Accounting for errors in wildlife surveys is necessary for reliable status assessments and quantification of uncertainty in estimates of population size. We apply a hierarchical log-linear Poisson regression model that accounts for multiple sources of variability in count data collected for the Integrated Waterbird Management and Monitoring Program during 2010–2014. In some large-scale monitoring programs (e.g., Christmas Bird Count) there are diminishing returns in numbers counted as survey effort increases; therefore, we also explore the need to account for variable survey duration as a proxy for effort. In general, we found a high degree of concordance between counts and effort-adjusted estimates of relative abundance from the Integrated Waterbird Management and Monitoring Program (x̄difference = 0.02%; 0.25% SD). We suggest that the model-based adjustments were small because there is only a weak asymptotic relationship with effort and count. Whereas effort adjustments are reasonable and effective when applied to count data from plots of standardized area, such adjustments may not be necessary when the area of sample units is not standardized and surveyor effort increases with number of birds present. That is, large units require more effort only when there are many birds present. The general framework we implemented to evaluate effects of varying survey effort applies to a wide variety of wildlife monitoring efforts.
","language":"English","publisher":"U.S. Fish and Wildlife Service","doi":"10.3996/022018-JFWM-012","usgsCitation":"Aagaard, K., Lyons, J.E., and Thogmartin, W.E., 2018, Accounting for surveyor effort in large-scale monitoring programs: Journal of Fish and Wildlife Management, v. 9, no. 2, p. 459-466, https://doi.org/10.3996/022018-JFWM-012.","productDescription":"8 p.","startPage":"459","endPage":"466","ipdsId":"IP-079755","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":468218,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/022018-jfwm-012","text":"Publisher Index Page"},{"id":361285,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"2","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-08-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Aagaard, Kevin 0000-0003-0756-2172 kaagaard@usgs.gov","orcid":"https://orcid.org/0000-0003-0756-2172","contributorId":147393,"corporation":false,"usgs":true,"family":"Aagaard","given":"Kevin","email":"kaagaard@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":757317,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lyons, James E. 0000-0002-9810-8751 jelyons@usgs.gov","orcid":"https://orcid.org/0000-0002-9810-8751","contributorId":177546,"corporation":false,"usgs":true,"family":"Lyons","given":"James","email":"jelyons@usgs.gov","middleInitial":"E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":757318,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":757319,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70202212,"text":"70202212 - 2018 - Geomorphic evolution of a gravel‐bed river under sediment‐starved vs. sediment‐rich conditions: River response to the world's largest dam removal","interactions":[],"lastModifiedDate":"2019-02-14T12:21:52","indexId":"70202212","displayToPublicDate":"2018-12-01T12:21:45","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2318,"text":"Journal of Geophysical Research F: Earth Surface","active":true,"publicationSubtype":{"id":10}},"title":"Geomorphic evolution of a gravel‐bed river under sediment‐starved vs. sediment‐rich conditions: River response to the world's largest dam removal","docAbstract":"Understanding river response to sediment pulses is a fundamental problem in geomorphic process studies, with myriad implications for river management. However, because large sediment pulses are rare and usually unanticipated, they are seldom studied at field scale. We examine fluvial response to a massive (~20 Mt) sediment pulse released by the largest dam removal globally, on the Elwha River, Washington, United States, in an 11‐year before‐after/control‐impact study of channel morphology and grain size. We test the hypothesis that for a given flow magnitude, greater geomorphic change occurs under sediment‐rich conditions than under sediment‐starved conditions. Channel response to flow forcing was significantly different during the sediment‐pulse peak, 1–2 years after dam removal began, than earlier or later. During peak sediment supply our hypothesis was supported; major geomorphic change occurred under low flows and unit stream power ≤60 W/m2. However, by 4–6 years after dam removal began, rates of geomorphic change and sensitivity to stream power had decreased substantially such that our hypothesis was no longer unequivocally supported. These findings are consistent with a two‐phase conceptual model of dam‐removal response, involving a transport‐limited state followed by a more supply‐limited state. From comparisons with other dam removals and natural sediment pulses, we infer that the longevity of sediment‐pulse signals in gravel‐bed rivers depends upon gradient, river discharge, valley morphology, and sediment grain size. Stream power associated with substantial geomorphic change varies with sediment supply, such that assigning a general threshold stream power to gravel‐bed rivers may be untenable.
","language":"English","publisher":"AGU","doi":"10.1029/2018JF004703","usgsCitation":"East, A.E., Logan, J.B., Mastin, M.C., Ritchie, A.C., Bountry, J.A., Magirl, C.S., and Sankey, J.B., 2018, Geomorphic evolution of a gravel‐bed river under sediment‐starved vs. sediment‐rich conditions: River response to the world's largest dam removal: Journal of Geophysical Research F: Earth Surface, v. 123, no. 12, p. 3338-3369, https://doi.org/10.1029/2018JF004703.","productDescription":"32 p.","startPage":"3338","endPage":"3369","ipdsId":"IP-096606","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468219,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018jf004703","text":"Publisher Index Page"},{"id":361253,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Elwha River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.667,\n 47.9167\n ],\n [\n -123.5,\n 47.9167\n ],\n [\n -123.5,\n 48.1667\n ],\n [\n -123.667,\n 48.1667\n ],\n [\n -123.667,\n 47.9167\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"123","issue":"12","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-12-28","publicationStatus":"PW","contributors":{"authors":[{"text":"East, Amy E. 0000-0002-9567-9460 aeast@usgs.gov","orcid":"https://orcid.org/0000-0002-9567-9460","contributorId":196364,"corporation":false,"usgs":true,"family":"East","given":"Amy","email":"aeast@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":757268,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Logan, Joshua B. 0000-0002-6191-4119 jlogan@usgs.gov","orcid":"https://orcid.org/0000-0002-6191-4119","contributorId":2335,"corporation":false,"usgs":true,"family":"Logan","given":"Joshua","email":"jlogan@usgs.gov","middleInitial":"B.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":757269,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mastin, Mark C. 0000-0003-4018-7861 mcmastin@usgs.gov","orcid":"https://orcid.org/0000-0003-4018-7861","contributorId":1652,"corporation":false,"usgs":true,"family":"Mastin","given":"Mark","email":"mcmastin@usgs.gov","middleInitial":"C.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":757270,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ritchie, Andrew C. aritchie@usgs.gov","contributorId":4984,"corporation":false,"usgs":true,"family":"Ritchie","given":"Andrew","email":"aritchie@usgs.gov","middleInitial":"C.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":757271,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bountry, Jennifer A.","contributorId":30114,"corporation":false,"usgs":false,"family":"Bountry","given":"Jennifer","email":"","middleInitial":"A.","affiliations":[{"id":7183,"text":"U.S. Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":757272,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Magirl, Christopher S. 0000-0002-9922-6549 magirl@usgs.gov","orcid":"https://orcid.org/0000-0002-9922-6549","contributorId":1822,"corporation":false,"usgs":true,"family":"Magirl","given":"Christopher","email":"magirl@usgs.gov","middleInitial":"S.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true},{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":757273,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sankey, Joel B. 0000-0003-3150-4992 jsankey@usgs.gov","orcid":"https://orcid.org/0000-0003-3150-4992","contributorId":3935,"corporation":false,"usgs":true,"family":"Sankey","given":"Joel","email":"jsankey@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":757274,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70201660,"text":"70201660 - 2018 - Remote sensing vegetation index methods to evaluate changes in greenness and evapotranspiration in riparian vegetation in response to the Minute 319 environmental pulse flow to Mexico","interactions":[],"lastModifiedDate":"2018-12-21T11:42:18","indexId":"70201660","displayToPublicDate":"2018-12-01T11:42:13","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5272,"text":"Proceedings of the International Association of Hydrological Sciences","active":true,"publicationSubtype":{"id":10}},"title":"Remote sensing vegetation index methods to evaluate changes in greenness and evapotranspiration in riparian vegetation in response to the Minute 319 environmental pulse flow to Mexico","docAbstract":"During the spring of 2014, 130 million m3 of water were released from the United States' Morelos Dam on the lower Colorado River to Mexico, allowing water to reach the Gulf of California for the first time in 13 years. Our study assessed the effects of water transfer or ecological environmental flows from one nation to another, using remote sensing. Spatial applications for water resource evaluation are important for binational, integrated water resources management and planning for the Colorado River, which includes seven basin states in the US plus two states in Mexico. Our study examined the effects of the historic binational experiment (the Minute 319 agreement) on vegetative response along the riparian corridor. We used 250 m Moderate Resolution Imaging Spectroradiometer (MODIS), Enhanced Vegetation Index (EVI) and 30 m Landsat 8 satellite imagery to track evapotranspiration (ET) and the normalized difference vegetation index (NDVI). Our analysis showed an overall increase in NDVI and evapotranspiration (ET) in the year following the 2014 pulse, which reversed a decline in those metrics since the last major flood in 2000. NDVI and ET levels decreased in 2015, but were still significantly higher (P < 0.001) than pre-pulse (2013) levels. Preliminary findings show that the decline in 2015 persisted into 2016 and 2017. We continue to analyse results for 2018 in comparison to short-term (2013–2018) and long-term (2000–2018) trends. Our results support the conclusion that these environmental flows from the US to Mexico via the Minute 319 “pulse” had a positive, but short-lived (1 year), impact on vegetation growth in the delta.
","language":"English","publisher":"International Association of Hydrological Sciences","doi":"10.5194/piahs-380-45-2018","usgsCitation":"Nagler, P.L., Jarchow, C., and Glenn, E., 2018, Remote sensing vegetation index methods to evaluate changes in greenness and evapotranspiration in riparian vegetation in response to the Minute 319 environmental pulse flow to Mexico: Proceedings of the International Association of Hydrological Sciences, v. 380, p. 45-54, https://doi.org/10.5194/piahs-380-45-2018.","productDescription":"10 p.","startPage":"45","endPage":"54","ipdsId":"IP-097590","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":468221,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/piahs-380-45-2018","text":"Publisher Index Page"},{"id":360670,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico","otherGeospatial":" Colorado River Delta","volume":"380","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-12-18","publicationStatus":"PW","scienceBaseUri":"5c1e0a30e4b0708288cb021b","contributors":{"authors":[{"text":"Nagler, Pamela L. 0000-0003-0674-103X pnagler@usgs.gov","orcid":"https://orcid.org/0000-0003-0674-103X","contributorId":1398,"corporation":false,"usgs":true,"family":"Nagler","given":"Pamela","email":"pnagler@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":754756,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jarchow, Christopher J. 0000-0002-0424-4104","orcid":"https://orcid.org/0000-0002-0424-4104","contributorId":211737,"corporation":false,"usgs":false,"family":"Jarchow","given":"Christopher J.","affiliations":[{"id":38314,"text":"USGS Southwest Biological Science Center, Flagstaff, AZ","active":true,"usgs":false}],"preferred":false,"id":754757,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Glenn, Edward P.","contributorId":56542,"corporation":false,"usgs":false,"family":"Glenn","given":"Edward P.","affiliations":[{"id":13060,"text":"Department of Soil, Water and Environmental Science, University of Arizona","active":true,"usgs":false}],"preferred":false,"id":754758,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70201572,"text":"70201572 - 2018 - The National Elevation Dataset","interactions":[],"lastModifiedDate":"2018-12-20T11:11:14","indexId":"70201572","displayToPublicDate":"2018-12-01T11:11:10","publicationYear":"2018","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"The National Elevation Dataset","docAbstract":"The National Elevation Dataset (NED) is a primary elevation data product that has been produced and distributed by the U.S. Geological Survey (USGS). Since its inception, the USGS has compiled and published topographic information in many forms, and the NED is a significant development in this long line of products that describe the land surface. The NED provides seamless raster elevation data of the conterminous United States (CONUS), Alaska, Hawaii, U.S. island territories, Mexico, and Canada. The NED is derived from diverse source datasets that are processed to a specification with consistent resolutions, coordinate system, elevation units, and horizontal and vertical datums. The NED was developed as the logical result of the maturation of the long-standing USGS elevation program, which for many years concentrated on production of quadrangle-based digital elevation models (DEM). The NED contributes to the elevation layer of The National Map, and it provides basic elevation information for earth science studies and mapping applications in the U.S. and most of North America.\n For over 15 years (1999–2014), the NED served as the flagship elevation product of the USGS. In 2015, the 3D Elevation Program (3DEP) was initiated. When the 3DEP initiative became operational, the name “National Elevation Dataset” (and the abbreviation “NED”) were retired as the USGS elevation activities and data were rebranded under the 3DEP banner. However, elevation data produced and distributed as part of the NED are still widely used (and distributed by other entities), so there is a continuing need for detailed documentation, including how it was produced, its accuracy, and how it is used. This chapter directly addresses that need for detailed information about the NED. The most recent detailed description of the NED appeared in the 2nd edition of the DEM Users Manual (2007), and because NED production continued through 2014, the details reported herein provide valuable information for data accessed by the user community from 2007 through 2014. The NED has been widely used in operational applications and research studies and is extensively cited in reports on those activities, so it is important for the user community to have access to information about the NED to better judge how its qualities and characteristics might affect results derived from its use as the elevation data source. Additionally, the NED seamless layers serve as one of the input data sources for the current 3DEP elevation production system, so, as with any input data source, an understanding of the data characteristics is critical.","language":"English","publisher":"American Society for Photogrammetry and Remote Sensing","usgsCitation":"Gesch, D.B., Evans, G.A., Oimoen, M., and Arundel, S., 2018, The National Elevation Dataset, p. 83-110.","productDescription":"28 p.","startPage":"83","endPage":"110","ipdsId":"IP-051285","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":360618,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":360617,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.asprs.org/dem"}],"publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5c1cb860e4b0708288c8382d","contributors":{"authors":[{"text":"Gesch, Dean B. 0000-0002-8992-4933 gesch@usgs.gov","orcid":"https://orcid.org/0000-0002-8992-4933","contributorId":2956,"corporation":false,"usgs":true,"family":"Gesch","given":"Dean","email":"gesch@usgs.gov","middleInitial":"B.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":754462,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Evans, Gayla A. 0000-0001-5072-4232 gevans@usgs.gov","orcid":"https://orcid.org/0000-0001-5072-4232","contributorId":3125,"corporation":false,"usgs":true,"family":"Evans","given":"Gayla","email":"gevans@usgs.gov","middleInitial":"A.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":754463,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Oimoen, Michael J. 0000-0003-3611-6227","orcid":"https://orcid.org/0000-0003-3611-6227","contributorId":211599,"corporation":false,"usgs":true,"family":"Oimoen","given":"Michael J.","affiliations":[{"id":38270,"text":"SGT Inc., contractor to USGS EROS","active":true,"usgs":false}],"preferred":false,"id":754464,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Arundel, Samantha T. 0000-0002-4863-0138 sarundel@usgs.gov","orcid":"https://orcid.org/0000-0002-4863-0138","contributorId":192598,"corporation":false,"usgs":true,"family":"Arundel","given":"Samantha","email":"sarundel@usgs.gov","middleInitial":"T.","affiliations":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true},{"id":404,"text":"NGTOC Rolla","active":true,"usgs":true}],"preferred":true,"id":754465,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70201999,"text":"70201999 - 2018 - Executive summary. In Second State of the Carbon Cycle Report (SOCCR2): A Sustained Assessment Report","interactions":[],"lastModifiedDate":"2019-02-05T11:08:01","indexId":"70201999","displayToPublicDate":"2018-12-01T11:07:41","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"title":"Executive summary. In Second State of the Carbon Cycle Report (SOCCR2): A Sustained Assessment Report","docAbstract":"Central to life on Earth, carbon is essential to the molecular makeup of all living things and plays a key role in regulating global climate. To understand carbon’s role in these processes, researchers measure and evaluate carbon stocks and fluxes. A stock is the quantity of carbon contained in a pool or reservoir in the Earth system (e.g., carbon in forest trees), and a flux is the direction and rate of carbon’s transfer between pools (e.g., the movement of carbon from the atmosphere into forest trees during photosynthesis). This document, the Second State of the Carbon Cycle Report (SOCCR2), examines the patterns of carbon stocks and fluxes—collectively called the “carbon cycle.” Emphasis is given to these patterns in specific sectors (e.g., agriculture and energy) and ecosystems (e.g., forests and coastal waters) and to the response of the carbon cycle to human activity. The purpose of SOCCR2 is to assess the current state of the North American carbon cycle and to present recent advances in understanding the factors that influence it. Concentrating on North America—Canada, the United States, and Mexico—the report describes carbon cycling for air, land, inland waters (streams, rivers, lakes, and reservoirs), and coastal waters (see Figure ES.1, p. 23).
The questions framing the publication A U.S. Carbon Cycle Science Plan (Michalak et al., 2011) inspired development of three slightly modified questions that guide SOCCR2’s content and focus on North America in a global context:
SOCCR2 synthesizes the most recent understanding of carbon cycling in North America, assessing new carbon cycle findings and information, the state of knowledge regarding core methods used to study the carbon cycle, and future research needed to best inform carbon management and policy options. Focusing on scientific developments in the decade since the First State of the Carbon Cycle Report (SOCCR1; CCSP 2007), SOCCR2 summarizes the past, current, and projected state of carbon sources, sinks, and natural processes, as well as contributions by human activities. In addition to CO2 and CH4, the report sometimes discusses nitrous oxide (N2O), a GHG associated with activities and processes that affect fluxes of carbon gases.1 SOCCR2 also describes improvements in analysis tools; developments in decision support; and new insights into ecosystem carbon cycling, human causes of changes in the carbon cycle, and social science perspectives on carbon. Since publication of SOCCR1, coordinated research from agencies in the three North American countries has enabled innovative observational, analytical, and modeling capabilities to further advance understanding of the North American carbon cycle (see Appendix D: Carbon Measurement Approaches and Accounting Frameworks, p. 834). Some of the report’s main conclusions, based on the Key Findings of each chapter, are highlighted in Box ES.1, Main Findings of SOCCR2, p. 24.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Second State of the Carbon Cycle Report (SOCCR2): A Sustained Assessment Report","largerWorkSubtype":{"id":1,"text":"Federal Government Series"},"language":"English","publisher":"U.S. Global Change Research Program","doi":"10.7930/SOCCR2.2018.ES","usgsCitation":"Birdsey, R., Mayes, M.A., Romero-Lankao, P., Najjar, R., Reed, S.C., Cavallaro, N., Shrestha, G., Hayes, D.J., Lorenzoni, L., Marsh, A., Tedesco, K., Wirth, T., and Zhu, Z., 2018, Executive summary. In Second State of the Carbon Cycle Report (SOCCR2): A Sustained Assessment Report, 20 p., https://doi.org/10.7930/SOCCR2.2018.ES.","productDescription":"20 p.","startPage":"21","endPage":"40","ipdsId":"IP-088979","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":361013,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Cavallaro, Nancy","contributorId":212784,"corporation":false,"usgs":false,"family":"Cavallaro","given":"Nancy","email":"","affiliations":[{"id":38681,"text":"USDA National Institute of Food and Agriculture","active":true,"usgs":false}],"preferred":false,"id":756620,"contributorType":{"id":2,"text":"Editors"},"rank":1},{"text":"Shrestha, Gyami","contributorId":145521,"corporation":false,"usgs":false,"family":"Shrestha","given":"Gyami","email":"","affiliations":[],"preferred":false,"id":756621,"contributorType":{"id":2,"text":"Editors"},"rank":2},{"text":"Birdsey, Richard","contributorId":210640,"corporation":false,"usgs":false,"family":"Birdsey","given":"Richard","affiliations":[{"id":25456,"text":"Woods Hole Research Center, Falmouth, MA, United States","active":true,"usgs":false}],"preferred":false,"id":756622,"contributorType":{"id":2,"text":"Editors"},"rank":3},{"text":"Mayes, Melanie A.","contributorId":212782,"corporation":false,"usgs":false,"family":"Mayes","given":"Melanie","email":"","middleInitial":"A.","affiliations":[{"id":37070,"text":"Oak Ridge National Laboratory","active":true,"usgs":false}],"preferred":false,"id":756623,"contributorType":{"id":2,"text":"Editors"},"rank":4},{"text":"Najjar, Raymond G.","contributorId":168568,"corporation":false,"usgs":false,"family":"Najjar","given":"Raymond 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Open population features of the robust design allow for estimation of rates of death or permanent emigration, and closed population features enhance estimation of population sizes. We describe a similar design, but for use with removal data. Data collection occurs on secondary sampling occasions clustered within primary sampling periods. Primary sampling periods are intervals of brief enough duration that it can be safely assumed that the population is unchanged by births, deaths, immigration or emigration during them; all population change and movement occurs between primary sampling periods. Our model provides a basis for inference about population size, changes in population size, and movement rates among sample locations between primary sampling periods. Movement rates are modeled as functions of distance and time. Capture probabilities are modeled as a function of effort. 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M.","contributorId":214279,"corporation":false,"usgs":false,"family":"Smith","given":"Zachary","email":"","middleInitial":"M.","affiliations":[{"id":39005,"text":"ICPRB","active":true,"usgs":false}],"preferred":false,"id":759530,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buchanan, Claire","contributorId":214280,"corporation":false,"usgs":false,"family":"Buchanan","given":"Claire","affiliations":[{"id":39005,"text":"ICPRB","active":true,"usgs":false}],"preferred":false,"id":759531,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nagel, Andrea","contributorId":214281,"corporation":false,"usgs":false,"family":"Nagel","given":"Andrea","email":"","affiliations":[{"id":39005,"text":"ICPRB","active":true,"usgs":false}],"preferred":false,"id":759532,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Young, John A. 0000-0002-4500-3673 jyoung@usgs.gov","orcid":"https://orcid.org/0000-0002-4500-3673","contributorId":3777,"corporation":false,"usgs":true,"family":"Young","given":"John","email":"jyoung@usgs.gov","middleInitial":"A.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":759533,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70263478,"text":"70263478 - 2018 - A proposed seismic velocity profile database model","interactions":[],"lastModifiedDate":"2025-02-12T15:07:57.436066","indexId":"70263478","displayToPublicDate":"2018-12-01T09:00:20","publicationYear":"2018","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"A proposed seismic velocity profile database model","docAbstract":"We describe the data model that we intend to use in a publicly available site profile database under development for the United States. The initial implementation of the database contains data from California. Currently, our prototype data model consists of JavaScript Object Notation (JSON) format files for storing metadata and data. For a site to be included in the database, the minimum metadata requirements are geodetic coordinates and elevation values, and the minimum data requirement is a shear-wave velocity profile. The JSON files are structured in a hierarchal manner to store metadata and data using a nested structure consisting of location, velocity profiles, dispersion curve data (for surface-wave methods), geotechnical data, and horizontal-to-vertical spectral ratios. The database schema at the current stage of the project, and as we continue to develop the data model we will consider including other relevant data, as well as evaluate other file formats to increase the efficiency of data storage and querying. In the current data model, location information includes site geodetic values (latitude, longitude, and elevation) and various site descriptors related to surface geology, geomorphic terrain category, slope gradient at various resolutions, and a geotechnical site category. Velocity data include the geophysical method(s) used to obtain the shear-wave velocity profile, type of data recorded, modeled primary- and shear-wave velocity as a function of depth, modeled profile maximum depth, and the calculated VS30 value. In the case of surface-wave based data, dispersion curve data can be recorded in data structure as phase velocity versus either wavelength or frequency. Geotechnical data includes boring logs penetration resistance, cone penetration test sounding logs, and laboratory index test results. Horizontal-to-vertical spectral ratio plots are given as a function of frequency.
","conferenceTitle":"11th United States National Conference on Earthquake Engineering","conferenceDate":"June 25-29, 2018","conferenceLocation":"Los Angeles, CA","language":"English","publisher":"Earthquake Engineering Research Institute","usgsCitation":"Sadiq, S., Ilkan, O., Ahdi, S.K., Bozorgina, Y., Hashash, Y., Kwak, D., Park, D., Yong, A., and Stewart, J., 2018, A proposed seismic velocity profile database model, 11th United States National Conference on Earthquake Engineering, Los Angeles, CA, June 25-29, 2018, 9 p.","productDescription":"9 p.","ipdsId":"IP-092618","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":481974,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sadiq, Shamsher","contributorId":350844,"corporation":false,"usgs":false,"family":"Sadiq","given":"Shamsher","affiliations":[{"id":83848,"text":"Dept. Civil & Env. Eng., Hanyang Univ.; email: shamshersadi@hanyang.ac.kr","active":true,"usgs":false}],"preferred":false,"id":927112,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ilkan, Okan","contributorId":350848,"corporation":false,"usgs":false,"family":"Ilkan","given":"Okan","affiliations":[{"id":83854,"text":"University of Illinois, Urbana, U.S.A.","active":true,"usgs":false}],"preferred":false,"id":927113,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ahdi, Sean K","contributorId":217355,"corporation":false,"usgs":false,"family":"Ahdi","given":"Sean","email":"","middleInitial":"K","affiliations":[{"id":39605,"text":"Exponent, Inc. and UCLA","active":true,"usgs":false}],"preferred":false,"id":927114,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bozorgina, Yousef","contributorId":271024,"corporation":false,"usgs":false,"family":"Bozorgina","given":"Yousef","email":"","affiliations":[{"id":56148,"text":"University of California, Los Angeles, CA 90095","active":true,"usgs":false}],"preferred":false,"id":927115,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hashash, Youssef M.A.","contributorId":350851,"corporation":false,"usgs":false,"family":"Hashash","given":"Youssef M.A.","affiliations":[{"id":83854,"text":"University of Illinois, Urbana, U.S.A.","active":true,"usgs":false}],"preferred":false,"id":927116,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kwak, Dong Youp","contributorId":350845,"corporation":false,"usgs":false,"family":"Kwak","given":"Dong Youp","affiliations":[{"id":83850,"text":"RMS, Inc., Newark, CA; email: Dongyoup.Kwak@rms.com","active":true,"usgs":false}],"preferred":false,"id":927117,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Park, Duhee","contributorId":350846,"corporation":false,"usgs":false,"family":"Park","given":"Duhee","affiliations":[{"id":83851,"text":"Dept. Civil & Env. Eng., Hanyang Univ.; email: dpark@hanyang.ac.kr","active":true,"usgs":false}],"preferred":false,"id":927118,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Yong, Alan 0000-0003-1807-5847","orcid":"https://orcid.org/0000-0003-1807-5847","contributorId":204730,"corporation":false,"usgs":true,"family":"Yong","given":"Alan","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":927119,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Stewart, Jonathan P.","contributorId":350854,"corporation":false,"usgs":false,"family":"Stewart","given":"Jonathan P.","affiliations":[{"id":83855,"text":"University of California, Los Angeles, U.S.A.","active":true,"usgs":false}],"preferred":false,"id":927120,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70259538,"text":"70259538 - 2018 - A geophysical characterization of the structural framework of the Camas Prairie Geothermal System, southcentral Idaho","interactions":[],"lastModifiedDate":"2024-10-11T13:49:16.719504","indexId":"70259538","displayToPublicDate":"2018-12-01T08:38:45","publicationYear":"2018","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"A geophysical characterization of the structural framework of the Camas Prairie Geothermal System, southcentral Idaho","docAbstract":"Play Fairway Analysis methods, utilizing existing geologic, thermal, geochemical, and geophysical data were employed in an initial assessment of geothermal resources in the Snake River Plain. These efforts identified the Camas Prairie in southcentral Idaho as a region with elevated resource potential. Subsequent efforts included structural and geophysical data collection to identify the most favorable structural settings for exploiting resources in the valley. The present work involved high-resolution gravity, magnetic, magnetotellurics (MT), field mapping, and seismic surveys to further characterize the system and target sites for exploration drilling around Barron’s Hot Springs (BHS) in the southwest part of the valley.
Geophysical mapping and modeling reveal that the BHS coincides with a complex intersection of two major fault systems: a prominent NW-trending system that includes the Pothole fault, and EW-trending basin-bounding faults that control NS-extension. This complex zone includes a dense network of EW-oriented faults and a right stepover in the Pothole fault which, given the dominant dextral-normal to normal slip inferred for this fault, would promote extension in the immediate vicinity of the BHS.
Surface faulting in this region indicate Pleistocene or younger slip, and seismic imaging documents offsets of shallow strata that suggest ongoing activity on these structures. MT modeling results show that this zone also coincides with a prominent conductive anomaly, characteristic of the presence of hydrothermal alteration or hydrothermal fluids. These results point to the importance of these structures in maintaining current and long-lived shallow hydrothermal activity around the BHS.
The detailed structural mapping and conceptual framework developed from this study provide critical constraints for siting a drill hole aimed at documenting reservoir characteristics and informing potential future development of these geothermal resources.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Geothermal's role in today's energy market","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Geothermal Resource Council","usgsCitation":"Glen, J.M., Liberty, L., Peacock, J., Gasperikova, E., Earney, T.E., Schermerhorn, W.D., Siler, D.L., Shervais, J., and Dobson, P., 2018, A geophysical characterization of the structural framework of the Camas Prairie Geothermal System, southcentral Idaho, in Geothermal's role in today's energy market, v. 42, p. 466-481.","productDescription":"16 p.","startPage":"466","endPage":"481","ipdsId":"IP-098962","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":462814,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.geothermal-library.org/index.php?mode=pubs&action=view&record=1033924"},{"id":462825,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Camas Prairie study area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -115.5,\n 43.5\n ],\n [\n -115.5,\n 43.1667\n ],\n [\n -114.5,\n 43.1667\n ],\n [\n -114.5,\n 43.5\n ],\n [\n -115.5,\n 43.5\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"42","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Glen, Jonathan M.G. 0000-0002-3502-3355 jglen@usgs.gov","orcid":"https://orcid.org/0000-0002-3502-3355","contributorId":176530,"corporation":false,"usgs":true,"family":"Glen","given":"Jonathan","email":"jglen@usgs.gov","middleInitial":"M.G.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":915655,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Liberty, Lee","contributorId":345105,"corporation":false,"usgs":false,"family":"Liberty","given":"Lee","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":915656,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peacock, Jared R. 0000-0002-0439-0224","orcid":"https://orcid.org/0000-0002-0439-0224","contributorId":210082,"corporation":false,"usgs":true,"family":"Peacock","given":"Jared R.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":915657,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gasperikova, Erika 0000-0003-1553-4569","orcid":"https://orcid.org/0000-0003-1553-4569","contributorId":345107,"corporation":false,"usgs":false,"family":"Gasperikova","given":"Erika","email":"","affiliations":[{"id":38900,"text":"Lawrence Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":915658,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Earney, Tait E. 0000-0002-1504-0457","orcid":"https://orcid.org/0000-0002-1504-0457","contributorId":210080,"corporation":false,"usgs":true,"family":"Earney","given":"Tait","email":"","middleInitial":"E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":915659,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schermerhorn, William D. 0000-0002-0167-378X","orcid":"https://orcid.org/0000-0002-0167-378X","contributorId":210081,"corporation":false,"usgs":true,"family":"Schermerhorn","given":"William","email":"","middleInitial":"D.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":915660,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Siler, Drew L. 0000-0001-7540-8244","orcid":"https://orcid.org/0000-0001-7540-8244","contributorId":203341,"corporation":false,"usgs":true,"family":"Siler","given":"Drew","email":"","middleInitial":"L.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":915661,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Shervais, John 0000-0003-4370-7500","orcid":"https://orcid.org/0000-0003-4370-7500","contributorId":345109,"corporation":false,"usgs":false,"family":"Shervais","given":"John","email":"","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":915662,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Dobson, Patrick","contributorId":345111,"corporation":false,"usgs":false,"family":"Dobson","given":"Patrick","affiliations":[{"id":38900,"text":"Lawrence Berkeley National Laboratory","active":true,"usgs":false}],"preferred":false,"id":915663,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70259533,"text":"70259533 - 2018 - Geothermal potential of the Umatilla Indian Reservation, Oregon: Evidence from detailed geophysical investigations","interactions":[],"lastModifiedDate":"2024-10-11T13:36:56.07466","indexId":"70259533","displayToPublicDate":"2018-12-01T08:18:40","publicationYear":"2018","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Geothermal potential of the Umatilla Indian Reservation, Oregon: Evidence from detailed geophysical investigations","docAbstract":"Recent geologic and geophysical investigations were undertaken in northeastern Oregon to better assess earthquake hazards in the region and determine relative favorability for geothermal energy development on lands of the Confederated Tribes of the Umatilla Indian Reservation (CTUIR). This work was funded in part by a Bureau of Indian Affairs grant awarded to the CTUIR to identify areas most suitable for further exploration of geothermal resources. Results from this work were utilized as inputs to a geothermal favorability modeling process that led to the identification of target sites for further geothermal investigation. Beyond the geothermal aspect of this project, the region is of great tectonic significance as it marks the intersection of two major physiographic and geophysical features, the Klamath-Blue Mountain lineament (KBL) and Olympic-Wallowa lineament (OWL), inferred to represent major basement boundaries. The Thorn Hollow and Hite faults, which appear to be major linkages between the KBL and OWL, run through the study area.\nNew aeromagnetic, gravity and magnetotelluric (MT) surveying, along with fault analyses, were conducted as part of this effort. Detailed geophysical exploration resulted in the collection of 1,380 new gravity stations, 34,524-line kilometers of aeromagnetic data (covering 12,524 km2) and measurements from 36 MT stations. Two-dimensional (2D) forward-modeling was executed along several profiles using gravity and aeromagnetic data, combined with existing geologic mapping and rock property constraints measured from hand samples and outcrops. These models are used to define lithologic contacts in the subsurface in the absence of well logs or borehole data to determine possible geothermal fluid reservoirs, as well as identify major structures that may act as conduits for the upward migration of geothermal fluids.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Geothermal's role in today's energy market","largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Geothermal Resources Council","usgsCitation":"Ritzinger, B., Glen, J.M., Peacock, J., Blakely, R.J., Mills, P., Staisch, L.M., Bennett, S.E., and Sherrod, B.L., 2018, Geothermal potential of the Umatilla Indian Reservation, Oregon: Evidence from detailed geophysical investigations, in Geothermal's role in today's energy market, v. 42, p. 925-942.","productDescription":"18 p.","startPage":"925","endPage":"942","ipdsId":"IP-098936","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":462823,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.geothermal-library.org/index.php?mode=pubs&action=view&record=1033960"},{"id":462824,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Umatilla Indian Reservation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -118.74244913340956,\n 45.79556361851067\n ],\n [\n -118.7698549962068,\n 45.454060713964566\n ],\n [\n -118.2292120664795,\n 45.454060713964566\n ],\n [\n -118.25910937134924,\n 45.80945769607672\n ],\n [\n -118.74244913340956,\n 45.79556361851067\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"42","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Ritzinger, Brent 0000-0002-5379-1390 britzinger@usgs.gov","orcid":"https://orcid.org/0000-0002-5379-1390","contributorId":216213,"corporation":false,"usgs":true,"family":"Ritzinger","given":"Brent","email":"britzinger@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":915635,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Glen, Jonathan M.G. 0000-0002-3502-3355 jglen@usgs.gov","orcid":"https://orcid.org/0000-0002-3502-3355","contributorId":176530,"corporation":false,"usgs":true,"family":"Glen","given":"Jonathan","email":"jglen@usgs.gov","middleInitial":"M.G.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":915636,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peacock, Jared R. 0000-0002-0439-0224","orcid":"https://orcid.org/0000-0002-0439-0224","contributorId":210082,"corporation":false,"usgs":true,"family":"Peacock","given":"Jared R.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":915637,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Blakely, Richard J. 0000-0003-1701-5236 blakely@usgs.gov","orcid":"https://orcid.org/0000-0003-1701-5236","contributorId":1540,"corporation":false,"usgs":true,"family":"Blakely","given":"Richard","email":"blakely@usgs.gov","middleInitial":"J.","affiliations":[{"id":662,"text":"Western Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":915638,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mills, Patrick","contributorId":345096,"corporation":false,"usgs":false,"family":"Mills","given":"Patrick","email":"","affiliations":[{"id":13345,"text":"Confederated Tribes of the Umatilla Indian Reservation","active":true,"usgs":false}],"preferred":false,"id":915639,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Staisch, Lydia M. 0000-0002-1414-5994 lstaisch@usgs.gov","orcid":"https://orcid.org/0000-0002-1414-5994","contributorId":167068,"corporation":false,"usgs":true,"family":"Staisch","given":"Lydia","email":"lstaisch@usgs.gov","middleInitial":"M.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":915640,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Bennett, Scott E.K. 0000-0002-9772-4122 sekbennett@usgs.gov","orcid":"https://orcid.org/0000-0002-9772-4122","contributorId":5340,"corporation":false,"usgs":true,"family":"Bennett","given":"Scott","email":"sekbennett@usgs.gov","middleInitial":"E.K.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":915641,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Sherrod, Brian L. 0000-0002-4492-8631 bsherrod@usgs.gov","orcid":"https://orcid.org/0000-0002-4492-8631","contributorId":2834,"corporation":false,"usgs":true,"family":"Sherrod","given":"Brian","email":"bsherrod@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":915642,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70199070,"text":"sir20185116 - 2018 - Estimating metal concentrations with regression analysis and water-quality surrogates at nine sites on the Animas and San Juan Rivers, Colorado, New Mexico, and Utah","interactions":[],"lastModifiedDate":"2018-12-03T14:33:08","indexId":"sir20185116","displayToPublicDate":"2018-11-30T17:15:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-5116","title":"Estimating metal concentrations with regression analysis and water-quality surrogates at nine sites on the Animas and San Juan Rivers, Colorado, New Mexico, and Utah","docAbstract":"The purpose of this report is to evaluate the use of site-specific regression models to estimate metal concentrations at nine U.S. Geological Survey streamflow-gaging stations on the Animas and San Juan Rivers in Colorado, New Mexico, and Utah. Downstream users could use these regression models to determine if metal concentrations are elevated and pose a risk to water supplies, agriculture, and recreation. Multiple linear-regression models were developed by relating metal concentrations in discrete water-quality samples to continuously monitored streamflow and surrogate parameters (specific conductance, pH, turbidity, and water temperature) collected at the U.S. Geological Survey stations. Models were developed for dissolved and total concentrations of aluminum, arsenic, cadmium, copper, iron, lead, manganese, and zinc using water-quality samples collected from 2005 to 2017 by several Federal, State, Tribal, and local agencies using different collection methods and analytical laboratories. Model performance varied but, in general, models for dissolved metals did not perform as well as those for total metals. Dissolved metals generally were correlated to specific conductance or streamflow and total metals generally were better correlated with turbidity.
Explanatory variables in the models reflected hydrologic and geochemical processes within the basin. A larger number of regression models were statistically significant for the most upstream sites, where metal concentrations were elevated by drainage from abandoned mines and mineralized bedrock. Models generally did not perform as well at downstream sites, especially for dissolved metals, which occurred at lower concentrations than at the upstream sites. In the lower reaches of the rivers, the input of more alkaline water from tributaries and groundwater reduced metal solubility and diluted metal concentrations. The number and distribution of samples in the calibration datasets also may have been a factor in model development. At some sites on the San Juan River, calibration datasets were more limited and did not represent the full range of observed hydrologic and water-quality conditions, especially during storm events in summer and fall. Recommendations for model use are given based on estimates of model precision, biases, and adequacy of the calibration datasets in terms of the number of samples and representativeness of the observed range of streamflow and water-quality conditions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185116","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Mast, M.A., 2018, Estimating metal concentrations with regression analysis and water-quality surrogates at nine sites on the Animas and San Juan Rivers, Colorado, New Mexico, and Utah: U.S. Geological Survey Scientific Investigations Report 2018–5116, 68 p., https://doi.org/10.3133/sir20185116.","productDescription":"Report: vii, 68 p.; Data release","onlineOnly":"Y","ipdsId":"IP-095270","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":359772,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5116/ofr20185116.pdf","text":"Report","size":"77.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5116"},{"id":359771,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5116/coverthb.jpg"},{"id":359773,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9THSFE0","text":"USGS data release","linkHelpText":"Calibration datasets and model archive summaries for regression models developed to estimate metal concentrations at nine sites on the Animas and San Juan Rivers, Colorado, New Mexico, and Utah"}],"country":"United States","state":"Colorado, New Mexico, Utah","otherGeospatial":"Animas River, San Juan River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110,\n 36.5\n ],\n [\n -107.5,\n 36.5\n ],\n [\n -107.5,\n 38\n ],\n [\n -110,\n 38\n ],\n [\n -110,\n 36.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Colorado Water Science Center
U.S. Geological Survey
Box 25046, MS-415
Denver, CO 80225-0046
The explosive growth of geospatial data has stimulated the development of many standards aimed at decreasing data heterogeneity and enhancing data use. Well-established design methods for geospatial data standards typically involve the creation of two schemas for data structure, designated here as logical and physical, but this can lead to conceptual inconsistencies and modelling inefficiencies. In this paper we describe a design method that overcomes these issues by incorporating an additional schema – the conceptual schema – and demonstrate its application to the design of GroundWaterML2 (GWML2), a new international standard for groundwater data. Results include not only a new data standard, robustly constructed and tested, but also an enhanced method for geospatial data standard design.
","language":"English","publisher":"Springer","doi":"10.1186/s40965-018-0058-3","usgsCitation":"Brodaric, B., Boisvert, E., Dahlhaus, P., Grellet, S., Kmoch, A., Letourneau, F., Lucido, J., Simons, B., and Wagner, B., 2018, The conceptual schema in geospatial data standard design with application to GroundWaterML2: Open Geospatial Data, Software and Standards, v. 3, p. 1-15, https://doi.org/10.1186/s40965-018-0058-3.","productDescription":"15 p.","startPage":"1","endPage":"15","ipdsId":"IP-104677","costCenters":[{"id":39013,"text":"WMA - Project Management Office","active":true,"usgs":true}],"links":[{"id":468224,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40965-018-0058-3","text":"Publisher Index Page"},{"id":362256,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"3","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-11-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Brodaric, Boyan","contributorId":214353,"corporation":false,"usgs":false,"family":"Brodaric","given":"Boyan","email":"","affiliations":[{"id":13092,"text":"Geological Survey of Canada","active":true,"usgs":false}],"preferred":false,"id":759704,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boisvert, Eric","contributorId":167613,"corporation":false,"usgs":false,"family":"Boisvert","given":"Eric","email":"","affiliations":[{"id":24780,"text":"Geological Survey of Canada, Quebec, QC, Canada","active":true,"usgs":false}],"preferred":false,"id":759705,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dahlhaus, Peter","contributorId":214354,"corporation":false,"usgs":false,"family":"Dahlhaus","given":"Peter","email":"","affiliations":[{"id":39014,"text":"Federation University Australia","active":true,"usgs":false}],"preferred":false,"id":759706,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Grellet, Sylvain","contributorId":214355,"corporation":false,"usgs":false,"family":"Grellet","given":"Sylvain","email":"","affiliations":[{"id":39015,"text":"Bureau de Recherche Géologiques et Minières (BRGM)","active":true,"usgs":false}],"preferred":false,"id":759707,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kmoch, Alexander","contributorId":214356,"corporation":false,"usgs":false,"family":"Kmoch","given":"Alexander","email":"","affiliations":[{"id":39016,"text":"University of Salzburg (Z_GIS)","active":true,"usgs":false}],"preferred":false,"id":759708,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Letourneau, Francois","contributorId":214357,"corporation":false,"usgs":false,"family":"Letourneau","given":"Francois","email":"","affiliations":[{"id":13092,"text":"Geological Survey of Canada","active":true,"usgs":false}],"preferred":false,"id":759709,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Lucido, Jessica 0000-0003-2249-4796 jlucido@usgs.gov","orcid":"https://orcid.org/0000-0003-2249-4796","contributorId":214352,"corporation":false,"usgs":true,"family":"Lucido","given":"Jessica","email":"jlucido@usgs.gov","affiliations":[{"id":39013,"text":"WMA - Project Management Office","active":true,"usgs":true}],"preferred":true,"id":759703,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Simons, Bruce","contributorId":214358,"corporation":false,"usgs":false,"family":"Simons","given":"Bruce","email":"","affiliations":[{"id":39017,"text":"CSIRO Land and Water","active":true,"usgs":false}],"preferred":false,"id":759710,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Wagner, Bernhard","contributorId":214359,"corporation":false,"usgs":false,"family":"Wagner","given":"Bernhard","email":"","affiliations":[{"id":39018,"text":"Geological Survey of Bavaria","active":true,"usgs":false}],"preferred":false,"id":759711,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70201809,"text":"70201809 - 2018 - Estimating soil respiration in a subalpine landscape using point, terrain, climate and greenness data","interactions":[],"lastModifiedDate":"2019-01-30T16:10:17","indexId":"70201809","displayToPublicDate":"2018-11-30T15:18:46","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2319,"text":"Journal of Geophysical Research G: Biogeosciences","active":true,"publicationSubtype":{"id":10}},"title":"Estimating soil respiration in a subalpine landscape using point, terrain, climate and greenness data","docAbstract":"Landscape carbon (C) flux estimates are necessary for assessing the ability of terrestrial ecosystems to buffer further increases in anthropogenic carbon dioxide (CO2) emissions. Advances in remote sensing have allowed for coarse-scale estimates of gross primary productivity (GPP) (e.g., MODIS 17), yet efforts to assess spatial patterns in respiration lag behind those of GPP. Here, we demonstrate a method to predict growing season soil respiration at a regional scale in a forested ecosystem. We related field measurements (n=144) of growing season soil respiration across subalpine forests in the Southern Rocky Mountains ecoregion to a suite of biophysical predictors with a Random Forest model (30 m pixel size). We found that Landsat Enhanced Vegetation Index (EVI), growing season AI, temperature, precipitation, elevation, and slope aspect explained spatiotemporal variability in soil respiration. Our model had a psuedo-r2 of 0.45 and root mean squared error (RMSE) of roughly one-quarter of the mean value of respiration. Predicted growing season soil respiration across the region was remarkably consistent across 2004, 2005 and 2006 (150-d averages of 542.8, 544.3, and 536.5 g C m-2, respectively). Yet, we observed substantial variability in spatial patterns of soil respiration predictions that varied between years, suggesting that our method is sensitive to changes in respiration drivers. We compared our estimates to MODIS GPP and nocturnal net ecosystem exchange (NEE) derived from eddy covariance towers as a proxy for ecosystem respiration. Averaged across the predictive region, mean predicted growing season soil respiration was 73% of MODIS GPP, while predicted soil respiration was generally within 20% of nocturnal NEE from eddy covariance towers. This study demonstrated that geospatial and remotely-sensed datasets can be used in a statistical modeling framework to estimate soil respiration at landscape scales.
","language":"English","publisher":"AGU","doi":"10.1029/2018JG004613","usgsCitation":"Berryman, E.M., Vanderhoof, M.K., Bradford, J.B., Hawbaker, T., Henne, P., Burns, S.P., Frank, J.M., Birdsey, R.A., and Ryan, M.G., 2018, Estimating soil respiration in a subalpine landscape using point, terrain, climate and greenness data: Journal of Geophysical Research G: Biogeosciences, v. 123, no. 10, p. 3231-3249, https://doi.org/10.1029/2018JG004613.","productDescription":"19 p.","startPage":"3231","endPage":"3249","ipdsId":"IP-097679","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":437667,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P99TRHPB","text":"USGS data release","linkHelpText":"Data release for estimating soil respiration in a subalpine landscape using point, terrain, climate and greenness data"},{"id":360845,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108,\n 39\n ],\n [\n -104,\n 39\n ],\n [\n -104,\n 41.5\n ],\n [\n -108,\n 41.5\n ],\n [\n -108,\n 39\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"123","issue":"10","noUsgsAuthors":false,"publicationDate":"2018-10-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Berryman, Erin Michele 0000-0001-8699-2474 eberryman@usgs.gov","orcid":"https://orcid.org/0000-0001-8699-2474","contributorId":5765,"corporation":false,"usgs":true,"family":"Berryman","given":"Erin","email":"eberryman@usgs.gov","middleInitial":"Michele","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":755441,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vanderhoof, Melanie K. 0000-0002-0101-5533 mvanderhoof@usgs.gov","orcid":"https://orcid.org/0000-0002-0101-5533","contributorId":168395,"corporation":false,"usgs":true,"family":"Vanderhoof","given":"Melanie","email":"mvanderhoof@usgs.gov","middleInitial":"K.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":755442,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bradford, John B. 0000-0001-9257-6303 jbradford@usgs.gov","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":611,"corporation":false,"usgs":true,"family":"Bradford","given":"John","email":"jbradford@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":755443,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hawbaker, Todd 0000-0003-0930-9154 tjhawbaker@usgs.gov","orcid":"https://orcid.org/0000-0003-0930-9154","contributorId":568,"corporation":false,"usgs":true,"family":"Hawbaker","given":"Todd","email":"tjhawbaker@usgs.gov","affiliations":[{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":755444,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Henne, Paul D. 0000-0003-1211-5545 phenne@usgs.gov","orcid":"https://orcid.org/0000-0003-1211-5545","contributorId":169166,"corporation":false,"usgs":true,"family":"Henne","given":"Paul D.","email":"phenne@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":755445,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Burns, Sean P.","contributorId":98921,"corporation":false,"usgs":true,"family":"Burns","given":"Sean","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":755446,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Frank, John M.","contributorId":11969,"corporation":false,"usgs":true,"family":"Frank","given":"John","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":755447,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Birdsey, Richard A.","contributorId":17751,"corporation":false,"usgs":true,"family":"Birdsey","given":"Richard","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":755448,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Ryan, Michael G.","contributorId":202371,"corporation":false,"usgs":false,"family":"Ryan","given":"Michael","email":"","middleInitial":"G.","affiliations":[{"id":33176,"text":"Rocky Mountain Research Station, USDA Forest Service","active":true,"usgs":false}],"preferred":false,"id":755449,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70201136,"text":"70201136 - 2018 - Sewage loading and microbial risk in urban waters of the Great Lakes","interactions":[],"lastModifiedDate":"2018-11-30T15:08:37","indexId":"70201136","displayToPublicDate":"2018-11-30T15:07:27","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3888,"text":"Elementa: Science of the Anthropocene","active":true,"publicationSubtype":{"id":10}},"title":"Sewage loading and microbial risk in urban waters of the Great Lakes","docAbstract":"Despite modern sewer system infrastructure, the release of sewage from deteriorating pipes and sewer overflows is a major water pollution problem in US cities, particularly in coastal watersheds that are highly developed with large human populations. We quantified fecal pollution sources and loads entering Lake Michigan from a large watershed of mixed land use using host-associated indicators. Wastewater treatment plant influent had stable concentrations of human Bacteroides and human Lachnospiraceae with geometric mean concentrations of 2.77 × 107 and 5.94 × 107 copy number (by quantitative PCR) per 100 ml, respectively. Human-associated indicator levels were four orders of magnitude higher than norovirus concentrations, suggesting that these human-associated bacteria could be sensitive indicators of pathogen risk. Norovirus concentrations in these same samples were used in calculations for quantitative microbial risk assessment. Assuming a typical recreational exposure to untreated sewage in water, concentrations of 7,800 copy number of human Bacteroides per 100 mL or 14,000 copy number of human Lachnospiraceae per 100 mL corresponded to an illness risk of 0.03. These levels were exceeded in estuarine waters during storm events with greater than 5 cm of rainfall. Following overflows from combined sewer systems (which must accommodate both sewage and stormwater), concentrations were 10-fold higher than under rainfall conditions. Automated high frequency sampling allowed for loads of human-associated markers to be determined, which could then be related back to equivalent volumes of untreated sewage that were released. Evidence of sewage contamination decreased as ruminant-associated indicators increased approximately one day post-storm, demonstrating the delayed impact of upstream agricultural sources on the estuary. These results demonstrate that urban areas are a diffuse source of sewage contamination to urban waters and that storm-driven release of sewage, particularly when sewage overflows occur, creates a serious though transient human health risk.
","language":"English","publisher":"University of California Press","doi":"10.1525/elementa.301","usgsCitation":"McLellan, S.L., Sauer, E.P., Corsi, S., Bootsma, M.J., Boehm, A.B., Spencer, S.K., and Borchardt, M.A., 2018, Sewage loading and microbial risk in urban waters of the Great Lakes: Elementa: Science of the Anthropocene, v. 6, p. 1-15, https://doi.org/10.1525/elementa.301.","productDescription":"Article 46; 15 p.","startPage":"1","endPage":"15","ipdsId":"IP-096539","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":468225,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1525/elementa.301","text":"Publisher Index Page"},{"id":359858,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Milwaukee River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.5,\n 42.9\n ],\n [\n -87.835693359375,\n 42.9\n ],\n [\n -87.835693359375,\n 43.7\n ],\n [\n -88.5,\n 43.7\n ],\n [\n -88.5,\n 42.9\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"6","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-20","publicationStatus":"PW","scienceBaseUri":"5c025a68e4b0815414cc782c","contributors":{"authors":[{"text":"McLellan, Sandra L. 0000-0003-3283-1151","orcid":"https://orcid.org/0000-0003-3283-1151","contributorId":210968,"corporation":false,"usgs":false,"family":"McLellan","given":"Sandra","email":"","middleInitial":"L.","affiliations":[{"id":7200,"text":"University of Wisconsin-Milwaukee","active":true,"usgs":false}],"preferred":false,"id":752869,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sauer, Elizabeth P.","contributorId":210969,"corporation":false,"usgs":false,"family":"Sauer","given":"Elizabeth","email":"","middleInitial":"P.","affiliations":[{"id":7200,"text":"University of Wisconsin-Milwaukee","active":true,"usgs":false}],"preferred":false,"id":752870,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Corsi, Steven R. 0000-0003-0583-5536 srcorsi@usgs.gov","orcid":"https://orcid.org/0000-0003-0583-5536","contributorId":172002,"corporation":false,"usgs":true,"family":"Corsi","given":"Steven R.","email":"srcorsi@usgs.gov","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":752868,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bootsma, Melinda J.","contributorId":210970,"corporation":false,"usgs":false,"family":"Bootsma","given":"Melinda","email":"","middleInitial":"J.","affiliations":[{"id":7200,"text":"University of Wisconsin-Milwaukee","active":true,"usgs":false}],"preferred":false,"id":752871,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Boehm, Alexandria B. 0000-0002-8162-5090","orcid":"https://orcid.org/0000-0002-8162-5090","contributorId":210971,"corporation":false,"usgs":false,"family":"Boehm","given":"Alexandria","email":"","middleInitial":"B.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":752872,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Spencer, Susan K.","contributorId":210972,"corporation":false,"usgs":false,"family":"Spencer","given":"Susan","email":"","middleInitial":"K.","affiliations":[{"id":38162,"text":"United States Department of Agriculture Agricultural Research Service","active":true,"usgs":false}],"preferred":false,"id":752873,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Borchardt, Mark A. 0000-0002-6471-2627","orcid":"https://orcid.org/0000-0002-6471-2627","contributorId":210973,"corporation":false,"usgs":false,"family":"Borchardt","given":"Mark","email":"","middleInitial":"A.","affiliations":[{"id":38162,"text":"United States Department of Agriculture Agricultural Research Service","active":true,"usgs":false}],"preferred":false,"id":752874,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70201417,"text":"70201417 - 2018 - Serpentinite‐rich gouge in a creeping segment of the Bartlett Springs Fault, northern California: Comparison with SAFOD and implications for seismic hazard","interactions":[],"lastModifiedDate":"2019-01-28T08:31:21","indexId":"70201417","displayToPublicDate":"2018-11-30T15:03:32","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3524,"text":"Tectonics","active":true,"publicationSubtype":{"id":10}},"title":"Serpentinite‐rich gouge in a creeping segment of the Bartlett Springs Fault, northern California: Comparison with SAFOD and implications for seismic hazard","docAbstract":"An exposure of a creeping segment of the Bartlett Springs Fault (BSF), part of the San Andreas Fault system in northern California, is a ~1.5‐m‐wide zone of serpentinite‐bearing fault gouge cutting through Late Pleistocene fluvial deposits. The fault gouge consists of porphyroclasts of antigorite serpentinite, talc, chlorite, and tremolite‐actinolite, along with some Franciscan metamorphic rocks, in a matrix of the same materials. The Mg‐mineral assemblage is stable at temperatures above 250–300 °C. The BSF gouge is interpreted to have been tectonically incorporated into the fault from depths near the base of the seismogenic zone and to have risen buoyantly to the surface where it is now undergoing right‐lateral displacement. The ultramafic‐rich composition, frictional properties, and inferred mode of emplacement of the BSF serpentinitic gouge correspond to those of the creeping traces of the San Andreas Fault identified in the SAFOD (San Andreas Fault Observatory at Depth) drill hole. This suggests a common origin for creep at both locations. A tectonic model for the source of the ultramafic‐rich materials in the BSF is proposed that potentially could explain the distribution of creep throughout the northernmost San Andreas Fault system.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2018TC005307","usgsCitation":"Moore, D.E., McLaughlin, R., and Lienkaemper, J.J., 2018, Serpentinite‐rich gouge in a creeping segment of the Bartlett Springs Fault, northern California: Comparison with SAFOD and implications for seismic hazard: Tectonics, v. 37, no. 12, p. 4515-4534, https://doi.org/10.1029/2018TC005307.","productDescription":"20 p.","startPage":"4515","endPage":"4534","ipdsId":"IP-092866","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":468226,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2018tc005307","text":"Publisher Index Page"},{"id":437668,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9OUFFKS","text":"USGS data release","linkHelpText":"Data for "Serpentinite-rich Gouge in a Creeping Segment of the Bartlett Springs Fault, Northern California: Comparison with SAFOD and Implications for Seismic Hazard""},{"id":360255,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","volume":"37","issue":"12","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-12-11","publicationStatus":"PW","scienceBaseUri":"5c137dd4e4b006c4f851488c","contributors":{"authors":[{"text":"Moore, Diane E. 0000-0002-8641-1075 dmoore@usgs.gov","orcid":"https://orcid.org/0000-0002-8641-1075","contributorId":2704,"corporation":false,"usgs":true,"family":"Moore","given":"Diane","email":"dmoore@usgs.gov","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":754093,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McLaughlin, Robert J. 0000-0002-4390-2288","orcid":"https://orcid.org/0000-0002-4390-2288","contributorId":211450,"corporation":false,"usgs":true,"family":"McLaughlin","given":"Robert J.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":754094,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lienkaemper, James J. 0000-0002-7578-7042 jlienk@usgs.gov","orcid":"https://orcid.org/0000-0002-7578-7042","contributorId":1941,"corporation":false,"usgs":true,"family":"Lienkaemper","given":"James","email":"jlienk@usgs.gov","middleInitial":"J.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":754095,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70202549,"text":"70202549 - 2018 - A video surveillance system to monitor breeding colonies of common terns (Sterna Hirundo)","interactions":[],"lastModifiedDate":"2019-03-08T15:03:15","indexId":"70202549","displayToPublicDate":"2018-11-30T14:52:35","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2498,"text":"Journal of Visualized Experiments","active":true,"publicationSubtype":{"id":10}},"displayTitle":"A video surveillance system to monitor breeding colonies of common terns (Sterna Hirundo)","title":"A video surveillance system to monitor breeding colonies of common terns (Sterna Hirundo)","docAbstract":"Many waterbird populations have faced declines over the last century, including the common tern (Sterna hirundo), a waterbird species with a widespread breeding distribution, that has been recently listed as endangered in some habitats of its range. Waterbird monitoring programs exist to track populations through time; however, some of the more intensive approaches require entering colonies and can be disruptive to nesting populations. This paper describes a protocol that utilizes a minimally invasive surveillance system to continuously monitor common tern nesting behavior in typical ground-nesting colonies. The video monitoring system utilizes wireless cameras focused on individual nests as well as over the colony as a whole, and allows for observation without entering the colony. The video system is powered with several 12 V car batteries that are continuously recharged using solar panels. Footage is recorded using a digital video recorder (DVR) connected to a hard drive, which can be replaced when full. The DVR may be placed outside of the colony to reduce disturbance. In this study, 3,624 h of footage recorded over 63 days in weather conditions ranging from 12.8 °C to 35.0 °C produced 3,006 h (83%) of usable behavioral data. The types of data retrieved from the recorded video can vary; we used it to detect external disturbances and measure nesting behavior during incubation. Although the protocol detailed here was designed for ground-nesting waterbirds, the principal system could easily be modified to accommodate alternative scenarios, such as colonial arboreal nesting species, making it widely applicable to a variety of research needs.
","language":"English","doi":"10.3791/57928","usgsCitation":"Wall, J., Marban, P., Brinker, D., Sullivan, J., Zimnik, M., Murrow, J., McGowan, P.C., Callahan, C.R., and Prosser, D.J., 2018, A video surveillance system to monitor breeding colonies of common terns (Sterna Hirundo): Journal of Visualized Experiments, v. 137, e57928, https://doi.org/10.3791/57928.","productDescription":"e57928","ipdsId":"IP-093212","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":468227,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.3791/57928","text":"External Repository"},{"id":361902,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"137","noUsgsAuthors":false,"publicationDate":"2018-07-22","publicationStatus":"PW","contributors":{"authors":[{"text":"Wall, J.L.","contributorId":214070,"corporation":false,"usgs":false,"family":"Wall","given":"J.L.","email":"","affiliations":[],"preferred":false,"id":759063,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Marban, Paul 0000-0002-4910-6565 pmarban@usgs.gov","orcid":"https://orcid.org/0000-0002-4910-6565","contributorId":196581,"corporation":false,"usgs":true,"family":"Marban","given":"Paul","email":"pmarban@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":759064,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brinker, D.F.","contributorId":10523,"corporation":false,"usgs":true,"family":"Brinker","given":"D.F.","email":"","affiliations":[],"preferred":false,"id":759065,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sullivan, J.D.","contributorId":214071,"corporation":false,"usgs":false,"family":"Sullivan","given":"J.D.","email":"","affiliations":[],"preferred":false,"id":759066,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zimnik, M.","contributorId":214072,"corporation":false,"usgs":false,"family":"Zimnik","given":"M.","affiliations":[],"preferred":false,"id":759067,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Murrow, J.L.","contributorId":101490,"corporation":false,"usgs":true,"family":"Murrow","given":"J.L.","affiliations":[],"preferred":false,"id":759068,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McGowan, P. C.","contributorId":67191,"corporation":false,"usgs":false,"family":"McGowan","given":"P.","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":759069,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Callahan, Carl R.","contributorId":205289,"corporation":false,"usgs":false,"family":"Callahan","given":"Carl","email":"","middleInitial":"R.","affiliations":[{"id":37073,"text":"USFWS, Annapolis MD","active":true,"usgs":false}],"preferred":false,"id":759070,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Prosser, Diann J. 0000-0002-5251-1799 dprosser@usgs.gov","orcid":"https://orcid.org/0000-0002-5251-1799","contributorId":2389,"corporation":false,"usgs":true,"family":"Prosser","given":"Diann","email":"dprosser@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":759071,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70204264,"text":"70204264 - 2018 - Tidal Wetlands and Estuaries ","interactions":[],"lastModifiedDate":"2019-07-16T14:27:37","indexId":"70204264","displayToPublicDate":"2018-11-30T14:25:59","publicationYear":"2018","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"chapter":"15","title":"Tidal Wetlands and Estuaries ","docAbstract":"1. The top 1 m of tidal wetland soils and estuarine sediments of North America contains 1,886 ± 1046 teragrams of carbon (Tg C). [High confidence, Very likely]
2. Soil carbon accumulation rate (i.e., sediment burial) in North American tidal wetlands is currently 9 ± 5 Tg C per year and estuarine carbon burial is 5 ± 3 Tg C per year. [High confidence, Likely]
3. The lateral flux of carbon from tidal wetlands to estuaries is 16 ± 10 Tg C per year for North America. [Low confidence, Likely]
4. In North America, tidal wetlands remove 27 ± 13 Tg C per year from the atmosphere, estuaries outgas 10 ± 10 Tg C per year to the atmosphere, and the net uptake by the combined wetland-estuary system is 17 ± 16 Tg C per year. [Low confidence, Likely]
5. Research and modeling needs are greatest for understanding responses to accelerated sea level rise, mapping tidal wetland and estuarine extent and quantification of CO2 and CH4 exchange with the atmosphere, especially in large, under-sampled, and rapidly changing regions. [High confidence, Likely]
Note: Confidence levels are provided as appropriate for quantitative, but not qualitative, Key Findings and statements.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Second state of the carbon cycle report (SOCCR2): A sustained assessment report","largerWorkSubtype":{"id":1,"text":"Federal Government Series"},"language":"English","doi":"10.7930/SOCCR2.2018.Ch15","usgsCitation":"Windham-Myers, L., Cai, W.J., Alin, S., Andersson, A., Crosswell, J., Dunton, K., Hernandez-Ayon, J.M., Herrmann, M., Hinson, A.L., Charles Hopkinson, Howard, J., Xinping Hu, Knox, S.H., Kroeger, K., David Lagomasino, Megonigal, P., Najjar, R., Paulsen, M., Dorothy Peteet, Pidgeon, E., Karina Schafer, Elizabeth Watson, Wang, Z.A., and Maria Tzortziou, 2018, Tidal Wetlands and Estuaries , chap. 15 of Second state of the carbon cycle report (SOCCR2): A sustained assessment report, p. 596-648, https://doi.org/10.7930/SOCCR2.2018.Ch15.","productDescription":"53 p.","startPage":"596","endPage":"648","ipdsId":"IP-098391","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":365625,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, Mexico, United States","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Howard, Jennifer","contributorId":149225,"corporation":false,"usgs":false,"family":"Howard","given":"Jennifer","email":"","affiliations":[{"id":17683,"text":"AAAS Science & Technology Policy Fellow/NOAA","active":true,"usgs":false}],"preferred":false,"id":766252,"contributorType":{"id":2,"text":"Editors"},"rank":18},{"text":"Pidgeon, Emily","contributorId":217016,"corporation":false,"usgs":false,"family":"Pidgeon","given":"Emily","email":"","affiliations":[{"id":16938,"text":"Conservation International","active":true,"usgs":false}],"preferred":false,"id":766253,"contributorType":{"id":2,"text":"Editors"},"rank":19}],"authors":[{"text":"Windham-Myers, Lisamarie","contributorId":216999,"corporation":false,"usgs":true,"family":"Windham-Myers","given":"Lisamarie","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":766231,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cai, Wei Jun","contributorId":217000,"corporation":false,"usgs":false,"family":"Cai","given":"Wei","email":"","middleInitial":"Jun","affiliations":[{"id":39556,"text":"U. 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and maintain coupled models of surface water and groundwater. However, developing inputs to these models is usually time-consuming and requires extensive knowledge of software engineering, often prohibiting their use by many researchers and water managers, thus reducing these models' potential to promote science-driven decision-making in an era of global change and increasing water resource stress. In response to this need, we have developed GSFLOW–GRASS, a bundled set of open-source tools that develops inputs for, executes, and graphically displays the results of GSFLOW, the U.S. Geological Survey's coupled groundwater and surface-water flow model. In order to create a robust tool that can be widely implemented over diverse hydro(geo)logic settings, we built a series of GRASS GIS extensions that automatically discretizes a topological surface-water flow network that is linked with an underlying gridded groundwater domain. As inputs, GSFLOW–GRASS requires at a minimum a digital elevation model, a precipitation and temperature record, and estimates of channel parameters and hydraulic conductivity. We demonstrate the broad applicability of the toolbox by successfully testing it in environments with varying degrees of drainage integration, landscape relief, and grid resolution, as well as the presence of irregular coastal boundaries. These examples also show how GSFLOW–GRASS can be implemented to examine the role of groundwater–surface-water interactions in a diverse range of water resource and land management applications.
","language":"English","publisher":"European Geosciences Union","doi":"10.5194/gmd-11-4755-2018","usgsCitation":"Ng, G., Wickert, A.D., Somers, L.D., Saberi, L., Cronkite-Ratcliff, C., Niswonger, R.G., and McKenzie, J.M., 2018, GSFLOW-GRASS v1.0.0: GIS-enabled hydrologic modeling of coupled groundwater–surface-water systems: Geoscientific Model Development, v. 11, p. 4755-4777, https://doi.org/10.5194/gmd-11-4755-2018.","productDescription":"23 p.","startPage":"4755","endPage":"4777","ipdsId":"IP-094852","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":468228,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/gmd-11-4755-2018","text":"Publisher Index Page"},{"id":359917,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-11-30","publicationStatus":"PW","scienceBaseUri":"5c07a063e4b0815414cee77f","contributors":{"authors":[{"text":"Ng, G.-H. 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The importation of surface water beginning in the early 1950s through the Delta-Mendota Canal and in the early 1970s through the California Aqueduct resulted in decreased groundwater pumping, recovery of water levels, and a reduced rate of compaction in some areas of the San Joaquin Valley. However, drought conditions during 1976–77, 1987–92, and drought conditions and operational reductions in surface-water deliveries during 2007–10 decreased surface-water availability, causing pumping to increase, water levels to decline, and renewed compaction. Land subsidence from this compaction has reduced freeboard and flow capacity of the California Aqueduct, Delta-Mendota Canal, and other canals that deliver irrigation water and transport floodwater.
The U.S. Geological Survey, in cooperation with the California Department of Water Resources, assessed more recent land subsidence near a 145-kilometer reach of the California Aqueduct in the west-central part of the San Joaquin Valley as part of an effort to minimize future subsidence-related damages to the California Aqueduct. The location, magnitude, and stress regime of land-surface deformation during 2003–10 were determined by using data and analyses associated with extensometers, Global Positioning System surveys, Interferometric Synthetic Aperture Radar, spirit-leveling surveys, and groundwater wells. Comparison of continuous Global Positioning System, shallow-extensometer, and groundwater-level data indicated that most of the compaction in this area took place beneath the Corcoran Clay, the primary regional confining unit. The integration of measurements strengthens confidence in individual measurement methods and provides the information at spatial and temporal scales that water managers need to design and implement groundwater sustainability plans in compliance with California’s Sustainable Groundwater Management Act.
Measurements of land-surface deformation during 2003–10 indicated that the parts of the California Aqueduct closest to the Coast Ranges in the west-central part of the San Joaquin Valley were fairly stable or minimally subsiding on an annual basis; some areas show seasonal periods of subsidence and uplift that resulted in little or no longer-term elevation loss. Many groundwater levels in these areas did not reach historical lows during 2003–10, indicating that deformation nearest the Coast Ranges was likely primarily elastic.
Land-surface deformation measurements indicated that some parts of the California Aqueduct that traverse farther from the Coast Ranges toward the valley center subsided. Some parts of the California Aqueduct subsided locally, but generally the California Aqueduct is within part of a 12,000-square-kilometer area affected by 25 millimeters or more of subsidence during 2008–10, with maxima in Madera County, south of the town of El Nido near the San Joaquin River and the Eastside Bypass (540 millimeters), and in Tulare County, west of the town of Pixley (345 millimeters). Interferometric Synthetic Aperture Radar-derived subsidence maps for various periods during 2003–10 show that the area of maximum active subsidence (that is, the largest rates of subsidence) shifted from its historical (1926–70) location southwest of the town of Mendota to these areas nearer the valley center. Calculations indicated that the subsidence rate doubled in 2008 in parts of the study area. Water levels declined during 2007–10 in many shallow and deep wells in the most rapidly subsiding areas, where water levels in many deep wells reached their historical lows, indicating that subsidence measured during this period was largely inelastic.
Continued groundwater-level and land-subsidence monitoring in the San Joaquin Valley is important because (1) operational- and drought-related reductions in surface-water deliveries since 1976 have resulted in increased groundwater pumping and associated water-level declines and land subsidence, (2) land use and associated pumping continue to change throughout the valley, and (3) subsidence management is stipulated in the Sustainable Groundwater Management Act. The availability of surface water remains uncertain; even during record-setting precipitation years, such as 2010–11, water deliveries fell short of requests and groundwater pumping was required to meet the irrigation demand. In some areas, the infrastructure is not available to supply surface water, and groundwater is the only source of water. Because of the expected continued demand for water and the limitations and uncertainty of surface-water supplies, groundwater pumping and associated land subsidence remains a concern. Spatially detailed information on land subsidence is needed to minimize future subsidence-related damages to the California Aqueduct and other infrastructure in the San Joaquin Valley, as well as alterations to natural resources such as stream gradients, water depths, and water temperatures. The integration of data on land-surface elevation, subsurface deformation, and water levels—particularly continuous measurements—enables the analysis of aquifer-system response to groundwater pumping, which in turn, enables estimation of the preconsolidation head and calculation of aquifer-system storage properties. This information can be used to improve numerical model simulations of groundwater flow and aquifer-system compaction and allow for consideration of land subsidence in the evaluation of water resource management alternatives and compliance with the Sustainable Groundwater Management Act.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185144","collaboration":"Prepared in cooperation with the California Department of Water Resources","usgsCitation":"Sneed, M., Brandt, J.T., and Solt, M., 2018, Land subsidence along the California Aqueduct in west-central San Joaquin Valley, California, 2003–10: U.S. Geological Survey Scientific Investigations Report 2018–5144, 67 p., https://doi.org/10.3133/sir20185144. ","productDescription":"x, 67 p.","onlineOnly":"Y","ipdsId":"IP-044802","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":437670,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NC9LLL","text":"USGS data release","linkHelpText":"Interferometric Synthetic Aperture Radar-Derived Subsidence Contours for the West-Central San Joaquin Valley, California, 2008-10"},{"id":359739,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5144/sir20185144.pdf","text":"Report","size":"16 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Scientfic Investigations Report 2018-5144"},{"id":359738,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5144/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Joaquin Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.5,\n 35.75\n ],\n [\n -119.5,\n 35.75\n ],\n [\n -119.5,\n 37.5\n ],\n [\n -121.5,\n 37.5\n ],\n [\n -121.5,\n 35.75]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
The U.S. Geological Survey, in cooperation with the Bureau of Reclamation and the Oklahoma Water Resources Board, (1) quantified the groundwater resources of the Rush Springs aquifer in western Oklahoma by developing a numerical groundwater-flow model, (2) evaluated the effects of estimated equal-proportionate-share (EPS) pumping rates on aquifer storage and streamflow for time periods of 20, 40, and 50 years into the future, (3) assessed the uncertainty in the EPS scenario results, and (4) evaluated the effects of (a) projected groundwater-use rates extended 50 years into the future and (b) sustained hypothetical drought conditions over a 10-year period on stream base flow and groundwater in storage.
The Rush Springs aquifer is an important source of water for municipal and irrigation use by many communities and agricultural users in the study area. The study area is composed of about 4,970 square miles (3,181,003 acres) of Rush Springs aquifer bedrock deposits located in 14 counties. The study area also includes the alluvium and terrace deposits of the Canadian and Washita Rivers, as well as alluvium along the Little Washita River, Deer Creek, and a number of smaller tributaries of the Washita River that overlie the bedrock.
A numerical groundwater-flow model of the Rush Springs aquifer was constructed by using MODFLOW with the Newton solver. Groundwater flow was simulated for January 1979–December 2015 by using monthly stress periods, and an initial steady-state stress period was configured to represent mean annual inflows and outflows. The model was calibrated to groundwater-level observations at selected wells, monthly base flow at nine streamgages, stream seepage as estimated for the conceptual water budget, and Fort Cobb Reservoir stage.
The EPS scenarios for the Rush Springs aquifer were run for periods of 20, 40, and 50 years. The 20-, 40-, and 50-year EPS pumping rates under normal recharge conditions were 0.82, 0.49, and 0.43 acre-foot per acre per year, respectively. Given the 2,954,545-acre aquifer area used for the EPS scenarios, the 20-year rate corresponds to an annual yield of about 2,422,727 acre-feet per year. Groundwater storage at the end of the 20-year EPS scenario was about 13,321,000 acre-feet, or about 31,516,437 acre-feet (70 percent) less than the starting EPS scenario storage. This decrease in storage was equivalent to a mean groundwater-level decline of about 152 feet. Water availability under the EPS pumping rate was primarily from the western area of the model. Saturation was sustained though the entire EPS scenario where the aquifer was sufficiently thick or a shallow hydraulic gradient was present. Fort Cobb Reservoir stage was below the dead-pool stage after about 5 years of 20-year EPS pumping.
An uncertainty analysis was conducted to assess the uncertainty in the EPS scenario results. An ensemble of 400 random sets of possible parameter values was performed for the uncertainty analysis by using a multivariate normal distribution centered on the calibrated parameter values. The parameter bounds for the uncertainty analysis were determined by using the posterior covariance matrix, which allows for the incorporation of knowledge gained during the calibration process as well as observation uncertainty and the correlation between estimated parameters. The uncertainty results indicate a 95-percent confidence interval for the 20-year EPS pumping rate between 0.73 and 0.95 acre-foot per acre per year.
Projected 50-year pumping scenarios were used to simulate the effects of selected well withdrawal rates on groundwater storage of the Rush Springs aquifer. The effects of well withdrawals were evaluated by comparing changes in groundwater storage between four 50-year scenarios using (1) no groundwater use, (2) mean groundwater use for the study period (1979–2015), (3) increasing groundwater use, and (4) groundwater use at the 2015 rate. The increasing-use scenario assumed a 38-percent increase in pumping over 50 years on the basis of 2010–60 demand projections for western Oklahoma. Simulated groundwater storage changes ranged between an increase of 6.3 percent for the scenario with no groundwater use, and 0.9 percent for the scenario with 2015 groundwater-use rates. For the Fort Cobb Reservoir surface watershed, simulated groundwater storage changes ranged between an increase of 23.6 percent for the scenario with no groundwater use and a decrease of 4.0 percent for the increasing groundwater-use scenario. Groundwater-level changes were generally greater in areas with a large concentration of groundwater wells and groundwater use such as the Fort Cobb Reservoir surface watershed.
A hypothetical 10-year drought scenario was used to simulate the effects of a prolonged period of reduced recharge on the Rush Springs aquifer groundwater storage and Fort Cobb Reservoir stage and storage. Drought effects were quantified by comparing the results of the drought scenario to those of the calibrated numerical model. To simulate the hypothetical drought, recharge in the calibrated numerical model was reduced by 50 percent during the simulated drought period (1983–1992), and upstream inflows to the Canadian and Washita Rivers and associated tributaries were reduced by 37 percent. Groundwater storage at the end of the hypothetical drought period in December 1992 was about 42,983,000 acre-feet, or about 3,525,000 acre-feet (7.6 percent) less than the groundwater storage of the calibrated numerical model. This change in groundwater storage is equivalent to a mean groundwater-level decline of 15.8 feet. Simulated mean base-flow declines at the Canadian and Washita River streamgages were between 39 and 59 percent during the drought period. The minimum stage in Fort Cobb Reservoir at the end of the hypothetical drought period was 1,311 feet, indicating a storage capacity of only 10 percent of active conservation pool storage. The Fort Cobb Reservoir storage declines mostly resulted from reduced base flows in Cobb, Lake, and Willow Creeks upstream from the reservoir.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185136","collaboration":"Prepared in cooperation with the Bureau of Reclamation and the Oklahoma Water Resources Board","usgsCitation":"Ellis, J.H., 2018, Simulation of groundwater flow and analysis of projected water use for the Rush Springs aquifer, western Oklahoma: U.S. Geological Survey Scientific Investigations Report 2018–5136, 156 p., https://doi.org/10.3133/sir20185136.","productDescription":"Report: xi, 156 p.; Data Release","numberOfPages":"172","onlineOnly":"N","ipdsId":"IP-095386","costCenters":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"links":[{"id":359756,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7Q52NXK","text":"USGS data release","linkHelpText":"MODFLOW model used in simulation of groundwater flow and analysis of projected water use for the Rush Springs aquifer, western Oklahoma"},{"id":359754,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5136/coverthb.jpg"},{"id":359755,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5136/sir20185136.pdf","text":"Report","size":"40.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5136"}],"country":"United States","state":"Oklahoma","otherGeospatial":"Rush Springs Aquifer","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99.75,\n 34.5\n ],\n [\n -97.75,\n 34.5\n ],\n [\n -97.75,\n 36.5\n ],\n [\n -99.75,\n 36.5\n ],\n [\n -99.75,\n 34.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oklahoma Water Science Center
U.S. Geological Survey
202 NW 66th Street, Building 7
Oklahoma City, Oklahoma 73116
An imaging sonar was used to assess the behavior and abundance of fish sized the same as salmonid smolt and bull trout (Salvelinus confluentus) at the entrance to the juvenile fish floating surface collector (FSC) at North Fork Reservoir, Oregon. The purpose of the FSC is to collect downriver migrating juvenile salmonids (Chinook salmon [Oncorhynchus tshawytscha], Coho salmon [Oncorhynchus kisutch], and steelhead [Oncorhynchus mykiss]) at the North Fork Dam and to safely route them around the hydroelectric projects. The objective of the imaging sonar component of this study was to assess the behaviors of both smolt and predator-size fish (smolt [60–250 millimeter] and predator 350–650 [millimeter]) observed near the FSC and to determine if the presence of predator-size fish influenced the abundance of smolt-size fish. An imaging sonar was deployed near the entrance to the FSC during the spring smolt out-migration period. The imaging sonar technology was an informative tool for assessing abundance and spatial and temporal behaviors of both smolt and predator-size fish near the entrance of the FSC. Both smolt and predator-size fish were regularly observed near the entrance, with greater abundances observed during day than during night. Behavioral differences were also observed between the two fish-size classes, with smolt-size fish traveling straighter with more directed movement, and predator-size fish generally showing more milling behavior. Additionally, the presence of predator-size fish may be effecting the abundance and direction of travel of smolt-size fish, as counts of smolt-size fish were reduced in conjunction with the presence of predator-size fish and a greater proportion of smolt-size fish were observed traveling away from the FSC when predator-size fish were present than when predator-size fish were absent. Results of modeling potential predator-prey interactions and influences indicated that both the number of juvenile fish tracks and photoperiod had the strongest effects on the number of predator fish tracks, with more predator-size fish tracks observed as the number of smolt-size fish tracks increased. Overall, the results indicate that predator-size fish are present near the entrance of the FSC, concomitant with smolt-size fish, and their abundances and behaviors indicate that they may be drawn to the entrance of the FSC because of the abundance of prey-sized fish found there.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181182","collaboration":"Prepared in cooperation with Portland General Electric","usgsCitation":"Smith, C.D., Plumb J.M., and Adams, N.S. 2018, Fish behavior and abundance monitoring near a floating surface collector in North Fork Reservoir, Clackamas River, Oregon, using multi-beam acoustic imaging sonar: U.S. Geological Survey Open-File Report 2018-1182, 28 p., https://doi.org/10.3133/ofr20181182.","productDescription":"vi, 28 p.","onlineOnly":"Y","ipdsId":"IP-100791","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":359740,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1182/coverthb2.jpg"},{"id":359741,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1182/ofr20181182.pdf","text":"Report","size":"5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1182"}],"country":"United States","state":"Oregon","otherGeospatial":"North Fork Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.73376464843749,\n 45.0657615477031\n ],\n [\n -121.73263549804688,\n 45.0657615477031\n ],\n [\n -121.73263549804688,\n 45.45724086262233\n ],\n [\n -122.73376464843749,\n 45.45724086262233\n ],\n [\n -122.73376464843749,\n 45.0657615477031\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115
We related Louisiana Waterthrush (Parkesia motacilla) demographic response and nest survival to benthic macroinvertebrate aquatic prey and to shale gas development parameters using models that accounted for both spatial and non-spatial sources of variability in a Central Appalachian USA watershed. In 2013, aquatic prey density and pollution intolerant genera (i.e., pollution tolerance value <4) decreased statistically with increased waterthrush territory length but not in 2014 when territory densities were lower. In general, most demographic responses to aquatic prey were variable and negatively related to aquatic prey in 2013 but positively related in 2014. Competing aquatic prey covariate models to explain nest survival were not statistically significant but differed annually and in general reversed from negative to positive influence on daily survival rate. Potential hydraulic fracturing runoff decreased nest survival both years and was statistically significant in 2014. The EPA Rapid Bioassessment protocol (EPA) and Habitat Suitability Index (HSI) designed for assessing suitability requirements for waterthrush were positively linked to aquatic prey where higher scores increased aquatic prey metrics, but EPA was more strongly linked than HSI and varied annually. While potential hydraulic fracturing runoff in 2013 may have increased Ephemeroptera, Plecoptera, and Trichoptera (EPT) richness, in 2014 shale gas territory disturbance decreased EPT richness. In 2014, intolerant genera decreased at the territory and nest level with increased shale gas disturbance suggesting the potential for localized negative effects on waterthrush. Loss of food resources does not seem directly or solely responsible for demographic declines where waterthrush likely were able to meet their foraging needs. However collective evidence suggests there may be a shale gas disturbance threshold at which waterthrush respond negatively to aquatic prey community changes. Density-dependent regulation of their ability to adapt to environmental change through acquisition of additional resources may also alter demographic response.
","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0206077","usgsCitation":"Frantz, M.W., Wood, P.B., and Merovich, G.T., 2018, Demographic characteristics of an avian predator, Louisiana Waterthrush (Parkesia motacilla), in response to its aquatic prey in a Central Appalachian USA watershed impacted by shale gas development: PLoS ONE, v. 13, no. 11, p. 1-19, https://doi.org/10.1371/journal.pone.0206077.","productDescription":"e0206077, 19 p.","startPage":"1","endPage":"19","ipdsId":"IP-095412","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":468230,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0206077","text":"Publisher Index Page"},{"id":395279,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"West Virginia","otherGeospatial":"Lewis Wetzel Wildlife Management Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.66818714141846,\n 39.514702147872995\n ],\n [\n -80.64299583435057,\n 39.514702147872995\n ],\n [\n -80.64299583435057,\n 39.530790543485786\n ],\n [\n -80.66818714141846,\n 39.530790543485786\n ],\n [\n -80.66818714141846,\n 39.514702147872995\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"11","noUsgsAuthors":false,"publicationDate":"2018-11-28","publicationStatus":"PW","contributors":{"editors":[{"text":"Lightfoot, David A.","contributorId":273594,"corporation":false,"usgs":false,"family":"Lightfoot","given":"David","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":832745,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Frantz, Mack W.","contributorId":272515,"corporation":false,"usgs":false,"family":"Frantz","given":"Mack","email":"","middleInitial":"W.","affiliations":[{"id":12432,"text":"West Virginia University","active":true,"usgs":false}],"preferred":false,"id":832653,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wood, Petra B. 0000-0002-8575-1705 pbwood@usgs.gov","orcid":"https://orcid.org/0000-0002-8575-1705","contributorId":199090,"corporation":false,"usgs":true,"family":"Wood","given":"Petra","email":"pbwood@usgs.gov","middleInitial":"B.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":832652,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Merovich, George T. Jr.","contributorId":172041,"corporation":false,"usgs":false,"family":"Merovich","given":"George","suffix":"Jr.","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":832654,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70227756,"text":"70227756 - 2018 - Influence of river discharge on grass carp occupancy dynamics in south-eastern Iowa rivers","interactions":[],"lastModifiedDate":"2022-01-28T14:42:30.747171","indexId":"70227756","displayToPublicDate":"2018-11-28T08:37:39","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Influence of river discharge on grass carp occupancy dynamics in south-eastern Iowa rivers","docAbstract":"Despite the longstanding presence of grass carp Ctenopharyngodon idella in the Upper Mississippi River (UMR) watershed, information regarding their populations remains largely unknown, in part because capture is difficult. Occupancy models are a popular wildlife assessment tool to account for imperfect detections but have been slow to be adopted in fisheries. Herein, we used occupancy modelling to evaluate the influence of two environmental covariates (river discharge and water temperature) on grass carp occupancy, extinction, colonization, and detection at nine sites within south-eastern Iowa rivers from April to October 2014 and 2015. Grass carp were detected at least once at all but one site. The most parsimonious model indicated that grass carp colonization probability increased from 0.15 to 0.67 with increases in river discharge. In contrast, occupancy (0.20), extinction (0.29), and detection (0.50) probabilities were temporally constant. Models indicated that water temperatures did not influence grass carp extinction or colonization probabilities relative to river discharge. Cumulative grass carp detection probability approached 1.0, whereas conditional occupancy estimates were less than 0.1 when using five or more sampling transects. The use of a robust design occupancy model allowed us to estimate site occupancy rates of grass carp corrected for imperfect detections, while demonstrating the importance of river discharge for site colonization. These results can be used to assess the distribution of a cryptic fish while helping to guide grass carp sampling and removal efforts.
","language":"English","publisher":"Wiley","doi":"10.1002/rra.3385","usgsCitation":"Sullivan, C.J., Weber, M., Pierce, C., and Camacho, C.A., 2018, Influence of river discharge on grass carp occupancy dynamics in south-eastern Iowa rivers: River Research and Applications, v. 35, no. 1, p. 60-67, https://doi.org/10.1002/rra.3385.","productDescription":"8 p.","startPage":"60","endPage":"67","ipdsId":"IP-090729","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":502456,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://lib.dr.iastate.edu/nrem_pubs/296","text":"External Repository"},{"id":395045,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.24072265625,\n 40.17887331434696\n ],\n [\n -90.54931640625,\n 40.17887331434696\n ],\n [\n -90.54931640625,\n 42.65012181368022\n ],\n [\n -94.24072265625,\n 42.65012181368022\n ],\n [\n -94.24072265625,\n 40.17887331434696\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"35","issue":"1","noUsgsAuthors":false,"publicationDate":"2018-11-28","publicationStatus":"PW","contributors":{"editors":[{"text":"Weber, Michael J.","contributorId":272530,"corporation":false,"usgs":false,"family":"Weber","given":"Michael J.","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":832053,"contributorType":{"id":2,"text":"Editors"},"rank":2}],"authors":[{"text":"Sullivan, Christopher J.","contributorId":272528,"corporation":false,"usgs":false,"family":"Sullivan","given":"Christopher","email":"","middleInitial":"J.","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":832051,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Weber, Michael J.","contributorId":272530,"corporation":false,"usgs":false,"family":"Weber","given":"Michael J.","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":832102,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pierce, Clay 0000-0001-5088-5431 cpierce@usgs.gov","orcid":"https://orcid.org/0000-0001-5088-5431","contributorId":150492,"corporation":false,"usgs":true,"family":"Pierce","given":"Clay","email":"cpierce@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":832050,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Camacho, Carlos A.","contributorId":272529,"corporation":false,"usgs":false,"family":"Camacho","given":"Carlos","email":"","middleInitial":"A.","affiliations":[{"id":6911,"text":"Iowa State University","active":true,"usgs":false}],"preferred":false,"id":832052,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70250181,"text":"70250181 - 2018 - Sediment transport model including short-lived radioisotopes: Model description and idealized test cases","interactions":[],"lastModifiedDate":"2023-11-28T11:54:23.3422","indexId":"70250181","displayToPublicDate":"2018-11-27T11:27:26","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2380,"text":"Journal of Marine Science and Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Sediment transport model including short-lived radioisotopes: Model description and idealized test cases","docAbstract":"Geochronologies derived from sediment cores in coastal locations are often used to infer event bed characteristics such as deposit thicknesses and accumulation rates. Such studies commonly use naturally occurring, short-lived radioisotopes, such as Beryllium-7 (7Be) and Thorium-234 (234Th), to study depositional and post-depositional processes. These radioisotope activities, however, are not generally represented in sediment transport models that characterize coastal flood and storm deposition with grain size patterns and deposit thicknesses. We modified the Community Sediment Transport Modeling System (CSTMS) to account for reactive tracers and used this capability to represent the behavior of these short-lived radioisotopes on the sediment bed. This paper describes the model and presents results from a set of idealized, one-dimensional (vertical) test cases. The model configuration represented fluvial deposition followed by periods of episodic storm resuspension. Sensitivity tests explored the influence on seabed radioisotope profiles by the intensities of bioturbation and wave resuspension and the thickness of fluvial deposits. The intensity of biodiffusion affected the persistence of fluvial event beds as evidenced by 7Be. Both resuspension and biodiffusion increased the modeled seabed inventory of 234Th. A thick fluvial deposit increased the seabed inventory of 7Be and 234Th but mixing over time greatly reduced the difference in inventory of 234Th in fluvial deposits of different thicknesses.
","language":"English","publisher":"MDPI","doi":"10.3390/jmse6040144","usgsCitation":"Birchler, J.J., Harris, C.K., Sherwood, C.R., and Kniskern, T.A., 2018, Sediment transport model including short-lived radioisotopes: Model description and idealized test cases: Journal of Marine Science and Engineering, v. 6, no. 4, p. 1-17, https://doi.org/10.3390/jmse6040144.","productDescription":"144, 17 p.","startPage":"1","endPage":"17","ipdsId":"IP-094563","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468231,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/jmse6040144","text":"Publisher Index Page"},{"id":422975,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","issue":"4","noUsgsAuthors":false,"publicationDate":"2018-11-27","publicationStatus":"PW","contributors":{"authors":[{"text":"Birchler, Justin J. 0000-0002-0379-2192 jbirchler@usgs.gov","orcid":"https://orcid.org/0000-0002-0379-2192","contributorId":169117,"corporation":false,"usgs":true,"family":"Birchler","given":"Justin","email":"jbirchler@usgs.gov","middleInitial":"J.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":888694,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Harris, Courtney K.","contributorId":19620,"corporation":false,"usgs":false,"family":"Harris","given":"Courtney","email":"","middleInitial":"K.","affiliations":[{"id":6708,"text":"Virginia Institute of Marine Science","active":true,"usgs":false}],"preferred":false,"id":888695,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sherwood, Christopher R. 0000-0001-6135-3553 csherwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6135-3553","contributorId":2866,"corporation":false,"usgs":true,"family":"Sherwood","given":"Christopher","email":"csherwood@usgs.gov","middleInitial":"R.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":888696,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kniskern, Tara A","contributorId":202170,"corporation":false,"usgs":false,"family":"Kniskern","given":"Tara","email":"","middleInitial":"A","affiliations":[{"id":36356,"text":"Virginia Institute of Marine Science, College of William & Mary","active":true,"usgs":false}],"preferred":false,"id":888697,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70199945,"text":"sir20185134 - 2018 - Modeling hydrodynamics, water temperature, and water quality in Klamath Straits Drain, Oregon and California, 2012–15","interactions":[],"lastModifiedDate":"2018-11-27T10:58:23","indexId":"sir20185134","displayToPublicDate":"2018-11-26T15:04:48","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-5134","displayTitle":"Modeling Hydrodynamics, Water Temperature, and Water Quality in Klamath Straits Drain, Oregon and California, 2012–15","title":"Modeling hydrodynamics, water temperature, and water quality in Klamath Straits Drain, Oregon and California, 2012–15","docAbstract":"Located southwest of Klamath Falls, Oregon, Klamath Straits Drain is a 10.1-mile-long canal that conveys water uphill and northward through the use of pumps before discharging to the Klamath River. Klamath Straits Drain traverses an area that historically encompassed Lower Klamath Lake. Currently, the Drain receives water from farmland and from parts of the Lower Klamath Lake National Wildlife Refuge. To support water-quality improvement in Klamath Straits Drain, a hydrodynamic and water-temperature model was constructed and calibrated for calendar years 2012–15 with the two-dimensional model CE-QUAL-W2 (version 4.0). Water quality was calibrated for a subset of that time, from April 1, 2012 to March 31, 2015. Flows in calendar year 2012 were within the normal range, while calendar years 2013–15 were dry years. Significant findings from this study include:
This newly constructed model of the Klamath Straits Drain simulates flow, water levels, water temperature, and water quality with acceptable accuracy but with certain data limitations. This model should prove useful in evaluating potential strategies for flow and water-quality management and restoration.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185134","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Sullivan, A.B., and Rounds, S.A., 2018, Modeling hydrodynamics, water temperature, and water quality in Klamath Straits Drain, Oregon and California, 2012–15: U.S. Geological Survey Scientific Investigations Report 2018-5134, 30 p., https://doi.org/10.3133/sir20185134.","productDescription":"vii, 30 p.","onlineOnly":"Y","ipdsId":"IP-099157","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":359688,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5134/coverthb.jpg"},{"id":359690,"rank":3,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://or.water.usgs.gov/proj/keno_reach/models.html","text":"Klamath Straits Models —","description":"SIR 2018-5134 Klamath Straits Model","linkHelpText":"Water-Quality Monitoring and Modeling of the Keno Reach of the Klamath River"},{"id":359689,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5134/sir20185134.pdf","text":"Report","size":"8.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5134"}],"country":"United States","state":"California, Oregon","otherGeospatial":"Klamath Straits Drain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122,\n 41.8333\n ],\n [\n -121.5,\n 41.8333\n ],\n [\n -121.5,\n 42.33\n ],\n [\n -122,\n 42.33\n ],\n [\n -122,\n 41.8333\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201