Native Coastal Cutthroat Trout Oncorhynchus clarkii clarkii and Coastal Steelhead O. mykiss irideus hybridize naturally in watersheds of the Pacific Northwest yet maintain species integrity. Partial reproductive isolation due to differences in spawning habitat may limit hybridization between these species, but this process is poorly understood. We used a riverscape approach to determine the spatial distribution of spawning habitats used by native Coastal Cutthroat Trout and Steelhead as evidenced by the distribution of recently emerged fry. Molecular genetic markers were used to classify individuals as pure species or hybrids, and individuals were assigned to age-classes based on length. Fish and physical habitat data were collected in a spatially continuous framework to assess the relationship between habitat and watershed features and the spatial distribution of parental species and hybrids. Sampling occurred in 35 reaches from tidewaters to headwaters in a small (20 km2) coastal watershed in Washington State. Cutthroat, Steelhead, and hybrid trout accounted for 35%, 42%, and 23% of the fish collected, respectively. Strong segregation of spawning areas between Coastal Cutthroat Trout and Steelhead was evidenced by the distribution of age-0 trout. Cutthroat Trout were located farther upstream and in smaller tributaries than Steelhead were. The best predictor of species occurrence at a site was the drainage area of the watershed that contributed to the site. This area was positively correlated with the occurrence of age-0 Steelhead and negatively with the presence of Cutthroat Trout, whereas hybrids were found in areas occupied by both parental species. A similar pattern was observed in older juveniles of both species but overlap was greater, suggesting substantial dispersal of trout after emergence. Our results offer support for spatial reproductive segregation as a factor limiting hybridization between Steelhead and Coastal Cutthroat Trout.
","language":"English","publisher":"American Fisheries Society","doi":"10.1080/00028487.2012.728165","usgsCitation":"Buehrens, T., Glasgow, J., Ostberg, C.O., and Quinn, T., 2013, Spatial segregation of spawning habitat limits hybridization between sympatric native Steelhead and Coastal Cutthroat Trout: Transactions of the American Fisheries Society, v. 142, no. 1, p. 221-233, https://doi.org/10.1080/00028487.2012.728165.","productDescription":"13 p.","startPage":"221","endPage":"233","numberOfPages":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-037064","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":271795,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Ellsworth Creek, Willapa Bay","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.05,46.37 ], [ -124.05,46.70 ], [ -123.94,46.70 ], [ -123.94,46.37 ], [ -124.05,46.37 ] ] ] } } ] }","volume":"142","issue":"1","noUsgsAuthors":false,"publicationDate":"2012-12-21","publicationStatus":"PW","scienceBaseUri":"5184dc65e4b04d6ec94d62bd","contributors":{"authors":[{"text":"Buehrens, T.W.","contributorId":9149,"corporation":false,"usgs":true,"family":"Buehrens","given":"T.W.","email":"","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":false,"id":475133,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Glasgow, J.","contributorId":17116,"corporation":false,"usgs":true,"family":"Glasgow","given":"J.","email":"","affiliations":[],"preferred":false,"id":475134,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ostberg, Carl O. 0000-0003-1479-8458 costberg@usgs.gov","orcid":"https://orcid.org/0000-0003-1479-8458","contributorId":3031,"corporation":false,"usgs":true,"family":"Ostberg","given":"Carl","email":"costberg@usgs.gov","middleInitial":"O.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":475132,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Quinn, T.P.","contributorId":64535,"corporation":false,"usgs":false,"family":"Quinn","given":"T.P.","email":"","affiliations":[{"id":13190,"text":"School of Aquatic and Fishery Sciences, University of Washington","active":true,"usgs":false}],"preferred":false,"id":475135,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70045584,"text":"70045584 - 2013 - Estimating floodplain sedimentation in the Laguna de Santa Rosa, Sonoma County, CA","interactions":[],"lastModifiedDate":"2013-04-24T16:57:38","indexId":"70045584","displayToPublicDate":"2013-04-24T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3750,"text":"Wetlands","onlineIssn":"1943-6246","printIssn":"0277-5212","active":true,"publicationSubtype":{"id":10}},"title":"Estimating floodplain sedimentation in the Laguna de Santa Rosa, Sonoma County, CA","docAbstract":"We present a conceptual and analytical framework for predicting the spatial distribution of floodplain sedimentation for the Laguna de Santa Rosa, Sonoma County, CA. We assess the role of the floodplain as a sink for fine-grained sediment and investigate concerns regarding the potential loss of flood storage capacity due to historic sedimentation. We characterized the spatial distribution of sedimentation during a post-flood survey and developed a spatially distributed sediment deposition potential map that highlights zones of floodplain sedimentation. The sediment deposition potential map, built using raster files that describe the spatial distribution of relevant hydrologic and landscape variables, was calibrated using 2 years of measured overbank sedimentation data and verified using longer-term rates determined using dendrochronology. The calibrated floodplain deposition potential relation was used to estimate an average annual floodplain sedimentation rate (3.6 mm/year) for the ~11 km2 floodplain. This study documents the development of a conceptual model of overbank sedimentation, describes a methodology to estimate the potential for various parts of a floodplain complex to accumulate sediment over time, and provides estimates of short and long-term overbank sedimentation rates that can be used for ecosystem management and prioritization of restoration activities.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Wetlands","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Springer","doi":"10.1007/s13157-012-0350-4","usgsCitation":"Curtis, J.A., Flint, L.E., and Hupp, C.R., 2013, Estimating floodplain sedimentation in the Laguna de Santa Rosa, Sonoma County, CA: Wetlands, v. 33, no. 1, p. 29-45, https://doi.org/10.1007/s13157-012-0350-4.","productDescription":"17 p.","startPage":"29","endPage":"45","ipdsId":"IP-018988","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":271425,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":271424,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1007/s13157-012-0350-4"}],"country":"United States","state":"California","county":"Sonoma County","city":"Santa Rosa","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.8341,38.3637 ], [ -122.8341,38.5074 ], [ -122.573,38.5074 ], [ -122.573,38.3637 ], [ -122.8341,38.3637 ] ] ] } } ] }","volume":"33","issue":"1","noUsgsAuthors":false,"publicationDate":"2012-12-20","publicationStatus":"PW","scienceBaseUri":"5178f0dee4b0d842c705f6b8","contributors":{"authors":[{"text":"Curtis, Jennifer A. 0000-0001-7766-994X jacurtis@usgs.gov","orcid":"https://orcid.org/0000-0001-7766-994X","contributorId":927,"corporation":false,"usgs":true,"family":"Curtis","given":"Jennifer","email":"jacurtis@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477874,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Flint, Lorraine E. 0000-0002-7868-441X lflint@usgs.gov","orcid":"https://orcid.org/0000-0002-7868-441X","contributorId":1184,"corporation":false,"usgs":true,"family":"Flint","given":"Lorraine","email":"lflint@usgs.gov","middleInitial":"E.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477875,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hupp, Cliff R. 0000-0003-1853-9197 crhupp@usgs.gov","orcid":"https://orcid.org/0000-0003-1853-9197","contributorId":2344,"corporation":false,"usgs":true,"family":"Hupp","given":"Cliff","email":"crhupp@usgs.gov","middleInitial":"R.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":477876,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70188332,"text":"70188332 - 2013 - Radiometric cross-calibration of EO-1 ALI with L7 ETM+ and Terra MODIS sensors using near-simultaneous desert observations","interactions":[],"lastModifiedDate":"2017-06-06T14:29:04","indexId":"70188332","displayToPublicDate":"2013-04-24T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1942,"text":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Radiometric cross-calibration of EO-1 ALI with L7 ETM+ and Terra MODIS sensors using near-simultaneous desert observations","docAbstract":"The Earth Observing-1 (EO-1) satellite was launched on November 21, 2000, as part of a one-year technology demonstration mission. The mission was extended because of the value it continued to add to the scientific community. EO-1 has now been operational for more than a decade, providing both multispectral and hyperspectral measurements. As part of the EO-1 mission, the Advanced Land Imager (ALI) sensor demonstrates a potential technological direction for the next generation of Landsat sensors. To evaluate the ALI sensor capabilities as a precursor to the Operational Land Imager (OLI) onboard the Landsat Data Continuity Mission (LDCM, or Landsat 8 after launch), its measured top-of-atmosphere (TOA) reflectances were compared to the well-calibrated Landsat 7 (L7) Enhanced Thematic Mapper Plus (ETM+) and the Terra Moderate Resolution Imaging Spectroradiometer (MODIS) sensors in the reflective solar bands (RSB). These three satellites operate in a near-polar, sun-synchronous orbit 705 km above the Earth's surface. EO-1 was designed to fly one minute behind L7 and approximately 30 minutes in front of Terra. In this configuration, all the three sensors can view near-identical ground targets with similar atmospheric, solar, and viewing conditions. However, because of the differences in the relative spectral response (RSR), the measured physical quantities can be significantly different while observing the same target. The cross-calibration of ALI with ETM+ and MODIS was performed using near-simultaneous surface observations based on image statistics from areas observed by these sensors over four desert sites (Libya 4, Mauritania 2, Arabia 1, and Sudan 1). The differences in the measured TOA reflectances due to RSR mismatches were compensated by using a spectral band adjustment factor (SBAF), which takes into account the spectral profile of the target and the RSR of each sensor. For this study, the spectral profile of the target comes from the near-simultaneous EO-1 Hyperion data over these sites. The results indicate that the TOA reflectance measurements for ALI agree with those of ETM+ and MODIS to within 5% after the application of SBAF.
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Taeyoung","contributorId":146955,"corporation":false,"usgs":false,"family":"Choi","given":"Taeyoung","email":"","affiliations":[],"preferred":false,"id":697314,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Xiong, Xiaoxiong","contributorId":15088,"corporation":false,"usgs":true,"family":"Xiong","given":"Xiaoxiong","email":"","affiliations":[],"preferred":false,"id":697315,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70042643,"text":"70042643 - 2013 - Descriptors of natural thermal regimes in streams and their responsiveness to change in the Pacific Northwest of North America","interactions":[],"lastModifiedDate":"2013-04-23T14:17:42","indexId":"70042643","displayToPublicDate":"2013-04-23T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1696,"text":"Freshwater Biology","active":true,"publicationSubtype":{"id":10}},"title":"Descriptors of natural thermal regimes in streams and their responsiveness to change in the Pacific Northwest of North America","docAbstract":"1. Temperature is a major driver of ecological processes in stream ecosystems, yet the dynamics of thermal regimes remain poorly described. Most work has focused on relatively simple descriptors that fail to capture the full range of conditions that characterise thermal regimes of streams across seasons or throughout the year.\n\n2. To more completely describe thermal regimes, we developed several descriptors of magnitude, variability, frequency, duration and timing of thermal events throughout a year. We evaluated how these descriptors change over time using long-term (1979–2009), continuous temperature data from five relatively undisturbed cold-water streams in western Oregon, U.S.A. In addition to trends for each descriptor, we evaluated similarities among them, as well as patterns of spatial coherence, and temporal synchrony.\n\n3. Using different groups of descriptors, we were able to more fully capture distinct aspects of the full range of variability in thermal regimes across space and time. A subset of descriptors showed both higher coherence and synchrony and, thus, an appropriate level of responsiveness to examine evidence of regional climatic influences on thermal regimes. Most notably, daily minimum values during winter–spring were the most responsive descriptors to potential climatic influences.\n\n4. Overall, thermal regimes in streams we studied showed high frequency and low variability of cold temperatures during the cold-water period in winter and spring, and high frequency and high variability of warm temperatures during the warm-water period in summer and autumn. The cold and warm periods differed in the distribution of events with a higher frequency and longer duration of warm events in summer than cold events in winter. The cold period exhibited lower variability in the duration of events, but showed more variability in timing.\n\n5. In conclusion, our results highlight the importance of a year-round perspective in identifying the most responsive characteristics or descriptors of thermal regimes in streams. The descriptors we provide herein can be applied across hydro-ecological regions to evaluate spatial and temporal patterns in thermal regimes. Evaluation of coherence and synchrony of different components of thermal regimes can facilitate identification of impacts of regional climate variability or local human or natural influences.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Freshwater Biology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1111/fwb.12094","usgsCitation":"Arismendi, I., Johnson, S.L., Dunham, J., and Haggerty, R., 2013, Descriptors of natural thermal regimes in streams and their responsiveness to change in the Pacific Northwest of North America: Freshwater Biology, v. 58, no. 5, p. 880-894, https://doi.org/10.1111/fwb.12094.","productDescription":"15 p.","startPage":"880","endPage":"894","ipdsId":"IP-042716","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":271407,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":271406,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/fwb.12094"}],"otherGeospatial":"North America","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 177.1,5.6 ], [ 177.1,85.4 ], [ -4.0,85.4 ], [ -4.0,5.6 ], [ 177.1,5.6 ] ] ] } } ] }","volume":"58","issue":"5","noUsgsAuthors":false,"publicationDate":"2013-01-15","publicationStatus":"PW","scienceBaseUri":"51779f57e4b095699adf2722","contributors":{"authors":[{"text":"Arismendi, Ivan","contributorId":70661,"corporation":false,"usgs":true,"family":"Arismendi","given":"Ivan","affiliations":[],"preferred":false,"id":471965,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Sherri L.","contributorId":91757,"corporation":false,"usgs":true,"family":"Johnson","given":"Sherri","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":471966,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dunham, Jason B.","contributorId":64791,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason B.","affiliations":[],"preferred":false,"id":471964,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haggerty, Roy","contributorId":102631,"corporation":false,"usgs":true,"family":"Haggerty","given":"Roy","affiliations":[],"preferred":false,"id":471967,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70045566,"text":"ds761 - 2013 - Archive of post-Hurricane Isabel coastal oblique aerial photographs collected during U.S. Geological Survey Field Activity 03CCH01 from Ocean City, Maryland, to Fort Caswell, North Carolina and Inland from Waynesboro to Redwood, Virginia, September 21 - 23, 2003","interactions":[],"lastModifiedDate":"2016-12-02T12:13:32","indexId":"ds761","displayToPublicDate":"2013-04-23T00:00:00","publicationYear":"2013","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":"761","title":"Archive of post-Hurricane Isabel coastal oblique aerial photographs collected during U.S. Geological Survey Field Activity 03CCH01 from Ocean City, Maryland, to Fort Caswell, North Carolina and Inland from Waynesboro to Redwood, Virginia, September 21 - 23, 2003","docAbstract":"On September 21 - 23, 2003, the United States Geological Survey (USGS) conducted an oblique aerial photographic survey along the Atlantic coast from Ocean City, Md., to Fort Caswell, N.C., and inland oblique aerial photographic survey from Waynesboro to Redwood, Va., aboard a Navajo Piper twin-engine airplane. The coastal survey was conducted at an altitude of 500 feet (ft) and approximately 1,000 ft offshore. For the inland photos, the aircraft tried to stay approximately 500 ft above the terrain. These coastal photos were used to document coastal changes like beach erosion and overwash caused by Hurricane Isabel, while the inland photos looked for potential landslides caused by heavy rains. The photos may also be used as baseline data for future coastal change analysis. The USGS and the National Aeronautics and Space Administration (NASA) surveyed the impact zone of Hurricane Isabel to better understand the changes in vulnerability of the Nation’s coasts to extreme storms (Morgan, 2009). This report serves as an archive of photographs collected during the September 21 - 23, 2003, post-Hurricane Isabel coastal and inland oblique aerial survey along with associated survey maps, KML files, navigation files, digital Field Activity Collection System (FACS) logs, and Federal Geographic Data Committee (FGDC) metadata. Refer to the Acronyms page for expansions of all acronyms and abbreviations used in this report.\n\nThe USGS St. Petersburg Coastal and Marine Science Center (SPCMSC) assigns a unique identifier to each cruise or field activity. For example, 03CCH01 tells us the data were collected in 2003 for the Coastal Change Hazards (CCH) study and the data were collected during the first field activity for that project in that calendar year. Refer to http://walrus.wr.usgs.gov/infobank/programs/html/definition/activity.html for a detailed description of the method used to assign the ID number.\n\nThe photographs provided here are Joint Photographic Experts Group (JPEG) scanned images of the analog 35 millimeter (mm) color positive slides. The photograph locations are estimates of the location of the plane (see the Navigation page). The metadata values for photo creation time, GPS latitude, GPS longitude, GPS position (latitude and longitude), keywords, credit, artist, caption, copyright, and contact were added to each photograph's EXIF header using EXIFtool (Subino and others, 2012). Photographs can be opened directly with any JPEG-compatible image viewer by clicking on a thumbnail on the contact sheet, or, when viewing the Google Earth KML file, by clicking on the marker and then clicking on either the thumbnail or the link below the thumbnail. Nathaniel Plant (USGS - St. Petersburg, Fla.), and Ann Marie Ascough (formerly contracted at the USGS - St. Petersburg, Fla.) helped with the creation of KML files. To view the photos and survey maps, proceed to the Photos and Maps page.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds761","collaboration":"Groundwater Resources Program","usgsCitation":"Subino, J.A., Morgan, K., Krohn, M.D., and Dadisman, S.V., 2013, Archive of post-Hurricane Isabel coastal oblique aerial photographs collected during U.S. Geological Survey Field Activity 03CCH01 from Ocean City, Maryland, to Fort Caswell, North Carolina and Inland from Waynesboro to Redwood, Virginia, September 21 - 23, 2003: U.S. Geological Survey Data Series 761, HTML Document, https://doi.org/10.3133/ds761.","productDescription":"HTML Document","onlineOnly":"N","additionalOnlineFiles":"Y","temporalStart":"2003-09-21","temporalEnd":"2003-09-23","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":271411,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds761.gif"},{"id":271409,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/761/"},{"id":271410,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/761/pubs761/index.html"}],"country":"United States","state":"Maryland, North Carolina, Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.70556640625,\n 33.37641235124676\n ],\n [\n -80.70556640625,\n 39.639537564366684\n ],\n [\n -73.67431640625,\n 39.639537564366684\n ],\n [\n -73.67431640625,\n 33.37641235124676\n ],\n [\n -80.70556640625,\n 33.37641235124676\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51779f4fe4b095699adf271a","contributors":{"authors":[{"text":"Subino, Janice A.","contributorId":50386,"corporation":false,"usgs":true,"family":"Subino","given":"Janice","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":477856,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morgan, Karen L.M. 0000-0002-2994-5572","orcid":"https://orcid.org/0000-0002-2994-5572","contributorId":95553,"corporation":false,"usgs":true,"family":"Morgan","given":"Karen L.M.","affiliations":[],"preferred":false,"id":477857,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Krohn, M. Dennis dkrohn@usgs.gov","contributorId":3378,"corporation":false,"usgs":true,"family":"Krohn","given":"M.","email":"dkrohn@usgs.gov","middleInitial":"Dennis","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":477855,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dadisman, Shawn V. sdadisman@usgs.gov","contributorId":2207,"corporation":false,"usgs":true,"family":"Dadisman","given":"Shawn","email":"sdadisman@usgs.gov","middleInitial":"V.","affiliations":[],"preferred":true,"id":477854,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70045552,"text":"sir20135044 - 2013 - Groundwater and surface-water interactions near White Bear Lake, Minnesota, through 2011","interactions":[],"lastModifiedDate":"2015-10-16T13:47:34","indexId":"sir20135044","displayToPublicDate":"2013-04-23T00:00:00","publicationYear":"2013","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":"2013-5044","title":"Groundwater and surface-water interactions near White Bear Lake, Minnesota, through 2011","docAbstract":"The U.S. Geological Survey, in cooperation with the White Bear Lake Conservation District, the Minnesota Pollution Control Agency, the Minnesota Department of Natural Resources, and other State, county, municipal, and regional planning agencies, watershed organizations, and private organizations, conducted a study to characterize groundwater and surface-water interactions near White Bear Lake through 2011. During 2010 and 2011, White Bear Lake and other lakes in the northeastern part of the Twin Cities Metropolitan Area were at historically low levels. Previous periods of lower water levels in White Bear Lake correlate with periods of lower precipitation; however, recent urban expansion and increased pumping from the Prairie du Chien-Jordan aquifer have raised the question of whether a decline in precipitation is the primary cause for the recent water-level decline in White Bear Lake. Understanding and quantifying the amount of groundwater inflow to a lake and water discharge from a lake to aquifers is commonly difficult but is important in the management of lake levels. Three methods were used in the study to assess groundwater and surface-water interactions on White Bear Lake: (1) a historical assessment (1978-2011) of levels in White Bear Lake, local groundwater levels, and their relation to historical precipitation and groundwater withdrawals in the White Bear Lake area; (2) recent (2010-11) hydrologic and water-quality data collected from White Bear Lake, other lakes, and wells; and (3) water-balance assessments for White Bear Lake in March and August 2011. An analysis of covariance between average annual lake-level change and annual precipitation indicated the relation between the two variables was significantly different from 2003 through 2011 compared with 1978 through 2002, requiring an average of 4 more inches of precipitation per year to maintain the lake level. This shift in the linear relation between annual lake-level change and annual precipitation indicated the net effect of the non-precipitation terms on the water balance has changed relative to precipitation. The average amount of precipitation required each year to maintain the lake level has increased from 33 inches per year during 1978-2002 to 37 inches per year during 2003-11. The combination of lower precipitation and an increase in groundwater withdrawals can explain the change in the lake-level response to precipitation. Annual and summer groundwater withdrawals from the Prairie du Chien-Jordan aquifer have more than doubled from 1980 through 2010. Results from a regression model constructed with annual lake-level change, annual precipitation minus evaporation, and annual volume of groundwater withdrawn from the Prairie du Chien-Jordan aquifer indicated groundwater withdrawals had a greater effect than precipitation minus evaporation on water levels in the White Bear Lake area for all years since 2003. The recent (2003-11) decline in White Bear Lake reflects the declining water levels in the Prairie du Chien-Jordan aquifer; increases in groundwater withdrawals from this aquifer are a likely cause for declines in groundwater levels and lake levels. Synoptic, static groundwater-level and lake-level measurements in March/April and August 2011 indicated groundwater was potentially flowing into White Bear Lake from glacial aquifers to the northeast and south, and lake water was potentially discharging from White Bear Lake to the underlying glacial and Prairie du Chien-Jordan aquifers and glacial aquifers to the northwest. Groundwater levels in the Prairie du Chien-Jordan aquifer below White Bear Lake are approximately 0 to 19 feet lower than surface-water levels in the lake, indicating groundwater from the aquifer likely does not flow into White Bear Lake, but lake water may discharge into the aquifer. Groundwater levels from March/April to August 2011 declined more than 10 feet in the Prairie du Chien-Jordan aquifer south of White Bear Lake and to the north in Hugo, Minnesota. Water-quality analyses of pore water from nearshore lake-sediment and well-water samples, seepage-meter measurements, and hydraulic-head differences measured in White Bear Lake also indicated groundwater was potentially flowing into White Bear Lake from shallow glacial aquifers to the east and south. Negative temperature anomalies determined in shallow waters in the water-quality survey conducted in White Bear Lake indicated several shallow-water areas where groundwater may be flowing into the lake from glacial aquifers below the lake. Cool lake-sediment temperatures (less than 18 degrees Celsius) were measured in eight areas along the northeast, east, south, and southwest shores of White Bear Lake, indicating potential areas where groundwater may flow into the lake. Stable isotope analyses of well-water, precipitation, and lake-water samples indicated wells downgradient from White Bear Lake screened in the glacial buried aquifer or open to the Prairie du Chien-Jordan aquifer receive a mixture of surface water and groundwater; the largest surface-water contributions are in wells closer to White Bear Lake. A wide range in oxygen-18/oxygen-16 and deuterium/protium ratios was measured in well-water samples, indicating different sources of water are supplying water to the wells. Well water with oxygen-18/oxygen-16 and deuterium/protium ratios that plot close to the meteoric water line consisted mostly of groundwater because deuterium/protium ratios for most groundwater usually are similar to ratios for rainwater and snow, plotting close to meteoric water lines. Well water with oxygen-18/oxygen-16 and deuterium/protium ratios that plot between the meteoric water line and ratios for the surface-water samples from White Bear Lake consists of a mixture of surface water and groundwater; the percentage of each source varies relative to its ratios. White Bear Lake is the likely source of the surface water to the wells that have a mixture of surface water and groundwater because (1) it is the only large, deep lake near these wells; (2) these wells are near and downgradient from White Bear Lake; and (3) these wells obtain their water from relatively deep depths, and White Bear Lake is the deepest lake in that area. The percentages of surface-water contribution to the three wells screened in the glacial buried aquifer receiving surface water were 16, 48, and 83 percent. The percentages of surface-water contribution ranged from 5 to 79 percent for the five wells open to the Prairie du Chien-Jordan aquifer receiving surface water; wells closest to White Bear Lake had the largest percentages of surface-water contribution. Water-balance analysis of White Bear Lake in March and August 2011 indicated a potential discharge of 2.8 and 4.5 inches per month, respectively, over the area of the lake from the lake to local aquifers. Most of the sediments from a 12.4-foot lake core collected at the deepest part of White Bear Lake consisted of silts, sands, and gravels likely slumped from shallower waters, with a very low amount of low-permeability, organic material.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135044","collaboration":"Prepared in cooperation with the White Bear Lake Conservation District, Minnesota Pollution Control Agency, Minnesota Department of Natural Resources, Minnesota Board of Water and Soil Resources, Twin Cities Metropolitan Council, and the Groundwater/Surface-Water Interaction Partners","usgsCitation":"Jones, P.M., Trost, J.J., Rosenberry, D.O., Jackson, P., Bode, J.A., and O’Grady, R.M., 2013, Groundwater and surface-water interactions near White Bear Lake, Minnesota, through 2011: U.S. Geological Survey Scientific Investigations Report 2013-5044, ix, 73 p.; Downloads Directory, https://doi.org/10.3133/sir20135044.","productDescription":"ix, 73 p.; Downloads Directory","numberOfPages":"88","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2011-01-01","temporalEnd":"2011-12-31","ipdsId":"IP-030440","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"links":[{"id":271388,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135044.gif"},{"id":271385,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5044/"},{"id":271387,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2013/5044/downloads/"},{"id":271386,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5044/sir2013-5044.pdf"}],"country":"United States","state":"Minnesota","county":"Anoka County, Ramsey County, Washington County","city":"Minneapolis","otherGeospatial":"White Bear Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.2080078125,\n 44.92883525162427\n ],\n [\n -93.2080078125,\n 45.2004253589021\n ],\n [\n -92.80357360839842,\n 45.2004253589021\n ],\n [\n -92.80357360839842,\n 44.92883525162427\n ],\n [\n -93.2080078125,\n 44.92883525162427\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51779f59e4b095699adf272a","contributors":{"authors":[{"text":"Jones, Perry M. 0000-0002-6569-5144 pmjones@usgs.gov","orcid":"https://orcid.org/0000-0002-6569-5144","contributorId":2231,"corporation":false,"usgs":true,"family":"Jones","given":"Perry","email":"pmjones@usgs.gov","middleInitial":"M.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477836,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Trost, Jared J. 0000-0003-0431-2151 jtrost@usgs.gov","orcid":"https://orcid.org/0000-0003-0431-2151","contributorId":3749,"corporation":false,"usgs":true,"family":"Trost","given":"Jared","email":"jtrost@usgs.gov","middleInitial":"J.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477837,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rosenberry, Donald O. 0000-0003-0681-5641 rosenber@usgs.gov","orcid":"https://orcid.org/0000-0003-0681-5641","contributorId":1312,"corporation":false,"usgs":true,"family":"Rosenberry","given":"Donald","email":"rosenber@usgs.gov","middleInitial":"O.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":477835,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jackson, P. Ryan","contributorId":68571,"corporation":false,"usgs":true,"family":"Jackson","given":"P. Ryan","affiliations":[],"preferred":false,"id":477839,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bode, Jenifer A. jabode@usgs.gov","contributorId":3857,"corporation":false,"usgs":true,"family":"Bode","given":"Jenifer","email":"jabode@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":477838,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"O’Grady, Ryan M.","contributorId":83433,"corporation":false,"usgs":true,"family":"O’Grady","given":"Ryan","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":477840,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70045548,"text":"ofr20131061 - 2013 - Groundwater-level trends and forecasts, and salinity trends, in the Azraq, Dead Sea, Hammad, Jordan Side Valleys, Yarmouk, and Zarqa groundwater basins, Jordan","interactions":[],"lastModifiedDate":"2013-04-22T13:18:43","indexId":"ofr20131061","displayToPublicDate":"2013-04-22T00:00:00","publicationYear":"2013","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":"2013-1061","title":"Groundwater-level trends and forecasts, and salinity trends, in the Azraq, Dead Sea, Hammad, Jordan Side Valleys, Yarmouk, and Zarqa groundwater basins, Jordan","docAbstract":"Changes in groundwater levels and salinity in six groundwater basins in Jordan were characterized by using linear trends fit to well-monitoring data collected from 1960 to early 2011. On the basis of data for 117 wells, groundwater levels in the six basins were declining, on average about -1 meter per year (m/yr), in 2010. The highest average rate of decline, -1.9 m/yr, occurred in the Jordan Side Valleys basin, and on average no decline occurred in the Hammad basin. The highest rate of decline for an individual well was -9 m/yr. Aquifer saturated thickness, a measure of water storage, was forecast for year 2030 by using linear extrapolation of the groundwater-level trend in 2010. From 30 to 40 percent of the saturated thickness, on average, was forecast to be depleted by 2030. Five percent of the wells evaluated were forecast to have zero saturated thickness by 2030. Electrical conductivity was used as a surrogate for salinity (total dissolved solids). Salinity trends in groundwater were much more variable and less linear than groundwater-level trends. The long-term linear salinity trend at most of the 205 wells evaluated was not increasing, although salinity trends are increasing in some areas. The salinity in about 58 percent of the wells in the Amman-Zarqa basin was substantially increasing, and the salinity in Hammad basin showed a long-term increasing trend. Salinity increases were not always observed in areas with groundwater-level declines. The highest rates of salinity increase were observed in regional discharge areas near groundwater pumping centers.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131061","collaboration":"Prepared in cooperation with the U.S. Agency for International Development and the U.S. Army Corps of Engineers","usgsCitation":"Goode, D., Senior, L.A., Subah, A., and Jaber, A., 2013, Groundwater-level trends and forecasts, and salinity trends, in the Azraq, Dead Sea, Hammad, Jordan Side Valleys, Yarmouk, and Zarqa groundwater basins, Jordan: U.S. Geological Survey Open-File Report 2013-1061, Report: viii, 80 p.; Executive Summary: 11 p.; ZIP of all files, https://doi.org/10.3133/ofr20131061.","productDescription":"Report: viii, 80 p.; Executive Summary: 11 p.; ZIP of all files","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":271361,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131061.png"},{"id":271358,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1061/"},{"id":271359,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2013/1061/support/ofr2013-1061.zip"},{"id":271360,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1061/support/ofr2013-1061.pdf"}],"projection":"Palestine 1923 Palestine Belt, Transverse Mercator","country":"Jordan","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 34.8706,29.1809 ], [ 34.8706,33.3764 ], [ 39.3036,33.3764 ], [ 39.3036,29.1809 ], [ 34.8706,29.1809 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51764ddce4b0f989f99e0096","contributors":{"authors":[{"text":"Goode, Daniel J. 0000-0002-8527-2456 djgoode@usgs.gov","orcid":"https://orcid.org/0000-0002-8527-2456","contributorId":2433,"corporation":false,"usgs":true,"family":"Goode","given":"Daniel J.","email":"djgoode@usgs.gov","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":false,"id":477816,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Senior, Lisa A. 0000-0003-2629-1996 lasenior@usgs.gov","orcid":"https://orcid.org/0000-0003-2629-1996","contributorId":2150,"corporation":false,"usgs":true,"family":"Senior","given":"Lisa","email":"lasenior@usgs.gov","middleInitial":"A.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477815,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Subah, Ali","contributorId":66994,"corporation":false,"usgs":true,"family":"Subah","given":"Ali","email":"","affiliations":[],"preferred":false,"id":477818,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jaber, Ayman","contributorId":46398,"corporation":false,"usgs":true,"family":"Jaber","given":"Ayman","email":"","affiliations":[],"preferred":false,"id":477817,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70045542,"text":"70045542 - 2013 - Comparing Laser Desorption Ionization and Atmospheric Pressure Photoionization Coupled to Fourier Transform Ion Cyclotron Resonance Mass Spectrometry To Characterize Shale Oils at the Molecular Level","interactions":[],"lastModifiedDate":"2013-04-22T12:44:56","indexId":"70045542","displayToPublicDate":"2013-04-22T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1506,"text":"Energy & Fuels","active":true,"publicationSubtype":{"id":10}},"title":"Comparing Laser Desorption Ionization and Atmospheric Pressure Photoionization Coupled to Fourier Transform Ion Cyclotron Resonance Mass Spectrometry To Characterize Shale Oils at the Molecular Level","docAbstract":"Laser desorption ionization (LDI) coupled to Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) was used to analyze shale oils. Previous work showed that LDI is a sensitive ionization technique for assessing aromatic nitrogen compounds, and oils generated from Green River Formation oil shales are well-documented as being rich in nitrogen. The data presented here demonstrate that LDI is effective in ionizing high-double-bond-equivalent (DBE) compounds and, therefore, is a suitable method for characterizing compounds with condensed structures. Additionally, LDI generates radical cations and protonated ions concurrently, the distribution of which depends upon the molecular structures and elemental compositions, and the basicity of compounds is closely related to the generation of protonated ions. This study demonstrates that LDI FT-ICR MS is an effective ionization technique for use in the study of shale oils at the molecular level. To the best of our knowledge, this is the first time that LDI FT-ICR MS has been applied to shale oils.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Energy & Fuels","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"ACS Publications (American Chemical Society)","publisherLocation":"Washington, DC","doi":"10.1021/ef3015662","usgsCitation":"Cho, Y., Jin, J.M., Witt, M., Birdwell, J.E., Na, J., Roh, N., and Kim, S., 2013, Comparing Laser Desorption Ionization and Atmospheric Pressure Photoionization Coupled to Fourier Transform Ion Cyclotron Resonance Mass Spectrometry To Characterize Shale Oils at the Molecular Level: Energy & Fuels, v. 27, no. 4, p. 1830-1837, https://doi.org/10.1021/ef3015662.","startPage":"1830","endPage":"1837","numberOfPages":"8","additionalOnlineFiles":"N","ipdsId":"IP-041173","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":271351,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":271350,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1021/ef3015662"}],"volume":"27","issue":"4","noUsgsAuthors":false,"publicationDate":"2012-12-27","publicationStatus":"PW","scienceBaseUri":"51764dcfe4b0f989f99e0086","contributors":{"authors":[{"text":"Cho, Yunjo","contributorId":99860,"corporation":false,"usgs":true,"family":"Cho","given":"Yunjo","email":"","affiliations":[],"preferred":false,"id":477810,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jin, Jang Mi","contributorId":28877,"corporation":false,"usgs":true,"family":"Jin","given":"Jang","email":"","middleInitial":"Mi","affiliations":[],"preferred":false,"id":477805,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Witt, Matthias","contributorId":41719,"corporation":false,"usgs":true,"family":"Witt","given":"Matthias","email":"","affiliations":[],"preferred":false,"id":477806,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Birdwell, Justin E. 0000-0001-8263-1452 jbirdwell@usgs.gov","orcid":"https://orcid.org/0000-0001-8263-1452","contributorId":3302,"corporation":false,"usgs":true,"family":"Birdwell","given":"Justin","email":"jbirdwell@usgs.gov","middleInitial":"E.","affiliations":[{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":477804,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Na, Jeong-Geol","contributorId":95358,"corporation":false,"usgs":true,"family":"Na","given":"Jeong-Geol","email":"","affiliations":[],"preferred":false,"id":477809,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Roh, Nam-Sun","contributorId":51622,"corporation":false,"usgs":true,"family":"Roh","given":"Nam-Sun","email":"","affiliations":[],"preferred":false,"id":477808,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kim, Sunghwan","contributorId":45606,"corporation":false,"usgs":true,"family":"Kim","given":"Sunghwan","affiliations":[],"preferred":false,"id":477807,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70045470,"text":"70045470 - 2013 - Complex resistivity signatures of ethanol in sand-clay mixtures","interactions":[],"lastModifiedDate":"2013-04-21T19:27:31","indexId":"70045470","displayToPublicDate":"2013-04-21T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2233,"text":"Journal of Contaminant Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Complex resistivity signatures of ethanol in sand-clay mixtures","docAbstract":"We performed complex resistivity (CR) measurements on laboratory columns to investigate changes in electrical properties as a result of varying ethanol (EtOH) concentration (0% to 30% v/v) in a sand–clay (bentonite) matrix. We applied Debye decomposition, a phenomenological model commonly used to fit CR data, to determine model parameters (time constant: τ, chargeability: m, and normalized chargeability: mn). The CR data showed a significant (P ≤ 0.001) time-dependent variation in the clay driven polarization response (~ 12 mrad) for 0% EtOH concentration. This temporal variation probably results from the clay–water reaction kinetics trending towards equilibrium in the sand–clay–water system. The clay polarization is significantly suppressed (P ≤ 0.001) for both measured phase (ϕ) and imaginary conductivity (σ″) with increasing EtOH concentration. Normalized chargeability consistently decreases (by up to a factor of ~ 2) as EtOH concentration increases from 0% to 10% and 10 to 20%, respectively. We propose that such suppression effects are associated with alterations in the electrical double layer (EDL) at the clay–fluid interface due to (a) strong EtOH adsorption on clay, and (b) complex intermolecular EtOH–water interactions and subsequent changes in ionic mobility on the surface in the EDL. Changes in the CR data following a change of the saturating fluid from EtOH 20% to plain water indicate strong hysteresis effects in the electrical response, which we attribute to persistent EtOH adsorption on clay. Our results demonstrate high sensitivity of CR measurements to clay–EtOH interactions in porous media, indicating the potential application of this technique for characterization and monitoring of ethanol contamination in sediments containing clays.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Contaminant Hydrology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.jconhyd.2013.03.005","usgsCitation":"Personna, Y.R., Slater, L., Ntarlagiannis, D., Werkema, D.D., and Szabo, Z., 2013, Complex resistivity signatures of ethanol in sand-clay mixtures: Journal of Contaminant Hydrology, v. 149, p. 76-87, https://doi.org/10.1016/j.jconhyd.2013.03.005.","productDescription":"12 p.","startPage":"76","endPage":"87","ipdsId":"IP-045055","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":271323,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":271322,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.jconhyd.2013.03.005"}],"volume":"149","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5174fc5ee4b074c2b055647d","contributors":{"authors":[{"text":"Personna, Yves Robert","contributorId":77820,"corporation":false,"usgs":false,"family":"Personna","given":"Yves","email":"","middleInitial":"Robert","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":477578,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Slater, Lee","contributorId":55707,"corporation":false,"usgs":false,"family":"Slater","given":"Lee","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":477577,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ntarlagiannis, Dimitrios","contributorId":55303,"corporation":false,"usgs":false,"family":"Ntarlagiannis","given":"Dimitrios","affiliations":[{"id":12727,"text":"Rutgers University","active":true,"usgs":false}],"preferred":false,"id":477576,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Werkema, Dale D.","contributorId":40488,"corporation":false,"usgs":false,"family":"Werkema","given":"Dale","email":"","middleInitial":"D.","affiliations":[{"id":6914,"text":"U.S. Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":477575,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Szabo, Zoltan 0000-0002-0760-9607 zszabo@usgs.gov","orcid":"https://orcid.org/0000-0002-0760-9607","contributorId":2240,"corporation":false,"usgs":true,"family":"Szabo","given":"Zoltan","email":"zszabo@usgs.gov","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":false,"id":477574,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70043239,"text":"70043239 - 2013 - Climatic trends over Ethiopia: regional signals and drivers","interactions":[],"lastModifiedDate":"2013-06-17T09:07:21","indexId":"70043239","displayToPublicDate":"2013-04-21T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2032,"text":"International Journal of Climatology","active":true,"publicationSubtype":{"id":10}},"title":"Climatic trends over Ethiopia: regional signals and drivers","docAbstract":"This study analyses observed and projected climatic trends over Ethiopia, through analysis of temperature and rainfall records and related meteorological fields. The observed datasets include gridded station records and reanalysis products; while projected trends are analysed from coupled model simulations drawn from the IPCC 4th Assessment. Upward trends in air temperature of + 0.03 °C year−1 and downward trends in rainfall of − 0.4 mm month−1 year−1 have been observed over Ethiopia's southwestern region in the period 1948-2006. These trends are projected to continue to 2050 according to the Geophysical Fluid Dynamics Lab model using the A1B scenario. Large scale forcing derives from the West Indian Ocean where significant warming and increased rainfall are found. Anticyclonic circulations have strengthened over northern and southern Africa, limiting moisture transport from the Gulf of Guinea and Congo. Changes in the regional Walker and Hadley circulations modulate the observed and projected climatic trends. Comparing past and future patterns, the key features spread westward from Ethiopia across the Sahel and serve as an early warning of potential impacts.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"International Journal of Climatology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1002/joc.3560","usgsCitation":"Jury, M.R., and Funk, C.C., 2013, Climatic trends over Ethiopia: regional signals and drivers: International Journal of Climatology, v. 33, no. 8, p. 1924-1935, https://doi.org/10.1002/joc.3560.","productDescription":"12 p.","startPage":"1924","endPage":"1935","ipdsId":"IP-021460","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":271307,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":271306,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/joc.3560"}],"country":"Ethiopia","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 33.0,3.4 ], [ 33.0,15.0 ], [ 48.0,15.0 ], [ 48.0,3.4 ], [ 33.0,3.4 ] ] ] } } ] }","volume":"33","issue":"8","noUsgsAuthors":false,"publicationDate":"2012-08-15","publicationStatus":"PW","scienceBaseUri":"5174fc52e4b074c2b0556471","contributors":{"authors":[{"text":"Jury, Mark R.","contributorId":28145,"corporation":false,"usgs":true,"family":"Jury","given":"Mark","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":473217,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Funk, Christopher C. 0000-0002-9254-6718 cfunk@usgs.gov","orcid":"https://orcid.org/0000-0002-9254-6718","contributorId":721,"corporation":false,"usgs":true,"family":"Funk","given":"Christopher","email":"cfunk@usgs.gov","middleInitial":"C.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":473216,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70044145,"text":"70044145 - 2013 - CEOS visualization environment (COVE) tool for intercalibration of satellite instruments","interactions":[],"lastModifiedDate":"2013-04-20T18:19:54","indexId":"70044145","displayToPublicDate":"2013-04-20T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1944,"text":"IEEE Transactions on Geoscience and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"CEOS visualization environment (COVE) tool for intercalibration of satellite instruments","docAbstract":"Increasingly, data from multiple instruments are used to gain a more complete understanding of land surface processes at a variety of scales. Intercalibration, comparison, and coordination of satellite instrument coverage areas is a critical effort of international and domestic space agencies and organizations. The Committee on Earth Observation Satellites Visualization Environment (COVE) is a suite of browser-based applications that leverage Google Earth to display past, present, and future satellite instrument coverage areas and coincident calibration opportunities. This forecasting and ground coverage analysis and visualization capability greatly benefits the remote sensing calibration community in preparation for multisatellite ground calibration campaigns or individual satellite calibration studies. COVE has been developed for use by a broad international community to improve the efficiency and efficacy of such calibration planning efforts, whether those efforts require past, present, or future predictions. This paper provides a brief overview of the COVE tool, its validation, accuracies, and limitations with emphasis on the applicability of this visualization tool for supporting ground field campaigns and intercalibration of satellite instruments.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"IEEE Transactions on Geoscience and Remote Sensing","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"IEEE","publisherLocation":"Washington, D.C.","doi":"10.1109/TGRS.2012.2235841","usgsCitation":"Kessler, P., Killough, B., Gowda, S., Williams, B., Chander, G., and Qu, M., 2013, CEOS visualization environment (COVE) tool for intercalibration of satellite instruments: IEEE Transactions on Geoscience and Remote Sensing, v. 51, no. 3, p. 1081-1087, https://doi.org/10.1109/TGRS.2012.2235841.","productDescription":"7 p.","startPage":"1081","endPage":"1087","ipdsId":"IP-043733","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":271287,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1109/TGRS.2012.2235841"},{"id":271288,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"51","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5173b164e4b0e619a5806e9d","contributors":{"authors":[{"text":"Kessler, P.D.","contributorId":9940,"corporation":false,"usgs":true,"family":"Kessler","given":"P.D.","email":"","affiliations":[],"preferred":false,"id":474890,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Killough, B.D.","contributorId":48848,"corporation":false,"usgs":true,"family":"Killough","given":"B.D.","email":"","affiliations":[],"preferred":false,"id":474892,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gowda, S.","contributorId":21846,"corporation":false,"usgs":true,"family":"Gowda","given":"S.","email":"","affiliations":[],"preferred":false,"id":474891,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Williams, B.R.","contributorId":83420,"corporation":false,"usgs":true,"family":"Williams","given":"B.R.","email":"","affiliations":[],"preferred":false,"id":474895,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chander, G.","contributorId":51449,"corporation":false,"usgs":true,"family":"Chander","given":"G.","affiliations":[],"preferred":false,"id":474893,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Qu, Min","contributorId":79380,"corporation":false,"usgs":true,"family":"Qu","given":"Min","email":"","affiliations":[],"preferred":false,"id":474894,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70045509,"text":"70045509 - 2013 - Wetland fire scar monitoring and analysis using archival Landsat data for the Everglades","interactions":[],"lastModifiedDate":"2013-04-19T21:06:46","indexId":"70045509","displayToPublicDate":"2013-04-19T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1636,"text":"Fire Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Wetland fire scar monitoring and analysis using archival Landsat data for the Everglades","docAbstract":"The ability to document the frequency, extent, and severity of fires in wetlands, as well as the dynamics of post-fire wetland land cover, informs fire and wetland science, resource management, and ecosystem protection. Available information on Everglades burn history has been based on field data collection methods that evolved through time and differ by land management unit. Our objectives were to (1) design and test broadly applicable and repeatable metrics of not only fire scar delineation but also post-fire land cover dynamics through exhaustive use of the Landsat satellite data archives, and then (2) explore how those metrics relate to various hydrologic and anthropogenic factors that may influence post-fire land cover dynamics. Visual interpretation of every Landsat scene collected over the study region during the study time frame produced a new, detailed database of burn scars greater than 1.6 ha in size in the Water Conservation Areas and post-fire land cover dynamics for Everglades National Park fires greater than 1.6 ha in area. Median burn areas were compared across several landscape units of the Greater Everglades and found to differ as a function of administrative unit and fire history. Some burned areas transitioned to open water, exhibiting water depths and dynamics that support transition mechanisms proposed in the literature. Classification tree techniques showed that time to green-up and return to pre-burn character were largely explained by fire management practices and hydrology. Broadly applicable as they use data from the global, nearly 30-year-old Landsat archive, these methods for documenting wetland burn extent and post-fire land cover change enable cost-effective collection of new data on wetland fire ecology and independent assessment of fire management practice effectiveness.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Fire Ecology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Association for Fire Ecology","publisherLocation":"Eugene, OR","doi":"10.4996/fireecology.0901133","usgsCitation":"Jones, J., Hall, A.E., Foster, A.M., and Smith, T.J., 2013, Wetland fire scar monitoring and analysis using archival Landsat data for the Everglades: Fire Ecology, v. 9, no. 1, p. 133-150, https://doi.org/10.4996/fireecology.0901133.","productDescription":"18 p.","startPage":"133","endPage":"150","ipdsId":"IP-040357","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"links":[{"id":473873,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.4996/fireecology.0901133","text":"Publisher Index Page"},{"id":271273,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":271272,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.4996/fireecology.0901133"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -81.5205,24.851 ], [ -81.5205,25.8915 ], [ -80.3887,25.8915 ], [ -80.3887,24.851 ], [ -81.5205,24.851 ] ] ] } } ] }","volume":"9","issue":"1","noUsgsAuthors":false,"publicationDate":"2013-04-01","publicationStatus":"PW","scienceBaseUri":"5172595ee4b0c173799e78fa","contributors":{"authors":[{"text":"Jones, John W. 0000-0001-6117-3691 jwjones@usgs.gov","orcid":"https://orcid.org/0000-0001-6117-3691","contributorId":2220,"corporation":false,"usgs":true,"family":"Jones","given":"John","email":"jwjones@usgs.gov","middleInitial":"W.","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"preferred":true,"id":477670,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hall, Annette E. ahall@usgs.gov","contributorId":4791,"corporation":false,"usgs":true,"family":"Hall","given":"Annette","email":"ahall@usgs.gov","middleInitial":"E.","affiliations":[],"preferred":true,"id":477672,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Foster, Ann M. amfoster@usgs.gov","contributorId":3545,"corporation":false,"usgs":true,"family":"Foster","given":"Ann","email":"amfoster@usgs.gov","middleInitial":"M.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":477671,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, Thomas J. III tom_j_smith@usgs.gov","contributorId":1615,"corporation":false,"usgs":true,"family":"Smith","given":"Thomas","suffix":"III","email":"tom_j_smith@usgs.gov","middleInitial":"J.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":false,"id":477669,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70045494,"text":"ofr20131086 - 2013 - Estimation of capture zones and drawdown at the Northwest and West Well Fields, Miami-Dade County, Florida, using an unconstrained Monte Carlo analysis: recent (2004) and proposed conditions","interactions":[],"lastModifiedDate":"2013-04-19T10:55:31","indexId":"ofr20131086","displayToPublicDate":"2013-04-19T00:00:00","publicationYear":"2013","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":"2013-1086","title":"Estimation of capture zones and drawdown at the Northwest and West Well Fields, Miami-Dade County, Florida, using an unconstrained Monte Carlo analysis: recent (2004) and proposed conditions","docAbstract":"Travel-time capture zones and drawdown for two production well fields, used for drinking-water supply in Miami-Dade County, southeastern Florida, were delineated by the U.S Geological Survey using an unconstrained Monte Carlo analysis. The well fields, designed to supply a combined total of approximately 250 million gallons of water per day, pump from the highly transmissive Biscayne aquifer in the urban corridor between the Everglades and Biscayne Bay. A transient groundwater flow model was developed and calibrated to field data to ensure an acceptable match between simulated and observed values for aquifer heads and net exchange of water between the aquifer and canals. Steady-state conditions were imposed on the transient model and a post-processing backward particle-tracking approach was implemented. Multiple stochastic realizations of horizontal hydraulic conductivity, conductance of canals, and effective porosity were simulated for steady-state conditions representative of dry, average and wet hydrologic conditions to calculate travel-time capture zones of potential source areas of the well fields. Quarry lakes, formed as a product of rock-mining activities, whose effects have previously not been considered in estimation of capture zones, were represented using high hydraulic-conductivity, high-porosity cells, with the bulk hydraulic conductivity of each cell calculated based on estimates of aquifer hydraulic conductivity, lake depths and aquifer thicknesses. A post-processing adjustment, based on calculated residence times using lake outflows and known lake volumes, was utilized to adjust particle endpoints to account for an estimate of residence-time-based mixing of lakes. Drawdown contours of 0.1 and 0.25 foot were delineated for the dry, average, and wet hydrologic conditions as well. In addition, 95-percent confidence intervals (CIs) were calculated for the capture zones and drawdown contours to delineate a zone of uncertainty about the median estimates. Results of the Monte Carlo simulations indicate particle travel distances at the Northwest Well Field (NWWF) and West Well Field (WWF) are greatest to the west, towards the Everglades. The man-made quarry lakes substantially affect particle travel distances. In general near the NWWF, the capture zones in areas with lakes were smaller in areal extent than capture zones in areas without lakes. It is possible that contamination could reach the well fields quickly, within 10 days in some cases, if it were introduced into lakes nearest to supply wells, with one of the lakes being only approximately 650 feet from the nearest supply well. In addition to estimating drawdown and travel-time capture zones of 10, 30, 100, and 210 days for the NWWF and the WWF under more recent conditions, two proposed scenarios were evaluated with Monte Carlo simulations: the potential hydrologic effects of proposed Everglades groundwater seepage mitigation and quarry-lake expansion. The seepage mitigation scenario included the addition of two proposed anthropogenic features to the model: (1) an impermeable horizontal flow barrier east of the L-31N canal along the western model boundary between the Everglades and the urban areas of Miami-Dade County, and (2) a recharge canal along the Dade-Broward Levee near the NWWF. Capture zones and drawdown for the WWF were substantially affected by the addition of the barrier, which eliminates flow from the western boundary into the active model domain, shifting the predominant capture zone source area from the west more to the north and south. The 95-percent CI for the 210-day capture zone moved slightly in the NWWF as a result of the recharge canal. The lake-expansion scenario incorporated a proposed increase in the number and surface area of lakes by an additional 25 square miles. This scenario represents a 150-percent increase from the 2004 lake surface area near both well fields, but with the majority of increase proposed near the NWWF. The lake-expansion scenario substantially decreased the extent of the 210-day capture zone of the NWWF, which is limited to the lakes nearest the well field under proposed conditions.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131086","collaboration":"Prepared in cooperation with the Miami-Dade County Water and Sewer Department and Department of Regulatory and Economic Resources","usgsCitation":"Brakefield, L.K., Hughes, J.D., Langevin, C.D., and Chartier, K., 2013, Estimation of capture zones and drawdown at the Northwest and West Well Fields, Miami-Dade County, Florida, using an unconstrained Monte Carlo analysis: recent (2004) and proposed conditions: U.S. Geological Survey Open-File Report 2013-1086, x, 127 p., https://doi.org/10.3133/ofr20131086.","productDescription":"x, 127 p.","numberOfPages":"140","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":271256,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131086.gif"},{"id":271254,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1086/"},{"id":271255,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1086/pdf/ofr2013-1086.pdf"}],"country":"United States","state":"Florida","county":"Miami-dade","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -80.35,25.40 ], [ -80.35,25.60 ], [ -80.15,25.60 ], [ -80.15,25.40 ], [ -80.35,25.40 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5172595be4b0c173799e78de","contributors":{"authors":[{"text":"Brakefield, Linzy K. lbrake@usgs.gov","contributorId":2080,"corporation":false,"usgs":true,"family":"Brakefield","given":"Linzy","email":"lbrake@usgs.gov","middleInitial":"K.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":false,"id":477629,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hughes, Joseph D. 0000-0003-1311-2354 jdhughes@usgs.gov","orcid":"https://orcid.org/0000-0003-1311-2354","contributorId":2492,"corporation":false,"usgs":true,"family":"Hughes","given":"Joseph","email":"jdhughes@usgs.gov","middleInitial":"D.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":477630,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Langevin, Christian D. 0000-0001-5610-9759 langevin@usgs.gov","orcid":"https://orcid.org/0000-0001-5610-9759","contributorId":1030,"corporation":false,"usgs":true,"family":"Langevin","given":"Christian","email":"langevin@usgs.gov","middleInitial":"D.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":477628,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chartier, Kevin","contributorId":64128,"corporation":false,"usgs":true,"family":"Chartier","given":"Kevin","affiliations":[],"preferred":false,"id":477631,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70045451,"text":"70045451 - 2013 - A review of selected inorganic surface water quality-monitoring practices: are we really measuring what we think, and if so, are we doing it right?","interactions":[],"lastModifiedDate":"2016-11-30T13:14:40","indexId":"70045451","displayToPublicDate":"2013-04-19T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1565,"text":"Environmental Science & Technology","onlineIssn":"1520-5851","printIssn":"0013-936X","active":true,"publicationSubtype":{"id":10}},"title":"A review of selected inorganic surface water quality-monitoring practices: are we really measuring what we think, and if so, are we doing it right?","docAbstract":"Successful environmental/water quality-monitoring programs usually require a balance between analytical capabilities, the collection and preservation of representative samples, and available financial/personnel resources. Due to current economic conditions, monitoring programs are under increasing pressure to do more with less. Hence, a review of current sampling and analytical methodologies, and some of the underlying assumptions that form the bases for these programs seems appropriate, to see if they are achieving their intended objectives within acceptable error limits and/or measurement uncertainty, in a cost-effective manner. That evaluation appears to indicate that several common sampling/processing/analytical procedures (e.g., dip (point) samples/measurements, nitrogen determinations, total recoverable analytical procedures) are generating biased or nonrepresentative data, and that some of the underlying assumptions relative to current programs, such as calendar-based sampling and stationarity are no longer defensible. The extensive use of statistical models as well as surrogates (e.g., turbidity) also needs to be re-examined because the hydrologic interrelationships that support their use tend to be dynamic rather than static. As a result, a number of monitoring programs may need redesigning, some sampling and analytical procedures may need to be updated, and model/surrogate interrelationships may require recalibration.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Environmental Science and Technology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"ACS Publications","publisherLocation":"Washington, D.C.","doi":"10.1021/es304058q","usgsCitation":"Horowitz, A.J., 2013, A review of selected inorganic surface water quality-monitoring practices: are we really measuring what we think, and if so, are we doing it right?: Environmental Science & Technology, v. 47, no. 6, p. 2471-2486, https://doi.org/10.1021/es304058q.","productDescription":"16 p.","startPage":"2471","endPage":"2486","ipdsId":"IP-043699","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":271277,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":271276,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1021/es304058q"}],"volume":"47","issue":"6","noUsgsAuthors":false,"publicationDate":"2013-03-01","publicationStatus":"PW","scienceBaseUri":"51725951e4b0c173799e78d6","contributors":{"authors":[{"text":"Horowitz, Arthur J. 0000-0002-3296-730X horowitz@usgs.gov","orcid":"https://orcid.org/0000-0002-3296-730X","contributorId":1400,"corporation":false,"usgs":true,"family":"Horowitz","given":"Arthur","email":"horowitz@usgs.gov","middleInitial":"J.","affiliations":[{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477514,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70045493,"text":"sir20135082 - 2013 - Water volume and sediment volume and density in Lake Linganore between Boyers Mill Road Bridge and Bens Branch, Frederick County, Maryland, 2012","interactions":[],"lastModifiedDate":"2023-03-09T20:13:19.08246","indexId":"sir20135082","displayToPublicDate":"2013-04-19T00:00:00","publicationYear":"2013","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":"2013-5082","title":"Water volume and sediment volume and density in Lake Linganore between Boyers Mill Road Bridge and Bens Branch, Frederick County, Maryland, 2012","docAbstract":"To assist in understanding sediment loadings and the management of water resources, a bathymetric survey was conducted in the part of Lake Linganore between Boyers Mill Road Bridge and Bens Branch in Frederick County, Maryland. The bathymetric survey was performed in January 2012 by the U.S. Geological Survey, in cooperation with the City of Frederick and Frederick County. A separate, but related, field effort to collect 18 sediment cores was conducted in March and April 2012. Depth and location data from the bathymetric survey and location data for the sediment cores were compiled and edited by using geographic information system (GIS) software. A three-dimensional triangulated irregular network (TIN) model of the lake bottom was created to calculate the volume of stored water in the reservoir. Large-scale topographic maps of the valley prior to inundation in 1972 were provided by the Frederick County Division of Utilities and Solid Waste Management and digitized for comparison with current (2012) conditions in order to calculate sediment volume. Cartographic representations of both water depth and sediment accumulation were produced, along with an accuracy assessment for the resulting bathymetric model. Vertical accuracies at the 95-percent confidence level for the collected data, the bathymetric surface model, and the bathymetric contour map were calculated to be 0.64 feet (ft), 1.77 ft, and 2.30 ft, respectively. A dry bulk sediment density was calculated for each of the 18 sediment cores collected during March and April 2012, and used to determine accumulated sediment mass. Water-storage capacity in the study area is 110 acre-feet (acre-ft) at a full-pool elevation 308 ft above the National Geodetic Vertical Datum of 1929, whereas total sediment volume in the study area is 202 acre-ft. These totals indicate a loss of about 65 percent of the original water-storage capacity in the 40 years since dam construction. This corresponds to an average rate of sediment accumulation of 5.1 acre-ft per year since Linganore Creek was impounded. Sediment thicknesses ranged from 0 to 16.7 ft. Sediment densities ranged from 0.38 to 1.08 grams per cubic centimeter, and generally decreased in the downstream direction. The total accumulated-sediment mass was 156,000 metric tons between 1972 and 2012.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135082","collaboration":"Prepared in cooperation with the City of Frederick, Maryland and Frederick County, Maryland","usgsCitation":"Sekellick, A.J., Banks, W.S., and Myers, M., 2013, Water volume and sediment volume and density in Lake Linganore between Boyers Mill Road Bridge and Bens Branch, Frederick County, Maryland, 2012: U.S. Geological Survey Scientific Investigations Report 2013-5082, vi, 17 p., https://doi.org/10.3133/sir20135082.","productDescription":"vi, 17 p.","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":271218,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5082/pdf/sir2013-5082.pdf"},{"id":271217,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5082/"},{"id":271219,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135082.gif"}],"country":"United States","state":"Maryl","county":"Frederick","otherGeospatial":"Linganore Creek Watershed","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -77.40,39.15 ], [ -77.40,39.45 ], [ -77.05,39.45 ], [ -77.05,39.15 ], [ -77.40,39.15 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5172595ee4b0c173799e78f6","contributors":{"authors":[{"text":"Sekellick, Andrew J. 0000-0002-0440-7655 ajsekell@usgs.gov","orcid":"https://orcid.org/0000-0002-0440-7655","contributorId":4125,"corporation":false,"usgs":true,"family":"Sekellick","given":"Andrew","email":"ajsekell@usgs.gov","middleInitial":"J.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477625,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Banks, William S.L.","contributorId":35281,"corporation":false,"usgs":true,"family":"Banks","given":"William","email":"","middleInitial":"S.L.","affiliations":[],"preferred":false,"id":477627,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Myers, Michael K. mkmyers@usgs.gov","contributorId":5160,"corporation":false,"usgs":true,"family":"Myers","given":"Michael K.","email":"mkmyers@usgs.gov","affiliations":[{"id":375,"text":"Maryland, Delaware, and the District of Columbia Water Science Center","active":false,"usgs":true}],"preferred":false,"id":477626,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70045491,"text":"sir20135083 - 2013 - Sediment transport in the lower Snake and Clearwater River Basins, Idaho and Washington, 2008–11","interactions":[],"lastModifiedDate":"2013-04-19T09:29:00","indexId":"sir20135083","displayToPublicDate":"2013-04-19T00:00:00","publicationYear":"2013","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":"2013-5083","title":"Sediment transport in the lower Snake and Clearwater River Basins, Idaho and Washington, 2008–11","docAbstract":"Sedimentation is an ongoing maintenance problem for reservoirs, limiting reservoir storage capacity and navigation. Because Lower Granite Reservoir in Washington is the most upstream of the four U.S. Army Corps of Engineers reservoirs on the lower Snake River, it receives and retains the largest amount of sediment. In 2008, in cooperation with the U.S. Army Corps of Engineers, the U.S. Geological Survey began a study to quantify sediment transport to Lower Granite Reservoir. Samples of suspended sediment and bedload were collected from streamgaging stations on the Snake River near Anatone, Washington, and the Clearwater River at Spalding, Idaho. Both streamgages were equipped with an acoustic Doppler velocity meter to evaluate the efficacy of acoustic backscatter for estimating suspended-sediment concentrations and transport. In 2009, sediment sampling was extended to 10 additional locations in tributary watersheds to help identify the dominant source areas for sediment delivery to Lower Granite Reservoir. Suspended-sediment samples were collected 9–15 times per year at each location to encompass a range of streamflow conditions and to capture significant hydrologic events such as peak snowmelt runoff and rain-on-snow. Bedload samples were collected at a subset of stations where the stream conditions were conducive for sampling, and when streamflow was sufficiently high for bedload transport. At most sampling locations, the concentration of suspended sediment varied by 3–5 orders of magnitude with concentrations directly correlated to streamflow. The largest median concentrations of suspended sediment (100 and 94 mg/L) were in samples collected from stations on the Palouse River at Hooper, Washington, and the Salmon River at White Bird, Idaho, respectively. The smallest median concentrations were in samples collected from the Selway River near Lowell, Idaho (11 mg/L), the Lochsa River near Lowell, Idaho (11 mg/L), the Clearwater River at Orofino, Idaho (13 mg/L), and the Middle Fork Clearwater River at Kooskia, Idaho (15 mg/L). The largest measured concentrations of suspended sediment (3,300 and 1,400 mg/L) during a rain-on-snow event in January 2011 were from samples collected at the Potlatch River near Spalding, Idaho, and the Palouse River at Hooper, Washington, respectively. Generally, samples collected from agricultural watersheds had a high percentage of silt and clay-sized suspended sediment, whereas samples collected from forested watersheds had a high percentage of sand. During water years 2009–11, Lower Granite Reservoir received about 10 million tons of suspended sediment from the combined loads of the Snake and Clearwater Rivers. The Snake River accounted for about 2.97 million tons per year (about 89 percent) of the total suspended sediment, 1.48 million tons per year (about 90 percent) of the suspended sand, and about 1.52 million tons per year (87 percent) of the suspended silt and clay. Of the suspended sediment transported to Lower Granite Reservoir, the Salmon River accounted for about 51 percent of the total suspended sediment, about 56 percent of the suspended sand, and about 44 percent of the suspended silt and clay. About 6.2 million tons (62 percent) of the sediment contributed to Lower Granite Reservoir during 2009–11 entered during water year 2011, which was characterized by an above average winter snowpack and sustained spring runoff. A comparison of historical data collected from the Snake River near Anatone with data collected during this study indicates that concentrations of total suspended sediment and suspended sand in the Snake River were significantly smaller during water years 1972–79 than during 2008–11. Most of the increased sediment content in the Snake River is attributable to an increase of sand-size material. During 1972–79, sand accounted for an average of 28 percent of the suspended-sediment load; during 2008–11, sand accounted for an average of 48 percent. Historical data from the Clearwater River at Spalding indicates that the concentrations of total suspended sediment collected during 1972–79 were not significantly different from the concentrations measured during this study. However, the suspended-sand concentrations in the Clearwater River were significantly smaller during 1972–79 than during 2008–11. The increase in suspended-sand concentrations in the Snake and Clearwater Rivers are probably attributable to numerous severe forest fires that burned large areas of central Idaho from 1980–2010. Acoustic backscatter from an acoustic Doppler velocity meter proved to be an effective method of estimating suspended-sediment concentration and load for most streamflow conditions in the Snake and Clearwater Rivers. Models based on acoustic backscatter were able to simulate most of the variability in suspended-sediment concentrations in the Clearwater River at Spalding (coefficient of determination [R2]=0.93) and the Snake River near Anatone (R2=0.92). Acoustic backscatter seems to be especially effective for estimating suspended-sediment concentration and load over short (monthly and single storm event) and long (annual) time scales when sediment load is highly variable. However, during high streamflow events acoustic surrogate tools may be unable to capture the contribution of suspended sand moving near the bottom of the water column and thus, underestimate the total load of suspended sediment. At the stations where bedload was collected, the particle-size distribution at low streamflows typically was unimodal with sand comprising the dominant particle size. At higher streamflows and during peak bedload discharge, the particle size typically was bimodal and was comprised primarily of sand and coarse gravel. About 55,000 tons of bedload was discharged from the Snake River to Lower Granite Reservoir during water years 2009–11, about 0.62 percent of the total sediment load delivered by the Snake River. About 9,500 tons of bedload was discharged from the Clearwater River to Lower Granite Reservoir during 2009–11, about 0.83 percent of the total sediment load discharged by the Clearwater River during 2009–11.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135083","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Clark, G.M., Fosness, R.L., and Wood, M.S., 2013, Sediment transport in the lower Snake and Clearwater River Basins, Idaho and Washington, 2008–11: U.S. Geological Survey Scientific Investigations Report 2013-5083, vi, 58 p., https://doi.org/10.3133/sir20135083.","productDescription":"vi, 58 p.","numberOfPages":"66","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":271216,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135083.jpg"},{"id":271214,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5083/"},{"id":271215,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5083/pdf/sir20135083.pdf"}],"country":"United States","state":"Idaho;Washington","otherGeospatial":"Lower Snake And Clearwater River Basins","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -119,44 ], [ -119,47.5 ], [ -113,47.5 ], [ -113,44 ], [ -119,44 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5172595de4b0c173799e78f2","contributors":{"authors":[{"text":"Clark, Gregory M. gmclark@usgs.gov","contributorId":1377,"corporation":false,"usgs":true,"family":"Clark","given":"Gregory","email":"gmclark@usgs.gov","middleInitial":"M.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477621,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fosness, Ryan L. 0000-0003-4089-2704 rfosness@usgs.gov","orcid":"https://orcid.org/0000-0003-4089-2704","contributorId":2703,"corporation":false,"usgs":true,"family":"Fosness","given":"Ryan","email":"rfosness@usgs.gov","middleInitial":"L.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477622,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wood, Molly S. 0000-0002-5184-8306 mswood@usgs.gov","orcid":"https://orcid.org/0000-0002-5184-8306","contributorId":788,"corporation":false,"usgs":true,"family":"Wood","given":"Molly","email":"mswood@usgs.gov","middleInitial":"S.","affiliations":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477620,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70045499,"text":"ds766 - 2013 - Groundwater geochemical and selected volatile organic compound data, Operable Unit 1, Naval Undersea Warfare Center, Division Keyport, Washington, June and October 2012","interactions":[],"lastModifiedDate":"2013-04-19T13:33:31","indexId":"ds766","displayToPublicDate":"2013-04-19T00:00:00","publicationYear":"2013","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":"766","title":"Groundwater geochemical and selected volatile organic compound data, Operable Unit 1, Naval Undersea Warfare Center, Division Keyport, Washington, June and October 2012","docAbstract":"Previous investigations indicate that concentrations of chlorinated volatile organic compounds are substantial in groundwater beneath the 9-acre former landfill at Operable Unit 1, Naval Undersea Warfare Center, Division Keyport, Washington. The U.S. Geological Survey has continued to monitor groundwater geochemistry to ensure that conditions remain favorable for contaminant biodegradation as specified in the Record of Decision for the site. This report presents groundwater geochemical and selected chlorinated volatile organic compound data collected at Operable Unit 1 by the U.S. Geological Survey during June and October 2012, in support of long-term monitoring for natural attenuation. Groundwater samples were collected from 13 wells and 9 piezometers, as well as from 10 shallow groundwater passive-diffusion sampling sites in the nearby marsh. Samples from all wells and piezometers were analyzed for oxidation-reduction (redox) sensitive constituents and dissolved gases. Samples from all piezometers also were analyzed for chlorinated volatile organic compounds, as were all samples from the passive-diffusion sampling sites. In 2012, concentrations of redox-sensitive constituents measured at all wells and piezometers were consistent with those measured in previous years, with dissolved oxygen concentrations all at 0.4 milligram per liter or less; little to no detectable nitrate; abundant dissolved manganese, iron, and methane; and commonly detected sulfide. In the upper aquifer of the northern plantation in 2012, chlorinated volatile organic compound (CVOC) concentrations at all piezometers were similar to those measured in previous years, and concentrations of the reductive dechlorination byproducts ethane and ethene were slightly higher or the same as concentrations measured in 2011. In the upper aquifer of the southern plantation, CVOC concentrations measured in piezometers during 2012 continued to be extremely variable as in previous years, and often very high, and reductive dechlorination byproducts were detected in two of the four wells and in all piezometers. Beneath the marsh adjacent to the southern plantation, chloroethene concentrations measured in 2012 continued to vary spatially and temporarily, and also were very high. Additionally, CVOC concentrations measured in samplers deployed in access tubes were about two to four times less than those measured in the two samplers buried nearby, beneath the marsh stream. Total CVOC concentration, at what has been historically the most contaminated passive-diffusion sampler site (S-4), continued an increasing trend. For the intermediate aquifer in 2012, concentrations of reductive dechlorination byproducts ethane and ethene were consistent with those measured in previous years.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds766","collaboration":"Prepared in cooperation with the Department of the Navy, Naval Facilities Engineering Command, Northwest","usgsCitation":"Huffman, R., 2013, Groundwater geochemical and selected volatile organic compound data, Operable Unit 1, Naval Undersea Warfare Center, Division Keyport, Washington, June and October 2012: U.S. Geological Survey Data Series 766, iv, 46 p., https://doi.org/10.3133/ds766.","productDescription":"iv, 46 p.","numberOfPages":"52","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":271259,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds766.jpg"},{"id":271257,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/766/"},{"id":271258,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/766/pdf/ds766.pdf"}],"country":"United States","state":"Washington","otherGeospatial":"Organic Compound Data;Operable Unit 1;Naval Undersea Warfare Center;Division Keyport","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.63,47.69 ], [ -122.63,47.70 ], [ -122.61,47.70 ], [ -122.61,47.69 ], [ -122.63,47.69 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5172595be4b0c173799e78e6","contributors":{"authors":[{"text":"Huffman, R.L.","contributorId":44956,"corporation":false,"usgs":true,"family":"Huffman","given":"R.L.","email":"","affiliations":[],"preferred":false,"id":477641,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70045489,"text":"ofr20131044 - 2013 - Role of stranded gas in increasing global gas supplies","interactions":[],"lastModifiedDate":"2018-03-23T14:28:01","indexId":"ofr20131044","displayToPublicDate":"2013-04-19T00:00:00","publicationYear":"2013","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":"2013-1044","title":"Role of stranded gas in increasing global gas supplies","docAbstract":"This report synthesizes the findings of three regional studies in order to evaluate, at the global scale, the contribution that stranded gas resources can make to global natural gas supplies. Stranded gas, as defined for this study, is natural gas in discovered conventional gas and oil fields that is currently not commercially producible for either physical or economic reasons. The regional studies evaluated the cost of bringing the large volumes of undeveloped gas in stranded gas fields to selected markets. In particular, stranded gas fields of selected Atlantic Basin countries, north Africa, Russia, and central Asia are screened to determine whether the volumes are sufficient to meet Europe’s increasing demand for gas imports. Stranded gas fields in Russia, central Asia, Southeast Asia, and Australia are also screened to estimate development, production, and transport costs and corresponding gas volumes that could be supplied to Asian markets in China, India, Japan, and South Korea. The data and cost analysis presented here suggest that for the European market and the markets examined in Asia, the development of stranded gas provides a way to meet projected gas import demands for the 2020-to-2040 period. Although this is a reconnaissance-type appraisal, it is based on volumes of gas that are associated with individual identified fields. Individual field data were carefully examined. Some fields were not evaluated because current technology was insufficient or it appeared the gas was likely to be held off the export market. Most of the evaluated stranded gas can be produced and delivered to markets at costs comparable to historical prices. Moreover, the associated volumes of gas are sufficient to provide an interim supply while additional technologies are developed to unlock gas diffused in shale and hydrates or while countries transition to making a greater use of renewable energy sources.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131044","usgsCitation":"Attanasi, E., and Freeman, P., 2013, Role of stranded gas in increasing global gas supplies: U.S. Geological Survey Open-File Report 2013-1044, ix, 57 p., https://doi.org/10.3133/ofr20131044.","productDescription":"ix, 57 p.","numberOfPages":"65","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":271169,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131044.gif"},{"id":271167,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1044/OFR2013-1044.pdf"},{"id":271166,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1044/"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5172595ce4b0c173799e78ee","contributors":{"authors":[{"text":"Attanasi, Emil 0000-0001-6845-7160 attanasi@usgs.gov","orcid":"https://orcid.org/0000-0001-6845-7160","contributorId":1809,"corporation":false,"usgs":true,"family":"Attanasi","given":"Emil","email":"attanasi@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":477617,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Freeman, P.A. 0000-0002-0863-7431 pfreeman@usgs.gov","orcid":"https://orcid.org/0000-0002-0863-7431","contributorId":3154,"corporation":false,"usgs":true,"family":"Freeman","given":"P.A.","email":"pfreeman@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":477618,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70045469,"text":"sir20135059 - 2013 - Sources of suspended-sediment loads in the lower Nueces River watershed, downstream from Lake Corpus Christi to the Nueces Estuary, south Texas, 1958–2010","interactions":[],"lastModifiedDate":"2016-08-05T14:08:52","indexId":"sir20135059","displayToPublicDate":"2013-04-18T00:00:00","publicationYear":"2013","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":"2013-5059","title":"Sources of suspended-sediment loads in the lower Nueces River watershed, downstream from Lake Corpus Christi to the Nueces Estuary, south Texas, 1958–2010","docAbstract":"The U.S. Geological Survey (USGS), in cooperation with the U.S. Army Corps of Engineers, Fort Worth District; City of Corpus Christi; Guadalupe-Blanco River Authority; San Antonio River Authority; and San Antonio Water System, developed, calibrated, and tested a Hydrological Simulation Program-FORTRAN (HSPF) watershed model to simulate streamflow and suspended-sediment concentrations and loads during 1958-2010 in the lower Nueces River watershed, downstream from Lake Corpus Christi to the Nueces Estuary in south Texas. Data available to simulate suspended-sediment concentrations and loads consisted of historical sediment data collected during 1942-82 in the study area and suspended-sediment concentration data collected periodically by the USGS during 2006-7 and 2010 at three USGS streamflow-gaging stations (08211000 Nueces River near Mathis, Tex. [the Mathis gage], 08211200 Nueces River at Bluntzer, Tex. [the Bluntzer gage], and 08211500 Nueces River at Calallen, Tex. [the Calallen gage]), and at one ungaged location on a Nueces River tributary (USGS station 08211050 Bayou Creek at Farm Road 666 near Mathis, Tex.). The Mathis gage is downstream from Wesley E. Seale Dam, which was completed in 1958 to impound Lake Corpus Christi. Suspended-sediment data collected before and after completion of Wesley E. Seale Dam provide insights to the effects of the dam and reservoir on suspended-sediment loads transported by the lower Nueces River downstream from the dam to the Nueces Estuary. Annual suspended-sediment loads at the Nueces River near the Mathis, Tex., gage were considerably lower for a given annual mean discharge after the dam was completed than before the dam was completed.
\nMost of the suspended sediment transported by the Nueces River downstream from Wesley E. Seale Dam occurred during high-flow releases from the dam or during floods. During October 1964-September 1971, about 536,000 tons of suspended sediment were transported by the Nueces River past the Mathis gage. Of this amount, about 473,000 tons, or about 88 percent, were transported by large runoff events (mean streamflow exceeding 1,000 cubic feet per second).
\nTo develop the watershed model to simulate suspended-sediment concentrations and loads in the lower Nueces River watershed during 1958-2010, streamflow simulations were calibrated and tested with available data for 2001-10 from the Bluntzer and Calallen gages. Streamflow data for the Nueces River obtained from the Mathis gage were used as input to the model at the upstream boundary of the model. Simulated streamflow volumes for the Bluntzer and Calallen gages showed good agreement with measured streamflow volumes. For 2001-10, simulated streamflow at the Calallen gage was within 3 percent of measured streamflow.
\nThe HSPF model was calibrated to simulate suspended sediment using suspended-sediment data collected at the Mathis, Bluntzer, and Calallen gages during 2006-7. Model simulated suspended-sediment loads at the Calallen gage were within 5 percent of loads that were estimated, by regression, from suspended-sediment sample analysis and measured streamflow. The calibrated watershed model was used to estimate streamflow and suspended-sediment loads for 1958-2010, including loads transported to the Nueces Estuary. During 1958-2010, on average, an estimated 288 tons per day (tons/d) of suspended sediment were delivered to the lower Nueces River; an estimated 278 tons/d were delivered to the estuary. The annual suspended-sediment load was highly variable, depending on the occurrence of runoff events and high streamflows. During 1958-2010, the annual total sediment loads to the estuary varied from an estimated 3.8 to 2,490 tons/d. On average, 113 tons/d, or about 39 percent of the estimated annual suspended-sediment contribution, originated from cropland in the study watershed. Releases from Lake Corpus Christi delivered an estimated 94 tons/d of suspended sediment or about 33 percent of the 288 tons/d estimated to have been delivered to the lower Nueces River. Erosion of stream-channel bed and banks accounted for 44 tons/d or about 15 percent of the estimated total suspended-sediment load. All other land categories, except cropland, accounted for an estimated 36 tons/d, or about 12 percent of the total. An estimated 10 tons/d of suspended sediment or about 3 percent of the suspended-sediment load delivered to the lower Nueces River were removed by water withdrawals before reaching the Nueces Estuary.
\nDuring 2010, additional suspended-sediment data were collected during selected runoff events to provide new data for model testing and to help better understand the sources of suspended-sediment loads. The model was updated and used to estimate and compare sediment yields from each of 64 subwatersheds comprising the lower Nueces River watershed study area for three selected runoff events: November 20-21, 2009, September 7-8, 2010, and September 20-21, 2010. These three runoff events were characterized by heavy rainfall centered near the study area and during which minimal streamflow and suspended-sediment load entered the lower Nueces River upstream from Wesley E. Seale Dam. During all three runoff events, model simulations showed that the greatest sediment yields originated from the subwatersheds, which were largely cropland. In particular, the Bayou Creek subwatersheds were major contributors of suspended-sediment load to the lower Nueces River during the selected runoff events. During the November 2009 runoff event, high suspended-sediment concentrations in the Nueces River water withdrawn for the City of Corpus Christi public-water supply caused problems during the water-treatment process, resulting in failure to meet State water-treatment standards for turbidity in drinking water. Model simulations of the November 2009 runoff event showed that the Bayou Creek subwatersheds were the primary source of suspended-sediment loads during that runoff event.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135059","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Fort Worth District; City of Corpus Christi; Guadalupe-Blanco River Authority; San Antonio River Authority; and San Antonio Water System","usgsCitation":"Ockerman, D.J., Heitmuller, F.T., and Wehmeyer, L.L., 2013, Sources of suspended-sediment loads in the lower Nueces River watershed, downstream from Lake Corpus Christi to the Nueces Estuary, south Texas, 1958–2010: U.S. Geological Survey Scientific Investigations Report 2013-5059, ix, 57 p., https://doi.org/10.3133/sir20135059.","productDescription":"ix, 57 p.","numberOfPages":"67","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":271052,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135059.gif"},{"id":271053,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5059/"},{"id":271054,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5059/pdf/sir2013-5059.pdf"}],"country":"United States","state":"Texas","otherGeospatial":"Lower Nueces River Watershed","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -98.15,27.72 ], [ -98.15,28.26 ], [ -97.15,28.26 ], [ -97.15,27.72 ], [ -98.15,27.72 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"517107dee4b0053160634243","contributors":{"authors":[{"text":"Ockerman, Darwin J. 0000-0003-1958-1688 ockerman@usgs.gov","orcid":"https://orcid.org/0000-0003-1958-1688","contributorId":1579,"corporation":false,"usgs":true,"family":"Ockerman","given":"Darwin","email":"ockerman@usgs.gov","middleInitial":"J.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477571,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Heitmuller, Franklin T.","contributorId":67476,"corporation":false,"usgs":true,"family":"Heitmuller","given":"Franklin","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":477572,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wehmeyer, Loren L.","contributorId":90412,"corporation":false,"usgs":true,"family":"Wehmeyer","given":"Loren","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":477573,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70045479,"text":"sir20135058 - 2013 - Baseline assessment of physical characteristics, aquatic biota, and selected water-quality properties at the reach and mesohabitat scale for reaches of Big Cypress, Black Cypress, and Little Cypress Bayous, Big Cypress Basin, northeastern Texas, 2010–11","interactions":[],"lastModifiedDate":"2016-08-05T14:06:37","indexId":"sir20135058","displayToPublicDate":"2013-04-18T00:00:00","publicationYear":"2013","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":"2013-5058","title":"Baseline assessment of physical characteristics, aquatic biota, and selected water-quality properties at the reach and mesohabitat scale for reaches of Big Cypress, Black Cypress, and Little Cypress Bayous, Big Cypress Basin, northeastern Texas, 2010–11","docAbstract":"In 2010 and 2011, the U.S. Geological Survey (USGS), in cooperation with the Northeast Texas Municipal Water District and the Texas Commission on Environmental Quality, did a baseline assessment of physical characteristics and aquatic biota (fish and mussels) collected at the mesohabitat scale for reaches of Big Cypress, Black Cypress, and Little Cypress Bayous in the Big Cypress Basin in northeastern Texas, and measured selected water-quality properties in isolated pools in Black Cypress and Little Cypress. All of the data were collected in the context of prescribed environmental flows. The information acquired during the course of the study will support the long-term monitoring of biota in relation to environmental flow prescriptions for Big Cypress Bayou, Black Cypress Bayou, and Little Cypress Bayou. Data collection and analysis were done at mesohabitat- and reach-specific scales, where a mesohabitat is defined as a discrete area within a stream that exhibits unique depth, velocity, slope, substrate, and cover.
\nBiological and physical characteristic data were collected from two sites on Big Cypress Bayou, and one site on both Black Cypress Bayou and Little Cypress Bayou. The upstream reach of Big Cypress Bayou (USGS station 07346015 Big Cypress Bayou at confluence of French Creek, Jefferson, Texas) is hereinafter referred to as the Big Cypress 02 site. The downstream site on Big Cypress Bayou (USGS station 07346017 Big Cypress Bayou near U.S. Highway 59 near Jefferson, Tex.) is hereinafter referred to as the Big Cypress 01 site and was sampled exclusively for mussels. The sites on Black Cypress Bayou (USGS station 07346044 Black Cypress Bayou near U.S. Highway 59 near Jefferson, Tex.) and Little Cypress Bayou (USGS station 07346071 Little Cypress Bayou near U.S. Highway 59 near Jefferson, Tex.) are hereinafter referred to as the Black Cypress and Little Cypress sites, respectively.
\nA small range of streamflows was targeted for data collection, including a period of low flow during July and August 2010 and a period of very low flow during July 2011. This scenario accounts for variability in the abundance and distribution of fish and mussels and in the physical characteristics of mesohabitats present during different flow conditions. Mussels were not collected from the Little Cypress site. However, a quantitative survey of freshwater mussels was conducted at Big Cypress 01.
\nOf the three reaches where physical habitat data were measured in 2010, Big Cypress 02 was both the widest and deepest, with a mean width of 62.2 feet (ft) and a mean depth of 5.5 ft in main-channel mesohabitats. Little Cypress was the second widest and deepest, with a mean width of 49.9 ft and a mean depth of 4.5 ft in main-channel mesohabitats. Black Cypress was by far the narrowest of the three reaches, with a mean width of 29.1 ft and a mean depth of 3.3 ft in main-channel mesohabitats but it had the highest mean velocity of 0.42 feet per second (ft/s). Appreciably more fish were collected from Big Cypress 02 (596) in summer 2010 compared to Black Cypress (273) or Little Cypress (359), but the total number of fish species collected among the three reaches was similar. Longear sunfish was the most abundant fish species collected from all three sites. The total number of fish species was largest in slow run mesohabitats at Big Cypress 02, fast runs at Black Cypress, and slow runs at Little Cypress. The catch-per-unit-effort of native minnows was largest in fast runs at Big Cypress 02. More species of native minnows, including the ironcolor and emerald shiner, were collected from Little Cypress relative to all other mesohabitats at all sites.
\nFifteen species and 182 individuals of freshwater mussels were collected, with 69.8 percent of the individual mussels collected from Big Cypress 02, 23.6 percent collected from Big Cypress 01, and 6.6 percent collected from Black Cypress. Big Cypress 01was the most species rich site with 13 species, and washboards were the most abundant species overall. Mussels were not collected from Little Cypress because there was no flow in this stream during the targeted sampling period in 2011.
\nOn July 30, 2010, when the estimated streamflow at the site (based on daily mean discharge measured at the upstream gage in conjunction with powerplant withdrawals) was 45 cubic feet per second (ft3/s), Big Cypress 02 had a mean width of 62.2 ft and a mean depth of 5.5 ft in main-channel mesohabitats. On July 27, 2011, when instantaneous streamflow at the site was 10 ft3/s, the mean width and mean depth in main-channel mesohabitats decreased to 49.6 ft and 3.1 ft, respectively. Mean velocity in 2010 (0.31 ft/s) was approximately twice as high as 2011 (0.17 ft/s) in main-channel mesohabitats. About 14 percent more fish were collected from Big Cypress 02 in 2010 relative to 2011, and about 18 percent fewer fish species were identified in 2011 at this site compared to 2010. Longear sunfish, which was the most abundant fish species collected in 2010, was second to western mosquitofish in 2011.
\nIn the absence of flow during fall 2011, the reach at Black Cypress was reduced to four isolated pools, and the reach at Little Cypress was reduced to three isolated pools. Dissolved oxygen, temperature, pH, and specific conductance data were collected from the pools because it was hypothesized that these conditions would be the most limiting with respect to aquatic life. Dissolved oxygen concentrations ranged from 0.58 milligrams per liter (mg/L) to 4.79 mg/L at Black Cypress and from 0.24 mg/L to 5.33 mg/L at Little Cypress; both sites exhibited a stratified pattern in dissolved oxygen concentrations along transect lines, but the pattern was less pronounced at Black Cypress.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135058","collaboration":"Prepared in cooperation with the Northeast Texas Municipal Water District and the Texas Commission on Environmental Quality","usgsCitation":"Braun, C.L., and Moring, J., 2013, Baseline assessment of physical characteristics, aquatic biota, and selected water-quality properties at the reach and mesohabitat scale for reaches of Big Cypress, Black Cypress, and Little Cypress Bayous, Big Cypress Basin, northeastern Texas, 2010–11: U.S. Geological Survey Scientific Investigations Report 2013-5058, vii, 90 p., https://doi.org/10.3133/sir20135058.","productDescription":"vii, 90 p.","numberOfPages":"101","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":271057,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20135058.gif"},{"id":271055,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5058/"},{"id":271056,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5058/sir2013-5058.pdf"}],"country":"United States","state":"Texas","otherGeospatial":"Big Cypress Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -94.5,32.6 ], [ -94.5,32.5 ], [ -94.17,32.5 ], [ -94.17,32.6 ], [ -94.5,32.6 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"517107d2e4b005316063423f","contributors":{"authors":[{"text":"Braun, Christopher L. 0000-0002-5540-2854 clbraun@usgs.gov","orcid":"https://orcid.org/0000-0002-5540-2854","contributorId":925,"corporation":false,"usgs":true,"family":"Braun","given":"Christopher","email":"clbraun@usgs.gov","middleInitial":"L.","affiliations":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477595,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Moring, James B. jbmoring@usgs.gov","contributorId":1509,"corporation":false,"usgs":true,"family":"Moring","given":"James B.","email":"jbmoring@usgs.gov","affiliations":[],"preferred":false,"id":477596,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70045456,"text":"ofr20131073 - 2013 - Residential and service-population exposure to multiple natural hazards in the Mount Hood region of Clackamas County, Oregon","interactions":[],"lastModifiedDate":"2013-04-16T16:17:45","indexId":"ofr20131073","displayToPublicDate":"2013-04-16T00:00:00","publicationYear":"2013","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":"2013-1073","title":"Residential and service-population exposure to multiple natural hazards in the Mount Hood region of Clackamas County, Oregon","docAbstract":"The objective of this research is to document residential and service-population exposure to natural hazards in the rural communities of Clackamas County, Oregon, near Mount Hood. The Mount Hood region of Clackamas County has a long history of natural events that have impacted its small, tourism-based communities. To support preparedness and emergency-management planning in the region, a geospatial analysis of population exposure was used to determine the number and type of residents and service populations in flood-, wildfire-, and volcano-related hazard zones. Service populations are a mix of residents and tourists temporarily benefitting from local services, such as retail, education, or recreation. In this study, service population includes day-use visitors at recreational sites, overnight visitors at hotels and resorts, children at schools, and community-center visitors. Although the heavily-forested, rural landscape suggests few people are in the area, there are seasonal peaks of thousands of visitors to the region. “Intelligent” dasymetric mapping efforts using 30-meter resolution land-cover imagery and U.S. Census Bureau data proved ineffective at adequately capturing either the spatial distribution or magnitude of population at risk. Consequently, an address-point-based hybrid dasymetric methodology of assigning population to the physical location of buildings mapped with a global positioning system was employed. The resulting maps of the population (1) provide more precise spatial distributions for hazard-vulnerability assessments, (2) depict appropriate clustering due to higher density structures, such as apartment complexes and multi-unit commercial buildings, and (3) provide new information on the spatial distribution and temporal variation of people utilizing services within the study area.\n\nEstimates of population exposure to flooding, wildfire, and volcanic hazards were determined by using overlay analysis in a geographic information system. Population exposure to flood hazards is low (less than 10 percent of residents) and does not vary substantially between 100-year and 500-year flood-hazard scenarios. Moderate, moderate-to-high, and high wildfire-risk areas within the study region account for 72 percent of residents, 62 percent of employees, and 60 percent of daytime visitors to recreation sites. Fifteen percent of businesses in the study area are in moderate-to-high or high wildfire-risk areas but these businesses represent 51 percent of the local workforce. A volcanic event at Mount Hood could directly impact up to 60 percent of residents in their homes and 87 percent of employees at their workplaces. The proximal volcanic-hazard zone alone includes 65 percent of employees, 80 percent of schools and community facilities, more than 60 percent of overnight visitors in peak seasons, and 82–100 percent of daytime visitors to recreation sites during the summer and winter months, respectively. The number of day-use visitors to recreation sites in the region is greatest during winter months (averaging 129,300 people per month), whereas overnight visitors are greatest during summer months (averaging 34,000 per month). This analysis of residential and service-population exposure to natural hazards supports the development of targeted risk-reduction efforts in the region, while also expanding the discourse on characterizing and assessing population dynamics in tourist-frequented areas.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131073","collaboration":"Prepared in cooperation with the Clackamas County Emergency Management Department","usgsCitation":"Mathie, A., and Wood, N., 2013, Residential and service-population exposure to multiple natural hazards in the Mount Hood region of Clackamas County, Oregon: U.S. Geological Survey Open-File Report 2013-1073, iv, 48 p., https://doi.org/10.3133/ofr20131073.","productDescription":"iv, 48 p.","numberOfPages":"54","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":271018,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20131073.jpg"},{"id":271017,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1073/pdf/ofr20131073.pdf"},{"id":271016,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1073/"}],"country":"United States","state":"Oregon","county":"Clackamas County","otherGeospatial":"Mount Hood","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.868,44.8857 ], [ -122.868,45.4617 ], [ -121.651,45.4617 ], [ -121.651,44.8857 ], [ -122.868,44.8857 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"516e64dbe4b00154e4368b6b","contributors":{"authors":[{"text":"Mathie, Amy M.","contributorId":82803,"corporation":false,"usgs":true,"family":"Mathie","given":"Amy M.","affiliations":[],"preferred":false,"id":477522,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wood, Nathan 0000-0002-6060-9729 nwood@usgs.gov","orcid":"https://orcid.org/0000-0002-6060-9729","contributorId":71151,"corporation":false,"usgs":true,"family":"Wood","given":"Nathan","email":"nwood@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":false,"id":477521,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ]}