Surveys of environmental DNA (eDNA) have become an important and multifaceted tool for monitoring and identifying distributions and occupancy of aquatic species. This tool is attractive because it is powerful, easy to apply, and provides an alternative to traditional field survey methods. However, validating eDNA survey methods against traditional field survey methods is warranted prior to their application. We used eDNA and electrofishing to survey 10 sites in 3 tributaries of the Chehalis River, Washington, to infer distribution and occupancy of Entosphenus tridentatus and Lampetra spp. Both methods produced similar detection rates for E. tridentatus, and Lampetra spp. were detected at slightly greater frequency with eDNA in the Black River and Skookumchuck River. Within each of the three tributaries, eDNA concentration was negatively related to sample distance from the Chehalis River mainstem for E. tridentatus but not for Lampetra spp., which indicates E. tridentatus and Lampetra spp. may be distributed differently within tributaries. Application of lamprey eDNA data to a multiscale occupancy model indicated high probability of detecting eDNA in water samples and quantitative PCR (qPCR) assays. Broad distribution and high detection of E. tridentatus and Lampetra spp. suggest robust populations inhabit the Chehalis River basin. Our findings suggest eDNA surveys may be comparable to electrofishing for informing lamprey occupancy and distributions. Such sampling is efficient and cost‐effective and we anticipate that eDNA surveys will become a valuable tool in addressing key research and monitoring needs for conservation and restoration of lampreys in general.
The 1994 Northridge earthquake generated world-record ground motions. At the time, the horizontal peak ground acceleration of 1.8 g measured by a seismometer in Tarzana was the largest ever. The same is true of the peak ground velocity of 148 cm/s measured in Granada Hills. Both measurements were within approximately 15 km of the source of the earthquake; they were also near most of the damage described in other articles of this series. Consequently, the near-source design forces from the seismic zone maps in the Uniform Building Code (UBC) were increased. From the 1994 to 1997 editions, acceleration- and velocity-related near-source factors were introduced. The factors increased the design forces in Zone 4, already the highest seismic zone, by a multiplier as large as 2.0. More enduringly, generational changes were made to the seismic design maps in the NEHRP Recommended Seismic Provisions for New Buildings and Other Structures. The NEHRP maps were – and continue to be – adopted into the International Building Code (IBC), which supplanted the UBC and other model building codes. As described below, the changes to the NEHRP maps took advantage of another post-Northridge change: the modern generation of U.S. Geological Survey (USGS) National Seismic Hazard Maps.
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refuges","interactions":[],"lastModifiedDate":"2020-12-14T17:53:28.904407","indexId":"70209570","displayToPublicDate":"2019-06-30T11:52:13","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"seriesTitle":{"id":7461,"text":"Final Project Memorandum","active":true,"publicationSubtype":{"id":9}},"title":"Climate change adaptation for coastal national wildlife refuges","docAbstract":"National Wildlife Refuges (NWRs) along the East Coast of the United States protect habitat for a host of wildlife species, while also offering storm surge protection, improving water quality, supporting nurseries for commercially important fish and shellfish, and providing recreation opportunities for coastal communities. Yet in the last century, coastal ecosystems in the eastern U.S. have been severely altered by human development activities as well as sea-level rise and more frequent extreme events related to climate change. These influences threaten the ability of NWRs to protect our nation’s natural resources and to sustain their many beneficial services.
Through this project, researchers are collaborating with managers of the North Carolina Coastal Refuges Complex, Cape Romain NWR, South Carolina, and other local interested partners to assist with their long-term planning under uncertain conditions regarding sea-level rise and other global change processes. Researchers are using a variety of state-of-the-art approaches, including formal decision science for systematically analyzing management alternatives and scenario planning methods for engaging with stakeholders to explore possible futures. These approaches are aimed at helping NWR staff develop management objectives, identify and weigh potential management actions for adaptation, and generate decision-support tools and models. Outcomes and products from these efforts will aid managers as they plan for and adapt to the complex challenges facing the NWR system as changing climate and other conditions make their work increasingly more difficult.
","language":"English","publisher":"Southeast Climate Adaptation Science Center","usgsCitation":"Eaton, M.J., Costanza, J.K., Johnson, F.A., Martin, J., and Taylor, L., 2019, Climate change adaptation for coastal national wildlife refuges: Final Project Memorandum, 12 p.","productDescription":"12 p.","ipdsId":"IP-115967","costCenters":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true},{"id":40926,"text":"Southeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":381264,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":381263,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://cascprojects.org/#/project/4f8c6557e4b0546c0c397b4c/553fddf0e4b0a658d7938ef5"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Eaton, Mitchell J. 0000-0001-7324-6333","orcid":"https://orcid.org/0000-0001-7324-6333","contributorId":213526,"corporation":false,"usgs":true,"family":"Eaton","given":"Mitchell","middleInitial":"J.","affiliations":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":786933,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Costanza, Jennifer K.","contributorId":176907,"corporation":false,"usgs":false,"family":"Costanza","given":"Jennifer","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":786934,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Fred A 0000-0002-5854-3695","orcid":"https://orcid.org/0000-0002-5854-3695","contributorId":224058,"corporation":false,"usgs":false,"family":"Johnson","given":"Fred","email":"","middleInitial":"A","affiliations":[{"id":37318,"text":"Aarhus University","active":true,"usgs":false}],"preferred":false,"id":786935,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Martin, Julien 0000-0002-7375-129X","orcid":"https://orcid.org/0000-0002-7375-129X","contributorId":218445,"corporation":false,"usgs":true,"family":"Martin","given":"Julien","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":786936,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Taylor, Laura","contributorId":224059,"corporation":false,"usgs":false,"family":"Taylor","given":"Laura","affiliations":[{"id":25510,"text":"NC State University","active":true,"usgs":false}],"preferred":false,"id":786937,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70227825,"text":"70227825 - 2019 - Evaluation of a microsatellite panel for use across North American populations of white-tailed deer (Odocoileus virginianus)","interactions":[],"lastModifiedDate":"2022-02-02T14:38:48.7666","indexId":"70227825","displayToPublicDate":"2019-06-30T11:51:28","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10076,"text":"BMC Genetics","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Evaluation of a microsatellite panel for use across North American populations of white-tailed deer (Odocoileus virginianus)","title":"Evaluation of a microsatellite panel for use across North American populations of white-tailed deer (Odocoileus virginianus)","docAbstract":"Background Microsatellite loci have been used extensively over the past two decades to study the genetic characteristics of non-model species. The relative ease of microsatellite development and ability to adapt markers from related species has led to the proliferation of available markers, particularly for those species that are intensively studied and managed. Because it is often infeasible to genotype individuals across all available loci, researchers generally rely on subsets of markers. Marker choice and genotyping errors can bias inferences made using disparate suites of microsatellite loci. This can limit comparative and collaborative efforts among research groups and has been a primary motivation for panel standardization efforts. Here, we develop a methodology for identifying a suite of markers from previous literature that can be generalizable across the range of commonly studied organisms. We specifically focus on producing a broadly applicable microsatellite panel for white-tailed deer (Odocoileus virginianus). Results We reviewed microsatellite panels from 58 previous or ongoing projects and identified a total of 106 candidate loci. We developed a multiplex protocol and evaluated the efficacy of 17 of the most commonly used loci using 720 DNA samples collected from the Mid-Atlantic region of the United States, an area where few previous studies were conducted. Amplification errors were detected in six of these loci. The properties of the remaining 11 loci suggest that they are applicable for many common research objectives. Specifically, this panel is highly polymorphic (eight to 20 alleles per locus, polymorphic information criterion = 0.492 to 0.917), exhibits low frequencies of genotyping errors (null alleles < 10%), and is relatively easy to interpret with the aid of allele binning software. Conclusions We were able to identify a panel of microsatellite markers that show potential for broad applicability over the geographic range of white-tailed deer, as evidenced by the distribution of previous studies that utilized them. Validation in an additional region confirmed this. These results suggest that marker standardization and evaluation procedures based on literature reviews offers an effective method for identifying consolidated panels for future studies. This simple procedure addresses previous concerns about the infeasibility of standardization efforts.
","language":"English","doi":"10.1186/s12863-019-0750-z","usgsCitation":"Miller, W.L., Edson, J., Pietrandrea, P., Cassandra Miller-Butterworth, and Walter, W., 2019, Evaluation of a microsatellite panel for use across North American populations of white-tailed deer (Odocoileus virginianus): BMC Genetics, v. 20, no. 1, 49, 14 p., https://doi.org/10.1186/s12863-019-0750-z.","productDescription":"49, 14 p.","ipdsId":"IP-099036","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":467494,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s12863-019-0750-z","text":"Publisher Index Page"},{"id":395250,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland, Pennsylvania, Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.7607421875,\n 38.805470223177466\n ],\n [\n -76.4208984375,\n 38.805470223177466\n ],\n [\n -76.4208984375,\n 41.178653972331674\n ],\n [\n -79.7607421875,\n 41.178653972331674\n ],\n [\n -79.7607421875,\n 38.805470223177466\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"20","issue":"1","noUsgsAuthors":false,"publicationDate":"2019-06-06","publicationStatus":"PW","contributors":{"authors":[{"text":"Miller, William L.","contributorId":272898,"corporation":false,"usgs":false,"family":"Miller","given":"William","email":"","middleInitial":"L.","affiliations":[{"id":6975,"text":"Penn State","active":true,"usgs":false}],"preferred":false,"id":832375,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Edson, Jessie","contributorId":272899,"corporation":false,"usgs":false,"family":"Edson","given":"Jessie","email":"","affiliations":[{"id":6975,"text":"Penn State","active":true,"usgs":false}],"preferred":false,"id":832376,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pietrandrea, Peter","contributorId":272902,"corporation":false,"usgs":false,"family":"Pietrandrea","given":"Peter","email":"","affiliations":[{"id":56403,"text":"Penn State","active":true,"usgs":false}],"preferred":false,"id":832377,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cassandra Miller-Butterworth","contributorId":272903,"corporation":false,"usgs":false,"family":"Cassandra Miller-Butterworth","affiliations":[{"id":6975,"text":"Penn State","active":true,"usgs":false}],"preferred":false,"id":832378,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Walter, W. 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In 2017, the IWG adopted an Interim Harvest Strategy consisting of a constant harvest rate (on adults) of 3% for the Central Management Unit (MU) of Taiga Bean Geese. The interim strategy is intended to provide limited hunting opportunity while rebuilding the population. Based on a January count of 41,927, the harvest quota for the 2019 hunting season is 1,740 Taiga Bean Geese (compared to 2,335 and 1,610 for the 2017 and 2018 seasons, respectively). We emphasize that these quotas include both, harvest during the regular season and derogation shooting. Going forward, we describe how an Integrated Population Model (IPM) will use counts at multiple times during the year, along with other demographic information, to estimate population size (and its precision). The IPM can be used to develop an adaptive harvest strategy if unambiguous management objectives can be agreed upon. We provide some initial guidance for formulating those objectives.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"AEWA European Goose Management Platform","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"4th Meeting of the AEWA European Goose Management International Working Group","conferenceDate":"18-20 June, 2019","conferenceLocation":"Perth, Scotland, United Kingdom","language":"English","publisher":"Scottish National Heritage","usgsCitation":"Johnson, F., Heldbjerg, H., Alhainen, M., and Madsen, J., 2019, Harvest assessment for Taiga bean geese in the Central Management Unit: 2019, in AEWA European Goose Management Platform, Perth, Scotland, United Kingdom, 18-20 June, 2019.","productDescription":"10 p.","startPage":"1-10","ipdsId":"IP-108160","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":365985,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":365961,"type":{"id":15,"text":"Index Page"},"url":"https://egmp.aewa.info/meetings/iwg/detail/4th-meeting-aewa-european-goose-management-international-working-group-egm-iwg-4"}],"publicComments":"Document AEWA/EGMIWG/4.10","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Johnson, Fred 0000-0002-5854-3695","orcid":"https://orcid.org/0000-0002-5854-3695","contributorId":217602,"corporation":false,"usgs":true,"family":"Johnson","given":"Fred","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":767153,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Heldbjerg, Henning","contributorId":174479,"corporation":false,"usgs":false,"family":"Heldbjerg","given":"Henning","email":"","affiliations":[],"preferred":false,"id":767154,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Alhainen, Mikko","contributorId":141140,"corporation":false,"usgs":false,"family":"Alhainen","given":"Mikko","email":"","affiliations":[{"id":13690,"text":"Finnish Wildlife Agency","active":true,"usgs":false}],"preferred":false,"id":767155,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Madsen, Jesper","contributorId":178168,"corporation":false,"usgs":false,"family":"Madsen","given":"Jesper","email":"","affiliations":[],"preferred":false,"id":767156,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70212624,"text":"70212624 - 2019 - Refining the Baseline Sediment Budget for the Klamath River, California","interactions":[],"lastModifiedDate":"2022-01-11T17:32:19.904133","indexId":"70212624","displayToPublicDate":"2019-06-30T10:39:35","publicationYear":"2019","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Refining the Baseline Sediment Budget for the Klamath River, California","docAbstract":"Four dams in the Klamath River Hydroelectric Project (KHP) in Oregon and California (Figure 1) are currently scheduled to be removed over a period of a few weeks or months, beginning in January 2021. The Klamath dam removal will be the largest in the world by almost all measures, and is an unprecedented opportunity to advance science of river responses to such events. The KHP contains approximately 10-12 million cubic meters of mostly fine sediment and model estimates suggest approximately 1/3-2/3 of this volume is expected to be eroded from reservoirs. Much of this sediment is expected to be eventually transported by the river to, or through, the Klamath River Estuary, a distance of more than 300 kilometers. To improve the success of restoration activities following dam removal, agencies must understand the baseline conditions for biological, chemical, and physical processes, prior to the removal. We expect large changes in water quality (turbidity, suspended sediment, dissolved oxygen, temperature, and algal toxins) and in fish habitat in the Hydroelectric Reach and the main-stem of the Klamath River to the ocean. For example, modeled sediment concentrations in the Klamath River during dam removal were estimated exceed 10,000 – 15,000 mg/L, depending on streamflows, location, and the dam removal process, and to remain > 100 – 1000 mg/L for months at a time. Final time to achieve background concentrations post dam removal may take over two years (Reclamation, 2011). Plans to assess many of these changes post-dam removal are still being formulated.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of SEDHYD 2019","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"SEDHYD 2019 Conference","conferenceDate":"Jun 24-28, 2019","conferenceLocation":"Reno, NV","language":"English","publisher":"Federal Interagency Sedimentation Conference (FISC) and Federal Interagency Hydrologic Modeling Conference (FIHMC)","usgsCitation":"Anderson, C.W., Wright, S., Schenk, L.N., Skalak, K., Curtis, J., East, A.E., and Benthem, A.J., 2019, Refining the Baseline Sediment Budget for the Klamath River, California, in Proceedings of SEDHYD 2019, v. 5, Reno, NV, Jun 24-28, 2019, 4 p.","productDescription":"4 p.","ipdsId":"IP-105518","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":377828,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":377827,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.sedhyd.org/2019/openconf/modules/request.php?module=oc_proceedings&action=proceedings.php&a=Accept"}],"country":"United States","state":"California, Oregon","otherGeospatial":"Klamath River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.49069213867188,\n 41.899210607606115\n ],\n [\n -121.83563232421875,\n 41.899210607606115\n ],\n [\n -121.83563232421875,\n 42.157295553651664\n ],\n [\n -122.49069213867188,\n 42.157295553651664\n ],\n [\n -122.49069213867188,\n 41.899210607606115\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"5","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Anderson, Chauncey W. 0000-0002-1016-3781 chauncey@usgs.gov","orcid":"https://orcid.org/0000-0002-1016-3781","contributorId":140160,"corporation":false,"usgs":true,"family":"Anderson","given":"Chauncey","email":"chauncey@usgs.gov","middleInitial":"W.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":797165,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wright, Scott 0000-0002-0387-5713 sawright@usgs.gov","orcid":"https://orcid.org/0000-0002-0387-5713","contributorId":1536,"corporation":false,"usgs":true,"family":"Wright","given":"Scott","email":"sawright@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":797166,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schenk, Liam N. 0000-0002-2491-0813 lschenk@usgs.gov","orcid":"https://orcid.org/0000-0002-2491-0813","contributorId":4273,"corporation":false,"usgs":true,"family":"Schenk","given":"Liam","email":"lschenk@usgs.gov","middleInitial":"N.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":797167,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Skalak, Katherine 0000-0003-4122-1240 kskalak@usgs.gov","orcid":"https://orcid.org/0000-0003-4122-1240","contributorId":3990,"corporation":false,"usgs":true,"family":"Skalak","given":"Katherine","email":"kskalak@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":797168,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Curtis, Jennifer A. 0000-0001-7766-994X","orcid":"https://orcid.org/0000-0001-7766-994X","contributorId":239547,"corporation":false,"usgs":true,"family":"Curtis","given":"Jennifer A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":797169,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"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":797170,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Benthem, Adam J. 0000-0003-2372-0281","orcid":"https://orcid.org/0000-0003-2372-0281","contributorId":220000,"corporation":false,"usgs":true,"family":"Benthem","given":"Adam","middleInitial":"J.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":797171,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70204481,"text":"70204481 - 2019 - Hawai‘i Groundwater Recharge Tool","interactions":[],"lastModifiedDate":"2019-12-03T09:36:08","indexId":"70204481","displayToPublicDate":"2019-06-30T09:32:07","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":9,"text":"Other Report"},"title":"Hawai‘i Groundwater Recharge Tool","docAbstract":"The Hawai‘i Groundwater Recharge Tool allows users to evaluate the potential effects of land-cover and climate changes on groundwater recharge. This website provides a baseline estimate of recharge representing recent conditions of precipitation (1978–2008 average) and land cover (2010). Users can change land cover and rainfall conditions to evaluate the effects on groundwater recharge. Results will be displayed as on-screen maps, and users will be given options to generate interpretive graphics or export results in various formats. Results from this website are based on soil water-balance models. This is a pilot website that is currently limited to the island of O‘ahu, but the website has been designed to be expandable so that other islands and conditions can be added in the future.","language":"English","publisher":"University of Hawaii","usgsCitation":"McLean, J.H., Rotzoll, K., Cleaveland, S.B., and Izuka, S.K., 2019, Hawai‘i Groundwater Recharge Tool, HTML Document.","productDescription":"HTML Document","ipdsId":"IP-104867","costCenters":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"links":[{"id":369857,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":365986,"rank":1,"type":{"id":18,"text":"Project Site"},"url":"https://recharge.ikewai.org/#/workspace"}],"country":"United States","state":"Hawaii","otherGeospatial":"Oahu","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -158.33496093749997,\n 21.210019282760218\n ],\n [\n -157.62359619140625,\n 21.210019282760218\n ],\n [\n -157.62359619140625,\n 21.728885873951494\n ],\n [\n -158.33496093749997,\n 21.728885873951494\n ],\n [\n -158.33496093749997,\n 21.210019282760218\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McLean, Jared H.","contributorId":217618,"corporation":false,"usgs":false,"family":"McLean","given":"Jared","email":"","middleInitial":"H.","affiliations":[{"id":37291,"text":"University of Hawaii at Hilo","active":true,"usgs":false}],"preferred":false,"id":767179,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rotzoll, Kolja 0000-0002-5910-888X kolja@usgs.gov","orcid":"https://orcid.org/0000-0002-5910-888X","contributorId":3325,"corporation":false,"usgs":true,"family":"Rotzoll","given":"Kolja","email":"kolja@usgs.gov","affiliations":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"preferred":false,"id":767180,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cleaveland, Sean B.","contributorId":217619,"corporation":false,"usgs":false,"family":"Cleaveland","given":"Sean","email":"","middleInitial":"B.","affiliations":[{"id":39036,"text":"University of Hawaii at Manoa","active":true,"usgs":false}],"preferred":false,"id":767181,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Izuka, Scot K. 0000-0002-8758-9414 skizuka@usgs.gov","orcid":"https://orcid.org/0000-0002-8758-9414","contributorId":2645,"corporation":false,"usgs":true,"family":"Izuka","given":"Scot","email":"skizuka@usgs.gov","middleInitial":"K.","affiliations":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"preferred":true,"id":767178,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70202422,"text":"70202422 - 2019 - Forecasts of coastal change hazards","interactions":[],"lastModifiedDate":"2019-12-05T08:27:47","indexId":"70202422","displayToPublicDate":"2019-06-30T08:27:37","publicationYear":"2019","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Forecasts of coastal change hazards","docAbstract":"Model predictions of severe storm impacts provide coastal residents, emergency managers, and partner organizations valuable predictive information for planning and response to extreme storm events. The foundation of this work is a USGS-developed numerical model to forecast storm-induced coastal water levels and expected coastal change, including dune erosion, overwash, and inundation. The model is operated in three modes: generalized scenarios, real-time storms, and an operational forecast, with each mode requiring slightly different water level inputs. To evaluate and improve the accuracy of the models, we collect data on water levels and coastal change. In particular, observations before, after, and during storm conditions are used to test the different model applications. Forecast validation for Hurricanes Matthew (2016) and Irma (2017) illustrate three cases with demonstrated forecast skill and three cases with poor skill, and reveal elements of the modeling and/or testing approach which require improvement.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Coastal Sediments 2019: Proceedings of the 9th international conference ","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"Coastal Sediments 2019","conferenceDate":"May 27-31, 2019","conferenceLocation":"Tampa/St. Petersburg, FL","language":"English","publisher":"World Scientific","doi":"10.1142/9789811204487_0122","usgsCitation":"Doran, K.S., Stockdon, H.F., Joseph Long, and Plant, N.G., 2019, Forecasts of coastal change hazards, in Coastal Sediments 2019: Proceedings of the 9th international conference , Tampa/St. Petersburg, FL, May 27-31, 2019, p. 1400-1409, https://doi.org/10.1142/9789811204487_0122.","productDescription":"10 p.","startPage":"1400","endPage":"1409","ipdsId":"IP-105870","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":369944,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2019-05-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Doran, Kara S. 0000-0001-8050-5727 kdoran@usgs.gov","orcid":"https://orcid.org/0000-0001-8050-5727","contributorId":148059,"corporation":false,"usgs":true,"family":"Doran","given":"Kara","email":"kdoran@usgs.gov","middleInitial":"S.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":758393,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stockdon, Hilary F. 0000-0003-0791-4676 hstockdon@usgs.gov","orcid":"https://orcid.org/0000-0003-0791-4676","contributorId":2153,"corporation":false,"usgs":true,"family":"Stockdon","given":"Hilary","email":"hstockdon@usgs.gov","middleInitial":"F.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":758394,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Joseph Long","contributorId":213744,"corporation":false,"usgs":false,"family":"Joseph Long","affiliations":[{"id":38846,"text":"UNC Wilmington","active":true,"usgs":false}],"preferred":false,"id":758395,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Plant, Nathaniel G. 0000-0002-5703-5672 nplant@usgs.gov","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":3503,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","email":"nplant@usgs.gov","middleInitial":"G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"preferred":true,"id":758396,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70205847,"text":"70205847 - 2019 - Consistency counts: Modeling the effects of a change in protocol on Breeding Bird Survey counts","interactions":[],"lastModifiedDate":"2019-10-21T14:40:37","indexId":"70205847","displayToPublicDate":"2019-06-29T12:59:41","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3551,"text":"The Condor","active":true,"publicationSubtype":{"id":10}},"title":"Consistency counts: Modeling the effects of a change in protocol on Breeding Bird Survey counts","docAbstract":"Analysis of North American Breeding Bird Survey (BBS) data requires controls for factors that influence detectability of birds along survey routes. Identifying factors that influence the counting process and incorporating them into analyses is a primary means of limiting bias in estimates of population change. Twedt (2015) implemented an alternative counting protocol on operational and non-random BBS survey routes in the southeastern United States. Observers on selected routes employed a time-distance protocol in which they recorded birds in 1-minute intervals and in 2 distance categories. We hypothesized that processing and recording observations using this time-distance protocol could cause observers to count fewer birds relative to observers using the standard protocol. We used a hierarchical log-linear model with a categorical covariate associated with protocol (standard vs time-distance) to assess whether use of the time-distance protocol had a measurable effect on counting birds along BBS routes. We applied this model to BBS data from portions of eight states in which the time-distance protocol was implemented and estimated a protocol effect for 167 bird species. We documented a significant overall effect of the time-distance protocol on observers’ counts of birds. On average, the effect of the time-distance protocol was a 10% decline in count, and 80% of species had lower counts when the time-distance protocol was used on a survey route. However, because the time-distance protocol was only used on a small portion of the operational BBS routes and for a limited time, including the covariate for the time-distance protocol data had insignificant effects on analysis of population change. Although the covariate controlled for the effects of the time-distance protocol in BBS data, the results emphasize the importance of standardization as well as a need to track and, if necessary, control in analyses for changes in counting procedures along BBS routes.","language":"English","publisher":"Oxford Academic","doi":"10.1093/condor/duz009","usgsCitation":"Sauer, J.R., Link, W.A., Ziolkowski, D., Pardieck, K.L., and Twedt, D.J., 2019, Consistency counts: Modeling the effects of a change in protocol on Breeding Bird Survey counts: The Condor, v. 121, no. 2, duz009, 12 p., https://doi.org/10.1093/condor/duz009.","productDescription":"duz009, 12 p.","ipdsId":"IP-081193","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":467495,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/condor/duz009","text":"Publisher Index Page"},{"id":368104,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"121","issue":"2","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2019-06-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Sauer, John R. 0000-0002-4557-3019 jrsauer@usgs.gov","orcid":"https://orcid.org/0000-0002-4557-3019","contributorId":146917,"corporation":false,"usgs":true,"family":"Sauer","given":"John","email":"jrsauer@usgs.gov","middleInitial":"R.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":772603,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Link, William A. 0000-0002-9913-0256 wlink@usgs.gov","orcid":"https://orcid.org/0000-0002-9913-0256","contributorId":146920,"corporation":false,"usgs":true,"family":"Link","given":"William","email":"wlink@usgs.gov","middleInitial":"A.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":773533,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ziolkowski, David 0000-0002-2500-4417 dziolkowski@usgs.gov","orcid":"https://orcid.org/0000-0002-2500-4417","contributorId":195409,"corporation":false,"usgs":true,"family":"Ziolkowski","given":"David","email":"dziolkowski@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":773534,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pardieck, Keith L. 0000-0003-2779-4392 kpardieck@usgs.gov","orcid":"https://orcid.org/0000-0003-2779-4392","contributorId":4104,"corporation":false,"usgs":true,"family":"Pardieck","given":"Keith","email":"kpardieck@usgs.gov","middleInitial":"L.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":773535,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Twedt, Daniel J. 0000-0003-1223-5045 dtwedt@usgs.gov","orcid":"https://orcid.org/0000-0003-1223-5045","contributorId":398,"corporation":false,"usgs":true,"family":"Twedt","given":"Daniel","email":"dtwedt@usgs.gov","middleInitial":"J.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":773536,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70203002,"text":"sir20195029 - 2019 - Groundwater quality and hydrology with emphasis on selenium mobilization and transport in the Lower Gunnison River Basin, Colorado, 2012–16","interactions":[],"lastModifiedDate":"2019-07-01T09:22:29","indexId":"sir20195029","displayToPublicDate":"2019-06-28T13:00:00","publicationYear":"2019","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":"2019-5029","title":"Groundwater quality and hydrology with emphasis on selenium mobilization and transport in the Lower Gunnison River Basin, Colorado, 2012–16","docAbstract":"Dissolved selenium is a contaminant of concern in the lower Gunnison River Basin, Colorado. Selenium is naturally present in the Cretaceous Mancos Shale and is leached to groundwater and surface water by irrigation. The groundwater on the east side of the Uncompahgre River in Delta and Montrose Counties is one of the primary sources of selenium concentration and load to surface water in the lower Gunnison River Basin. Although little information about the contribution of groundwater to surface water has been historically available, groundwater has often been implicated as an appreciable source of selenium to surface water. From 2012 to 2016, the U.S. Geological Survey, in cooperation with the Bureau of Reclamation, the Colorado Water Conservation Board, and the Gunnison Basin Selenium Management Program, established a 30-well groundwater-monitoring network on irrigated land to characterize the hydrology and groundwater quality of the shallow groundwater system on the east side of the Uncompahgre River in the lower Gunnison River Basin. The installation of the 30-well network and the data collected allowed for the development of a conceptual model of selenium mobilization and transport in the shallow groundwater system. Monitoring wells were completed in surficial deposits and in weathered Mancos Shale, which generally exhibited unconfined and confined conditions, respectively. Groundwater-quality monitoring provides information on the distribution of selenium and the geochemical processes controlling selenium concentrations in shallow groundwater. Monitoring wells were sampled between August 2013 and March 2015 to understand groundwater quality, seasonality, sources of recharge, and groundwater age. Concentrations of dissolved selenium ranged from below the limit of detection to 4,100 micrograms per liter (µg/L), with a median concentration of 14 µg/L. Concentrations showed a high degree of spatial variability and no seasonal difference. Similarly, no seasonal pattern was observed in specific conductance values of groundwater despite the considerably lower specific conductance value of irrigation water.
Reduction-oxidation processes are important controls on selenium mobility. Nitrate derived from geologic material was a primary control on reduction-oxidation conditions in groundwater and inhibited selenium reduction to less mobile forms. Nitrate was reduced by denitrification in groundwater, but it was not reduced to the extent necessary to allow for selenium reduction. Groundwater ages were determined for groundwater samples from eight wells and ranged from 6 to 20 years old. Isotopic data indicate groundwater was recharged by irrigation water; no information collected supported an older, deeper source of recharge to the shallow groundwater system. Data on water level in all wells showed response to irrigation practices, but the response was delayed in some wells, which may be an indication of distance from recharge source.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/sir20195029","collaboration":"Prepared in cooperation with the Bureau of Reclamation, the Colorado Water Conservation Board, and the Gunnison Basin Selenium Management Program","usgsCitation":"Thomas, J.C., McMahon, P.B., and Arnold, L.R., 2019, Groundwater quality and hydrology with emphasis on selenium mobilization and transport in the lower Gunnison River Basin, Colorado, 2012–16: U.S. Geological Survey Scientific Investigations Report 2019–5029, 69 p., https://doi.org/10.3133/sir20195029.","productDescription":"viii, 69 p.","onlineOnly":"Y","ipdsId":"IP-084069","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":365132,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5029/coverthb.jpg"},{"id":365133,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5029/sir20195029.pdf","text":"Report","size":"10.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5029"}],"country":"United States","state":"Colorado","otherGeospatial":"Lower Gunnison River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.80584716796875,\n 39.01064750994083\n ],\n [\n -109.11895751953125,\n 38.8782049970615\n ],\n [\n -108.6328125,\n 38.10214399750345\n ],\n [\n -108.69598388671875,\n 37.77288579232439\n ],\n [\n -107.87750244140625,\n 37.309014074275915\n ],\n [\n -107.4462890625,\n 37.31338308990806\n ],\n [\n -107.1441650390625,\n 37.727280276860036\n ],\n [\n -107.18536376953125,\n 38.07620357665235\n ],\n [\n -107.26776123046875,\n 38.50304202775689\n ],\n [\n -107.50671386718749,\n 38.9380483825641\n ],\n [\n -107.6495361328125,\n 39.115144700901475\n ],\n [\n -108.80584716796875,\n 39.01064750994083\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 Stochastic Empirical Loading and Dilution Model (SELDM) was developed by the U.S. Geological Survey (USGS) in cooperation with the Federal Highway Administration to simulate stormwater quality. To assess the effects of runoff, SELDM uses a stochastic mass-balance approach to estimate combinations of pre-storm streamflow, stormflow, highway runoff, event mean concentrations (EMCs) and stormwater constituent loads from a site of interest. In addition, SELDM can be used to assess the effects of stormwater Best Management Practices (BMPs), which are designed to mitigate the adverse effects of runoff into a waterbody.
Adverse effects of stormwater on receiving waters are one of the greatest unsolved water-quality problems Nationwide. State DOTs, municipalities, Federal facilities, and private property owners who manage impervious surfaces need information about the potential magnitude of their contributions and the potential effectiveness of methods to mitigate the adverse effects of runoff. Because the efficacy of at-site controls are limited, information about the potential effectiveness of alternative strategies is needed.
The USGS, in cooperation with the Oregon Department of Transportation (ODOT), conducted a study to research methods in which SELDM can be used to enhance the efficiency of ODOT’s stormwater program, support the development of a stormwater banking program, and meet environmental goals. Results can be used to develop a strategic, systems-level approach to stormwater management by considering entire watersheds instead of individual road crossings. Two watersheds, Bear Creek and Mill Creek, in western Oregon were selected for analysis. Within each watershed, seven road crossings were selected for demonstrating the utility of SELDM in nested basins.
Precipitation statistics, pre-storm streamflow, runoff coefficients, and hydrograph recession factors were calculated for each location and used in SELDM to simulate flow, water-quality concentrations, and constituent loads in the upstream basin, from the highway (or developed area), and downstream from the road crossing. Three water-quality constituents were selected for modeling: suspended-sediment concentration (SSC), total phosphorus (TP), and total copper (TCu). Using water-quality transport curves, the relations between streamflow and SSC and between streamflow and TP were simulated. Concentrations of TCu were simulated by configuring a linear relation between SSC and TCu. A generic BMP was simulated using the median treatment statistics for flow reductions, hydrograph extensions, concentration reductions, and minimum irreducible concentrations from nine BMP categories with data from the 2012 International BMP database.
Five simulation scenarios were modeled for demonstrative purposes. These simulations were used to evaluate potential effects of different watershed properties, water-quality inputs, and stormwater mitigation measures. Instream EMCs were compared to hypothetical water-quality criteria for suspended sediment, total phosphorus, and total copper to demonstrate the concept of water-quality risk analysis. For all five scenarios, it was assumed that highway runoff concentrations were independent of location or average annual daily traffic. These five scenarios are as follows:
• Simulation Scenario 1—Natural Conditions (hereafter Simulation Scenario 1) represents conditions in an undeveloped watershed. This scenario demonstrates that the strategic placement of a hypothetical road crossing within a watershed could be used to avoid exceeding water-quality standards of TP and SSC, but that no location choice results in meeting TCu standards. Implementation of BMP had the most pronounced effects on downstream water-quality constituent EMCs at road crossings with the highest ratio of highway catchment area to upstream drainage area, but the largest effect of BMP treatment on mean annual load is based on highway catchment area alone.
• Simulation Scenario 2—Current Conditions (hereafter Simulation Scenario 2) represents current watershed conditions, where all developed area upstream from the road crossing was modeled as a highway and combined with the undeveloped part of the upstream drainage area (scenario 2A) and where the output from scenario 2A is used for the upstream area (developed area and the undeveloped area), and where the road crossing is added as usual (scenario 2B). Scenario 2 results indicate that attaining water-quality standards is more difficult with upstream developed areas. Specific road-crossing sites can be selected to achieve the fewest water-quality exceedances per year, but water-quality targets are not met without BMP implementation, and in some instances are not achievable even with BMP implementation. Results from this scenario also serve to quantify the upper limit of constituent reduction if funding were available to implement BMPs to large areas of development, and to quantify how much area would need BMP implementation to achieve water-quality targets.
• Simulation Scenario 3—Alternative Road Layouts (hereafter Simulation Scenario 3) was designed to assess the sensitivity of SELDM to various road layouts. In this scenario, different highway configurations were superimposed at one road crossing. Results indicate that downstream waterquality constituent EMCs did not exhibit much variation, but annual water-quality constituent loads varied considerably.
• Simulation Scenario 4—Varying Road Width (hereafter Simulation Scenario 4) was designed to assess the sensitivity of SELDM to road width. Similar to scenario 3, the results indicate little variation in downstream water-quality constituent EMCs, but annual water-quality constituent loads increased in proportion to road width.
• Simulation scenario 5—Changes to Impervious Area (hereafter Simulation Scenario 5) was designed to investigate the effects of changing amounts of imperviousness upstream from the road crossing. Results indicate that the downstream water-quality constituent EMCs are highly correlated with the percentage of impervious area upstream.
Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
Water samples from 50 domestic wells located <1 km (proximal) and >1 km (distal) from shale-gas wells in upland areas of the Marcellus Shale region were analyzed for chemical, isotopic, and groundwater-age tracers. Uplands were targeted because natural mixing with brine and hydrocarbons from deep formations is less common in those areas compared to valleys. CH4-isotope, predrill CH4-concentration, and other data indicate that one proximal sample (5% of proximal samples) contains thermogenic CH4 (2.6 mg/L) from a relatively shallow source (Catskill/Lock Haven Formations) that appears to have been mobilized by shale-gas production activities. Another proximal sample contains five other volatile hydrocarbons (0.03–0.4 μg/L), including benzene, more hydrocarbons than in any other sample. Modeled groundwater-age distributions, calibrated to 3H, SF6, and 14C concentrations, indicate that water in that sample recharged prior to shale-gas development, suggesting that land-surface releases associated with shale-gas production were not the source of those hydrocarbons, although subsurface leakage from a nearby gas well directly into the groundwater cannot be ruled out. Age distributions in the samples span ∼20 to >10000 years and have implications for relating occurrences of hydrocarbons in groundwater to land-surface releases associated with recent shale-gas production and for the time required to flush contaminants from the system.
","language":"English","publisher":"American Chemical Society","doi":"10.1021/acs.est.9b01440","usgsCitation":"McMahon, P.B., Lindsey, B.D., Conlon, M.D., Hunt, A.G., Belitz, K., Jurgens, B., and Varela, B.A., 2019, Hydrocarbons in upland groundwater, Marcellus Shale Region, Northeastern Pennsylvania and Southern New York, USA: Environmental Science & Technology, v. 53, no. 14, p. 8027-8035, https://doi.org/10.1021/acs.est.9b01440.","productDescription":"9 p.","startPage":"8027","endPage":"8035","ipdsId":"IP-104959","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true},{"id":5078,"text":"Southwest Regional Director's Office","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"links":[{"id":437401,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93M7JCD","text":"USGS data release","linkHelpText":"Data Release for Hydrocarbons in Upland Groundwater, Marcellus Shale Region, Northeastern Pennsylvania and Southern New York, USA"},{"id":365631,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York, Pennsylvania","volume":" 53","issue":"14","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2019-06-27","publicationStatus":"PW","contributors":{"authors":[{"text":"McMahon, Peter B. 0000-0001-7452-2379 pmcmahon@usgs.gov","orcid":"https://orcid.org/0000-0001-7452-2379","contributorId":724,"corporation":false,"usgs":true,"family":"McMahon","given":"Peter","email":"pmcmahon@usgs.gov","middleInitial":"B.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":766203,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lindsey, Bruce D. 0000-0002-7180-4319 blindsey@usgs.gov","orcid":"https://orcid.org/0000-0002-7180-4319","contributorId":175346,"corporation":false,"usgs":true,"family":"Lindsey","given":"Bruce","email":"blindsey@usgs.gov","middleInitial":"D.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":766204,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Conlon, Matthew D. 0000-0001-8266-9610 mconlon@usgs.gov","orcid":"https://orcid.org/0000-0001-8266-9610","contributorId":201291,"corporation":false,"usgs":true,"family":"Conlon","given":"Matthew","email":"mconlon@usgs.gov","middleInitial":"D.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":766205,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hunt, Andrew G. 0000-0002-3810-8610 ahunt@usgs.gov","orcid":"https://orcid.org/0000-0002-3810-8610","contributorId":1582,"corporation":false,"usgs":true,"family":"Hunt","given":"Andrew","email":"ahunt@usgs.gov","middleInitial":"G.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":766206,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Belitz, Kenneth 0000-0003-4481-2345","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":201889,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":766207,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jurgens, Bryant C. 0000-0002-1572-113X","orcid":"https://orcid.org/0000-0002-1572-113X","contributorId":203409,"corporation":false,"usgs":true,"family":"Jurgens","given":"Bryant","middleInitial":"C.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":766208,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Varela, Brian A. 0000-0001-9849-6742 bvarela@usgs.gov","orcid":"https://orcid.org/0000-0001-9849-6742","contributorId":178091,"corporation":false,"usgs":true,"family":"Varela","given":"Brian","email":"bvarela@usgs.gov","middleInitial":"A.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":766209,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70204037,"text":"70204037 - 2019 - Morphology and genesis of giant seafloor depressions on the southeasterncontinental shelf of the Korean Peninsula","interactions":[],"lastModifiedDate":"2019-06-28T09:25:09","indexId":"70204037","displayToPublicDate":"2019-06-27T14:31:58","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2667,"text":"Marine Geology","active":true,"publicationSubtype":{"id":10}},"title":"Morphology and genesis of giant seafloor depressions on the southeasterncontinental shelf of the Korean Peninsula","docAbstract":"We identify and describe five giant seafloor depressions from the southeastern continental shelf of the Korean Peninsula using multibeam bathymetry, sub-bottom profiler, and multi-channel seismic reflection data, supplemented by piston cores. Multibeam bathymetry data from the shelf show four crescent-shaped depressions (SD1 to SD4) and one near-circular depression (SD5) within a group of NW-SE trending depressions, the largest covering an area of about 7 km2 on the seafloor. The depressions reach up to ~4.5 km in width and ~2 km in length and have asymmetric cross-sections. Some have depths as large as 40 m below the surrounding seafloor with walls as steep as 45°. The depressions are confined to water depths between 130 and 170 m and bounded on the north by a large submarine channel that was plausibly formed by fluvial or tidal processes during the Last Glacial Maximum (LGM) sea-level lowstand. Multi-channel seismic and sub-bottom profiler data reveal truncated depression walls and the presence of sediment drift deposits within the depressions, indicating that both erosion and deposition are active processes. Flaser and lenticular bedding in the cored drift deposits along with variable grain size (ranging between ~2.6 phi and ~4.3 phi) are diagnostic features of the bottom currents influenced by tidal forces. Depressions SD1 to SD4 lack evidence of fluid or gas escape. In contrast, many features of depression SD5 are characteristic of gas escapes and blowouts, including acoustic anomalies, a 20-m-high carbonate mound or carbonate-encrusted mound, and mud dikes and mud patches in cores. Based on the SD5 example, we think it is likely that the other crescent-shaped seafloor depressions formed originally as pockmarks by gas/fluid venting, and have since become inactive. The pockmarks represent zones of weakened sediment that were eroded, expanded, and merged by bottom currents to form larger seafloor depressions. Modern currents are strong enough to transport shelf sediments, and these currents were probably much stronger at lower sea levels when the Korea Strait was a more restricted passage between the East China Sea and East Sea.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.margeo.2019.105966","usgsCitation":"Cukur, D., Kong, G., Chun, J., Kang, M., Um, I., Kwon, T., Jordan, S.E., and Kim, K., 2019, Morphology and genesis of giant seafloor depressions on the southeasterncontinental shelf of the Korean Peninsula: Marine Geology, v. 415, 105966, 13 p., https://doi.org/10.1016/j.margeo.2019.105966.","productDescription":"105966, 13 p.","ipdsId":"IP-106382","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":365123,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"North Korea, South Korea","otherGeospatial":"Korea Strait","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 127.869873046875,\n 33.284619968887675\n ],\n [\n 130.97900390625,\n 33.284619968887675\n ],\n [\n 130.97900390625,\n 37.18657859524883\n ],\n [\n 127.869873046875,\n 37.18657859524883\n ],\n [\n 127.869873046875,\n 33.284619968887675\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"415","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Cukur, Deniz","contributorId":216636,"corporation":false,"usgs":false,"family":"Cukur","given":"Deniz","email":"","affiliations":[{"id":39491,"text":"Korea Institute of Geoscience and Mineral Resources (KIGAM","active":true,"usgs":false}],"preferred":false,"id":765221,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kong, Gee-Soo","contributorId":216637,"corporation":false,"usgs":false,"family":"Kong","given":"Gee-Soo","email":"","affiliations":[{"id":39491,"text":"Korea Institute of Geoscience and Mineral Resources (KIGAM","active":true,"usgs":false}],"preferred":false,"id":765254,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chun, Jong-Hwa","contributorId":216638,"corporation":false,"usgs":false,"family":"Chun","given":"Jong-Hwa","email":"","affiliations":[{"id":39491,"text":"Korea Institute of Geoscience and Mineral Resources (KIGAM","active":true,"usgs":false}],"preferred":false,"id":765223,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kang, Moo-Hee","contributorId":216639,"corporation":false,"usgs":false,"family":"Kang","given":"Moo-Hee","email":"","affiliations":[{"id":39491,"text":"Korea Institute of Geoscience and Mineral Resources (KIGAM","active":true,"usgs":false}],"preferred":false,"id":765224,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Um, In-Kwon","contributorId":216640,"corporation":false,"usgs":false,"family":"Um","given":"In-Kwon","email":"","affiliations":[{"id":39491,"text":"Korea Institute of Geoscience and Mineral Resources (KIGAM","active":true,"usgs":false}],"preferred":false,"id":765225,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kwon, Taekhyun","contributorId":216641,"corporation":false,"usgs":false,"family":"Kwon","given":"Taekhyun","email":"","affiliations":[{"id":39491,"text":"Korea Institute of Geoscience and Mineral Resources (KIGAM","active":true,"usgs":false}],"preferred":false,"id":765226,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jordan, Samuel E. 0000-0001-6074-3330","orcid":"https://orcid.org/0000-0001-6074-3330","contributorId":216635,"corporation":false,"usgs":true,"family":"Jordan","given":"Samuel","email":"","middleInitial":"E.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":765220,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kim, Kyong-O","contributorId":216642,"corporation":false,"usgs":false,"family":"Kim","given":"Kyong-O","email":"","affiliations":[{"id":39491,"text":"Korea Institute of Geoscience and Mineral Resources (KIGAM","active":true,"usgs":false}],"preferred":false,"id":765227,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70263727,"text":"70263727 - 2019 - Evaluating tradeoffs in the response of Sora (Porzana carolina) and waterfowl to the timing of early autumn wetland inundation","interactions":[],"lastModifiedDate":"2025-02-20T19:12:23.90001","indexId":"70263727","displayToPublicDate":"2019-06-27T13:04:35","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3731,"text":"Waterbirds","onlineIssn":"19385390","printIssn":"15244695","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Evaluating tradeoffs in the response of Sora (Porzana carolina) and waterfowl to the timing of early autumn wetland inundation","title":"Evaluating tradeoffs in the response of Sora (Porzana carolina) and waterfowl to the timing of early autumn wetland inundation","docAbstract":"Wetland loss has increased the importance of multi-species management in remaining wetlands, which provide habitat for a multitude of wetland-dependent species. Many public wetlands across the mid-latitude United States are managed as moist soil impoundments with emphasis on migratory waterfowl. However, how the timing of these water management decisions affects rails is still uncertain. Wetland managers identified this as an area of uncertainty regarding timing of alternative water management strategies to benefit waterfowl and rails, which was addressed through a 3-year management experiment. Sora (Porzana carolina) and waterfowl were surveyed on 10 public wetland properties in Missouri, USA from 2014-2016, and their responses to early autumn inundation of managed palustrine wetlands were compared. A total of 558 Sora surveys detected 5,755 birds (20.6 birds/survey ± 30.8 SD), and 1,304 waterfowl surveys detected 1,411,779 birds (15,686.4 birds/survey ± 23,933.9 SD). Sora responded positively (birds/ha) to inundation of moist soil impoundments earlier in autumn migration (August). The top model for Sora included treatment, year and region of Missouri. There was no difference in waterfowl abundance between early or late inundation. Inundating wetlands earlier in autumn migration can provide habitat for migrating Sora without negative effects on waterfowl use of those wetlands, and wetland managers can incorporate this into their decision-making framework.
","language":"English","publisher":"BioOne","doi":"10.1675/063.042.0203","usgsCitation":"Fournier, A., Mengel, D., Gbur, E., Raedeke, A., and Krementz, D.G., 2019, Evaluating tradeoffs in the response of Sora (Porzana carolina) and waterfowl to the timing of early autumn wetland inundation: Waterbirds, v. 42, no. 2, p. 168-178, https://doi.org/10.1675/063.042.0203.","productDescription":"11 p.","startPage":"168","endPage":"178","ipdsId":"IP-093134","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":489951,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1675/063.042.0203","text":"Publisher Index Page"},{"id":482298,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"42","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Fournier, Ariel M.","contributorId":351134,"corporation":false,"usgs":false,"family":"Fournier","given":"Ariel M.","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":927964,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mengel, Doreen C.","contributorId":351135,"corporation":false,"usgs":false,"family":"Mengel","given":"Doreen C.","affiliations":[{"id":16971,"text":"Missouri Department of Conservation","active":true,"usgs":false}],"preferred":false,"id":927965,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gbur, Edward","contributorId":351136,"corporation":false,"usgs":false,"family":"Gbur","given":"Edward","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":927966,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Raedeke, Andy","contributorId":341916,"corporation":false,"usgs":false,"family":"Raedeke","given":"Andy","affiliations":[{"id":16971,"text":"Missouri Department of Conservation","active":true,"usgs":false}],"preferred":false,"id":927967,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Krementz, David G. 0000-0002-5661-4541 dkrementz@usgs.gov","orcid":"https://orcid.org/0000-0002-5661-4541","contributorId":2827,"corporation":false,"usgs":true,"family":"Krementz","given":"David","email":"dkrementz@usgs.gov","middleInitial":"G.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":927968,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70204078,"text":"70204078 - 2019 - Spatial conservation planning under uncertainty: Adapting to climate change risks using modern portfolio theory","interactions":[],"lastModifiedDate":"2020-12-08T18:02:17.95215","indexId":"70204078","displayToPublicDate":"2019-06-27T12:47:12","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Spatial conservation planning under uncertainty: Adapting to climate change risks using modern portfolio theory","docAbstract":"Climate change and urban growth impact habitats, species, and ecosystem services. To buffer against global change, an established adaptation strategy is designing protected areas to increase representation and complementarity of biodiversity features. Uncertainty regarding the scale and magnitude of landscape change complicates reserve planning and exposes decision makers to risk of failing to meet conservation goals. Conservation planning tends to treat risk as an absolute measure, ignoring the context of the management problem and risk preferences of stakeholders. Application to conservation of risk management theory emphasizes diversification of portfolio of assets, with the goal of reducing the impact of system volatility on investment return. We use principles of Modern Portfolio Theory (MPT), which quantifies risk as the variance and correlation among assets, to formalize diversification as an explicit strategy for managing risk in climate‐driven reserve design. We extend MPT to specify a framework that evaluates multiple conservation objectives, allows decision makers to balance management benefits and risk when preferences are contested or unknown, and includes additional decision options such as parcel divestment when evaluating candidate reserve designs. We apply an efficient search algorithm that optimizes portfolio design for large conservation problems and a game theoretic approach to evaluate portfolio tradeoffs that satisfy decision makers with divergent benefit and risk tolerances, or when a single decision maker cannot resolve their own preferences. Evaluating several risk profiles for a case study in South Carolina, our results suggest that a reserve design may be somewhat robust to differences in risk attitude but that budgets will likely be important determinants of conservation planning strategies, particularly when divestment is considered a viable alternative. We identify a possible fiscal threshold where adequate resources allow protecting a sufficiently diverse portfolio of habitats such that the risk of failing to achieve conservation objectives is considerably lower. For a range of sea‐level rise projections, conversion of habitat to open water (14‐180%) and wetland loss (1‐7%) are unable to be compensated under the current protected network. In contrast, optimal reserve design outcomes are predicted to ameliorate expected losses relative to current and future habitat protected under the existing conservation estate.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.1962","usgsCitation":"Eaton, M., Yurek, S., Haider, Z., Martin, J., Johnson, F., Udell, B., Charkhgard, H., and Kwon, C., 2019, Spatial conservation planning under uncertainty: Adapting to climate change risks using modern portfolio theory: Ecological Applications, v. 29, no. 2, e01962, 19 p., https://doi.org/10.1002/eap.1962.","productDescription":"e01962, 19 p.","ipdsId":"IP-103774","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":40926,"text":"Southeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":365283,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"South Carolina","otherGeospatial":"Cape Romain National Wildlife Refuge, Frances Marion National Forest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": 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Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-5050","displayTitle":"Flood-Inundation Maps for the Iowa River at the Meskwaki Settlement in Iowa, 2019","title":"Flood-inundation maps for the Iowa River at the Meskwaki Settlement in Iowa, 2019","docAbstract":"Digital flood-inundation maps for a 9.3-mile reach of the Iowa River along the Meskwaki Settlement, Iowa, were created by the U.S. Geological Survey (USGS) in cooperation with the Sac and Fox Tribe of the Mississippi in Iowa. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science website at https://water.usgs.gov/osw/flood_inundation/, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage 05451770 on the Iowa River at County Highway E49 near Tama, Iowa. Near-real-time stages at this streamgage may be obtained on the internet from the USGS National Water Information System at https://waterdata.usgs.gov/ or the National Weather Service (NWS) Advanced Hydrologic Prediction Service at https://water.weather.gov/ahps/, which also forecasts flood hydrographs at this site.
Flood profiles were computed for the stream reach by means of a calibrated one-dimensional and two-dimensional step-backwater hydraulic model. The model was calibrated by using the current stage-discharge relation at the USGS streamgage 05451770 on the Iowa River at County Highway E49 near Tama, Iowa, and stage and discharge data from historic flooding events that were recorded at the streamgage.
The hydraulic model was then used to compute eight water-surface profiles for flood stages at 1-foot intervals referenced to the streamgage datum and ranging from the NWS “action stage” of 11 feet (ft) to 18 ft, the stage exceeding the estimated 0.2-percent annual exceedance probability (500-year recurrence interval) flood, as determined at the USGS streamgage 05451770. The simulated water-surface profiles were then combined with a geographic information system digital elevation model to delineate the area flooded at each flood stage (water level).
In addition, potential modifications to hydraulic structures within the flood plain were modeled so any effects from the potential modifications could be evaluated. Four comparison points, which were along the flood plain, showed little to no change (less than 0.1 ft) in flood elevation from the existing conditions within the flood plain for the 11- to 16-ft stages as referenced to the USGS streamgage 05451770. There were greater changes (more than 0.1 ft) in flood elevation for the 2 comparison points that were closest to the modified hydraulic structure for the 2 highest modeled stages of 17 and 18 ft.
The availability of these maps, along with internet information regarding current stage from the USGS streamgage and forecasted high-flow stages from the NWS, will provide emergency management personnel and residents with information that is critical for flood-response activities such as evacuations and road closures, as well as for postflood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195050","collaboration":"Prepared in cooperation with the Sac and Fox Tribe of the Mississippi in Iowa","usgsCitation":"Cigrand, C.V., 2019, Flood-inundation maps for the Iowa River at the Meskwaki Settlement in Iowa, 2019: U.S. Geological Survey Scientific Investigations Report 2019–5050, 12 p., https://doi.org/10.3133/sir20195050.","productDescription":"12 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-103795","costCenters":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":365048,"rank":3,"type":{"id":30,"text":"Data Release"},"url":" https://doi.org/10.5066/P912FO3L ","text":"USGS data release","description":"USGS data release","linkHelpText":"Geospatial datasets for the flood-inundation study for the Iowa River at the Meskwaki Settlement in Iowa, 2019"},{"id":365046,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5050/coverthb.jpg"},{"id":365047,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5050/sir20195050.pdf","text":"Report","size":"26.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5050"}],"country":"United States","state":"Iowa","otherGeospatial":"Meskwaki Settlement","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -92.7175,41.916666666666664 ], [ -92.7175,42.034166666666664 ], [ -92.55,42.034166666666664 ], [ -92.55,41.916666666666664 ], [ -92.7175,41.916666666666664 ] ] ] } } ] }","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
400 South Clinton Street, Suite 269
Iowa City, IA 52240
We present a petrologic and mineral physics database as part of the U.S. Geological Survey National Crustal Model (NCM). Each of 209 geologic units, 134 of which are currently part of the geologic framework within the NCM, was assigned a mineralogical composition according to generalized classifications with some refinement for specific geologic formations. This report is concerned with the petrology and mineral physics of each geologic unit within the NCM, which control the physical behavior of the solid mineral matrix within the rock.
This mineral physics database builds on the work of Abers and Hacker to include 13 minerals specific to continental rock types. We explored the effect of this database on zero-porosity anharmonic P- and S-wave rock velocities and density relative to a well-used empirical study of relations between wavespeeds and density by Brocher. We found that empirical relations between P-wave velocity and S-wave velocity or density do well on average but can differ from mineral physics calculations by up to 15 percent in S-wave velocity and almost 40 percent in density. This is consistent with Brocher’s study where he obtained similar results for in situ measurements and laboratory rock specimens.
Additionally, the substantial presence of quartz in many rocks plays a major role in crustal seismic velocities and density due to quartz’s α–β phase transition, which can interfere with these empirical relationships. With increasing depth, quartz P-wave velocity can suddenly jump by 15 percent accompanied by little change in S-wave velocity and a modest decrease in density. Empirical relations based on observed P-wave velocity where P-wave velocity is positively correlated with S-wave velocity and density would then significantly overestimate both S-wave velocity and density.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191035","usgsCitation":"Sowers, T., and Boyd, O.S., 2019, Petrologic and mineral physics database for use with the U.S. Geological Survey National Crustal Model: U.S. Geological Survey Open-File Report 2019–1035, 17 p.,https://doi.org/10.3133/ofr20191035.","productDescription":"17 p.","onlineOnly":"Y","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":437403,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FK25WM","text":"USGS data release","linkHelpText":"MinVel"},{"id":364257,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9HN170G","text":"USGS data release","linkHelpText":"Petrologic and Mineral Physics Database for use with the USGS National Crustal Model - Data Release"},{"id":365082,"rank":4,"type":{"id":4,"text":"Application Site"},"url":"https://github.com/usgs/MinVel","text":"MinVel ","linkHelpText":"software that supports this report is available in the GitHub repository."},{"id":364255,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1035/coverthb.jpg"},{"id":364256,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1035/ofr20191035.pdf","text":"Report","size":"1.20 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1035"}],"contact":"Director, Geologic Hazards Science Center
U.S. Geological Survey
Box 25046, MS-966
Denver, CO 80225-0046
The Cerulean Warbler (Setophaga cerulea) is a species of conservation need, with declines linked in part to forest habitat loss on its breeding grounds. Active management of forests benefit the Cerulean Warbler by creating the complex structural conditions preferred by the species, but further research is needed to determine optimal silvicultural strategies. We quantified and compared the broad-scale influence of timber harvests within central Appalachian hardwood forests on estimated abundance and territory density of Cerulean Warblers. We conducted point counts at seven study areas across three states within the central Appalachian region (West Virginia [n = 4], Kentucky [n = 1], Virginia [n = 2]) and territory mapping at two of the study areas in West Virginia, pre- and post-harvest, for up to five breeding seasons from 2013 to 2017. Our primary objective was to relate change in abundance to topographic and vegetation metrics to evaluate the effectiveness of current Cerulean Warbler habitat management guidelines. We used single-species hierarchical (N-mixture) models to estimate abundance while accounting for detection biases. Pre-harvest mean basal area among study areas was 29.3 m2/ha. Harvesting reduced mean basal area among study areas by 40% (mean 17.2 m2/ha) at harvest interior and harvest edge points. Territory density increased 100% (P = 0.003) from pre-harvest to two years post-harvest. Cerulean Warbler abundance increased with increasing percentage of basal area that comprised tree species preferred for foraging and nesting (i.e., white oak species, sugar maple [Acer saccharum], hickories) or of large diameter trees (≥40.6 cm diameter at breast height). Positive population growth was predicted to occur where these vegetation metrics were >50% of residual basal area. Post-harvest abundance at harvest interior points was greater than at reference points and when accounting for years-post-harvest in modeling abundance, Cerulean Warbler abundance increased at harvest interior and reference points two years post-harvest and subsequently decreased three years post-harvest. Modeled abundance remained the same at harvest edge points. Increases in abundance and territory density were greater in stands with low pre-harvest densities (<2 birds/point or <0.40 territory/ha) of Cerulean Warblers, whereas populations within stands with higher densities pre-harvest had minimal changes in abundance and territory density. Overall, our results indicate that harvests based on the Cerulean Warbler Management Guidelines for Enhancing Breeding Habitat in Appalachian Hardwood Forests, at all available slope positions and aspects where pre-harvest densities are <0.40 territory/ha, may provide breeding habitat for Cerulean Warblers for at least two years post-harvest in the central Appalachian region.
The State of Nebraska requires a sustainable balance between long-term water supplies and uses of groundwater and surface water and requires Natural Resources Districts to include the effect of groundwater use on surface-water systems as part of their respective integrated management plans. Recent droughts in Nebraska (2000–6; 2012–13) have amplified concerns about the long-term sustainability of groundwater and surface-water resources in the state, and concerns about the effect of groundwater irrigation on both streamflow and the water supplies needed to meet wildlife, recreational, and municipal needs. The lower Platte River provides nearly 100 percent of drinking-water supplies to Lincoln, Nebraska, 40 to 60 percent of drinking-water supplies to Omaha, Nebr., and critical aquatic and riparian habitat for threatened and endangered species. The Lower Platte River Basin-wide Management Plan has been jointly developed by the Nebraska Department of Natural Resources and seven Natural Resources Districts to address some of these concerns by managing groundwater and surface-water resources conjunctively.
To sustain flows in the lower Platte River that are needed for municipal water supplies, water managers have proposed projects aimed at temporary storage of surface water in upstream parts of the basin to mitigate periods of low flow in the lower Platte River. To increase scientific understanding and provide support for any potential future streamflow augmentation projects, the Papio-Missouri River Natural Resources District, the Lower Platte North Natural Resources District, and the Nebraska Department of Natural Resources, in cooperation with the U.S. Geological Survey, initiated this study to examine groundwater/surface-water interaction along the lower Platte and Elkhorn Rivers upstream from their confluence. The study design described herein focused on understanding seasonal characteristics of groundwater movement and interaction with surface water during periods of high groundwater demand (June through August) and low groundwater demand (all other months). Understanding how groundwater movement and interaction with surface water are affected by streamflow conditions and local groundwater demand is critical to the development of any streamflow augmentation project intended to sustain streamflow and mitigate periods of low flow in the lower Platte River.
The characteristics of groundwater movement and interaction with surface water are affected by hydrologic and local climatic conditions. For the study area, 2016–18 conditions can be broadly characterized as above normal precipitation. The flows measured at the Elkhorn River at Waterloo, Nebr., streamflow-gaging station (U.S. Geological Survey station 06800500) were above the long-term median, and the streamflow of the Platte River near Leshara, Nebr., streamflow-gaging station (06796500) remained normal or slightly above normal for the duration of this study.
Continuous streamflow and water-level data were interpreted to examine differences in groundwater movement and interaction with surface water between the Platte and Elkhorn Rivers during high and low groundwater demand periods. Although the streamflow for the Platte and Elkhorn Rivers and their tributaries was less during the high groundwater demand period, the hydraulic gradient along a transect of recorder wells was identical (0.0012 foot per foot) during the high and low groundwater demand synoptic water-level and streamflow surveys. The hydraulic gradient between the Platte and Elkhorn Rivers generally remained between 0.0011 and 0.0012 foot per foot. It can be inferred that the hydraulic gradient, which is the only temporally variable factor in Darcy’s Law, is consistent throughout the study period and that groundwater flow does not vary appreciably along this transect.
The northern part of the study area (north of the transect of recorder wells) has consistent groundwater and tributary flow from Big Slough, Rawhide Creek (Old Channel), and Rawhide Creek for low and high groundwater demand periods. In the southern part of the study area (south of the transect of recorder wells), tributary flow is more variable and dependent on local groundwater demand and flow conditions of the Platte River. Small decreases (less than 2 feet) in the groundwater levels, such as those measured during the high groundwater demand period, can have substantial changes in the streamflow in an unnamed tributary to the Elkhorn River. The streamflow measured during the high groundwater demand synoptic water-level and streamflow survey had decreased by nearly a factor of 20 when compared to the low groundwater demand period.
The volume of groundwater discharge received by the Elkhorn River was estimated by examining the changes in streamflow between measurement locations. Streamflow measurements indicate that the groundwater discharge received by the Elkhorn River in the southern part of the study area was seasonably variable, making it difficult if not impossible to estimate an annual value. In the Elkhorn River, between the Elkhorn River at Waterloo, Nebr., streamflow-gaging station and the Q Street Bridge, streamflow measurements collected during the low groundwater demand period indicated a gain of 80 cubic feet per second, which is comparable to the gain estimated using aerial thermal infrared imagery and water temperature data. Streamflow measurements collected during the high groundwater demand period indicate a loss of 80 cubic feet per second across this same reach. In assessing water supply conditions in the lower Platte River system, the term “loss” in reference to streamflow in the Elkhorn River should be used with caution. Most likely, flow from the Elkhorn River which is “lost” to the groundwater system will later discharge to surface water closer to the confluence of the Platte and Elkhorn Rivers as underflow. A calibrated groundwater flow model of the study area likely is required to predict the fate of this water and to quantify groundwater discharge during varying hydrologic conditions along this reach.
Aerial thermal infrared imagery indicated that much of the groundwater discharge in the southern part of the study area is focused across a 3-mile reach where the Elkhorn River turns southwest, perpendicular to the regional groundwater flow direction. Points of focused groundwater discharge were not detected with aerial thermal infrared imagery, indicating that groundwater discharge is diffuse rather than concentrated at focused points. Temperature-based streambed flux estimates indicated that strong regional groundwater gradients are not driving groundwater discharge and hyporheic flow is the dominant groundwater/surface-water exchange process.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195048","collaboration":"Prepared in cooperation with the Papio-Missouri River and Lower Platte North Natural Resources Districts and the Nebraska Department of Natural Resources","usgsCitation":"Hobza, C.M., Johnson, M.J., Woodward, P.W., Strauch, K.R., and Schepers, A.R., 2019, Groundwater movement and interaction with surface water near the confluence of the Platte and Elkhorn Rivers, Nebraska, 2016–18: U.S. Geological Survey Scientific Investigations Report 2019–5048, 38 p., https://doi.org/10.3133/sir20195048.","productDescription":"Report: vi, 38 p.; Data Release","numberOfPages":"48","onlineOnly":"Y","ipdsId":"IP-101680","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":365092,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5048/sir20195048.pdf","text":"Report","size":"4.36 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5048"},{"id":365093,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9EZLGSC","text":"USGS data release ","description":"USGS Data Release","linkHelpText":"Water-level and aerial thermal infrared imagery data collected along the lower Platte and Elkhorn Rivers, Nebraska, 2016–2017"},{"id":365091,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5048/coverthb.jpg"}],"country":"United States","state":"Nebraska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.503662109375,\n 40.613952441166596\n ],\n [\n -95.7073974609375,\n 40.613952441166596\n ],\n [\n -95.7073974609375,\n 42.09007006868398\n ],\n [\n -97.503662109375,\n 42.09007006868398\n ],\n [\n -97.503662109375,\n 40.613952441166596\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Nebraska Water Science Center
U.S. Geological Survey
5231 South 19th Street
Lincoln, NE 68512