Climate change threatens global biodiversity. Many species vulnerable to climate change are important to humans for nutritional, cultural, and economic reasons. Polar bears Ursus maritimus are threatened by sea-ice loss and represent a subsistence resource for Indigenous people. We applied a novel population modeling-management framework that is based on species life history and accounts for habitat loss to evaluate subsistence harvest for the Chukchi Sea (CS) polar bear subpopulation. Harvest strategies followed a state-dependent approach under which new data were used to update the harvest on a predetermined management interval. We found that a harvest strategy with a starting total harvest rate of 2.7% (˜85 bears/yr at current abundance), a 2:1 male-to-female ratio, and a 10-yr management interval would likely maintain subpopulation abundance above maximum net productivity level for the next 35 yr (approximately three polar bear generations), our primary criterion for sustainability. Plausible bounds on starting total harvest rate were 1.7–3.9%, where the range reflects uncertainty due to sampling variation, environmental variation, model selection, and differing levels of risk tolerance. The risk of undesired demographic outcomes (e.g., overharvest) was positively related to harvest rate, management interval, and projected declines in environmental carrying capacity; and negatively related to precision in population data. Results reflect several lines of evidence that the CS subpopulation has been productive in recent years, although it is uncertain how long this will last as sea-ice loss continues. Our methods provide a template for balancing trade-offs among protection, use, research investment, and other factors. Demographic risk assessment and state-dependent management will become increasingly important for harvested species, like polar bears, that exhibit spatiotemporal variation in their response to climate change.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.2461","usgsCitation":"Regehr, E.V., Runge, M.C., Von Duyke, A.L., Wilson, R., Polasek, L., Rode, K.D., Hostetter, N.J., and Converse, S.J., 2021, Demographic risk assessment for a harvested species threatened by climate change: Polar bears in the Chukchi Sea: Ecological Applications, v. 31, no. 8, e02461, 13 p., https://doi.org/10.1002/eap.2461.","productDescription":"e02461, 13 p.","ipdsId":"IP-119837","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":450636,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1002/eap.2461","text":"External Repository"},{"id":429876,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Russia, United States","otherGeospatial":"Chukchi Sea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -157.44241992486556,\n 73.07923094153199\n ],\n [\n -179.9,\n 73.07923094153199\n ],\n [\n -179.9,\n 66.33440002284189\n ],\n [\n -157.44241992486556,\n 66.33440002284189\n ],\n [\n -157.44241992486556,\n 73.07923094153199\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"31","issue":"8","noUsgsAuthors":false,"publicationDate":"2021-10-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Regehr, Eric V. 0000-0003-4487-3105","orcid":"https://orcid.org/0000-0003-4487-3105","contributorId":66364,"corporation":false,"usgs":false,"family":"Regehr","given":"Eric","email":"","middleInitial":"V.","affiliations":[{"id":12428,"text":"U. S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":902940,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Runge, Michael C. 0000-0002-8081-536X mrunge@usgs.gov","orcid":"https://orcid.org/0000-0002-8081-536X","contributorId":3358,"corporation":false,"usgs":true,"family":"Runge","given":"Michael","email":"mrunge@usgs.gov","middleInitial":"C.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":902941,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Von Duyke, Andrew L.","contributorId":214208,"corporation":false,"usgs":false,"family":"Von Duyke","given":"Andrew","email":"","middleInitial":"L.","affiliations":[{"id":38995,"text":"North Slope Borough Department of Wildlife Management","active":true,"usgs":false}],"preferred":false,"id":903129,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wilson, Ryan R. ","contributorId":222456,"corporation":false,"usgs":false,"family":"Wilson","given":"Ryan R. ","affiliations":[{"id":6654,"text":"USFWS","active":true,"usgs":false}],"preferred":false,"id":903130,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Polasek, Lori","contributorId":338318,"corporation":false,"usgs":false,"family":"Polasek","given":"Lori","email":"","affiliations":[],"preferred":false,"id":903131,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rode, Karyn D. 0000-0002-3328-8202 krode@usgs.gov","orcid":"https://orcid.org/0000-0002-3328-8202","contributorId":5053,"corporation":false,"usgs":true,"family":"Rode","given":"Karyn","email":"krode@usgs.gov","middleInitial":"D.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":902942,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hostetter, Nathan J. 0000-0001-6075-2157 nhostetter@usgs.gov","orcid":"https://orcid.org/0000-0001-6075-2157","contributorId":198843,"corporation":false,"usgs":true,"family":"Hostetter","given":"Nathan","email":"nhostetter@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":903132,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Converse, Sarah J. 0000-0002-3719-5441 sconverse@usgs.gov","orcid":"https://orcid.org/0000-0002-3719-5441","contributorId":173772,"corporation":false,"usgs":true,"family":"Converse","given":"Sarah","email":"sconverse@usgs.gov","middleInitial":"J.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":902943,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70224534,"text":"ofr20211080 - 2021 - Optimization of salt marsh management at the Rachel Carson National Wildlife Refuge, Maine, through use of structured decision making","interactions":[],"lastModifiedDate":"2021-09-29T11:36:22.700641","indexId":"ofr20211080","displayToPublicDate":"2021-09-28T09:20:00","publicationYear":"2021","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-1080","displayTitle":"Optimization of Salt Marsh Management at the Rachel Carson National Wildlife Refuge, Maine, Through Use of Structured Decision Making","title":"Optimization of salt marsh management at the Rachel Carson National Wildlife Refuge, Maine, through use of structured decision making","docAbstract":"Structured decision making is a systematic, transparent process for improving the quality of complex decisions by identifying measurable management objectives and feasible management actions; predicting the potential consequences of management actions relative to the stated objectives; and selecting a course of action that maximizes the total benefit achieved and balances tradeoffs among objectives. The U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service, applied an existing, regional framework for structured decision making to develop an example of a prototype tool for optimizing tidal marsh management decisions for selected marsh management units at the Rachel Carson National Wildlife Refuge in Maine. The goal was to create a prototype that could be available for future implementation. Refuge biologists, refuge managers, and research scientists identified multiple potential management actions to improve the ecological integrity of seven marsh management units within the refuge and estimated the outcomes of each action in terms of regional performance metrics associated with each management objective. Value functions previously developed at the regional level were used to transform metric scores to a common utility scale, and utilities were summed to produce a single score representing the total management benefit that could be accrued from each potential management action. Constrained optimization was used to identify the set of management actions, one per marsh management unit, that could maximize total management benefits at different cost constraints at the refuge scale.
Management costs were estimated using limited available information, and estimated costs of individual management actions reflected relative differences among actions rather than actual expected expenditures. Results from this prototype showed how, for the objectives, actions, and estimated outcomes used for this example, total management benefits may increase consistently up to a certain estimated cost, and may continue to increase, at a lower rate, with further expenditures. Potential management actions in optimal portfolios at moderate total estimated costs included breaching or removing dikes, roads, or embankments; planting Spartina alterniflora (smooth cordgrass); and digging runnels, or shallow creeks, on the marsh platform to improve surface-water drainage. Potential management actions in optimal portfolios at high estimated costs (for example, up to $550,000) included breaching embankments to restore tidal exchange followed by planting salt marsh vegetation. The potential management benefits were derived from predicted increases in the numbers of tidal marsh obligate birds and spiders (as an indicator of trophic health), and expected improvement in the capacity of marsh elevation to keep pace with sea-level rise and reduced duration of marsh-surface inundation. The prototype presented here does not resolve current management decisions; rather, it provides a framework for decision making at the Rachel Carson National Wildlife Refuge that can be updated for implementation as new data and information become available. Insights from this process may also be useful to inform future habitat management planning at the refuges.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211080","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Neckles, H.A., Lyons, J.E., Nagel, J.L., Adamowicz, S.C., Mikula, T., O’Brien, K.M., Benvenuti, B., and Kleinert, R., 2021, Optimization of salt marsh management at the Rachel Carson National Wildlife Refuge, Maine, through use of structured decision making: U.S. Geological Survey Open-File Report 2021–1080, 35 p., https://doi.org/10.3133/ofr20211080.","productDescription":"vi, 35 p.","numberOfPages":"35","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-126540","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":389743,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1080/coverthb.jpg"},{"id":389744,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1080/ofr20211080.pdf","text":"Report","size":"4.44 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1080"},{"id":389737,"rank":1,"type":{"id":9,"text":"Database"},"url":"https://ecos.fws.gov/ServCat/Reference/Profile/121918","text":"U.S. Fish and Wildlife Service database","linkHelpText":"- Salt marsh integrity and Hurricane Sandy vegetation, bird and nekton data"},{"id":389746,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1080/images/"},{"id":389747,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1080/ofr20211080.XML"}],"country":"United States","state":"Maine","otherGeospatial":"Rachel Carson National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.63796997070312,\n 43.20417480788432\n ],\n [\n -70.61325073242188,\n 43.153101551466385\n ],\n [\n -70.477294921875,\n 43.257205668363206\n ],\n [\n -70.43472290039062,\n 43.38508989465156\n ],\n [\n -70.53634643554688,\n 43.393073720674415\n ],\n [\n -70.63796997070312,\n 43.31418735795809\n ],\n [\n -70.63796997070312,\n 43.20417480788432\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Eastern Ecological Science Center
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11649 Leetown Road
Kearneysville, WV 25430
Using available data, the U.S. Geological Survey estimated that 306 billion cubic feet of recoverable helium is presently within the known geologic natural gas reservoirs of the United States.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215085","usgsCitation":"Brennan, S.T., Rivera, J.L., Varela, B.A., and Park, A.J., 2021, National assessment of helium resources within known natural gas reservoirs: U.S. Geological Survey Scientific Investigations Report 2021–5085, 5 p., https://doi.org/10.3133/sir20215085.","productDescription":"Report: vi, 5 p.; Data Release","numberOfPages":"5","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-112618","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":389388,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20215085/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"SIR 2021-5085"},{"id":389060,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P92QL79J","text":"USGS data release","linkHelpText":"Dataset of helium concentrations in United States wells"},{"id":389058,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5085/coverthb.jpg"},{"id":389059,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5085/sir20215085.pdf","text":"Report","size":"4.28 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5085"},{"id":389386,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5085/images/"},{"id":389385,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5085/sir20215085.XML"}],"contact":"Director, Energy Resources Program
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The Los Angeles Coastal Plain (LACP) covers about 580 square miles and is the largest coastal plain of semiarid southern California. The LACP is heavily developed with mostly residential, commercial, and industrial land uses that rely heavily on groundwater for water supply. In 2010, the LACP was home to about 14 percent of California’s population, or about 5.4 million residents. The LACP is also a major commercial and industrial hub with industries including manufacturing, aerospace, entertainment, and tourism.
There has been a heavy reliance on groundwater from the LACP for many years. An average of 305,000 acre-feet per year (acre-ft/yr) of groundwater was used annually from the LACP from 1971 to 2015. The need to replenish the groundwater basins within the LACP was recognized as far back as the 1930s, when spreading grounds were first used to replenish groundwater basins and store water underground during times of water surplus to meet demands in times of shortage. Seawater intrusion resulting from freshwater pumping was first observed in the 1940s. As a result, injection of imported water through wells at what is now the West Coast Basin Barrier Project began on an experimental basis in 1951. Managed aquifer recharge from the spreading grounds and barrier wells is now a substantial component of the LACP’s groundwater supply. The average annual recharge from water spreading from 1971 to 2015 was about 120,000 acre-ft/yr, and the average annual injection into the barrier wells was about 33,000 acre-ft/yr. Other inflows include areal recharge, underflow from San Gabriel and San Fernando Valleys, and onshore flow from the ocean. The average annual recharge from these sources was 100,000 acre-feet (acre-ft) from 1971 to 2015. Additionally, cross-boundary flow from Orange County into the western Orange County subareas of the LACP was simulated as 48,000 acre-ft from 1971 to 2015.
This study, conducted in cooperation with the Water Replenishment District of Southern California (WRD), involved an assessment of the historical and present status of groundwater resources in the LACP and the development of tools to better understand the groundwater system. These efforts were built upon results from previous studies and incorporate new information and developments in modeling capabilities to provide a more detailed analysis of the aquifer systems.
This study includes a comprehensive compilation of geologic and hydrologic data (Chapter A), development of a chronostratigraphic model that provides a detailed description of the LACP aquifer systems (Chapter B), characterization of the groundwater hydrology of the LACP, including a down-hole analysis of grain size using lithologic and geophysical logs (Chapter C), and development and application of the Los Angeles Coastal Plain Groundwater-flow Model (LACPGM) to simulate past groundwater conditions, estimate groundwater-budget components and flow paths, and approximate future groundwater conditions under different scenarios (Chapter D).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215088","collaboration":"Prepared in cooperation with the Water Replenishment District of Southern California","usgsCitation":"Paulinski, S., ed., 2021, Development of a groundwater-simulation model in the Los Angeles Coastal Plain, Los Angeles County, California (ver. 1.1, May 2023): U.S. Geological Survey Scientific Investigations Report 2021-5088, 489 p., https://doi.org/10.3133/sir20215088.","productDescription":"Report: xiii, 489 p.; Data Release","numberOfPages":"489","onlineOnly":"Y","ipdsId":"IP-023155","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":389755,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9H15ZAX","linkHelpText":"MODFLOW-USG model used to evaluate water management issues in the Los Angeles Coastal Plain, California"},{"id":389754,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5088/sir20215088_v1.1.pdf","text":"Report","size":"66 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":389753,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5088/covrthb_.jpg"},{"id":416877,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2021/5088/versionHist.txt","size":"2 KB","linkFileType":{"id":2,"text":"txt"}},{"id":436182,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TJD4IE","text":"USGS data release","linkHelpText":"MODFLOW-6 model to update and extend the Los Angeles Coastal Plain Groundwater Model"},{"id":500446,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_111785.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"California","county":"Los Angeles County","otherGeospatial":"Los Angeles Coastal Plain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.90802001953125,\n 33.59860671494885\n ],\n [\n -117.59490966796875,\n 33.876116579321206\n ],\n [\n -117.82012939453125,\n 34.14249823152873\n ],\n [\n -118.20327758789062,\n 34.23337699755914\n ],\n [\n -118.53973388671874,\n 34.03672867489511\n ],\n [\n -118.41476440429686,\n 33.80083235326659\n ],\n [\n -118.24722290039061,\n 33.72776616734189\n ],\n [\n -117.90802001953125,\n 33.59860671494885\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: September 2021; Version 1.1: May 2023","contact":"Director,
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Some avian species have developed the capacity to leverage resource subsidies associated with human manipulated landscapes to increase population densities in habitats with naturally low carrying capacities. Elevated corvid densities and new territory establishment have led to an unsustainable increase in depredation pressure on sympatric native wildlife prey populations as well as in crop damage. Yet, subsidized predator removal programs aimed at reducing densities are likely most effective longer-term when conducted in tandem with subsidy control, habitat management, and robust assessment monitoring programs. We developed decision support software that leverages stage structured Lefkovitch population matrices to compare and identify treatment strategies that reduce subsidized avian predator densities most efficiently, in terms of limiting both cost and take levels. The StallPOPd (Version 4; available at https://doi.org/10.7298/sk2e-0c38.4) software enables managers to enter the area of their management stratum and the demographic properties (vital rates) of target bird population(s) of interest to evaluate strategies to decrease or curtail further population growth. Strategies explicitly include the reduction in fertility (i.e., eggs hatched) and/or the culling of hatchlings, non-breeders and/or breeders, but implicitly comprise reduction in survival or reproduction through subsidy denial. We illustrate the utilities of the software with examples using common ravens (Corvus corax; ravens) in the Mojave Desert of California, USA. Unfortunately, the survival and reproduction effects of each unit of a particular subsidy in that system have remained elusive, though this is the priority of current research. Because the software leverages a life history representation that is known to characterize hundreds of wildlife species in addition to ravens, the work expands the suite of tools available to wildlife managers and agricultural industry specialists to abate bird damage and impacts on sensitive wildlife in habitats with persistent human subsidies.
Schistosome parasites infect more than 200 million people annually, mostly in sub-Saharan Africa, where people may be co-infected with more than one species of the parasite. Infection risk for any single species is determined, in part, by the distribution of its obligate intermediate host snail. As the World Health Organization reprioritizes snail control to reduce the global burden of schistosomiasis, there is renewed importance in knowing when and where to target those efforts, which could vary by schistosome species. This study estimates factors associated with schistosomiasis risk in 16 villages located in the Senegal River Basin, a region hyperendemic for Schistosoma haematobium and S. mansoni. We first analyzed the spatial distributions of the two schistosomes’ intermediate host snails (Bulinus spp. and Biomphalaria pfeifferi, respectively) at village water access sites. Then, we separately evaluated the relationships between human S. haematobium and S. mansoni infections and (i) the area of remotely-sensed snail habitat across spatial extents ranging from 1 to 120 m from shorelines, and (ii) water access site size and shape characteristics. We compared the influence of snail habitat across spatial extents because, while snail sampling is traditionally done near shorelines, we hypothesized that snails further from shore also contribute to infection risk. We found that, controlling for demographic variables, human risk for S. haematobium infection was positively correlated with snail habitat when snail habitat was measured over a much greater radius from shore (45 m to 120 m) than usual. S. haematobium risk was also associated with large, open water access sites. However, S. mansoni infection risk was associated with small, sheltered water access sites, and was not positively correlated with snail habitat at any spatial sampling radius. Our findings highlight the need to consider different ecological and environmental factors driving the transmission of each schistosome species in co-endemic landscapes.
A numerical groundwater flow model of the Hualapai Valley Basin in northwestern Arizona was developed to assist water-resource managers in understanding the potential effects of projected groundwater withdrawals on groundwater levels in the basin. The Hualapai Valley Hydrologic Model (HVHM) simulates the hydrologic system for the years 1935 through 2219, including future withdrawal scenarios that simulate large-scale agricultural expansion with and without enhanced groundwater recharge from potential new infiltration basin projects. HVHM is a highly parameterized model (75,586 adjustable parameters) capable of simulating grid-scale variability in aquifer properties (for example, conductivity, specific yield, and specific storage) and system stresses (for instance, natural recharge and groundwater withdrawals). Parameter estimation and uncertainty quantification were performed using an iterative ensemble smoother software (PESTPP-IES) to produce an ensemble of models fit to historical data. Results via the future withdrawal scenario from this ensemble indicate that mean groundwater level will decline at wells in the Kingman subbasin 87 to 128 feet by the year 2050 and 204 to 241 feet by the year 2080. Mean groundwater level is expected to decline at wells in the Hualapai subbasin between 44 and 210 feet by 2050 and between 107 and 350 feet by 2080. The enhanced recharge scenario results show potential for these declines to be partially mitigated in the Kingman subbasin by between 8 and 23 feet in 2050 and between 23 and 43 feet in 2080. The enhanced recharge scenario has no simulated effect on groundwater levels in the Hualapai subbasin. All planned enhanced infiltration projects are located in the Kingman subbasin, which is simulated to become hydraulically disconnected from the Hualapai subbasin owing to groundwater-level declines before 2050. Mean depth to water in the Kingman subbasin as simulated in the future withdrawal scenario will exceed 1,200 feet between the years 2155 and 2214 (median year 2171). In the future withdrawal plus enhanced recharge scenario, mean depth to water in the Kingman subbasin exceeds 1,200 feet between the years 2163 and 2207 (median year 2180), except for one model realization in which the subbasin does not reach an mean depth to water of 1,200 feet by the end of forecast simulation (year 2220). Simulated dewatering of the basin margins reduces scenario pumping rates by as much as 7 percent in 2029 and 12 percent in 2079 below specified rates. Forecasts of groundwater-level declines are based on the reduced simulated pumping rates.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215077","collaboration":"Prepared in cooperation with Mohave County and the City of Kingman","usgsCitation":"Knight, J.E., Gungle, B., and Kennedy, J.R., 2021, Assessing potential groundwater-level declines from future withdrawals in the Hualapai Valley, northwestern Arizona: U.S. Geological Survey Scientific Investigations Report, 63 p., https://doi.org/10.3133/sir20215077.","productDescription":"Report: vii, 63 p.; Data Release","numberOfPages":"63","onlineOnly":"Y","ipdsId":"IP-118946","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":436183,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MJRMSQ","text":"USGS data release","linkHelpText":"Repeat microgravity data from the Hualapai Valley, Mohave County, Arizona, 2008-2019"},{"id":389758,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20125275","text":"Scientific Investigations Report 2012-5275","linkHelpText":"— Hydrogeologic framework and estimates of groundwater storage for the Hualapai Valley, Detrital Valley, and Sacramento Valley basins, Mohave County, Arizona"},{"id":389739,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5077/sir20215077.pdf","text":"Report","size":"26 MB"},{"id":389759,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20135122","text":"Scientific Investigations Report 2013-5122","linkHelpText":"— Preliminary groundwater flow model of the basin-fill aquifers in Detrital, Hualapai, and Sacramento Valleys, Mohave County, northwestern Arizona"},{"id":389740,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9017DI9","linkHelpText":"Data release for transient groundwater model of the Hualapai Valley Groundwater Basin, Mohave County, Arizona"},{"id":389738,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5077/covrthb.jpg"},{"id":389756,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20075182","text":"Scientific Investigations Report 2007-5182","linkHelpText":"— Ground-Water Occurrence and Movement, 2006, and Water-Level Changes in the Detrital, Hualapai, and Sacramento Valley Basins, Mohave County, Arizona"},{"id":389757,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/sir20115159","text":"Scientific Investigations Report 2011-5159","linkHelpText":"— Groundwater budgets for Detrital, Hualapai, and Sacramento Valleys, Mohave County, Arizona, 2007-08"}],"country":"United States","state":"Arizona","otherGeospatial":"Hualapai Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.5,\n 36\n ],\n [\n -113.5,\n 36\n ],\n [\n -113.5,\n 35\n ],\n [\n -114.5,\n 35\n ],\n [\n -114.5,\n 36\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Arizona Water Science Center
U.S. Geological Survey
520 N. Park Avenue
Tucson, AZ 85719
Reproductive strategies are an essential component of invasion ecology that influence invasion success and rates of population growth. Burmese Pythons (Python bivittatus) are large constrictor snakes that were introduced to the Greater Everglades Ecosystem of southern Florida, USA, from Asia. Since their introduction, these giant constrictors have spread throughout wetlands of southern Florida while increasing in abundance and causing declines in the native species upon which they prey. Multiple paternity in reproduction could facilitate invasion success by increasing the genetic diversity produced within each reproductive event. We used Diversity Arrays Technology genome-wide genotyping to assess multiple paternity in the progeny of wild Burmese Pythons in Florida. We analyzed >4,000 single nucleotide polymorphisms from 153 neonates belonging to 4 clutches collected in southwestern Florida. Complementary hierarchical and K-means clustering analyses of the genetic distances within clutches revealed that three clutches were each fertilized by two sires, with a fourth fertilized by a single sire. The proportions of offspring attributable to each sire within multiple paternity clutches ranged from nearly even to highly skewed. Analysis of multivariate dispersion showed significantly increased genetic variability in the multiple paternity clutches. These results improve our understanding of the reproductive strategy and invasion potential of a giant constrictor with significant ecological impacts.
Most studies of the ecological effects of climate change consider only a limited number of weather drivers that could affect populations, though we know that multiple weather drivers can simultaneously affect population growth rate. Multiple drivers could simultaneously increase/decrease one vital rate, or one may increase a vital rate while another decreases the same vital rate. Considering the impact of multiple weather drivers on vital rates is particularly important in a changing climate, in which correlations among drivers may not be preserved in the future. We used a long-term dataset on the endangered red-cockaded woodpecker (Dryobates borealis) to understand how multiple weather drivers jointly affect survival and reproductive vital rates and then assessed the contributions of individual weather drivers to historical trends in vital rates over time. We found that vital rates were often influenced by more than one weather driver and that weather drivers most commonly exerted opposing effects. For instance, some weather drivers increased vital rates over time, while others acted in the opposite direction, decreasing vital rates over time. Importantly, the historical correlations among weather drivers are almost always projected to change in the future climate, such that future trends in vital rates may not match historical trends. For example, we do not find historical trends in adult survival, but changing correlations among weather drivers could generate future trends in this vital rate. Our work provides an example of how multiple weather drivers can control a variety of vital rates and also illustrates how changes in the correlation structure of weather drivers through time might substantially affect future trends in individual and population performance.
Alewife (Alosa pseudoharengus) and blueback herring (Alosa aestivalis) are iteroparous anadromous fish found throughout the East Coast of North America. The phenology of anadromous fish migrations is important for fitness, and the duration of spawning migrations has been compressed in recent years in response to climate change. Anthropogenic barriers to movement, such as dams and culverts at road-stream crossings, can further disrupt migration phenology by delaying movement and increasing predation risk. We used passive integrated transponder (PIT) telemetry to quantify upstream and downstream migratory delay at five road-stream-crossing culverts on the Herring River (MA, USA). Groundspeeds were reduced at all culverts in both directions, confirming that the culverts impede movement despite high passage proportions. The cumulative delay of the culverts on the upstream migration was sufficient to more than double the amount of time required to traverse the river if the culverts had been absent. Furthermore, the presence of snapping turtles (Chelydra serpentina) ambushing river herring within one of the culverts resulted in reduced passage rates beyond the reduction in movement caused by the physical structure itself. This highlights that physical barriers can create cascading ecological consequences and the importance of taking a holistic approach to understanding barrier effects.
Basin-centric long short-term memory (LSTM) network models have recently been shown to be an exceptionally powerful tool for stream temperature (Ts) temporal prediction (training in one period and predicting in another period at the same sites). However, spatial extrapolation is a well-known challenge to modelling Ts and it is uncertain how an LSTM-based daily Ts model will perform in unmonitored or dammed basins. Here we compiled a new benchmark dataset consisting of >400 basins across the contiguous United States in different data availability groups (DAG, meaning the daily sampling frequency) with and without major dams, and studied how to assemble suitable training datasets for predictions in basins with or without temperature monitoring. For prediction in unmonitored basins (PUB), LSTM produced a root-mean-square error (RMSE) of 1.129°C and an R2 of 0.983. While these metrics declined from LSTM's temporal prediction performance, they far surpassed traditional models' PUB values, and were competitive with traditional models' temporal prediction on calibrated sites. Even for unmonitored basins with major reservoirs, we obtained a median RMSE of 1.202°C and an R2 of 0.984. For temporal prediction, the most suitable training set was the matching DAG that the basin could be grouped into (for example, the 60% DAG was most suitable for a basin with 61% data availability). However, for PUB, a training dataset including all basins with data was consistently preferred. An input-selection ensemble moderately mitigated attribute overfitting. Our results indicate there are influential latent processes not sufficiently described by the inputs (e.g., geology, wetland covers), but temporal fluctuations can still be predicted well, and LSTM appears to be a highly accurate Ts modelling tool even for spatial extrapolation.
In regions where water resources are scarce and in high demand, it is important to safeguard against contamination of groundwater aquifers by oil-field fluids (water, gas, oil). In this context, the geochemical characterisation of these fluids is critical so that anthropogenic contaminants can be readily identified. The first step is characterising pre-development geochemical fluid signatures (i.e., those unmodified by hydrocarbon resource development) and understanding how these signatures may have been perturbed by resource production, particularly in the context of enhanced oil recovery (EOR) techniques. Here, we present noble gas isotope data in fluids produced from oil wells in several water-stressed regions in California, USA, where EOR is prevalent. In oil-field systems, only casing gases are typically collected and measured for their noble gas compositions, even when oil and/or water phases are present, due to the relative ease of gas analyses. However, this approach relies on a number of assumptions (e.g., equilibrium between phases, water-to-oil ratio (WOR) and gas-to-oil ratio (GOR) in order to reconstruct the multiphase subsurface compositions. Here, we adopt a novel, more rigorous approach, and measure noble gases in both casing gas and produced fluid (oil-water-gas mixtures) samples from the Lost Hills, Fruitvale, North and South Belridge (San Joaquin Basin, SJB) and Orcutt (Santa Maria Basin) Oil Fields. Using this method, we are able to fully characterise the distribution of noble gases within a multiphase hydrocarbon system. We find that measured concentrations in the casing gases agree with those in the gas phase in the produced fluids and thus the two sample types can be used essentially interchangeably.
EOR signatures can readily be identified by their distinct air-derived noble gas elemental ratios (e.g., 20Ne/36Ar), which are elevated compared to pre-development oil-field fluids, and conspicuously trend towards air values with respect to elemental ratios and overall concentrations. We reconstruct reservoir 20Ne/36Ar values using both casing gas and produced fluids and show that noble gas ratios in the reservoir are strongly correlated (r2 = 0.88–0.98) to the amount of water injected within ~500 m of a well. We suggest that the 20Ne/36Ar increase resulting from injection is sensitive to the volume of fluid interacting with the injectate, the effective water-to-oil ratio, and the composition of the injectate. Defining both the pre-development and injection-modified hydrocarbon reservoir compositions are crucial for distinguishing the sources of hydrocarbons observed in proximal groundwaters, and for quantifying the transport mechanisms controlling this occurrence.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.chemgeo.2021.120540","usgsCitation":"Tyne, R.L., Barry, P.H., Karolytė, R., Bryne, D.J., Kulongoski, J.T., Hillegonds, D., and Ballentine, C.J., 2021, Investigating the effect of enhanced oil recovery on the noble gas signature of casing gases and produced waters from selected California oil fields: Chemical Geology, v. 584, 120540, 10 p., https://doi.org/10.1016/j.chemgeo.2021.120540.","productDescription":"120540, 10 p.","ipdsId":"IP-126638","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":450655,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.chemgeo.2021.120540","text":"Publisher Index Page"},{"id":393752,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","county":"Kern County","otherGeospatial":"Fruitvale, Lost Hills and North and South Belridge Oil Fields","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.73150634765625,\n 34.4069096565206\n ],\n [\n -119.24011230468749,\n 34.4069096565206\n ],\n [\n -119.24011230468749,\n 35.85566574217861\n ],\n [\n -120.73150634765625,\n 35.85566574217861\n ],\n [\n -120.73150634765625,\n 34.4069096565206\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"584","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Tyne, R. L.","contributorId":205891,"corporation":false,"usgs":false,"family":"Tyne","given":"R.","email":"","middleInitial":"L.","affiliations":[{"id":37187,"text":"Department of Earth Sciences, University of Oxford, Oxford, UK","active":true,"usgs":false}],"preferred":false,"id":829842,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barry, P. H.","contributorId":270728,"corporation":false,"usgs":false,"family":"Barry","given":"P.","email":"","middleInitial":"H.","affiliations":[{"id":56200,"text":"Dept. of Marine Chem. and Geochem., Woods Hole Oceanographic Institution, Woods Hole, MA, USA","active":true,"usgs":false}],"preferred":false,"id":829843,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Karolytė, R.","contributorId":270729,"corporation":false,"usgs":false,"family":"Karolytė","given":"R.","affiliations":[{"id":56201,"text":"Dept. of Earth Sci., University of Oxford, Oxford, UK","active":true,"usgs":false}],"preferred":false,"id":829844,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bryne, D. J.","contributorId":270730,"corporation":false,"usgs":false,"family":"Bryne","given":"D.","email":"","middleInitial":"J.","affiliations":[{"id":56201,"text":"Dept. of Earth Sci., University of Oxford, Oxford, UK","active":true,"usgs":false}],"preferred":false,"id":829845,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kulongoski, Justin T. 0000-0002-3498-4154 kulongos@usgs.gov","orcid":"https://orcid.org/0000-0002-3498-4154","contributorId":173457,"corporation":false,"usgs":true,"family":"Kulongoski","given":"Justin","email":"kulongos@usgs.gov","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":829846,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hillegonds, D.J.","contributorId":205892,"corporation":false,"usgs":false,"family":"Hillegonds","given":"D.J.","email":"","affiliations":[{"id":37187,"text":"Department of Earth Sciences, University of Oxford, Oxford, UK","active":true,"usgs":false}],"preferred":false,"id":829847,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ballentine, C. J.","contributorId":224737,"corporation":false,"usgs":false,"family":"Ballentine","given":"C.","email":"","middleInitial":"J.","affiliations":[{"id":40928,"text":"Oxford University","active":true,"usgs":false}],"preferred":false,"id":829848,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70224530,"text":"70224530 - 2021 - A simplified method for rapid estimation of emergency water supply needs after earthquakes","interactions":[],"lastModifiedDate":"2022-12-23T17:20:52.03908","indexId":"70224530","displayToPublicDate":"2021-09-25T09:53:24","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3709,"text":"Water","active":true,"publicationSubtype":{"id":10}},"title":"A simplified method for rapid estimation of emergency water supply needs after earthquakes","docAbstract":"Researchers are investigating the problem of estimating households with potable water service outages soon after an earthquake. Most of these modeling approaches are computationally intensive, have large proprietary data collection requirements or lack precision, making them unfeasible for rapid assessment, prioritization, and allocation of emergency water resources in large, complex disasters. This study proposes a new simplified analytical method—performed without proprietary water pipeline data—to estimate water supply needs after earthquakes, and a case study of its application in the HayWired earthquake scenario. In the HayWired scenario—a moment magnitude (Mw) 7.0 Hayward Fault earthquake in the San Francisco Bay Area, California (USA)—an analysis of potable water supply in two water utility districts was performed using the University of Colorado Water Network (CUWNet) model. In the case study, application of the simplified method extends these estimates of household water service outage to the nine counties adjacent to the San Francisco Bay, aggregated by a ~250 m2 (nine-arcsecond) grid. The study estimates about 1.38 million households (3.7 million residents) out of 7.6 million residents (2017, ambient, nighttime population) with potable water service outage soon after the earthquake—about an 8% increase from the HayWired scenario estimates.
","language":"English","publisher":"MDPI","doi":"10.3390/w13192635","usgsCitation":"Toland, J.C., and Wein, A., 2021, A simplified method for rapid estimation of emergency water supply needs after earthquakes: Water, v. 13, 2635, 27 p., https://doi.org/10.3390/w13192635.","productDescription":"2635, 27 p.","ipdsId":"IP-132813","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":450658,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/w13192635","text":"Publisher Index Page"},{"id":389813,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.79968261718749,\n 37.24782120155428\n ],\n [\n -121.55273437499999,\n 37.24782120155428\n ],\n [\n -121.55273437499999,\n 38.324420427006544\n ],\n [\n -122.79968261718749,\n 38.324420427006544\n ],\n [\n -122.79968261718749,\n 37.24782120155428\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","noUsgsAuthors":false,"publicationDate":"2021-09-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Toland, Joseph Charles 0000-0002-0092-0320","orcid":"https://orcid.org/0000-0002-0092-0320","contributorId":265976,"corporation":false,"usgs":true,"family":"Toland","given":"Joseph","email":"","middleInitial":"Charles","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":823911,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wein, Anne 0000-0002-5516-3697 awein@usgs.gov","orcid":"https://orcid.org/0000-0002-5516-3697","contributorId":589,"corporation":false,"usgs":true,"family":"Wein","given":"Anne","email":"awein@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":823912,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70252830,"text":"70252830 - 2021 - Age-0 Silver Carp otolith microchemistry and microstructure reveal multiple early life environments and protracted spawning in the upper Mississippi River","interactions":[],"lastModifiedDate":"2024-09-18T15:42:36.007312","indexId":"70252830","displayToPublicDate":"2021-09-25T06:43:02","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Age-0 Silver Carp otolith microchemistry and microstructure reveal multiple early life environments and protracted spawning in the upper Mississippi River","docAbstract":"Silver Carp Hypophthalmichthys molitrix are highly mobile and fecund planktivorous cyprinids that have invaded much of the Mississippi River and are known to alter food webs and compete with native planktivores. In 2016, for the first time, an abundance of age-0 Silver Carp (n = 12,208; 16–231 mm) were captured at many (n = 11) sites upstream of Lock and Dam 19 on the upper Mississippi River. Previous reports were of a few individuals at a few locations; however, effort to capture juveniles of this size was likely less in previous years. Determining the origin, frequency, and timing of the reproductive events that led to this large year-class is important for determining control strategies. We used otolith microstructure and microchemistry from age-0 Silver Carp to estimate timing and frequency of spawning and early life environments of these fish. Hatch dates were determined from the lapillus otoliths of 190 age-0 Silver Carp (16–231 mm), and early life environments were identified from otolith microchemistry for 124 of these fish (64–231 mm). Age-0 Silver Carp were collected from Pools 18 and 19 during July–October 2016 by using a variety of sampling gears. We identified 10 cohorts with hatch dates ranging from May to August 2016 and with main-stem Mississippi River (75%) and tributary (23%) early life signatures. Tributary otolith chemistry signatures were present in all cohorts between May and July (n = 8) but were absent from the August cohorts (n = 2). Our results indicate that tributaries and small tributary streams, in addition to the main-stem river, play an important role in Silver Carp recruitment in areas near the reproductive front, where management actions (e.g., contract removal and deterrents) are often targeted.
Nutrients, harmful algal blooms, and synthetic chemicals like per- and polyfluoroalkyl substances (PFAS) and 1,4-dioxane threaten Long Island’s water resources by affecting the quality of drinking water and ecologically sensitive habitats that support the diverse wildlife throughout the island. Understanding the occurrence, fate, and transport of these potentially harmful chemicals is critical to protect these vital resources. The U.S. Geological Survey (USGS) is collecting and analyzing data to support informed water-resource management decisions. This fact sheet introduces ongoing efforts and future areas of study aimed to help water professionals develop a comprehensive science strategy to address contamination of the Long Island aquifer system, the sole source of drinking water for nearly 3 million people. These studies include surface and groundwater collection and groundwater flow modeling. Funding for the data collection has been provided by the USGS, New York State Department of Environmental Conservation, New York City Department of Environmental Protection, Suffolk County Water Authority, Nassau County Department of Public Works, State and local agencies, and Tribal and Federal partners. Without the foresight and long-term commitment of these funding partners, evaluating sustainability and planning for future water needs would not be possible.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20213044","usgsCitation":"Breault, R.F., Masterson, J.P., Schubert, C.E., and Herdman, L.M., 2021, Managing water resources on Long Island, New York, with integrated, multidisciplinary science: U.S. Geological Survey Fact Sheet 2021–3044, 4 p., https://doi.org/10.3133/fs20213044.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-131602","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":389579,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2021/3044/fs20213044.pdf","text":"Report","size":"14.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2021-3044"},{"id":389578,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2021/3044/coverthb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Long Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.0478515625,\n 40.538851525354666\n ],\n [\n -73.7677001953125,\n 40.538851525354666\n ],\n [\n -73.1304931640625,\n 40.60561205826018\n ],\n [\n -72.5537109375,\n 40.76806170936614\n ],\n [\n -71.9549560546875,\n 40.97575093157534\n ],\n [\n -71.83959960937499,\n 41.10832999732831\n ],\n [\n -72.1417236328125,\n 41.24064190269475\n ],\n [\n -72.8338623046875,\n 41.10005163093046\n ],\n [\n -73.5205078125,\n 40.96330795307353\n ],\n [\n -73.883056640625,\n 40.83043687764923\n ],\n [\n -74.06982421875,\n 40.713955826286046\n ],\n [\n -74.0863037109375,\n 40.61812224225511\n ],\n [\n -74.0478515625,\n 40.538851525354666\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180–8349
The Columbia River Gorge is the Columbia River’s long-held yet evolving passage through the volcanic arc of the Cascade Range. The globally unique setting of a continental-scale river bisecting an active volcanic arc at the leading edge of a major plate boundary creates a remarkable setting where dynamic volcanic and tectonic processes interact with diverse and energetic fluvial processes. This three-day field trip explores several elements of the gorge and its remarkable geologic history—cast here as a contest between regional tectonic and volcanic processes building and displacing landscapes, and the relentless power of the Columbia River striving to maintain a smooth passage to the sea.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"From terranes to terrains: Geologic field guides on the construction and destruction of the Pacific Northwest","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Geological Society of America","doi":"10.1130/2021.0062(05)","usgsCitation":"O'Connor, J., Wells, R., Bennett, S.E., Cannon, C.M., Staisch, L.M., Anderson, J.L., Pivarunas, A.F., Gordon, G.W., Blakely, R.J., Stelten, M.E., and Evarts, R.C., 2021, Arc versus river: The geology of the Columbia River Gorge, chap. of From terranes to terrains: Geologic field guides on the construction and destruction of the Pacific Northwest, v. 62, p. 131-186, https://doi.org/10.1130/2021.0062(05).","productDescription":"56 p.","startPage":"131","endPage":"186","ipdsId":"IP-130012","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":421267,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon, Washington","otherGeospatial":"Columbia River Gorge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123,\n 46.5\n ],\n [\n -123,\n 45\n ],\n [\n -120.5,\n 45\n ],\n [\n -120.5,\n 46.5\n ],\n [\n -123,\n 46.5\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"62","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"O'Connor, Jim E. 0000-0002-7928-5883 oconnor@usgs.gov","orcid":"https://orcid.org/0000-0002-7928-5883","contributorId":140771,"corporation":false,"usgs":true,"family":"O'Connor","given":"Jim E.","email":"oconnor@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":884307,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wells, Ray 0000-0002-7796-0160","orcid":"https://orcid.org/0000-0002-7796-0160","contributorId":204016,"corporation":false,"usgs":true,"family":"Wells","given":"Ray","affiliations":[{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":884308,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bennett, Scott E.K. 0000-0002-9772-4122 sekbennett@usgs.gov","orcid":"https://orcid.org/0000-0002-9772-4122","contributorId":5340,"corporation":false,"usgs":true,"family":"Bennett","given":"Scott","email":"sekbennett@usgs.gov","middleInitial":"E.K.","affiliations":[{"id":237,"text":"Earthquake Science 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lstaisch@usgs.gov","orcid":"https://orcid.org/0000-0002-1414-5994","contributorId":167068,"corporation":false,"usgs":true,"family":"Staisch","given":"Lydia","email":"lstaisch@usgs.gov","middleInitial":"M.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":884311,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Anderson, James L","contributorId":330199,"corporation":false,"usgs":false,"family":"Anderson","given":"James","email":"","middleInitial":"L","affiliations":[{"id":36402,"text":"University of Hawaii","active":true,"usgs":false}],"preferred":false,"id":884312,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Pivarunas, Anthony Francis 0000-0002-0003-2059","orcid":"https://orcid.org/0000-0002-0003-2059","contributorId":301014,"corporation":false,"usgs":true,"family":"Pivarunas","given":"Anthony","email":"","middleInitial":"Francis","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":884313,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gordon, Gabriel Wells 0000-0003-0937-6250 ggordon@usgs.gov","orcid":"https://orcid.org/0000-0003-0937-6250","contributorId":330200,"corporation":false,"usgs":true,"family":"Gordon","given":"Gabriel","email":"ggordon@usgs.gov","middleInitial":"Wells","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":884314,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Blakely, Richard J. 0000-0003-1701-5236 blakely@usgs.gov","orcid":"https://orcid.org/0000-0003-1701-5236","contributorId":1540,"corporation":false,"usgs":true,"family":"Blakely","given":"Richard","email":"blakely@usgs.gov","middleInitial":"J.","affiliations":[{"id":662,"text":"Western Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":884315,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Stelten, Mark E. 0000-0002-5294-3161 mstelten@usgs.gov","orcid":"https://orcid.org/0000-0002-5294-3161","contributorId":145923,"corporation":false,"usgs":true,"family":"Stelten","given":"Mark","email":"mstelten@usgs.gov","middleInitial":"E.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":884316,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Evarts, Russell C. 0000-0001-5103-9085 revarts@usgs.gov","orcid":"https://orcid.org/0000-0001-5103-9085","contributorId":295784,"corporation":false,"usgs":true,"family":"Evarts","given":"Russell","email":"revarts@usgs.gov","middleInitial":"C.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":884317,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70211246,"text":"70211246 - 2021 - Paleozoic and Mesozoic tectonic events west of the Waterbury Dome: Results of new mapping in the western Connecticut Highlands","interactions":[],"lastModifiedDate":"2022-04-19T16:09:25.677111","indexId":"70211246","displayToPublicDate":"2021-09-24T11:01:40","publicationYear":"2021","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Paleozoic and Mesozoic tectonic events west of the Waterbury Dome: Results of new mapping in the western Connecticut Highlands","docAbstract":"This field trip highlights the results of recent U.S. Geological Survey (USGS) bedrock geologic mapping in four 7.5 min quadrangles in the western Connecticut highlands near Southbury, Connecticut, USA. The rocks are broadly within what Rodgers (1985) called the Hartland and Gneiss Dome belts of the Connecticut Valley Synclinorium (Rodgers, 1985; Fig. 1), the latter of which is now known as the Connecticut Valley–Gaspe Trough (Hibbard et al., 2006). The mapping occurred over two intervals: 2003–2005 and 2016–present. In the first, the goal was a detailed map of the early Mesozoic Pomperaug basin, which overlaps the four quadrangles. Portions of the basin had been separately mapped during the statewide 7.5 min quadrangle mapping campaign spanning the 1950s–1970s, resulting in an inaccurate depiction of the basin on the 1985 state geologic map (Rodgers, 1985). A new map of the basin was proposed in part to benefit an ongoing project by the USGS Connecticut Water Science Center to determine the contributions of natural and artificial contaminants to a public water-supply well in Woodbury, Connecticut, under the National Water-Quality Assessment (NAWQA) Program (Starn and Brown, 2007). The NAWQA project was partially funded by the Pomperaug River Watershed Coalition, which also provided logistical support to the geologic mapping project. Mapping of the basin was also a high priority for the Connecticut State Geologist at the time (Ralph Lewis, 2002, pers. comm.). The mapping resulted in an NEIGC (New England Intercollegiate Geologic Conference) field guide (Burton et al., 2005) and a 1:12,000-scale USGS open-file map (Burton, 2006) and was funded by the USGS National Cooperative Geologic Mapping Program (NCGMP).
The second phase of the mapping began in 2016 after the discovery of elevated levels of uranium and arsenic in domestic water wells in the igneous and metamorphic rocks that surround the sedimentary and volcanic rocks of the Pomperaug basin (Flanagan and Brown, 2017). Structural measurements in the surrounding crystalline rocks were made during Pomperaug basin mapping to better understand the tectonic setting, but a revision of the crystalline map units on Rodgers’ 1985 geologic map was not attempted. Nonetheless, discrepancies were noted between the new mapping and the 1985 map, particularly within the two northern quadrangles of Woodbury and Roxbury, which were originally mapped by Gates (1954) and Gates (1959), respectively. Based on these discrepancies, a new NCGMP project was proposed to remap the Woodbury and Roxbury 7.5 min quadrangles, commencing in the fall of 2016. The expected USGS product will be a two-quadrangle, 1:24,000-scale Scientific Investigations Map (SIM).
This field guide is not meant as a comprehensive review of all of the geologic research done in this area of Connecticut; rather, it looks at previous bedrock geologic mapping from the perspective of new and recent mapping in the four-quadrangle area and discusses the structural, stratigraphic, and nomenclatural revisions necessary for the next revision of the state geologic map.
Raikoke, a small, unmonitored volcano in the Kuril Islands, erupted in June 2019. We integrate data from satellites (including Sentinel-2, TROPOMI, MODIS, Himawari-8), the International Monitoring System (IMS) infrasound network, and global lightning detection network (GLD360) with information from local authorities and social media to retrospectively characterize the eruptive sequence and improve understanding of the pre-, syn- and post- eruptive behavior. We observe six infrasound pulses beginning on 21 June at 17:49:55 UTC as well as the main Plinian phase on 21 June at 22:29 UTC. Each pulse is tracked in space and time using lightning and satellite imagery as the plumes drift eastward. Post-eruption visible satellite imagery shows expansion of the island's surface area, an increase in crater size, and a possibly-linked algal bloom south of the island. We use thermal satellite imagery and plume modeling to estimate plume height at 10–12 km asl and 1.5–2 × 106 kg/s mass eruption rate. Remote infrasound data provide insight into syn-eruptive changes in eruption intensity. Our analysis illustrates the value of interdisciplinary analyses of remote data to illuminate eruptive processes. However, our inability to identify deformation, pre-eruptive outgassing, and thermal signals, which may reflect the relatively short duration (~12 h) of the eruption and minimal land area around the volcano and/or the character of closed-system eruptions, highlights current limitations in the application of remote sensing for eruption detection and characterization.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jvolgeores.2021.107354","usgsCitation":"McKee, K., Smith, C.M., Reath, K., Snee, E., Maher, S., Matoza, R.S., Carn, S.A., Mastin, L.G., Anderson, K.R., Damby, D., Roman, D., Degterev, A., Rybin, A., Chibisova, M., Assink, J.D., de Negri Levia, R., and Perttu, A., 2021, Evaluating the state-of-the-art in remote volcanic eruption characterization Part I: Raikoke volcano, Kuril Islands: Journal of Volcanology and Geothermal Research, v. 419, p. 1-14, https://doi.org/10.1016/j.jvolgeores.2021.107354.","productDescription":"107354, 14 p.","startPage":"1","endPage":"14","ipdsId":"IP-131053","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":450671,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jvolgeores.2021.107354","text":"Publisher Index Page"},{"id":389731,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Japan, Russia","state":"Hokkaido, Sakhalin Oblast","otherGeospatial":"Kuril Islands, Raikoke Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -206.73900604248047,\n 48.283078663405014\n ],\n [\n -206.7290496826172,\n 48.291531147204644\n ],\n [\n -206.73248291015625,\n 48.29963964777105\n ],\n [\n -206.74072265625,\n 48.30226606899445\n ],\n [\n -206.7620086669922,\n 48.30215187957729\n ],\n [\n -206.76630020141602,\n 48.29872607827854\n ],\n [\n -206.7688751220703,\n 48.292901688435585\n ],\n [\n -206.7688751220703,\n 48.29107429195301\n ],\n [\n -206.7614936828613,\n 48.28364982124273\n ],\n [\n -206.75445556640625,\n 48.28227903170258\n ],\n [\n -206.73900604248047,\n 48.283078663405014\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"419","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McKee, Kathleen 0000-0003-3189-9189","orcid":"https://orcid.org/0000-0003-3189-9189","contributorId":265977,"corporation":false,"usgs":false,"family":"McKee","given":"Kathleen","email":"","affiliations":[{"id":54848,"text":"Earth and Planets Laboratory, Carnegie Institution for Science, Washington, DC, USA","active":true,"usgs":false}],"preferred":false,"id":823913,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Cassandra Marie 0000-0003-2653-4249 cassandrasmith@usgs.gov","orcid":"https://orcid.org/0000-0003-2653-4249","contributorId":257000,"corporation":false,"usgs":true,"family":"Smith","given":"Cassandra","email":"cassandrasmith@usgs.gov","middleInitial":"Marie","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":823914,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reath, Kevin","contributorId":194091,"corporation":false,"usgs":false,"family":"Reath","given":"Kevin","email":"","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":823915,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Snee, Eveanjelene 0000-0002-3660-4020","orcid":"https://orcid.org/0000-0002-3660-4020","contributorId":265978,"corporation":false,"usgs":false,"family":"Snee","given":"Eveanjelene","email":"","affiliations":[{"id":54849,"text":"School of Earth and Ocean Sciences, Cardiff University, Cardiff, Wales, UK","active":true,"usgs":false}],"preferred":false,"id":823916,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Maher, Sean","contributorId":265979,"corporation":false,"usgs":false,"family":"Maher","given":"Sean","affiliations":[{"id":54850,"text":"Department of Earth Science and Earth Research Institute, University of California, Santa Barbara, Santa Barbara, CA, USA","active":true,"usgs":false}],"preferred":false,"id":823917,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Matoza, Robin S.","contributorId":257265,"corporation":false,"usgs":false,"family":"Matoza","given":"Robin","email":"","middleInitial":"S.","affiliations":[{"id":36524,"text":"University of California, Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":823918,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Carn, Simon A","contributorId":191165,"corporation":false,"usgs":false,"family":"Carn","given":"Simon","email":"","middleInitial":"A","affiliations":[],"preferred":false,"id":823919,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Mastin, Larry G. 0000-0002-4795-1992 lgmastin@usgs.gov","orcid":"https://orcid.org/0000-0002-4795-1992","contributorId":555,"corporation":false,"usgs":true,"family":"Mastin","given":"Larry","email":"lgmastin@usgs.gov","middleInitial":"G.","affiliations":[{"id":617,"text":"Volcano Science 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Diana","contributorId":237832,"corporation":false,"usgs":false,"family":"Roman","given":"Diana","affiliations":[{"id":47620,"text":"Dept. of Terrestrial Magnetism, Carnegie Institution for Science, Washington DC 20015","active":true,"usgs":false}],"preferred":false,"id":823923,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Degterev, Artem 0000-0001-6284-8830","orcid":"https://orcid.org/0000-0001-6284-8830","contributorId":265980,"corporation":false,"usgs":false,"family":"Degterev","given":"Artem","email":"","affiliations":[{"id":54851,"text":"Sakhalin Volcanic Eruptions Response Team (SVERT), Institute of Marine Geology and Geophysics, Yuzhno-Sakhalinsk, Russia","active":true,"usgs":false}],"preferred":false,"id":823924,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Rybin, Alexander 0000-0002-7734-0172","orcid":"https://orcid.org/0000-0002-7734-0172","contributorId":265981,"corporation":false,"usgs":false,"family":"Rybin","given":"Alexander","email":"","affiliations":[{"id":54851,"text":"Sakhalin Volcanic Eruptions Response Team (SVERT), Institute of Marine Geology and Geophysics, Yuzhno-Sakhalinsk, Russia","active":true,"usgs":false}],"preferred":false,"id":823925,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Chibisova, Marina 0000-0003-0677-6945","orcid":"https://orcid.org/0000-0003-0677-6945","contributorId":265982,"corporation":false,"usgs":false,"family":"Chibisova","given":"Marina","email":"","affiliations":[{"id":54851,"text":"Sakhalin Volcanic Eruptions Response Team (SVERT), Institute of Marine Geology and Geophysics, Yuzhno-Sakhalinsk, Russia","active":true,"usgs":false}],"preferred":false,"id":823926,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Assink, Jelle D.","contributorId":236650,"corporation":false,"usgs":false,"family":"Assink","given":"Jelle","email":"","middleInitial":"D.","affiliations":[{"id":47493,"text":"R and D Seismology and Acoustics, Royal Netherlands Meteorological Institute (KNMI), Utrechtseweg 297, 3731 GA De Bilt, The Netherlands","active":true,"usgs":false}],"preferred":false,"id":823927,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"de Negri Levia, Rodrigo 0000-0003-1283-2579","orcid":"https://orcid.org/0000-0003-1283-2579","contributorId":265983,"corporation":false,"usgs":false,"family":"de Negri Levia","given":"Rodrigo","email":"","affiliations":[{"id":54852,"text":"Department of Earth Science and Earth Research Institute, University of California, Santa Barbara, Santa Barbara, CA, USA; NDC-CTBT of the Chilean Nuclear Energy Commission, Chile","active":true,"usgs":false}],"preferred":false,"id":823928,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Perttu, Anna 0000-0003-3590-1549","orcid":"https://orcid.org/0000-0003-3590-1549","contributorId":265984,"corporation":false,"usgs":false,"family":"Perttu","given":"Anna","email":"","affiliations":[{"id":48937,"text":"Earth Observatory of Singapore, Nanyang Technological University, Singapore","active":true,"usgs":false}],"preferred":false,"id":823929,"contributorType":{"id":1,"text":"Authors"},"rank":17}]}} ,{"id":70223871,"text":"sir20215015 - 2021 - Methods for estimating regional skewness of annual peak flows in parts of eastern New York and Pennsylvania, based on data through water year 2013","interactions":[],"lastModifiedDate":"2021-09-27T12:03:37.39516","indexId":"sir20215015","displayToPublicDate":"2021-09-24T09:50:00","publicationYear":"2021","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":"2021-5015","displayTitle":"Methods for Estimating Regional Skewness of Annual Peak Flows in Parts of Eastern New York and Pennsylvania, Based on Data Through Water Year 2013","title":"Methods for estimating regional skewness of annual peak flows in parts of eastern New York and Pennsylvania, based on data through water year 2013","docAbstract":"Bulletin 17C (B17C) recommends fitting the log-Pearson Type III (LP−III) distribution to a series of annual peak flows at a streamgage by using the method of moments. The third moment, the skewness coefficient (or skew), is important because the magnitudes of annual exceedance probability (AEP) flows estimated by using the LP–III distribution are affected by the skew; interest is focused on the right-hand tail of the distribution, which represents the larger annual peak flows that correspond to small AEPs. For streamgages having modest record lengths, the skew is sensitive to extreme events like large floods, which cause a sample to be highly asymmetrical or “skewed.” For this reason, B17C recommends using a weighted-average skew computed from the skew of the annual peak flows for a given streamgage and a regional skew. This report presents an estimate of regional skew for a study area encompassing parts of eastern New York and Pennsylvania. A total of 232 candidate U.S. Geological Survey streamgages that were unaffected by extensive regulation, diversion, urbanization, or channelization were considered for use in the skew analysis; after screening for redundancy and pseudo record length (PRL) of at least 36 years, 183 streamgages were selected for use in the study.
Flood frequencies for candidate streamgages were analyzed by employing the expected moments algorithm, which extends the method of moments so that it can accommodate interval, censored, and historical/paleo flow data, as well as the multiple Grubbs-Beck test to identify potentially influential low floods in the data series. Bayesian weighted least squares/Bayesian generalized least squares regression was used to develop a regional skew model for the study area that would incorporate possible variables (basin characteristics) to explain the variation in skew in the study area. Ten basin characteristics were considered as possible explanatory variables; however, none produced a pseudo coefficient of determination greater than 1 percent; as a result, these characteristics did not help to explain the variation in skew in the study area. Therefore, a constant model that had a regional skew coefficient of 0.32 and an average variance of prediction at a new streamgage (AVPnew, which corresponds to the mean square error [MSE] of 0.11) was selected. The AVPnew corresponds to an effective record length of 68 years, a marked improvement over the Bulletin 17B national skew map, whose reported MSE of 0.302 indicated a corresponding effective record length of only 17 years.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215015","usgsCitation":"Veilleux, A.G., and Wagner, D.M., 2021, Methods for estimating regional skewness of annual peak flows in parts of eastern New York and Pennsylvania, based on data through water year 2013: U.S. Geological Survey Scientific Investigations Report 2021–5015, 38 p., https://doi.org/10.3133/sir20215015.","productDescription":"Report: vi, 38 p.; Data Release","numberOfPages":"38","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-114558","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":389079,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5015/coverthb.jpg"},{"id":389080,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5015/sir20215015.pdf","text":"Report","size":"6.43 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021-5015"},{"id":389081,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9PGAL0D","text":"USGS data release","linkHelpText":"Regional flood skew for parts of the mid-Atlantic region (hydrologic unit 02) in eastern New York and Pennsylvania"}],"country":"United States","state":"New York, Pennsylvania","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.56396484375,\n 39.740986355883564\n ],\n [\n -75.03662109375,\n 40.04443758460856\n ],\n [\n -74.86083984375,\n 40.34654412118006\n ],\n [\n -75.16845703124999,\n 40.713955826286046\n ],\n [\n -74.970703125,\n 41.062786068733026\n ],\n [\n -74.619140625,\n 41.393294288784865\n ],\n [\n -74.1796875,\n 41.65649719441145\n ],\n [\n -73.54248046875,\n 42.17968819665961\n ],\n [\n -73.23486328124999,\n 43.02071359427862\n ],\n [\n -73.32275390625,\n 43.628123412124616\n ],\n [\n -73.45458984375,\n 43.77109381775651\n ],\n [\n -73.80615234375,\n 43.35713822211053\n ],\n [\n -74.28955078125,\n 43.14909399920127\n ],\n [\n -74.77294921875,\n 42.79540065303723\n ],\n [\n -75.34423828125,\n 42.73087427928485\n ],\n [\n -75.82763671875,\n 42.68243539838623\n ],\n [\n -76.35498046875,\n 42.68243539838623\n ],\n [\n -76.88232421875,\n 42.68243539838623\n ],\n [\n -77.23388671874999,\n 42.45588764197166\n ],\n [\n -77.607421875,\n 42.19596877629178\n ],\n [\n -77.607421875,\n 42.01665183556825\n ],\n [\n -77.6513671875,\n 41.409775832009565\n ],\n [\n -77.80517578125,\n 41.1290213474951\n ],\n [\n -77.9150390625,\n 40.53050177574321\n ],\n [\n -78.11279296875,\n 40.16208338164617\n ],\n [\n -78.46435546875,\n 39.67337039176558\n ],\n [\n -75.56396484375,\n 39.740986355883564\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Integrated Modeling and Prediction Division
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12201 Sunrise Valley Drive
Reston, VA 20192
Freshwater mussels are one of the most imperiled groups of animals in the world and are among the most sensitive species to a variety of chemicals. However, little is known about the sensitivity of freshwater mussels to wastewater effluents. The objectives of the present study were to (1) assess the toxicity of a permitted effluent, which entered the Deep Fork River, Oklahoma (USA), to a unionid mussel (Lampsilis siliquoidea) and to two standard test species (cladoceran Ceriodaphnia dubia; and fathead minnow Pimephales promelas) in short-term 7-day effluent tests; (2) evaluate the relative sensitivities of the three species to potassium (K), an elevated major ion in the effluent, using 7-day toxicity tests with KCl spiked into a Deep Fork River upstream reference water; (3) determine the potential influences of background water characteristics on the acute K toxicity to the mussel (96-h exposures) and cladoceran (48-h exposure) in four reconstituted waters that mimicked the hardness and ionic composition ranges of the Deep Fork River; and (4) determine the potential influence of temperature on acute K toxicity to the mussel. The effluent was found to be toxic to mussels and cladocerans, and it contained elevated concentrations of major cations and anions relative to the upstream Deep Fork River reference water. The K concentration in the effluent was 48-fold greater than in the upstream water. Compared with the standard species, the mussel was more than 4-fold more sensitive to the effluent in the 7-day effluent tests and more than 8-fold more sensitive to K in the 7-day K toxicity tests. The acute K toxicity to the mussel decreased by a factor of 2 when the water hardness was increased from soft (42 mg/L as CaCO3) to very hard (314 mg/L as CaCO3), whereas the acute K toxicity to the cladoceran remained almost the same as hardness increased from 84 to 307 mg/L as CaCO3. Acute K toxicity to the mussel at 23 °C was similar to the toxicity at an elevated temperature of 28 °C. The overall results indicate that the two standard test species may not represent the sensitivity of the tested mussel to both the effluent and K, and the toxicity of K was influenced by the hardness in test waters, but by a limited magnitude.
","language":"English","publisher":"Society of Environmental Toxicology and Chemistry (SETAC)","doi":"10.1002/etc.5221","usgsCitation":"Kunz, J.L., Wang, N., Martinez, D., Dunn, S., Cleveland, D.M., and Steevens, J.A., 2021, The sensitivity of a unionid mussel (Lampsilis siliquoidea) to a permitted effluent and elevated potassium in the effluent: Environmental Toxicology and Chemistry, v. 40, no. 12, p. 3410-3420, https://doi.org/10.1002/etc.5221.","productDescription":"11 p.","startPage":"3410","endPage":"3420","ipdsId":"IP-129678","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":436187,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P92YZGDX","text":"USGS data release","linkHelpText":"Chemical and biological data from a study on sensitivity of a unionid mussel (Lampsilis siliquoidea) to a permitted effluent and elevated potassium"},{"id":396104,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oklahoma","city":"Okmulgee","otherGeospatial":"Deep Fork National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.60827636718749,\n 35.546753306701\n ],\n [\n -95.92849731445312,\n 35.546753306701\n ],\n [\n -95.92849731445312,\n 35.69968630125204\n ],\n [\n -96.60827636718749,\n 35.69968630125204\n ],\n [\n -96.60827636718749,\n 35.546753306701\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"40","issue":"12","noUsgsAuthors":false,"publicationDate":"2021-09-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Kunz, James L. 0000-0002-1027-158X jkunz@usgs.gov","orcid":"https://orcid.org/0000-0002-1027-158X","contributorId":3309,"corporation":false,"usgs":true,"family":"Kunz","given":"James","email":"jkunz@usgs.gov","middleInitial":"L.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":835189,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wang, Ning 0000-0002-2846-3352 nwang@usgs.gov","orcid":"https://orcid.org/0000-0002-2846-3352","contributorId":2818,"corporation":false,"usgs":true,"family":"Wang","given":"Ning","email":"nwang@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":835190,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Martinez, David","contributorId":279598,"corporation":false,"usgs":false,"family":"Martinez","given":"David","email":"","affiliations":[{"id":57309,"text":"US Fish Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":835191,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dunn, Suzanne","contributorId":279599,"corporation":false,"usgs":false,"family":"Dunn","given":"Suzanne","email":"","affiliations":[{"id":57309,"text":"US Fish Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":835192,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cleveland, Danielle M. 0000-0003-3880-4584 dcleveland@usgs.gov","orcid":"https://orcid.org/0000-0003-3880-4584","contributorId":187471,"corporation":false,"usgs":true,"family":"Cleveland","given":"Danielle","email":"dcleveland@usgs.gov","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":835193,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Steevens, Jeffery A. 0000-0003-3946-1229","orcid":"https://orcid.org/0000-0003-3946-1229","contributorId":207511,"corporation":false,"usgs":true,"family":"Steevens","given":"Jeffery","middleInitial":"A.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":835194,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70224533,"text":"70224533 - 2021 - Multidisciplinary constraints on magma compressibility, the pre-eruptive exsolved volatile fraction, and the H2O/CO2 molar ratio for the 2006 Augustine eruption, Alaska","interactions":[],"lastModifiedDate":"2021-09-24T15:09:47.418896","indexId":"70224533","displayToPublicDate":"2021-09-24T09:41:35","publicationYear":"2021","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9358,"text":"Geochemistry, Geophysics, Geosystems (G-Cubed)","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Multidisciplinary constraints on magma compressibility, the pre-eruptive exsolved volatile fraction, and the H2O/CO2 molar ratio for the 2006 Augustine eruption, Alaska","title":"Multidisciplinary constraints on magma compressibility, the pre-eruptive exsolved volatile fraction, and the H2O/CO2 molar ratio for the 2006 Augustine eruption, Alaska","docAbstract":"Geodetically modeled reservoir volume changes during volcanic eruptions are commonly much smaller than the observed eruptive volumes. This discrepancy is thought to be partially due to the compressibility of magma, which is largely controlled by the presence of exsolved volatiles. The 2006 eruption of Augustine Volcano, Alaska, produced an eruptive volume that was ∼3 times larger than the geodetically estimated syn-eruptive subsurface volume change. In this study, we use a multistep methodology that combines constraints from geodetic, volcanic gas, geologic, and petrologic data together with equations relating physical processes to observable parameters. We apply a Monte Carlo approach to quantify uncertainties. Ultimately, we solve for the exsolved volatile volume fraction and the magma compressibility. We estimate Augustine's 2006 pre-eruptive exsolved volatile phase to be ∼5.5 vol% of the magma at storage depths, yielding a bulk magma compressibility of ∼3.8 × 10−10 Pa−1. We develop a novel approach to estimate the H2O/CO2 ratio of the syn-eruptive gas emissions in the absence of direct H2O emission measurements which are hard to obtain due to the high background levels in ambient air. We find a best-fit H2O/CO2 molar ratio of 29. We also investigate the effects of applying different equations of state to our model. We find that the Ideal Gas Law might be used as a first approximation due to its simplicity; however, it overestimates volatile density and compressibility significantly at storage depths. This project capitalizes on the insights that can be gained by integrating multidisciplinary data with models of physical processes.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021GC009911","usgsCitation":"Wasser, V.K., Lopez, T., Anderson, K.R., Izbekov, P.E., and Freymueller, J., 2021, Multidisciplinary constraints on magma compressibility, the pre-eruptive exsolved volatile fraction, and the H2O/CO2 molar ratio for the 2006 Augustine eruption, Alaska: Geochemistry, Geophysics, Geosystems (G-Cubed), v. 22, no. 9, p. 1-24, https://doi.org/10.1029/2021GC009911.","productDescription":"e2021GC009911, 24 p.","startPage":"1","endPage":"24","ipdsId":"IP-116941","costCenters":[{"id":153,"text":"California Volcano Observatory","active":false,"usgs":true}],"links":[{"id":489770,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2021gc009911","text":"Publisher Index Page"},{"id":389721,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Augustine Volcano, Cook Inlet","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -153.38150024414062,\n 59.404209722248545\n ],\n [\n -153.38356018066406,\n 59.411198752750096\n ],\n [\n -153.4295654296875,\n 59.417836996163324\n ],\n [\n -153.46939086914062,\n 59.40840331358838\n ],\n [\n -153.47488403320312,\n 59.39966607911177\n ],\n [\n -153.51470947265625,\n 59.395471406154286\n ],\n [\n -153.52500915527344,\n 59.38987770116238\n ],\n [\n -153.5504150390625,\n 59.39652012307085\n ],\n [\n -153.56483459472653,\n 59.39337387496283\n ],\n [\n -153.57650756835938,\n 59.38218484937568\n ],\n [\n -153.58200073242188,\n 59.37379065648717\n ],\n [\n -153.577880859375,\n 59.36924293446236\n ],\n [\n -153.55934143066406,\n 59.36644403325385\n ],\n [\n -153.5504150390625,\n 59.345795005122895\n ],\n [\n -153.55865478515625,\n 59.33564087770051\n ],\n [\n -153.5504150390625,\n 59.32968704671643\n ],\n [\n -153.52157592773438,\n 59.3167251017617\n ],\n [\n -153.42613220214844,\n 59.32443279994899\n ],\n [\n -153.41720581054688,\n 59.32022881759866\n ],\n [\n -153.39797973632812,\n 59.32583401185328\n ],\n [\n -153.358154296875,\n 59.33669144545403\n ],\n [\n -153.336181640625,\n 59.35734600959442\n ],\n [\n -153.34304809570312,\n 59.380785961506966\n ],\n [\n -153.37051391601562,\n 59.39092659116679\n ],\n [\n -153.38150024414062,\n 59.404209722248545\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"22","issue":"9","noUsgsAuthors":false,"publicationDate":"2021-09-08","publicationStatus":"PW","contributors":{"authors":[{"text":"Wasser, Valerie K.","contributorId":265989,"corporation":false,"usgs":false,"family":"Wasser","given":"Valerie","email":"","middleInitial":"K.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":823947,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lopez, Taryn M.","contributorId":265990,"corporation":false,"usgs":false,"family":"Lopez","given":"Taryn M.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":823948,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, Kyle R. 0000-0001-8041-3996 kranderson@usgs.gov","orcid":"https://orcid.org/0000-0001-8041-3996","contributorId":3522,"corporation":false,"usgs":true,"family":"Anderson","given":"Kyle","email":"kranderson@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":823949,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Izbekov, Pavel E.","contributorId":265991,"corporation":false,"usgs":false,"family":"Izbekov","given":"Pavel","email":"","middleInitial":"E.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":823950,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Freymueller, Jeffrey T.","contributorId":96841,"corporation":false,"usgs":false,"family":"Freymueller","given":"Jeffrey T.","affiliations":[{"id":26875,"text":"Michigan State University, East Lansing, MI","active":true,"usgs":false}],"preferred":false,"id":823951,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ]}