorId":2590,"corporation":false,"usgs":true,"family":"Parcheso","given":"Francis","email":"parchaso@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":false,"id":304666,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Engelstad, Anita C. 0000-0002-0211-4189","orcid":"https://orcid.org/0000-0002-0211-4189","contributorId":24884,"corporation":false,"usgs":true,"family":"Engelstad","given":"Anita C.","affiliations":[],"preferred":true,"id":304668,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Greene, Valerie E.","contributorId":104600,"corporation":false,"usgs":true,"family":"Greene","given":"Valerie","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":304669,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":98183,"text":"sir20095253 - 2009 - A Multitracer Approach to Detecting Wastewater Plumes from Municipal Injection Wells in Nearshore Marine Waters at Kihei and Lahaina, Maui, Hawaii","interactions":[],"lastModifiedDate":"2012-03-08T17:16:30","indexId":"sir20095253","displayToPublicDate":"2010-02-10T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2009-5253","title":"A Multitracer Approach to Detecting Wastewater Plumes from Municipal Injection Wells in Nearshore Marine Waters at Kihei and Lahaina, Maui, Hawaii","docAbstract":"Municipal wastewater plumes discharging from aquifer to ocean were detected by nearshore wading surveys at Kihei and Lahaina, on the island of Maui in Hawaii. Developed in cooperation with the Hawaii State Department of Health, the survey methodology included instrument trolling to detect submarine groundwater discharge, followed by analysis of water and macroalgae for a suite of chemical and isotopic constituents that constitute a 'multitracer' approach. Surveys were conducted May 6-28, 2008, during fair-weather conditions and included: (1) wading and kayak trolling with a multiparameter water-quality sonde, (2) marine water-column sampling, and (3) collection of benthic algae samples. Instrument trolling helped guide the water sampling strategy by providing dense, continuous transects of water properties on which groundwater discharge zones could be identified. Water and algae samples for costly chemical and isotopic laboratory analyses were last to be collected but were highly diagnostic of wastewater presence and nutrient origin because of low detection levels and confirmation across multiple tracers. Laboratory results confirmed the presence of wastewater constituents in marine water-column samples at both locales and showed evidence of modifying processes such as denitrification and mixing of effluent with surrounding groundwater and seawater. Carbamazepine was the most diagnostic pharmaceutical, detected in several marine water-column samples and effluent at both Kihei and Lahaina. Heavy nitrogen-isotope compositions in water and algae were highly diagnostic of effluent, particularly where enriched to even heavier values than effluent source compositions by denitrification. Algae provided an added advantage of time-integrating their nitrogen source during growth. The measured Kihei plume coincided almost exactly with prior model predictions, but the Lahaina plume was detected well south of the expected direct path from injection wells to shore and may be guided by a buried valley fill from an ancestral course of Honokowai Stream. Nutrient concentrations in upland wells at Lahaina were comparable to concentrations in wastewater but originate instead from agricultural fertilizers. A key factor in detecting and mapping the wastewater plumes was sampling very close to shore (mostly within 20 m or so) and in very shallow water (mostly 0.5 to 2 m depth). Effluent probably discharges somewhat offshore as well, although prior attempts to detect an injected fluorescent tracer at Lahaina in the 1990s were inconclusive, having focused farther offshore in water mostly 10-30 m deep. Sampling of benthic porewater and algae would offer the best chances for further effluent detection and mapping offshore, and sampling of onland monitor wells could provide additional understanding of geochemical processes that take place in the effluent plumes and bring about some degree of natural attenuation of nutrients. \r\n","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/sir20095253","collaboration":"Prepared in Cooperation with the Hawaii State Department of Health, Clean Water Branch","usgsCitation":"Hunt, C.D., and Rosa, S.N., 2009, A Multitracer Approach to Detecting Wastewater Plumes from Municipal Injection Wells in Nearshore Marine Waters at Kihei and Lahaina, Maui, Hawaii: U.S. Geological Survey Scientific Investigations Report 2009-5253, xii, 166 p. , https://doi.org/10.3133/sir20095253.","productDescription":"xii, 166 p. ","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2008-05-06","temporalEnd":"2008-05-28","costCenters":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"links":[{"id":125884,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2009_5253.jpg"},{"id":13427,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2009/5253/","linkFileType":{"id":5,"text":"html"}}],"scale":"24000","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -156.75,20.583333333333332 ], [ -156.75,21.083333333333332 ], [ -155.91666666666666,21.083333333333332 ], [ -155.91666666666666,20.583333333333332 ], [ -156.75,20.583333333333332 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd495de4b0b290850ef19f","contributors":{"authors":[{"text":"Hunt, Charles D. Jr. cdhunt@usgs.gov","contributorId":1730,"corporation":false,"usgs":true,"family":"Hunt","given":"Charles","suffix":"Jr.","email":"cdhunt@usgs.gov","middleInitial":"D.","affiliations":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"preferred":false,"id":304582,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rosa, Sarah N. 0000-0002-3653-0826 snrosa@usgs.gov","orcid":"https://orcid.org/0000-0002-3653-0826","contributorId":2968,"corporation":false,"usgs":true,"family":"Rosa","given":"Sarah","email":"snrosa@usgs.gov","middleInitial":"N.","affiliations":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"preferred":true,"id":304583,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":98142,"text":"pp1765B - 2009 - Appendix B: Description of Map Units for Northeast Asia Summary Geodynamics Map ","interactions":[],"lastModifiedDate":"2012-02-10T00:11:51","indexId":"pp1765B","displayToPublicDate":"2010-01-23T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1765","chapter":"B","title":"Appendix B: Description of Map Units for Northeast Asia Summary Geodynamics Map ","docAbstract":"The major purposes of this chapter are to provide (1) an overview of the regional geology, tectonics, and metallogenesis of Northeast Asia for readers who are unfamiliar with the region, (2) a general scientific introduction to the succeeding chapters of this volume, and (3) an overview of the methodology of metallogenic and tectonic analysis used in this study. We also describe how a high-quality metallogenic and tectonic analysis, including construction of an associated metallogenic-tectonic model will greatly benefit other mineral resource studies, including synthesis of mineral-deposit models; improve prediction of undiscovered mineral deposit as part of a quantitative mineral-resource-assessment studies; assist land-use and mineral-exploration planning; improve interpretations of the origins of host rocks, mineral deposits, and metallogenic belts, and suggest new research. \r\n\r\nResearch on the metallogenesis and tectonics of such major regions as Northeast Asia (eastern Russia, Mongolia, northern China, South Korea, and Japan) and the Circum-North Pacific (the Russian Far East, Alaska, and the Canadian Cordillera) requires a complex methodology including (1) definitions of key terms, (2) compilation of a regional geologic base map that can be interpreted according to modern tectonic concepts and definitions, (3) compilation of a mineral-deposit database that enables a determination of mineral-deposit models and clarification of the relations of deposits to host rocks and tectonic origins, (4) synthesis of a series of mineral-deposit models that characterize the known mineral deposits and inferred undiscovered deposits in the region, (5) compilation of a series of metallogenic-belt belts constructed on the regional geologic base map, and (6) construction of a unified metallogenic and tectonic model. \r\n\r\nThe summary of regional geology and metallogenesis presented here is based on publications of the major international collaborative studies of the metallogenesis and tectonics of Northeast Asia that have been led by the U.S. Geological Survey (USGS). These studies have produced two broad types of publications (1) a series of regional geologic, mineral-deposit, and metallogenic-belt maps, with companion descriptions of the region, and (2) a suite of metallogenic and tectonic analyses of the same region. \r\n\r\nThe study area consists of eastern Russia (most of eastern Siberia and the Russian Far East), Mongolia, northern China, South Korea, Japan, and adjacent offshore areas. The major cooperative agencies are the Russian Academy of Sciences; the Academy of Sciences of the Sakha Republic (Yakutia); VNIIOkeangeologia and Ministry of Natural Resources of the Russian Federation; the Mongolian Academy of Sciences; the Mongolian University of Science and Technology; the Mongolian National University; Jilin University, Changchun, People?s Republic of China, the China Geological Survey; the Korea Institute of Geosciences and Mineral Resources; the Geological Survey of Japan/AIST; the University of Texas, Arlington, and the U.S. Geological Survey (USGS). \r\n\r\nThis study builds on and extends the data and interpretations from a previous project on the Major Mineral Deposits, Metallogenesis, and Tectonics of the Russian Far East, Alaska, and the Canadian Cordillera conducted by the USGS, the Russian Academy of Sciences, the Alaska Division of Geological and Geophysical Surveys, and the Geological Survey of Canada. The major products of this project were summarized by Naumova and others (2006) and are described in appendix A. \r\n","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Metallogenesis and Tectonics of Northeast Asia","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/pp1765B","collaboration":"Prepared in collaboration with the Russian Academy of Sciences, Mongolian Academy of Sciences, Korean Institute of Geosciences and Mineral Resources, Geological Survey of Japan/AIST, and Jilin University","usgsCitation":"Parfenov, L.M., Badarch, G., Berzin, N.A., Hwang, D., Khanchuk, A.I., Kuzmin, M.I., Nokleberg, W.J., Obolenskiy, A., Ogasawara, M., Prokopiev, A.V., Rodionov, S.M., Smelov, A., and Yan, H., 2009, Appendix B: Description of Map Units for Northeast Asia Summary Geodynamics Map : U.S. Geological Survey Professional Paper 1765, 12 p. Available online. , https://doi.org/10.3133/pp1765B.","productDescription":"12 p. Available online. ","onlineOnly":"N","costCenters":[{"id":662,"text":"Western Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":125819,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/pp_1765_B.jpg"},{"id":13385,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/pp/1765/index.html","linkFileType":{"id":5,"text":"html"}}],"scale":"5000000","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 75,3 ], [ 75,8.333333333333334 ], [ 144,8.333333333333334 ], [ 144,3 ], [ 75,3 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ac7e4b07f02db67ac8c","contributors":{"authors":[{"text":"Parfenov, Leonid M.","contributorId":59112,"corporation":false,"usgs":true,"family":"Parfenov","given":"Leonid","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":304403,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Badarch, Gombosuren","contributorId":6940,"corporation":false,"usgs":true,"family":"Badarch","given":"Gombosuren","email":"","affiliations":[],"preferred":false,"id":304395,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Berzin, Nikolai A.","contributorId":33793,"corporation":false,"usgs":true,"family":"Berzin","given":"Nikolai","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":304401,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hwang, Duk-Hwan","contributorId":43804,"corporation":false,"usgs":true,"family":"Hwang","given":"Duk-Hwan","email":"","affiliations":[],"preferred":false,"id":304402,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Khanchuk, Alexander I.","contributorId":19585,"corporation":false,"usgs":true,"family":"Khanchuk","given":"Alexander","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":304397,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kuzmin, Mikhail I.","contributorId":95956,"corporation":false,"usgs":true,"family":"Kuzmin","given":"Mikhail","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":304406,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nokleberg, Warren J. 0000-0002-1574-8869 wnokleberg@usgs.gov","orcid":"https://orcid.org/0000-0002-1574-8869","contributorId":2077,"corporation":false,"usgs":true,"family":"Nokleberg","given":"Warren","email":"wnokleberg@usgs.gov","middleInitial":"J.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":304394,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Obolenskiy, Alexander A.","contributorId":19632,"corporation":false,"usgs":true,"family":"Obolenskiy","given":"Alexander A.","affiliations":[],"preferred":false,"id":304398,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ogasawara, Masatsugu","contributorId":17638,"corporation":false,"usgs":true,"family":"Ogasawara","given":"Masatsugu","email":"","affiliations":[],"preferred":false,"id":304396,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Prokopiev, Andrei V.","contributorId":20825,"corporation":false,"usgs":true,"family":"Prokopiev","given":"Andrei","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":304399,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Rodionov, Sergey M.","contributorId":64726,"corporation":false,"usgs":true,"family":"Rodionov","given":"Sergey","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":304404,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Smelov, Alexander P.","contributorId":30685,"corporation":false,"usgs":true,"family":"Smelov","given":"Alexander P.","affiliations":[],"preferred":false,"id":304400,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Yan, Hongquan","contributorId":81559,"corporation":false,"usgs":true,"family":"Yan","given":"Hongquan","email":"","affiliations":[],"preferred":false,"id":304405,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":98128,"text":"ds465 - 2009 - ATM Coastal Topography - Louisiana, 2001: UTM Zone 16 (Part 2 of 2)","interactions":[],"lastModifiedDate":"2023-12-07T14:55:43.612491","indexId":"ds465","displayToPublicDate":"2010-01-19T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"465","title":"ATM Coastal Topography - Louisiana, 2001: UTM Zone 16 (Part 2 of 2)","docAbstract":"These remotely sensed, geographically referenced elevation measurements of lidar-derived first-surface (FS) topography were produced collaboratively by the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL, and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA.\r\n\r\nThis project provides highly detailed and accurate datasets of a portion of the Louisiana coastline beach face within UTM Zone 16, from Grand Isle to the Chandeleur Islands, acquired September 7 and 9, 2001. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative scanning lidar instrument originally developed by NASA, and known as the Airborne Topographic Mapper (ATM), was used during data acquisition. The ATM system is a scanning lidar system that measures high-resolution topography of the land surface and incorporates a green-wavelength laser operating at pulse rates of 2 to 10 kilohertz. Measurements from the laser-ranging device are coupled with data acquired from inertial navigation system (INS) attitude sensors and differentially corrected global positioning system (GPS) receivers to measure topography of the surface at accuracies of +/-15 centimeters. The nominal ATM platform is a Twin Otter or P-3 Orion aircraft, but the instrument may be deployed on a range of light aircraft.\r\n\r\nElevation measurements were collected over the survey area using the ATM system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or first-surface topography.","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/ds465","usgsCitation":"Yates, X., Nayegandhi, A., Brock, J., Sallenger, A., Klipp, E.S., and Wright, C.W., 2009, ATM Coastal Topography - Louisiana, 2001: UTM Zone 16 (Part 2 of 2): U.S. Geological Survey Data Series 465, HTML Document; DVD-ROM, https://doi.org/10.3133/ds465.","productDescription":"HTML Document; DVD-ROM","onlineOnly":"N","additionalOnlineFiles":"Y","temporalStart":"2001-09-07","temporalEnd":"2001-09-09","costCenters":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":13367,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/465/","linkFileType":{"id":5,"text":"html"}},{"id":125641,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_465.jpg"},{"id":423294,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_97202.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Louisiana","otherGeospatial":"Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -89.98346754311137,\n 30.071841541761785\n ],\n [\n -89.98346754311137,\n 29.197416296987143\n ],\n [\n -88.8222884468944,\n 29.197416296987143\n ],\n [\n -88.8222884468944,\n 30.071841541761785\n ],\n [\n -89.98346754311137,\n 30.071841541761785\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b14e4b07f02db6a478c","contributors":{"authors":[{"text":"Yates, Xan","contributorId":78291,"corporation":false,"usgs":true,"family":"Yates","given":"Xan","email":"","affiliations":[],"preferred":false,"id":304263,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nayegandhi, Amar","contributorId":37292,"corporation":false,"usgs":true,"family":"Nayegandhi","given":"Amar","affiliations":[],"preferred":false,"id":304261,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brock, John 0000-0002-5289-9332 jbrock@usgs.gov","orcid":"https://orcid.org/0000-0002-5289-9332","contributorId":2261,"corporation":false,"usgs":true,"family":"Brock","given":"John","email":"jbrock@usgs.gov","affiliations":[{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true}],"preferred":true,"id":304258,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sallenger, Asbury H. Jr.","contributorId":27458,"corporation":false,"usgs":true,"family":"Sallenger","given":"Asbury H.","suffix":"Jr.","affiliations":[],"preferred":false,"id":304260,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Klipp, Emily S. eklipp@usgs.gov","contributorId":2754,"corporation":false,"usgs":true,"family":"Klipp","given":"Emily","email":"eklipp@usgs.gov","middleInitial":"S.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":304259,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wright, C. Wayne wwright@usgs.gov","contributorId":57422,"corporation":false,"usgs":true,"family":"Wright","given":"C.","email":"wwright@usgs.gov","middleInitial":"Wayne","affiliations":[],"preferred":false,"id":304262,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":98107,"text":"sir20095233 - 2009 - Evaluation of catchment delineation methods for the medium-resolution National Hydrography Dataset","interactions":[],"lastModifiedDate":"2017-03-29T14:23:27","indexId":"sir20095233","displayToPublicDate":"2010-01-15T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2009-5233","title":"Evaluation of catchment delineation methods for the medium-resolution National Hydrography Dataset","docAbstract":"Different methods for determining catchments (incremental drainage areas) for stream segments of the medium-resolution (1:100,000-scale) National Hydrography Dataset (NHD) were evaluated by the U.S. Geological Survey (USGS), in cooperation with the U.S. Environmental Protection Agency (USEPA). The NHD is a comprehensive set of digital spatial data that contains information about surface-water features (such as lakes, ponds, streams, and rivers) of the United States. The need for NHD catchments was driven primarily by the goal to estimate NHD streamflow and velocity to support water-quality modeling. The application of catchments for this purpose also demonstrates the broader value of NHD catchments for supporting landscape characterization and analysis.\n\nFive catchment delineation methods were evaluated. Four of the methods use topographic information for the delineation of the NHD catchments. These methods include the Raster Seeding Method; two variants of a method first used in a USGS New England study-one used the Watershed Boundary Dataset (WBD) and the other did not-termed the 'New England Methods'; and the Outlet Matching Method. For these topographically based methods, the elevation data source was the 30-meter (m) resolution National Elevation Dataset (NED), as this was the highest resolution available for the conterminous United States and Hawaii. The fifth method evaluated, the Thiessen Polygon Method, uses distance to the nearest NHD stream segments to determine catchment boundaries.\n\nCatchments were generated using each method for NHD stream segments within six hydrologically and geographically distinct Subbasins to evaluate the applicability of the method across the United States. The five methods were evaluated by comparing the resulting catchments with the boundaries and the computed area measurements available from several verification datasets that were developed independently using manual methods.\n\nThe results of the evaluation indicated that the two New England Methods provided the most accurate catchment boundaries. The New England Method with the WBD provided the most accurate results. The time and cost to implement and apply these automated methods were also considered in ultimately selecting the methods used to produce NHD catchments for the conterminous United States and Hawaii.\n\nThis study was conducted by a joint USGS-USEPA team during the 2-year period that ended in September 2004. During the following 2-year period ending in the fall of 2006, the New England Methods were used to produce NHD catchments as part of a multiagency effort to generate the NHD streamflow and velocity estimates for a suite of integrated geospatial products known as 'NHDPlus.'","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20095233","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Johnston, C.M., Dewald, T.G., Bondelid, T., Worstell, B.B., McKay, L., Rea, A., Moore, R.B., and Goodall, J.L., 2009, Evaluation of catchment delineation methods for the medium-resolution National Hydrography Dataset: U.S. Geological Survey Scientific Investigations Report 2009-5233, x, 89 p., https://doi.org/10.3133/sir20095233.","productDescription":"x, 89 p.","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":468,"text":"New Hampshire-Vermont Water Science Center","active":false,"usgs":true}],"links":[{"id":125649,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2009_5233.jpg"},{"id":13346,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2009/5233/","linkFileType":{"id":5,"text":"html"}},{"id":338662,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2009/5233/pdf/sir2009-5233.pdf"}],"country":"United States","otherGeospatial":"New England","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -125,23 ], [ -125,50 ], [ -65,50 ], [ -65,23 ], [ -125,23 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a09e4b07f02db5fb018","contributors":{"authors":[{"text":"Johnston, Craig M. cmjohnst@usgs.gov","contributorId":1814,"corporation":false,"usgs":true,"family":"Johnston","given":"Craig","email":"cmjohnst@usgs.gov","middleInitial":"M.","affiliations":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":304185,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dewald, Thomas G.","contributorId":97600,"corporation":false,"usgs":true,"family":"Dewald","given":"Thomas","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":304191,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bondelid, Timothy R.","contributorId":90420,"corporation":false,"usgs":true,"family":"Bondelid","given":"Timothy R.","affiliations":[],"preferred":false,"id":304190,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Worstell, Bruce B. 0000-0001-8927-3336 worstell@usgs.gov","orcid":"https://orcid.org/0000-0001-8927-3336","contributorId":1815,"corporation":false,"usgs":true,"family":"Worstell","given":"Bruce","email":"worstell@usgs.gov","middleInitial":"B.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":304186,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McKay, Lucinda D.","contributorId":90010,"corporation":false,"usgs":true,"family":"McKay","given":"Lucinda D.","affiliations":[],"preferred":false,"id":304189,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rea, Alan","contributorId":41018,"corporation":false,"usgs":true,"family":"Rea","given":"Alan","affiliations":[],"preferred":false,"id":304187,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Moore, Richard B. rmoore@usgs.gov","contributorId":1464,"corporation":false,"usgs":true,"family":"Moore","given":"Richard","email":"rmoore@usgs.gov","middleInitial":"B.","affiliations":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":304184,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Goodall, Jonathan L.","contributorId":59535,"corporation":false,"usgs":true,"family":"Goodall","given":"Jonathan","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":304188,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":98104,"text":"sir20095261 - 2009 - Travel Times, Streamflow Velocities, and Dispersion Rates in the Yellowstone River, Montana","interactions":[],"lastModifiedDate":"2012-03-08T17:16:29","indexId":"sir20095261","displayToPublicDate":"2010-01-15T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2009-5261","title":"Travel Times, Streamflow Velocities, and Dispersion Rates in the Yellowstone River, Montana","docAbstract":"The Yellowstone River is a vital natural resource to the residents of southeastern Montana and is a primary source of water for irrigation and recreation and the primary source of municipal water for several cities. The Yellowstone River valley is the primary east-west transportation corridor through southern Montana. This complex of infrastructure makes the Yellowstone River especially vulnerable to accidental spills from various sources such as tanker cars and trucks. In 2008, the U.S. Geological Survey (USGS), in cooperation with the Montana Department of Environmental Quality, initiated a dye-tracer study to determine instream travel times, streamflow velocities, and dispersion rates for the Yellowstone River from Lockwood to Glendive, Montana. The purpose of this report is to describe the results of this study and summarize data collected at each of the measurement sites between Lockwood and Glendive. This report also compares the results of this study to estimated travel times from a transport model developed by the USGS for a previous study. For this study, Rhodamine WT dye was injected at four locations in late September and early October 2008 during reasonably steady streamflow conditions. Streamflows ranged from 3,490 to 3,770 cubic feet per second upstream from the confluence of the Bighorn River and ranged from 6,520 to 7,570 cubic feet per second downstream from the confluence of the Bighorn River.\r\n\r\nMean velocities were calculated for each subreach between measurement sites for the leading edge, peak concentration, centroid, and trailing edge at 10 percent of the peak concentration. Calculated velocities for the centroid of the dye plume for subreaches that were completely laterally mixed ranged from 1.83 to 3.18 ft/s within the study reach from Lockwood Bridge to Glendive Bridge. The mean of the completely mixed centroid velocity for the entire study reach, excluding the subreach between Forsyth Bridge and Cartersville Dam, was 2.80 ft/s. Longitudinal dispersion rates of the dye plume for this study ranged from 0.06 ft/s for the subreach upstream from Forsyth Bridge to 2.25 ft/s for the subreach upstream from Calyspo Bridge for subreaches where the dye was completely laterally mixed. A relation was determined between travel time of the peak concentration and time for the dye plume to pass a site (duration). This relation can be used to estimate when the receding concentration of a potential contaminant reaches 10 percent of its peak concentration for accidental spills into the Yellowstone River.\r\n\r\nData from this dye-tracer study were used to evaluate velocity and concentration estimates from a transport model developed as part of an earlier USGS study. Comparison of the estimated and calculated velocities for the study reach indicate that the transport model estimates the velocities of the Yellowstone River between Huntley Bridge and Glendive Bridge with reasonable accuracy. Velocities of the peak concentration of the dye plume calculated for this study averaged 10 percent faster than the most probable velocities and averaged 12 percent slower than the maximum probable velocities estimated from the transport model. Peak Rhodamine WT dye concentrations were consistently lower than the transport model estimates except for the most upstream subreach of each dye injection. The most upstream subreach of each dye injection is expected to have a higher concentration because of incomplete lateral mixing. Lower measured peak concentrations for all other sites were expected because Rhodamine WT dye deteriorates when exposed to sunlight and will sorb onto the streambanks and stream bottom.\r\n\r\nVelocity-streamflow relations developed by using routine streamflow measurements at USGS gaging stations and the transport model can be used to estimate mean streamflow velocities throughout a range of streamflows. The variation in these velocity-streamflow relations emphasizes the uncertainty in estimating the mean streamflow veloc","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/sir20095261","isbn":"9781411326606","collaboration":"Prepared in cooperation with the Montana Department of Environmental Quality","usgsCitation":"McCarthy, P., 2009, Travel Times, Streamflow Velocities, and Dispersion Rates in the Yellowstone River, Montana: U.S. Geological Survey Scientific Investigations Report 2009-5261, Report: vi, 26 p.; 4 Appendixes (xls), https://doi.org/10.3133/sir20095261.","productDescription":"Report: vi, 26 p.; 4 Appendixes (xls)","onlineOnly":"N","additionalOnlineFiles":"Y","temporalStart":"2008-09-15","temporalEnd":"2008-10-15","costCenters":[{"id":400,"text":"Montana Water Science Center","active":false,"usgs":true}],"links":[{"id":125630,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2009_5261.jpg"},{"id":13341,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2009/5261/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -109,45 ], [ -109,47.5 ], [ -104,47.5 ], [ -104,45 ], [ -109,45 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a4ce4b07f02db626af7","contributors":{"authors":[{"text":"McCarthy, Peter 0000-0002-2396-7463 pmccarth@usgs.gov","orcid":"https://orcid.org/0000-0002-2396-7463","contributorId":2504,"corporation":false,"usgs":true,"family":"McCarthy","given":"Peter","email":"pmccarth@usgs.gov","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":304177,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":98103,"text":"fs20093108 - 2009 - US Topo: Topographic Maps for the Nation ","interactions":[],"lastModifiedDate":"2017-07-13T11:06:06","indexId":"fs20093108","displayToPublicDate":"2010-01-15T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2009-3108","title":"US Topo: Topographic Maps for the Nation ","docAbstract":"US Topo is the next generation of topographic maps from the U.S. Geological Survey (USGS). Arranged in the familiar 7.5-minute quadrangle format, digital US Topo maps are designed to look and feel (and perform) like the traditional paper topographic maps for which the USGS is so well known. In contrast to paper-based maps, US Topo maps provide modern technical advantages that support faster, wider public distribution and enable basic, on-screen geographic analysis for all users. \r\n\r\nUS Topo maps are available free on the Web. Each map quadrangle is constructed in GeoPDF? format from key layers of geographic data (orthoimagery, roads, geographic names, topographic contours, and hydrographic features) found in The National Map. \r\n\r\nUS Topo quadrangles can be printed from personal computers or plotters as complete, full-sized, maps or in customized sections, in a user-desired specific format. Paper copies of the maps can also be purchased from the USGS Store. Download links and a users guide are featured on the US Topo Web site.\r\n\r\nUS Topo users can turn geographic data layers on and off as needed; they can zoom in and out to highlight specific features or see a broader area. File size for each digital 7.5-minute quadrangle, about 15-20 megabytes, is suitable for most users. Associated electronic tools for geographic analysis are available free for download.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20093108","usgsCitation":"Hytes, P.L., 2009, US Topo: Topographic Maps for the Nation : U.S. Geological Survey Fact Sheet 2009-3108, 2 p., https://doi.org/10.3133/fs20093108.","productDescription":"2 p.","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"links":[{"id":13365,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2009/3108/","linkFileType":{"id":5,"text":"html"}},{"id":343787,"rank":4,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2009/3108/TopoMapBroch_New5F.pdf","text":"Brochure for Fact Sheet 2009-3108","size":"1773 KB","linkFileType":{"id":1,"text":"pdf"}},{"id":125633,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2009_3108.jpg"},{"id":13340,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2009/3108/fs2009-3108.pdf","size":"778 KB","linkFileType":{"id":1,"text":"pdf"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a29e4b07f02db611a40","contributors":{"authors":[{"text":"Hytes, Patricia L. plhytes@usgs.gov","contributorId":1417,"corporation":false,"usgs":true,"family":"Hytes","given":"Patricia","email":"plhytes@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":true,"id":304176,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":98101,"text":"ofr20091225 - 2009 - Natural offshore oil seepage and related tarball accumulation on the California coastline — Santa Barbara Channel and the southern Santa Maria Basin; source identification and inventory","interactions":[],"lastModifiedDate":"2022-06-09T20:25:10.852413","indexId":"ofr20091225","displayToPublicDate":"2010-01-14T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2009-1225","title":"Natural offshore oil seepage and related tarball accumulation on the California coastline — Santa Barbara Channel and the southern Santa Maria Basin; source identification and inventory","docAbstract":"Oil spillage from natural sources is very common in the waters of southern California. Active oil extraction and shipping is occurring concurrently within the region and it is of great interest to resource managers to be able to distinguish between natural seepage and anthropogenic oil spillage.
The major goal of this study was to establish the geologic setting, sources, and ultimate dispersal of natural oil seeps in the offshore southern Santa Maria Basin and Santa Barbara Basins. Our surveys focused on likely areas of hydrocarbon seepage that are known to occur between Point Arguello and Ventura, California.
Our approach was to 1) document the locations and geochemically fingerprint natural seep oils or tar; 2) geochemically fingerprint coastal tar residues and potential tar sources in this region, both onshore and offshore; 3) establish chemical correlations between offshore active seeps and coastal residues thus linking seep sources to oil residues; 4) measure the rate of natural seepage of individual seeps and attempt to assess regional natural oil and gas seepage rates; and 5) interpret the petroleum system history for the natural seeps.
To document the location of sub-sea oil seeps, we first looked into previous studies within and near our survey area. We measured the concentration of methane gas in the water column in areas of reported seepage and found numerous gas plumes and measured high concentrations of methane in the water column. The result of this work showed that the seeps were widely distributed between Point Conception east to the vicinity of Coal Oil Point, and that they by in large occur within the 3-mile limit of California State waters. Subsequent cruises used sidescan and high resolution seismic to map the seafloor, from just south of Point Arguello, east to near Gaviota, California. The results of the methane survey guided the exploration of the area west of Point Conception east to Gaviota using a combination of seismic instruments. The seafloor was mapped by sidescan sonar, and numerous lines of high -resolution seismic surveys were conducted over areas of interest.
Biomarker and stable carbon isotope ratios were used to infer the age, lithology, organic matter input, and depositional environment of the source rocks for 388 samples of produced crude oil, seep oil, and tarballs mainly from coastal California. These samples were used to construct a chemometric fingerprint (multivariate statistics) decision tree to classify 288 additional samples, including tarballs of unknown origin collected from Monterey and San Mateo County beaches after a storm in early 2007. A subset of 9 of 23 active offshore platform oils and one inactive platform oil representing a few oil reservoirs from the western Santa Barbara Channel were used in this analysis, and thus this model is not comprehensive and the findings are not conclusive. The platform oils included in this study are from west to east: Irene, Hildago, Harvest, Hermosa, Heritage, Harmony, Hondo, Holly, Platform A, and Hilda (now removed).
The results identify three “tribes” of 13C-rich oil samples inferred to originate from thermally mature equivalents of the clayey-siliceous, carbonaceous marl, and lower calcareous-siliceous members of the Monterey Formation. Tribe 1 contains four oil families having geochemical traits of clay-rich marine shale source rock deposited under suboxic conditions with substantial higher-plant input. Tribe 2 contains four oil families with intermediate traits, except for abundant 28,30-bisnorhopane, indicating suboxic to anoxic marine marl source rock with hemipelagic input. Tribe 3 contains five oil families with traits of distal marine carbonate source rock deposited under anoxic conditions with pelagic but little or no higher-plant input. Tribes 1 and 2 occur mainly south of Point Conception in paleogeographic settings where deep burial of the Monterey Formation source rock favored generation from all three members or their equivalents. In this area, oil from the clayey-siliceous and carbonaceous marl members (Tribes 1 and 2) may overwhelm that from the lower calcareous-siliceous member (Tribe 3) because the latter is thinner and less oil-prone than the overlying members. Tribe 3 occurs mainly north of Point Conception, where shallow burial caused preferential generation from the underlying lower calcareous-siliceous member or another unit with similar characteristics.
It is very desirable to be able to clearly distinguish the naturally occurring seep oils from the anthropogenically derived platform oils. Within the “training set” of oils and tars (388 samples), the biomarker parameters are sometimes sufficient to allow unique discrimination of individual platform oils. More often however, platform samples and seep samples with sources geographically close to each other are too similar to each other, with respect to the biomarker parameters, to definitively differentiate them on that basis alone. In some cases other parameters can be helpful. These other parameters are related to the degree of biogeochemical degradation or weathering that the oils or tars have experienced. These components include the typical oil distribution of n-alkane hydrocarbons and isoprenoids pristane and phytane. All of the platform oils in our sample set contain these components. On the other hand, the seep oils or tars have been exposed to significant biodegradation while in the near subsurface. The majority, but not all of seep oils or tars have been biodegraded up to or beyond the loss of n-alkanes and isoprenoids. Seep oils found in the vicinity of Coal Oil Point or Arroyo Burro are apparently the least weathered and are particularly likely to retain significant n-alkanes and isoprenoids. Therefore the combination of chemometric fingerprinting and the presence or absence of n-alkanes and isoprenoids help to differentiate anthropogenic production oils versus natural seeps oils and tars. The differentiation is not always definitive because of the close chemical similarity of some samples and the variability in the biodegradation progression. This is the case near Coal Oil Point, and near Platform A (Dos Cuadros Field) where seep oils and Platform Holly and Platform A oils are genetically very similar and cannot be definitively distinguished after a period of a few days of weathering. In contrast, oils from the Point Conception platforms can be distinguished on the basis of chemometric fingerprinting alone. In the middle of this spectrum are oils from Platforms Harmony, Heritage, and Hondo, where it is expected that oil weathering would take on the order of two weeks to a month to produce tarballs similar to those seen near Point Conception. In this case there is a much greater degree of weathering needed to proceed from produced oil to the biodegraded tar characteristic of tarball stranded on the beach.
Tar deposition on beaches was monitored as part of cooperative with the County of Santa Barbara Energy Division and the U.S. Geological Survey during 2001-2003. We found tar deposition varies on a seasonal basis. In general, tarballs accumulate at a faster rate or remain longer on all beaches during the summer and fall months. The reasons for this are unclear based on our limited observations, however we speculate that factors such as prevailing winds and currents combined with more quiescent wave conditions favors the accumulation and preservation of tarballs on the beach during the summer and fall months. In contrast, winter storms, with much greater wave action remove beach sand and other materials, and stormy seas tend to break up oil that might weather into tarballs. Natural seepage is affected by the spring/neap tidal cycle; however, the link to tar deposition is unclear. Longer periods of monitoring are needed to address the variability in the data and provide a more robust statistical analysis.
","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20091225","collaboration":"A study in cooperation with the Minerals Management Service and the Energy Division, County of Santa Barbara, California; Also released as MMS report 2009-030; This study was funded in part by the U. S. Department of the Interior, Minerals Management Service (MMS), through an Interagency Agreement No. 18985 with the U.S. Geological Survey, Western Coastal and Marine Geology Team, as part of the MMS Environmental Studies Program.","usgsCitation":"Lorenson, T., Hostettler, F.D., Rosenbauer, R.J., Peters, K., Dougherty, J.A., Kvenvolden, K.A., Gutmacher, C.E., Wong, F.L., and Normark, W.R., 2009, Natural offshore oil seepage and related tarball accumulation on the California coastline — Santa Barbara Channel and the southern Santa Maria Basin; source identification and inventory: U.S. Geological Survey Open-File Report 2009-1225, Report: iii, 116 p.; Appendixes, https://doi.org/10.3133/ofr20091225.","productDescription":"Report: iii, 116 p.; Appendixes","onlineOnly":"N","additionalOnlineFiles":"Y","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":645,"text":"Western Coastal and Marine Geology","active":false,"usgs":true}],"links":[{"id":125640,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2009_1225.jpg"},{"id":402029,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_90302.htm"},{"id":13337,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2009/1225/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"California","otherGeospatial":"Santa Barbara Channel, Santa Maria Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.014404296875,\n 34.134541681937364\n ],\n [\n -119.32250976562499,\n 34.134541681937364\n ],\n [\n -119.32250976562499,\n 35.146862906756304\n ],\n [\n -121.014404296875,\n 35.146862906756304\n ],\n [\n -121.014404296875,\n 34.134541681937364\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b00e4b07f02db6982ee","contributors":{"authors":[{"text":"Lorenson, T.D. tlorenson@usgs.gov","contributorId":2622,"corporation":false,"usgs":true,"family":"Lorenson","given":"T.D.","email":"tlorenson@usgs.gov","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":false,"id":304163,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hostettler, Frances D. fdhostet@usgs.gov","contributorId":3383,"corporation":false,"usgs":true,"family":"Hostettler","given":"Frances","email":"fdhostet@usgs.gov","middleInitial":"D.","affiliations":[],"preferred":true,"id":304164,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rosenbauer, Robert J. brosenbauer@usgs.gov","contributorId":204,"corporation":false,"usgs":true,"family":"Rosenbauer","given":"Robert","email":"brosenbauer@usgs.gov","middleInitial":"J.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":304161,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Peters, Kenneth E.","contributorId":10897,"corporation":false,"usgs":true,"family":"Peters","given":"Kenneth E.","affiliations":[],"preferred":false,"id":304167,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dougherty, Jennifer A.","contributorId":6114,"corporation":false,"usgs":true,"family":"Dougherty","given":"Jennifer","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":304166,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kvenvolden, Keith A. kkvenvolden@usgs.gov","contributorId":3384,"corporation":false,"usgs":true,"family":"Kvenvolden","given":"Keith","email":"kkvenvolden@usgs.gov","middleInitial":"A.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":304165,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gutmacher, Christina E.","contributorId":28272,"corporation":false,"usgs":true,"family":"Gutmacher","given":"Christina","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":304168,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wong, Florence L. 0000-0002-3918-5896 fwong@usgs.gov","orcid":"https://orcid.org/0000-0002-3918-5896","contributorId":1990,"corporation":false,"usgs":true,"family":"Wong","given":"Florence","email":"fwong@usgs.gov","middleInitial":"L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":304162,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Normark, William R.","contributorId":69570,"corporation":false,"usgs":true,"family":"Normark","given":"William","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":304169,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":98088,"text":"sir20095231 - 2009 - Regression models to estimate real-time concentrations of selected constituents in two tributaries to Lake Houston near Houston, Texas, 2005-07","interactions":[],"lastModifiedDate":"2016-08-15T11:00:28","indexId":"sir20095231","displayToPublicDate":"2010-01-05T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2009-5231","title":"Regression models to estimate real-time concentrations of selected constituents in two tributaries to Lake Houston near Houston, Texas, 2005-07","docAbstract":"In December 2005, the U.S. Geological Survey in cooperation with the City of Houston, Texas, began collecting discrete water-quality samples for nutrients, total organic carbon, bacteria (total coliform and Escherichia coli), atrazine, and suspended sediment at two U.S. Geological Survey streamflow-gaging stations upstream from Lake Houston near Houston (08068500 Spring Creek near Spring, Texas, and 08070200 East Fork San Jacinto River near New Caney, Texas). The data from the discrete water-quality samples collected during 2005-07, in conjunction with monitored real-time data already being collected - physical properties (specific conductance, pH, water temperature, turbidity, and dissolved oxygen), streamflow, and rainfall - were used to develop regression models for predicting water-quality constituent concentrations for inflows to Lake Houston. Rainfall data were obtained from a rain gage monitored by Harris County Homeland Security and Emergency Management and colocated with the Spring Creek station. The leaps and bounds algorithm was used to find the best subsets of possible regression models (minimum residual sum of squares for a given number of variables). The potential explanatory or predictive variables included discharge (streamflow), specific conductance, pH, water temperature, turbidity, dissolved oxygen, rainfall, and time (to account for seasonal variations inherent in some water-quality data). The response variables at each site were nitrite plus nitrate nitrogen, total phosphorus, organic carbon, Escherichia coli, atrazine, and suspended sediment. The explanatory variables provide easily measured quantities as a means to estimate concentrations of the various constituents under investigation, with accompanying estimates of measurement uncertainty. Each regression equation can be used to estimate concentrations of a given constituent in real time. In conjunction with estimated concentrations, constituent loads were estimated by multiplying the estimated concentration by the corresponding streamflow and applying the appropriate conversion factor. By computing loads from estimated constituent concentrations, a continuous record of estimated loads can be available for comparison to total maximum daily loads. The regression equations presented in this report are site specific to the Spring Creek and East Fork San Jacinto River streamflow-gaging stations; however, the methods that were developed and documented could be applied to other tributaries to Lake Houston for estimating real-time water-quality data for streams entering Lake Houston.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20095231","isbn":"9781411326286","collaboration":"Prepared in cooperation with the City of Houston","usgsCitation":"Oden, T., Asquith, W.H., and Milburn, M.S., 2009, Regression models to estimate real-time concentrations of selected constituents in two tributaries to Lake Houston near Houston, Texas, 2005-07: U.S. Geological Survey Scientific Investigations Report 2009-5231, vi, 44 p., https://doi.org/10.3133/sir20095231.","productDescription":"vi, 44 p.","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2005-01-01","temporalEnd":"2007-12-31","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":125870,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2009_5231.jpg"},{"id":326480,"rank":101,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2009/5231/pdf/sir2009-5231.pdf","text":"Report","size":"8.0 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":13322,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2009/5231/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -96.25,29.75 ], [ -96.25,31 ], [ -94.75,31 ], [ -94.75,29.75 ], [ -96.25,29.75 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a60e4b07f02db634da9","contributors":{"authors":[{"text":"Oden, Timothy D. toden@usgs.gov","contributorId":1284,"corporation":false,"usgs":true,"family":"Oden","given":"Timothy D.","email":"toden@usgs.gov","affiliations":[],"preferred":true,"id":304112,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":304111,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Milburn, Matthew S.","contributorId":53896,"corporation":false,"usgs":true,"family":"Milburn","given":"Matthew","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":304113,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":98087,"text":"sir20095248 - 2009 - The Water Availability Tool for Environmental Resources (WATER): A water-budget modeling approach for managing water-supply resources in non-karst areas of Kentucky (phase I) — Data processing and model structure documentstion","interactions":[],"lastModifiedDate":"2021-12-15T21:02:47.973093","indexId":"sir20095248","displayToPublicDate":"2010-01-05T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2009-5248","title":"The Water Availability Tool for Environmental Resources (WATER): A water-budget modeling approach for managing water-supply resources in non-karst areas of Kentucky (phase I) — Data processing and model structure documentstion","docAbstract":"The Water Availability Tool for Environmental Resources (WATER) was developed in cooperation with the Kentucky Division of Water to provide a consistent and defensible method of estimating streamflow and water availability in ungaged basins. WATER is process oriented; it is based on the TOPMODEL code and incorporates historical water-use data together with physiographic data that quantitatively describe topography and soil-water storage. The result is a user-friendly decision tool that can estimate water availability in non-karst areas of Kentucky without additional data or processing. The model runs on a daily time step, and critical source data include a historical record of daily temperature and precipitation, digital elevation models (DEMs), the Soil Survey Geographic Database (SSURGO), and historical records of water discharges and withdrawals. The model was calibrated and statistically evaluated for 12 basins by comparing the estimated discharge to that observed at U.S. Geological Survey streamflow-gaging stations. When statistically evaluated over a 2,119-day time period, the discharge estimates showed a bias of -0.29 to 0.42, a root mean square error of 1.66 to 5.06, a correlation of 0.54 to 0.85, and a Nash-Sutcliffe Efficiency of 0.26 to 0.72. The parameter and input modifications that most significantly improved the accuracy and precision of streamflow-discharge estimates were the addition of Next Generation radar (NEXRAD) precipitation data, a rooting depth of 30 centimeters, and a TOPMODEL scaling parameter (m) derived directly from SSURGO data that was multiplied by an adjustment factor of 0.10. No site-specific optimization was used.","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/sir20095248","collaboration":"Prepared in cooperation with the Kentucky Division of Water","usgsCitation":"Williamson, T., Odom, K.R., Newson, J.K., Downs, A.C., Nelson, H.L., Cinotto, P.J., and Ayers, M.A., 2009, The Water Availability Tool for Environmental Resources (WATER): A water-budget modeling approach for managing water-supply resources in non-karst areas of Kentucky (phase I) — Data processing and model structure documentstion: U.S. Geological Survey Scientific Investigations Report 2009-5248, vi, 34 p., https://doi.org/10.3133/sir20095248.","productDescription":"vi, 34 p.","costCenters":[{"id":354,"text":"Kentucky Water Science Center","active":true,"usgs":true}],"links":[{"id":125858,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2009_5248.jpg"},{"id":392968,"rank":3,"type":{"id":36,"text":"NGMDB Index 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Center","active":true,"usgs":true}],"preferred":false,"id":304108,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Downs, Aimee C. acdowns@usgs.gov","contributorId":929,"corporation":false,"usgs":true,"family":"Downs","given":"Aimee","email":"acdowns@usgs.gov","middleInitial":"C.","affiliations":[],"preferred":true,"id":304106,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Nelson, Hugh L. hlnelson@usgs.gov","contributorId":4158,"corporation":false,"usgs":true,"family":"Nelson","given":"Hugh","email":"hlnelson@usgs.gov","middleInitial":"L.","affiliations":[{"id":354,"text":"Kentucky Water Science Center","active":true,"usgs":true}],"preferred":true,"id":304107,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cinotto, Peter J. pcinotto@usgs.gov","contributorId":451,"corporation":false,"usgs":true,"family":"Cinotto","given":"Peter","email":"pcinotto@usgs.gov","middleInitial":"J.","affiliations":[{"id":354,"text":"Kentucky Water Science Center","active":true,"usgs":true}],"preferred":true,"id":304104,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ayers, Mark A.","contributorId":84730,"corporation":false,"usgs":true,"family":"Ayers","given":"Mark","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":304110,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70046864,"text":"70046864 - 2009 - Using a coupled groundwater/surface-water model to predict climate-change impacts to lakes in the Trout Lake Watershed, northern Wisconsin","interactions":[{"subject":{"id":70046864,"text":"70046864 - 2009 - Using a coupled groundwater/surface-water model to predict climate-change impacts to lakes in the Trout Lake Watershed, northern Wisconsin","indexId":"70046864","publicationYear":"2009","noYear":false,"title":"Using a coupled groundwater/surface-water model to predict climate-change impacts to lakes in the Trout Lake Watershed, northern Wisconsin"},"predicate":"IS_PART_OF","object":{"id":97928,"text":"sir20095049 - 2009 - Planning for an uncertain future - Monitoring, integration, and adaptation","indexId":"sir20095049","publicationYear":"2009","noYear":false,"title":"Planning for an uncertain future - Monitoring, integration, and adaptation"},"id":1}],"isPartOf":{"id":97928,"text":"sir20095049 - 2009 - Planning for an uncertain future - Monitoring, integration, and adaptation","indexId":"sir20095049","publicationYear":"2009","noYear":false,"title":"Planning for an uncertain future - Monitoring, integration, and adaptation"},"lastModifiedDate":"2016-08-18T16:10:55","indexId":"70046864","displayToPublicDate":"2010-01-01T11:49:00","publicationYear":"2009","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"seriesNumber":"2009-5049","title":"Using a coupled groundwater/surface-water model to predict climate-change impacts to lakes in the Trout Lake Watershed, northern Wisconsin","docAbstract":"A major focus of the U.S. Geological Survey’s Trout Lake Water, Energy, and Biogeochemical Budgets (WEBB) project is the development of a watershed model to allow predictions of hydrologic response to future conditions including land-use and climate change. The coupled groundwater/surface-water model GSFLOW was chosen for this purpose because it could easily incorporate an existing groundwater flow model and it provides for simulation of surface-water processes.
\n\n
The Trout Lake watershed in northern Wisconsin is underlain by a highly conductive outwash sand aquifer. In this area, streamflow is dominated by groudwater contributions, however, surface runoff occurs during intense rainfall periods and spring snowmelt. Surface runoff also occurs locally near stream/lake areas where the unsaturated zone is thin. A diverse data set, collected from 1992 to 2007 for the Trout Lake WEBB project and the co-located and NSF-funded North Temperate Lake LTER project, includes snowpack, solar radiation, potential evapotranspiration, lake levels, groundwater levels, and streamflow. The time-series processing software TSPROC (Doherty 2001)was used to distill the large time series data set to a smaller set of observations and summary statistics that captured the salient hydrologic information. The time-series processing reduced hundreds of thousands of observations to less than 5,000. Model calibration included specific predictions for several lakes in the study area using the PEST parameter estimation suit of software (Doherty 2007). The calibrated model was used to simulate the hydrologic response in the study lakes to a variety of climate change scenarios culled from the IPCC Fourth Assessment Report of the Intergovernmental Panel of Climate Change (Solomon et al. 2007). Results from the simulations indicate climate change could result in substantial changes to the lake levels and components of the hydrologic budget of a seepage lake in the flow system. For a drainage lake lower in the flow system, the impacts of climate change are diminished.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Planning for an uncertain future - monitoring, integration, and adaptation (SIR 2009-5049)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"conferenceTitle":"3rd interagency conference on research in the watersheds: planning for an uncertain future: monitoring, integration, and adaptation","conferenceDate":"8-11 September, 2008","conferenceLocation":"Estes Park, CO","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","usgsCitation":"Hunt, R., Walker, J.F., Markstrom, S., Hay, L.E., and Doherty, J., 2009, Using a coupled groundwater/surface-water model to predict climate-change impacts to lakes in the Trout Lake Watershed, northern Wisconsin, in Planning for an uncertain future - monitoring, integration, and adaptation (SIR 2009-5049), Estes Park, CO, 8-11 September, 2008, p. 155-161.","productDescription":"7 p.","startPage":"155","endPage":"161","numberOfPages":"7","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-009788","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":289370,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":326855,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2009/5049/pdf/SIR09-5049.pdf"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Trout Lake","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -89.703926,46.012934 ], [ -89.703926,46.079112 ], [ -89.646771,46.079112 ], [ -89.646771,46.012934 ], [ -89.703926,46.012934 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53b7b27ee4b0388651d9198c","contributors":{"editors":[{"text":"Webb, Richard M. T. 0000-0001-9531-2207","orcid":"https://orcid.org/0000-0001-9531-2207","contributorId":35772,"corporation":false,"usgs":true,"family":"Webb","given":"Richard M. T.","affiliations":[],"preferred":false,"id":646256,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Semmens, Darius J. 0000-0001-7924-6529 dsemmens@usgs.gov","orcid":"https://orcid.org/0000-0001-7924-6529","contributorId":1714,"corporation":false,"usgs":true,"family":"Semmens","given":"Darius","email":"dsemmens@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":646257,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Hunt, Randall J. 0000-0001-6465-9304","orcid":"https://orcid.org/0000-0001-6465-9304","contributorId":16118,"corporation":false,"usgs":true,"family":"Hunt","given":"Randall J.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":480496,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Walker, John F. jfwalker@usgs.gov","contributorId":1081,"corporation":false,"usgs":true,"family":"Walker","given":"John","email":"jfwalker@usgs.gov","middleInitial":"F.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":480493,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Markstrom, Steven L. 0000-0001-7630-9547 markstro@usgs.gov","orcid":"https://orcid.org/0000-0001-7630-9547","contributorId":1986,"corporation":false,"usgs":true,"family":"Markstrom","given":"Steven L.","email":"markstro@usgs.gov","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":false,"id":480495,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hay, Lauren E. 0000-0003-3763-4595 lhay@usgs.gov","orcid":"https://orcid.org/0000-0003-3763-4595","contributorId":1287,"corporation":false,"usgs":true,"family":"Hay","given":"Lauren","email":"lhay@usgs.gov","middleInitial":"E.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":480494,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Doherty, John","contributorId":43843,"corporation":false,"usgs":true,"family":"Doherty","given":"John","affiliations":[],"preferred":false,"id":480497,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70104212,"text":"70104212 - 2009 - Hindcasting of decadal‐timescale estuarine bathymetric change with a tidal‐timescale model","interactions":[],"lastModifiedDate":"2014-05-13T09:07:41","indexId":"70104212","displayToPublicDate":"2010-01-01T09:00:28","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2318,"text":"Journal of Geophysical Research F: Earth Surface","active":true,"publicationSubtype":{"id":10}},"title":"Hindcasting of decadal‐timescale estuarine bathymetric change with a tidal‐timescale model","docAbstract":"Hindcasting decadal-timescale bathymetric change in estuaries is prone to error due to limited data for initial conditions, boundary forcing, and calibration; computational limitations further hinder efforts. We developed and calibrated a tidal-timescale model to bathymetric change in Suisun Bay, California, over the 1867–1887 period. A general, multiple-timescale calibration ensured robustness over all timescales; two input reduction methods, the morphological hydrograph and the morphological acceleration factor, were applied at the decadal timescale. The model was calibrated to net bathymetric change in the entire basin; average error for bathymetric change over individual depth ranges was 37%. On a model cell-by-cell basis, performance for spatial amplitude correlation was poor over the majority of the domain, though spatial phase correlation was better, with 61% of the domain correctly indicated as erosional or depositional. Poor agreement was likely caused by the specification of initial bed composition, which was unknown during the 1867–1887 period. Cross-sectional bathymetric change between channels and flats, driven primarily by wind wave resuspension, was modeled with higher skill than longitudinal change, which is driven in part by gravitational circulation. The accelerated response of depth may have prevented gravitational circulation from being represented properly. As performance criteria became more stringent in a spatial sense, the error of the model increased. While these methods are useful for estimating basin-scale sedimentation changes, they may not be suitable for predicting specific locations of erosion or deposition. They do, however, provide a foundation for realistic estuarine geomorphic modeling applications.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Geophysical Research F: Earth Surface","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Amercan Geophysical Union","doi":"10.1029/2008JF001191","usgsCitation":"Ganju, N., Schoellhamer, D., and Jaffe, B.E., 2009, Hindcasting of decadal‐timescale estuarine bathymetric change with a tidal‐timescale model: Journal of Geophysical Research F: Earth Surface, v. 114, no. F4, 15 p., https://doi.org/10.1029/2008JF001191.","productDescription":"15 p.","numberOfPages":"15","temporalStart":"1866-12-31","temporalEnd":"1887-12-31","ipdsId":"IP-003086","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":476012,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/1912/3105","text":"External Repository"},{"id":287069,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":287063,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1029/2008JF001191"}],"country":"United States","state":"California","otherGeospatial":"Suisun Bay","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.75,37.75 ], [ -122.75,38.25 ], [ -121.75,38.25 ], [ -121.75,37.75 ], [ -122.75,37.75 ] ] ] } } ] }","volume":"114","issue":"F4","noUsgsAuthors":false,"publicationDate":"2009-12-02","publicationStatus":"PW","scienceBaseUri":"53733efae4b0497061278906","contributors":{"authors":[{"text":"Ganju, Neil K. 0000-0002-1096-0465","orcid":"https://orcid.org/0000-0002-1096-0465","contributorId":93543,"corporation":false,"usgs":true,"family":"Ganju","given":"Neil K.","affiliations":[],"preferred":false,"id":493638,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schoellhamer, David H. 0000-0001-9488-7340 dschoell@usgs.gov","orcid":"https://orcid.org/0000-0001-9488-7340","contributorId":631,"corporation":false,"usgs":true,"family":"Schoellhamer","given":"David H.","email":"dschoell@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":493636,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jaffe, Bruce E. 0000-0002-8816-5920 bjaffe@usgs.gov","orcid":"https://orcid.org/0000-0002-8816-5920","contributorId":2049,"corporation":false,"usgs":true,"family":"Jaffe","given":"Bruce","email":"bjaffe@usgs.gov","middleInitial":"E.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":493637,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":98085,"text":"sir20095257 - 2009 - Geomorphology and river dynamics of the lower Copper River, Alaska","interactions":[],"lastModifiedDate":"2018-04-23T10:30:15","indexId":"sir20095257","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2009-5257","title":"Geomorphology and river dynamics of the lower Copper River, Alaska","docAbstract":"Located in south-central Alaska, the Copper River drains an area of more than 24,000 square miles. The average annual flow of the river near its mouth is 63,600 cubic feet per second, but is highly variable between winter and summer. In the winter, flow averages approximately 11,700 cubic feet per second, and in the summer, due to snowmelt, rainfall, and glacial melt, flow averages approximately 113,000 cubic feet per second, an order of magnitude higher. About 15 miles upstream of its mouth, the Copper River flows past the face of Childs Glacier and enters a large, broad, delta. The Copper River Highway traverses this flood plain, and in 2008, 11 bridges were located along this section of the highway. The bridges cross several parts of the Copper River and in recent years, the changing course of the river has seriously damaged some of the bridges.
Analysis of aerial photography from 1991, 1996, 2002, 2006, and 2007 indicates the eastward migration of a channel of the Copper River that has resulted in damage to the Copper River Highway near Mile 43.5. Migration of another channel in the flood plain has resulted in damage to the approach of Bridge 339. As a verification of channel change, flow measurements were made at bridges along the Copper River Highway in 2005–07. Analysis of the flow measurements indicate that the total flow of the Copper River has shifted from approximately 50 percent passing through the bridges at Mile 27, near the western edge of the flood plain, and 50 percent passing through the bridges at Mile 36–37 to approximately 5 percent passing through the bridges at Mile 27 and 95 percent through the bridges at Mile 36–37 during average flow periods.
The U.S. Geological Survey’s Multi-Dimensional Surface-Water Modeling System was used to simulate water-surface elevation and velocity, and to compute bed shear stress at two areas where the Copper River is affecting the Copper River Highway. After calibration, the model was used to examine the effects that betterments, such as guide banks or bridge extensions, would have on flow conditions and to provide sound conceptual information that could help decide if a proposed betterment will work or determine potential problems that need to be addressed for a particular betterment. The ability of the model to simulate these hydraulic conditions was constrained by the accuracy and level of channel geometry detail, which is constantly changing in the lower Copper River.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20095257","collaboration":"Prepared in cooperation with the Alaska Department of Transportation and Public Facilities under Project COPPER RIVER HWY MP 27-49 HYDROLOGY STUDY - AKSAS 61959","usgsCitation":"Brabets, T.P., and Conaway, J.S., 2009, Geomorphology and river dynamics of the lower Copper River, Alaska: U.S. Geological Survey Scientific Investigations Report 2009-5257, vi, 43 p., https://doi.org/10.3133/sir20095257.","productDescription":"vi, 43 p.","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":125874,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2009_5257.jpg"},{"id":353645,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2009/5257/pdf/sir20095257.pdf","text":"Report","size":"6.8 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":13319,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2009/5257/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -148,60 ], [ -148,64 ], [ -140,64 ], [ -140,60 ], [ -148,60 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ac9e4b07f02db67c4c1","contributors":{"authors":[{"text":"Brabets, Timothy P. tbrabets@usgs.gov","contributorId":2087,"corporation":false,"usgs":true,"family":"Brabets","given":"Timothy","email":"tbrabets@usgs.gov","middleInitial":"P.","affiliations":[],"preferred":true,"id":304099,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Conaway, Jeffrey S. 0000-0002-3036-592X jconaway@usgs.gov","orcid":"https://orcid.org/0000-0002-3036-592X","contributorId":2026,"corporation":false,"usgs":true,"family":"Conaway","given":"Jeffrey","email":"jconaway@usgs.gov","middleInitial":"S.","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":304100,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70042388,"text":"70042388 - 2009 - Multi-scale measurements and modeling of denitrification in streams with varying flow and nitrate concentration in the upper Mississippi River basin, USA","interactions":[],"lastModifiedDate":"2018-10-05T09:50:25","indexId":"70042388","displayToPublicDate":"2010-01-01T00:00:00","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1007,"text":"Biogeochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Multi-scale measurements and modeling of denitrification in streams with varying flow and nitrate concentration in the upper Mississippi River basin, USA","docAbstract":"Denitrification is an important net sink for NO3− in streams, but direct measurements are limited and in situ controlling factors are not well known. We measured denitrification at multiple scales over a range of flow conditions and NO3− concentrations in streams draining agricultural land in the upper Mississippi River basin. Comparisons of reach-scale measurements (in-stream mass transport and tracer tests) with local-scale in situ measurements (pore-water profiles, benthic chambers) and laboratory data (sediment core microcosms) gave evidence for heterogeneity in factors affecting benthic denitrification both temporally (e.g., seasonal variation in NO3− concentrations and loads, flood-related disruption and re-growth of benthic communities and organic deposits) and spatially (e.g., local stream morphology and sediment characteristics). When expressed as vertical denitrification flux per unit area of streambed (Udenit, in μmol N m−2 h−1), results of different methods for a given set of conditions commonly were in agreement within a factor of 2–3. At approximately constant temperature (~20 ± 4°C) and with minimal benthic disturbance, our aggregated data indicated an overall positive relation between Udenit (~0–4,000 μmol N m−2 h−1) and stream NO3−concentration (~20–1,100 μmol L−1) representing seasonal variation from spring high flow (high NO3−) to late summer low flow (low NO3−). The temporal dependence of Udenit on NO3−was less than first-order and could be described about equally well with power-law or saturation equations (e.g., for the unweighted dataset, Udenit ≈26 * [NO3−]0.44 or Udenit≈640 * [NO3−]/[180 + NO3−]; for a partially weighted dataset, Udenit ≈14 * [NO3−]0.54 or Udenit ≈700 * [NO3−]/[320 + NO3−]). Similar parameters were derived from a recent spatial comparison of stream denitrification extending to lower NO3− concentrations (LINX2), and from the combined dataset from both studies over 3 orders of magnitude in NO3−concentration. Hypothetical models based on our results illustrate: (1) Udenit was inversely related to denitrification rate constant (k1denit, in day−1) and vertical transfer velocity (vf,denit, in m day−1) at seasonal and possibly event time scales; (2) although k1denit was relatively large at low flow (low NO3−), its impact on annual loads was relatively small because higher concentrations and loads at high flow were not fully compensated by increases in Udenit; and (3) although NO3− assimilation and denitrification were linked through production of organic reactants, rates of NO3− loss by these processes may have been partially decoupled by changes in flow and sediment transport. Whereas k1denit and vf,denit are linked implicitly with stream depth, NO3− concentration, and(or) NO3− load, estimates of Udenit may be related more directly to field factors (including NO3− concentration) affecting denitrification rates in benthic sediments. Regional regressions and simulations of benthic denitrification in stream networks might be improved by including a non-linear relation between Udenit and stream NO3−concentration and accounting for temporal variation.
","language":"English","publisher":"Springer","doi":"10.1007/s10533-008-9282-8","usgsCitation":"Bohlke, J., Antweiler, R.C., Harvey, J.W., Laursen, A.E., Smith, L.K., Smith, R.L., and Voytek, M.A., 2009, Multi-scale measurements and modeling of denitrification in streams with varying flow and nitrate concentration in the upper Mississippi River basin, USA: Biogeochemistry, v. 93, no. 1, p. 117-141, https://doi.org/10.1007/s10533-008-9282-8.","productDescription":"24 p.","startPage":"117","endPage":"141","ipdsId":"IP-008428","costCenters":[{"id":146,"text":"Branch of Regional Research-Eastern Region","active":false,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":476016,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10533-008-9282-8","text":"Publisher Index Page"},{"id":270742,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s10533-008-9282-8"},{"id":270743,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"93","issue":"1","noUsgsAuthors":false,"publicationDate":"2009-01-13","publicationStatus":"PW","scienceBaseUri":"5165386ce4b077fa94dadfc3","contributors":{"authors":[{"text":"Bohlke, J.K. 0000-0001-5693-6455 jkbohlke@usgs.gov","orcid":"https://orcid.org/0000-0001-5693-6455","contributorId":191103,"corporation":false,"usgs":true,"family":"Bohlke","given":"J.K.","email":"jkbohlke@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":471448,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Antweiler, Ronald C. 0000-0001-5652-6034 antweil@usgs.gov","orcid":"https://orcid.org/0000-0001-5652-6034","contributorId":1481,"corporation":false,"usgs":true,"family":"Antweiler","given":"Ronald","email":"antweil@usgs.gov","middleInitial":"C.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":471444,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harvey, Judson W. 0000-0002-2654-9873 jwharvey@usgs.gov","orcid":"https://orcid.org/0000-0002-2654-9873","contributorId":1796,"corporation":false,"usgs":true,"family":"Harvey","given":"Judson","email":"jwharvey@usgs.gov","middleInitial":"W.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":471446,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Laursen, Andrew E.","contributorId":99783,"corporation":false,"usgs":true,"family":"Laursen","given":"Andrew","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":471450,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smith, Lesley K.","contributorId":82657,"corporation":false,"usgs":true,"family":"Smith","given":"Lesley","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":471447,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Smith, Richard L. 0000-0002-3829-0125 rlsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-3829-0125","contributorId":1592,"corporation":false,"usgs":true,"family":"Smith","given":"Richard","email":"rlsmith@usgs.gov","middleInitial":"L.","affiliations":[{"id":38175,"text":"Toxics Substances Hydrology Program","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":36183,"text":"Hydro-Ecological Interactions Branch","active":true,"usgs":true}],"preferred":true,"id":471445,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Voytek, Mary A.","contributorId":91943,"corporation":false,"usgs":true,"family":"Voytek","given":"Mary","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":471449,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ]}