The U.S. Geological Survey has a long history of leading flood-frequency analysis studies. These studies play a critical role in the assessment of risk, protection of lives, and planning and design of flood protection infrastructure. Standard flood-frequency analysis is based on the assumption of stationarity—that is, that the distribution of floods at a given site varies around a particular mean within a particular envelope of variance (and skew) and that these parameters of the underlying statistical distribution representative of the floods do not vary over time. Gradual or abrupt changes in one or more of the distributional parameters are called nonstationarities and violate the underlying assumptions of current U.S. Federal Government guidelines for flood-frequency analysis. Uncertainty exists as to what degree of violations calls for the use of a modified method for flood-frequency analysis and what the modified method(s) should be.
When deciding whether to perform nonstationary flood-frequency analysis and choosing a method for such analysis, it is important to understand the causes of the nonstationarity. Gradual or abrupt changes in distributional properties of floods may be the result of numerous factors, such as regulation, diversion, land-use change, or climate change.
In the interest of developing a cohesive national approach for better understanding the causes of nonstationarities and incorporating potential or observed changes into flood-frequency estimates, subject-matter experts from the U.S. Geological Survey and cooperators worked together to develop a multiple working hypotheses framework for making attributions and a common vocabulary for making provisions of confidence. Seven regional teams of these experts used ancillary datasets and institutional knowledge to evaluate plausible causes for monotonic trends and change points in annual peak-streamflow data for the conterminous United States that had been identified in an earlier phase of the project.
The first chapter of this professional paper describes the development of a list of the potential attributions, presents a literature review of the potential attributions, describes the regional approach, summarizes insights obtained from the attribution process, and suggests future research. The other chapters provide the methods used for attribution in the seven regions—Pacific Northwest, Upper Plains, Midwest, Northeast, Southwest, South-Central, and Southeast—and summarize the regional patterns of nonstationarities.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1869","collaboration":"Prepared in cooperation with the U.S. Department of Transportation, Federal Highway Administration","usgsCitation":"Ryberg, K.R., ed., 2022, Attribution of monotonic trends and change points in peak streamflow across the conterminous United States using a multiple working hypotheses framework, 1941–2015 and 1966–2015: U.S. Geological Survey Professional Paper 1869, 8 chapters (A–H), variously paged, https://doi.org/10.3133/pp1869.","productDescription":"Report: 328 p.; 2 Data Releases","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-110840","costCenters":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"links":[{"id":501885,"rank":5,"type":{"id":36,"text":"NGMDB Index 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Water Resources Mission Area
U.S. Geological Survey
12201 Sunrise Valley Drive, Mail Stop 415
Reston, VA 20192
Southeast Florida is highly susceptible to flooding because of its low topography and porous, highly permeable Biscayne aquifer. Rising seas will likely result in increased groundwater levels in parts of Broward County, Florida, that will reduce available soil storage and therefore increase the likelihood of inundation and flooding from precipitation events. Moreover, rising seas may also reduce the capacity of the coastal water-control structures to discharge inland waters to tidal areas, thereby increasing surface-water stage and nearby groundwater levels. Increased rainfall intensity will likely further increase peak surface-water stages and groundwater levels, more quickly fill the reduced soil storage capacity, and increase the likelihood for inundation. Managers and planners in Broward County, Florida, face the challenge of understanding and preparing for the consequent risk to residents, businesses, and critical infrastructure posed by increased sea level and precipitation.
The U.S. Geological Survey, in cooperation with the Broward County Environmental Planning and Resilience Division, has developed a groundwater/surface-water model to evaluate the response of the drainage infrastructure and groundwater system in Broward County to projected increases in sea level and potential changes in precipitation. The model was constructed using Modular Finite-Difference Groundwater Flow Model Newton formulation, with the surface-water system represented using the Surface-Water Routing process and the Urban Runoff process. The aquifer layering and flow parameters rely heavily on existing hydrologic flow models developed by the U.S. Geological Survey for the same model area. The surface-water drainage system within this newly developed model actively simulates the extensive canal network using level-pool routing and active structures representing gates, weirs, culverts, and pumps. Steady-state and transient simulation results represented historical conditions (2013–17). The simulated historical groundwater levels and upstream stage and flow at the primary structures generally captured the behavior of the actual hydrologic system. Simulation results incorporating increased sea level and precipitation were used to evaluate the effects of these projected changes on the surface-water drainage system and wet season groundwater levels.
Four future sea-level scenarios were simulated by modifying the historical inputs for both steady-state and the transient versions of the model to represent mean sea levels of 0.5, 2.0, 2.5, and 3.0 feet (ft) above the North American Vertical Datum of 1988. These mean sea levels correspond to sea-level rises of 1.05, 2.55, 3.05, and 3.55 ft, respectively, above the 2013–17 mean measured tidal stage. Additional simulations represented a 15-percent increase in rainfall rates using the transient model and a 15-percent increase in rainfall recharge using the steady-state model. The simulated results indicated that (1) the effects of increased sea level were more evident in the easternmost, coastal areas of the county where increases in groundwater levels are nearly equivalent to sea-level rise; (2) groundwater levels west of the coastal water-control structures only changed slightly in response to increased sea level for most scenarios; (3) when the control elevations of the gravity-controlled coastal water-control structures were surpassed by sea-level rise, the resulting increases in upstream stage in the connected primary canal resulted in increased groundwater levels that can propagate into the western parts of the county; (4) the historical west-to-east downward gradient in groundwater levels decreased with increased sea level, and groundwater levels were lower in central parts of the county than areas west and east for the higher sea-level scenarios; (5) simulated upstream stage for most of the primary coastal water-control structures increased with increased sea level, with the largest increases occurring at gravity-controlled structures having the lowest control elevations; (6) total flow through the primary structures increased as sea level increased because of additional groundwater leakage into the surface-water network; (7) the 3.0-ft mean sea-level rise scenario resulted in an increase of 37.10 square miles in area having a wet season average depth to groundwater of less than 2 ft, and an increase of 22.84 square miles in newly inundated areas compared to historical simulation results; and (8) a 15-percent increase in rainfall rate for the entire simulation period produced little increase in upstream stages at the primary structures and an increase in total flow through the primary structures proportional to the increase in rainfall.
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Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
As of May 2021, public alerting is now operational for the ShakeAlert earthquake early warning system for the West Coast of the United States in California, Oregon, and Washington. Successful early warning systems require the scientific and technical implementation to be coupled with social and humanitarian considerations, including education and outreach campaigns. Community engagement with the over 50 million people who live in ShakeAlert states is important to increase public safety, security, and awareness of local earthquake hazards, how to prepare, and how ShakeAlert earthquake early warning can help. Here, we describe the efforts of the ShakeAlert Educational Resources Working Group around the rollout of public alerting in the Pacific Northwest for Oregon in March 2021 and Washington in May 2021, respectively. Our initial approach was to engage in formative dialogue with community members in each ShakeAlert state, develop educational activities and animations based on the collective feedback, and then to disseminate our resources in both formal (K‐16) and informal (free choice) learning environments through workshops and outreach events. The rollout of public alerting in the Pacific Northwest provided an opportunity to directly engage with various publics around a specific event, and to collaborate with local news and social media, communications and social science professionals, educators, emergency managers, and scientific and technical experts on the ShakeAlert system. Following the rollouts, we developed a strategic plan for the next five years of ShakeAlert to promote earthquake early warning, as the importance of earthquake preparedness competes with the stressors of everyday life. Because earthquake early warning systems are rapidly expanding worldwide, our education and outreach efforts provide a roadmap for building successful education and outreach campaigns, leading up to public alerting and maintaining earthquake preparedness in the public consciousness following rollout.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220220159","usgsCitation":"Sumy, D.F., Jenkins, M.R., Crayne, J., Olds, S., Anderson, M.L., Johnson, J., Magura, B., Pridmore, C., and deGroot, R.M., 2022, Education initiatives to support earthquake early warning: A retrospective and a roadmap: Seismological Research Letters, v. 93, no. 6, p. 34989-3513, https://doi.org/10.1785/0220220159.","productDescription":"15 p.","startPage":"34989","endPage":"3513","ipdsId":"IP-140766","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":481756,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.90185385586557,\n 45.894384591476296\n ],\n [\n -126.10099348944192,\n 45.894384591476296\n ],\n [\n -126.10099348944192,\n 42.81601016538801\n ],\n [\n -121.90185385586557,\n 42.81601016538801\n ],\n [\n -121.90185385586557,\n 45.894384591476296\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"93","issue":"6","noUsgsAuthors":false,"publicationDate":"2022-09-28","publicationStatus":"PW","contributors":{"authors":[{"text":"Sumy, Danielle F.","contributorId":197628,"corporation":false,"usgs":false,"family":"Sumy","given":"Danielle","middleInitial":"F.","affiliations":[],"preferred":false,"id":926506,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jenkins, Mariah Ramona 0000-0001-8944-4422","orcid":"https://orcid.org/0000-0001-8944-4422","contributorId":289695,"corporation":false,"usgs":true,"family":"Jenkins","given":"Mariah","email":"","middleInitial":"Ramona","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":926507,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Crayne, Jenny","contributorId":350631,"corporation":false,"usgs":false,"family":"Crayne","given":"Jenny","affiliations":[{"id":83800,"text":"Oregon Museum of Science and Industry","active":true,"usgs":false}],"preferred":false,"id":926508,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Olds, Shelley E","contributorId":350632,"corporation":false,"usgs":false,"family":"Olds","given":"Shelley E","affiliations":[{"id":5114,"text":"UNAVCO","active":true,"usgs":false}],"preferred":false,"id":926509,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Anderson, Megan L. 0000-0001-6864-7343","orcid":"https://orcid.org/0000-0001-6864-7343","contributorId":333918,"corporation":false,"usgs":false,"family":"Anderson","given":"Megan","email":"","middleInitial":"L.","affiliations":[{"id":62759,"text":"Washington Geological Survey","active":true,"usgs":false}],"preferred":false,"id":926510,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Johnson, Jenda","contributorId":350633,"corporation":false,"usgs":false,"family":"Johnson","given":"Jenda","affiliations":[{"id":39228,"text":"Incorporated Research Institutions for Seismology","active":true,"usgs":false}],"preferred":false,"id":926511,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Magura, Bonnie","contributorId":350634,"corporation":false,"usgs":false,"family":"Magura","given":"Bonnie","affiliations":[{"id":39228,"text":"Incorporated Research Institutions for Seismology","active":true,"usgs":false}],"preferred":false,"id":926512,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Pridmore, Cynthia L","contributorId":350635,"corporation":false,"usgs":false,"family":"Pridmore","given":"Cynthia L","affiliations":[{"id":83801,"text":"California Geological Survey (Department of Conservation)","active":true,"usgs":false}],"preferred":false,"id":926513,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"deGroot, Robert Michael 0000-0001-9995-4207","orcid":"https://orcid.org/0000-0001-9995-4207","contributorId":239577,"corporation":false,"usgs":true,"family":"deGroot","given":"Robert","email":"","middleInitial":"Michael","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":926514,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70237053,"text":"70237053 - 2022 - Treading water: Conservation of headwater-stream associated amphibians in northwestern North America","interactions":[],"lastModifiedDate":"2022-09-28T15:42:01.749715","indexId":"70237053","displayToPublicDate":"2022-09-28T10:29:08","publicationYear":"2022","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Treading water: Conservation of headwater-stream associated amphibians in northwestern North America","docAbstract":"Headwater streams of the Pacific Northwest of North America are home to 52 amphibian species, spanning a diversity of taxa and life histories. Headwater stream-associated amphibians occur both within coldwater-stream channels and throughout adjacent riparian habitat, reflective of the important role of old-growth forests in providing cool, moist microclimates for these sensitive species. Forests of the Pacific Northwest have undergone substantial change over the last century, due to a legacy of resource extraction and ever-evolving forest management practices, as well as climate change. These and other stressors have challenged the adaptive capacity of headwater stream-associated amphibians, as more than half of these species are considered to be of conservation concern at the state, provincial, or federal level in the U.S. and Canada. Here, we overview the primary threats to the persistence of this unique and imperiled taxonomic group and emphasize the urgent need for more research and conservation action to mitigate future decline.","language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-12-821139-7.00112-4","usgsCitation":"Thurman, L., Cousins, C., Button, S.T., Garcia, T.S., Henderson, A., Olson, D., and Piovia-Scott, J., 2022, Treading water: Conservation of headwater-stream associated amphibians in northwestern North America, p. 499-513, https://doi.org/10.1016/B978-0-12-821139-7.00112-4.","productDescription":"15 p.","startPage":"499","endPage":"513","ipdsId":"IP-127720","costCenters":[{"id":49226,"text":"Northwest Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":407516,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Alaska, British Columbia, Idaho, Oregon, Washington","otherGeospatial":"Pacific Northwest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.27734374999999,\n 42.00032514831621\n ],\n [\n -111.005859375,\n 41.983994270935625\n ],\n [\n -112.54394531249999,\n 44.33956524809713\n ],\n [\n -113.97216796875,\n 45.506346901083425\n ],\n [\n -114.43359375,\n 45.767522962149876\n ],\n [\n -114.43359375,\n 46.619261036171515\n ],\n [\n -115.86181640625001,\n 47.66538735632654\n ],\n [\n -117.158203125,\n 49.06666839558117\n ],\n [\n -118.21289062499999,\n 50.24720490139267\n ],\n [\n -119.66308593749999,\n 51.90361280788357\n ],\n [\n -121.025390625,\n 53.238920640924974\n ],\n [\n -120.7177734375,\n 53.76170183021049\n ],\n [\n -122.58544921875,\n 54.92714186454645\n ],\n [\n -124.71679687499999,\n 56.96893619436121\n ],\n [\n -125.48583984375,\n 58.112714441253125\n ],\n [\n -127.11181640625,\n 58.75680543225761\n ],\n [\n -128.56201171875,\n 59.99898612060444\n ],\n [\n -139.5263671875,\n 60.04290359809164\n ],\n [\n -139.9658203125,\n 59.5343180010956\n ],\n [\n -136.91162109374997,\n 58.228596132481435\n ],\n [\n -136.03271484375,\n 57.38578314962142\n ],\n [\n -136.03271484375,\n 56.90900226702048\n ],\n [\n -134.7802734375,\n 56.15778819063682\n ],\n [\n -133.13232421875,\n 54.686534234529695\n ],\n [\n -133.30810546875,\n 53.86548550842127\n ],\n [\n -132.275390625,\n 52.77618568896171\n ],\n [\n -127.59521484375,\n 49.89463439573421\n ],\n [\n -124.93652343749999,\n 48.531157010976706\n ],\n [\n -124.95849609375,\n 48.06339653776211\n ],\n [\n -124.60693359374999,\n 47.65058757118734\n ],\n [\n -124.16748046874999,\n 45.99696161820381\n ],\n [\n -124.29931640625,\n 44.213709909702054\n ],\n [\n -124.71679687499999,\n 42.827638636242284\n ],\n [\n -124.27734374999999,\n 42.00032514831621\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Thurman, Lindsey 0000-0003-3142-4909","orcid":"https://orcid.org/0000-0003-3142-4909","contributorId":269425,"corporation":false,"usgs":true,"family":"Thurman","given":"Lindsey","email":"","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":853181,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cousins, Christopher","contributorId":297053,"corporation":false,"usgs":false,"family":"Cousins","given":"Christopher","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":853182,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Button, Sky T. C.","contributorId":297054,"corporation":false,"usgs":false,"family":"Button","given":"Sky","email":"","middleInitial":"T. C.","affiliations":[{"id":37380,"text":"Washington State University","active":true,"usgs":false}],"preferred":false,"id":853183,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Garcia, Tiffany S.","contributorId":171591,"corporation":false,"usgs":false,"family":"Garcia","given":"Tiffany","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":853184,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Henderson, Alysha","contributorId":297055,"corporation":false,"usgs":false,"family":"Henderson","given":"Alysha","email":"","affiliations":[{"id":37380,"text":"Washington State University","active":true,"usgs":false}],"preferred":false,"id":853185,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Olson, Deanna H.","contributorId":257261,"corporation":false,"usgs":false,"family":"Olson","given":"Deanna H.","affiliations":[{"id":51996,"text":"USDA Forest Service Pacific Northwest Research Station","active":true,"usgs":false}],"preferred":false,"id":853186,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Piovia-Scott, Jonah","contributorId":297057,"corporation":false,"usgs":false,"family":"Piovia-Scott","given":"Jonah","affiliations":[{"id":37380,"text":"Washington State University","active":true,"usgs":false}],"preferred":false,"id":853187,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70237056,"text":"70237056 - 2022 - Does large dam removal restore downstream riparian vegetation diversity? Testing predictions on the Elwha River, Washington, USA","interactions":[],"lastModifiedDate":"2022-09-28T15:28:09.609653","indexId":"70237056","displayToPublicDate":"2022-09-28T10:08:16","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Does large dam removal restore downstream riparian vegetation diversity? Testing predictions on the Elwha River, Washington, USA","docAbstract":"Large dams and their removal can profoundly affect riparian ecosystems by altering flow and sediment regimes, hydrochory, and landform dynamics, yet few studies have documented these effects on downstream plant communities. Ecological theory and empirical results suggest that by altering disturbance regimes, reducing hydrochory, and shifting communities to later successional stages, dams reduce downstream plant diversity. Dam removal could reverse these processes, but the release of large volumes of sediment could have unexpected, transient effects. Two large dams were removed on the Elwha River in Washington State, USA, from 2011-2014, representing an unprecedented opportunity to study large dam removal effects on riparian plant communities. Our research objectives were to determine: 1) whether the Elwha River dams were associated with lower downstream plant diversity and altered species composition across riparian landforms pre-dam removal, and 2) whether dam removal has begun to restore downstream diversity and composition. To address these objectives, we compared plant species richness and community composition in river segments above, below, and between the two dams. Plant communities were sampled twice before (2005 and 2010) and four times after (2013, 2014, 2016, and 2017) the start of dam removal, with 2013 and 2014 sampled while the upstream dam removal was ongoing. Prior to dam removal, native species richness was 41% lower below dams compared to the upstream segment; six years after dam removal began, it increased ~31% between the dams, while nonnative species richness and cover were not apparently affected by dams or their removal. Deposition caused by large volumes of released reservoir sediment had mixed effects on native species richness (increased on floodplains, decreased elsewhere) in the lowest river segment. Plant community composition was also different downstream from dams compared to the upstream reference, and has changed in downstream floodplains and bars since dam removal. Long-term, we expect that diversity will continue to increase in downstream river segments. Our results provide evidence that 1) large dams reduce downstream native plant diversity, 2) dam removal may restore it, and 3) given the natural dynamics of riparian vegetation, long-term, multi-year before-and-after-monitoring is essential for understanding dam removal effects.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.2591","usgsCitation":"Brown, R.L., Thomas, C.C., Cubley, E.S., Clausen, A.J., and Shafroth, P., 2022, Does large dam removal restore downstream riparian vegetation diversity? Testing predictions on the Elwha River, Washington, USA: Ecological Applications, v. 32, no. 6, e2591, 24 p., https://doi.org/10.1002/eap.2591.","productDescription":"e2591, 24 p.","ipdsId":"IP-073767","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":435673,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P97MINOT","text":"USGS data release","linkHelpText":"Vascular plant diversity and associated environmental variables along the Elwha River, Washington, 2005-2017"},{"id":407513,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Elwha Dam, Elwha River, Geyser Valley, Glines Canyon Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 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J.","contributorId":290765,"corporation":false,"usgs":false,"family":"Clausen","given":"Aaron","email":"","middleInitial":"J.","affiliations":[{"id":36876,"text":"Eastern Washington University","active":true,"usgs":false}],"preferred":false,"id":853191,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shafroth, Patrick B. 0000-0002-6064-871X","orcid":"https://orcid.org/0000-0002-6064-871X","contributorId":225182,"corporation":false,"usgs":true,"family":"Shafroth","given":"Patrick B.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":853192,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70263359,"text":"70263359 - 2022 - Great expectations for earthquake early warnings on the United States West Coast","interactions":[],"lastModifiedDate":"2025-02-07T15:10:46.143807","indexId":"70263359","displayToPublicDate":"2022-09-28T09:07:12","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2036,"text":"International Journal of Disaster Risk Reduction","active":true,"publicationSubtype":{"id":10}},"title":"Great expectations for earthquake early warnings on the United States West Coast","docAbstract":"In October 2019, California became the first state in the United States to fully activate a public earthquake early warning system—ShakeAlert®—managed by the U.S. Geological Survey. The system was subsequently rolled out in March 2021 in Oregon and May 2021 in Washington. Earthquake early warning (EEW) systems can provide seconds of notice to people and technological systems that shaking is imminent, but their effectiveness depends on recipients’ expectations and actions as well as technical performance. To better understand these dependencies, we surveyed representative samples of adults in California (N = 1219), Oregon (N = 1020), and Washington (N = 1037) in February 2021. Most respondents had experienced earthquakes, but few had lived through violent shaking; most had not followed protective action guidance to Drop, Cover, and Hold On (DCHO) in earthquakes; and most reported no personal or social harm from prior earthquakes. Nevertheless, expectations and perceived usefulness of EEW were high, and higher still for those who expected alerts to be accurate and easy to use, expressed tolerance of missed and erroneous warnings, and expected to be affected by a damaging earthquake in their lifetime. Results suggest opportunities to better align public preferences and expectations with ShakeAlert operations. For example, some respondents preferred lower alerting thresholds than those proposed by government and scientists. Moreover, reported tolerance of warning errors was widespread, but respondents wanted explanations quickly, suggesting a need to further develop post-alert messaging. Findings from this study should be informative for future research on the co-evolution of experiences and expectations with EEW systems.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ijdrr.2022.103296","usgsCitation":"Bostrom, A., McBride, S., Becker, J., Goltz, J., deGroot, R.M., Peek, L., Terbush, B., and Dixon, M., 2022, Great expectations for earthquake early warnings on the United States West Coast: International Journal of Disaster Risk Reduction, v. 82, 103296, 24 p., https://doi.org/10.1016/j.ijdrr.2022.103296.","productDescription":"103296, 24 p.","ipdsId":"IP-138920","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":486986,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ijdrr.2022.103296","text":"Publisher Index Page"},{"id":481774,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Oregon, 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streamflow data with discrete measurements","interactions":[],"lastModifiedDate":"2022-09-28T15:15:05.348545","indexId":"sir20225083","displayToPublicDate":"2022-09-28T08:30:44","publicationYear":"2022","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":"2022-5083","displayTitle":"A Computer-Aided Approach for Adapting Stage-Discharge Ratings and Characterizing Uncertainties of Streamflow Data with Discrete Measurements","title":"A computer-aided approach for adapting stage-discharge ratings and characterizing uncertainties of streamflow data with discrete measurements","docAbstract":"Relations between stage (water level) and discharge of streamflow through a natural channel are the result of time-varying processes, which are commonly described by time-varying stage-discharge ratings. Hydrographers with the U.S. Geological Survey successfully maintain the accuracy of streamflow data by manually applying time-tested approaches to adapt ratings to temporal changes in hydraulic conditions. The difficulty with the manual approach is that it is a subjective, time-consuming process that requires considerable skill and experience to implement. In addition, manual adjustments of ratings make quantification of resulting streamflow data uncertainties problematic. A computer-aided adaptive stage-discharge estimation approach is proposed to track sequential changes in the relation between stage and discharge at continuous-record streamgages. In this report, adaptations are based strictly on discrete measurement data that are then used to compute the magnitudes and uncertainties of streamflow. The approach entails the parameterization of a cubic regression spline (CRS) for the stage-discharge relation based on an existing rating or on a set of discrete measurements. A state-space model is then parameterized to track temporal changes in stage-discharge relations beginning with the initial CRS parameterization using discrete measurements. Finally, Kalman estimation is used with the state-space model to estimate the magnitude and uncertainty of flows. In a case study using data from streamgage U.S. Geological Survey 04122500 Marquette River at Scottville, Michigan, a five-parameter CRS model was estimated from data in an existing stage-discharge rating to provide an initial CRS parameter set for a state-space model. The initial CRS parameters were updated sequentially in a state-space model based on periodic discrete measurements of stage and discharge that spanned a 30-year period for this analysis. Additional analysis is needed to determine the timing of rapidly varying shifts more precisely in stage-discharge relations than the relatively infrequent discrete measurements currently enabled. Unit streamflow estimates based on flow in a local streamgaging network may provide a basis for adapting a stage-discharge rating at unit time intervals by augmenting discrete measurement data within the state-space model.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225083","usgsCitation":"Holtschlag, D.J., 2022, A computer-aided approach for adapting stage-discharge ratings and characterizing uncertainties of streamflow data with discrete measurements: U.S. Geological Survey Scientific Investigations Report 2022–5083, 36 p., https://doi.org/10.3133/sir20225083.","productDescription":"viii, 36 p.","numberOfPages":"50","onlineOnly":"Y","ipdsId":"IP-130821","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":407483,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5083/images"},{"id":407482,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5083/sir20225083.XML"},{"id":407480,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5083/coverthb.jpg"},{"id":407481,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5083/sir20225083.pdf","text":"Report","size":"47.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022–5083"}],"country":"United States","state":"Michigan","otherGeospatial":"Pere Marquette River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -86.20147705078125,\n 43.56845179881218\n ],\n [\n -85.49011230468749,\n 43.56845179881218\n ],\n [\n -85.49011230468749,\n 44.03429525903966\n ],\n [\n -86.20147705078125,\n 44.03429525903966\n ],\n [\n -86.20147705078125,\n 43.56845179881218\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Upper Midwest Water Science Center
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Landslide hazards are present in all 50 States and most U.S. territories, and they affect lives, property, infrastructure, and the environment. Landslides are the downslope movement of earth materials under the force of gravity. They can occur without any obvious trigger. Widespread or severe landslide events are often driven by such hazards as hurricanes, earthquakes, volcanic eruptions, heavy rain events, flooding, and wildfires. Landslides can also cause their own cascading consequences, such as the spread of hazardous materials or the creation of devastating local tsunamis.
This strategy document describes goals and strategic actions of a comprehensive strategy to meet key challenges to reducing the Nation’s risk from landslide hazards equitably and effectively. The document follows the direction of the National Landslide Preparedness Act (Public Law 116–323) by presenting a strategy for addressing landslide hazards, including risk reduction and response. The act directs the Department of the Interior to establish a program that will work with State, Tribal, and local governments as well as with academia, the private sector, community-based groups, and nonprofit organizations to identify landslide hazards and risk and improve communication, coordination, and emergency preparedness, with the objective of reducing landslide losses. As the only Federal program dedicated to landslide hazard science, the U.S. Geological Survey’s Landslide Hazards Program will lead and coordinate many of the efforts described in this strategy document. Landslide hazard risk reduction must be undertaken collectively and collaboratively across the Federal Government. This strategy document will provide a framework for the creation of an interagency management plan that describes the programs, projects, workforce, and budgets required to carry out the national strategy.
The strategy outlined in this document presents a vision of how to equitably produce, communicate, and apply landslide data and science to support a broad range of land management, infrastructure, planning, and emergency response decisions. These decisions are made by a variety of actors, including private and nonprofit landholders; State, Tribal, territorial, city, and county planners; emergency managers; engineers; infrastructure managers; Federal agencies and their partners; and community leaders and individuals. Supporting those decisions and reducing the Nation’s vulnerability to landslides requires overcoming three main challenges: (1) gaps in basic information needed to describe and understand landslide occurrence and societal risk, (2) difficulty in accurately mapping and forecasting landslide hazards, and (3) communication and coordination among the many jurisdictions and sectors that have responsibility for and interest in reducing landslide losses. To address those challenges, this strategy document puts forward a series of strategic actions to achieve four goals:
These strategic actions focus on expanding the knowledge of societal risk posed by landslides as well as better understanding of where, when, and why they occur. They focus on applying that knowledge to support landslide risk reduction efforts and decisions, including the establishment of new advisory, coordination, and working groups focused on landslide hazard and risk. They take into account that supporting landslide loss reduction decisions also requires new guidance, tools, and training codeveloped with the entities, organizations, and individuals faced with making those decisions. Finally, they address actions needed to support and expand landslide warning information and improve the technical response to landslide emergencies.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221075","programNote":"USGS Landslide Hazards Program","usgsCitation":"Godt, J.W., Wood, N.J., Pennaz, A.B., Dacey, C.M., Mirus, B.B, Schaefer, L.N., and Slaughter, S.L., 2022, National strategy for landslide loss reduction: U.S. Geological Survey Open-File Report 2022–1075, 36 p., https://doi.org/10.3133/ofr20221075.","productDescription":"viii, 36 p.","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-136128","costCenters":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"links":[{"id":405658,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1075/ofr20221075.pdf","text":"Report","size":"3.81 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 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Natural Hazards Mission Area
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
Coastal wetlands are known for exceptional productivity, but they also receive intense land-based nitrogen (N) loading. In Narragansett Bay, RI (USA), coastal ecosystems have received anthropogenic N inputs from wastewater for more than two centuries. Greenhouse gas fluxes were studied throughout a growing season (2016) in three coastal wetlands with contrasting histories of nitrogen loading. The wetland with the highest historic N load (Mary’s Creek, Warwick, RI) had significantly greater nitrous oxide (N2O) and methane (CH4) emissions than the other two sites. However, the two marshes with historic N loads (Mary’s Creek and Mary Donovan, Little Compton, RI) also had greater rates of CO2 uptake than the reference site (Nag Marsh, Prudence Island, RI). Their CO2 uptake rates far outpaced their other greenhouse gas emissions. Mary’s Creek had the greatest above- and below-ground plant biomass, vertical accretion rates, and carbon content of soils. Spartina alterniflora height was greatest at Mary’s Creek and Mary Donovan marsh. The following growing season (2017), greenhouse gases were compared across four plant-defined ecological zones in Mary’s Creek. Higher rates of CO2 uptake and CH4 emissions were found in the S. alterniflora-vegetated creekbank compared to high marsh zones or bare mudflats. Potential denitrifying enzyme activity did not significantly differ across the four zones nor between Mary’s Creek and Nag Marsh, suggesting a consistently high capacity to completely reduce N loads. These results support efforts to protect and restore these coastal ecosystems for their carbon sequestration function even despite prevalence of anthropogenic N loading.
Background: Model simulations of wildfire spread and assessments of their accuracy are needed for understanding and managing altered fire regimes in semiarid regions. The accuracy of wildfire spread simulations can be evaluated from post hoc comparisons of simulated and actual wildfire perimeters, but this requires information on pre-fire vegetation fuels that is typically not available. We assessed the accuracy of the Fire-Area Simulator (FARSITE) model parameterized with maps of fire behavior fuel models (FBFMs) obtained from the widely used LANDFIRE, as well as alternative means which utilized the classification of Rangeland Analysis Platform (RAP) satellite-derived vegetation cover maps to create FBFM maps. We focused on the 2015 Soda wildfire, which burned 113,000 ha of sagebrush steppe in the western USA, and then assessed the transferability of our RAP-to-FBFM selection process, which produced the most accurate reconstruction of the Soda wildfire, on the nearby 2016 Cherry Road wildfire.
Results: Parameterizing FARSITE with maps of FBFMs from LANDFIRE resulted in low levels of agreement between simulated and observed area burned, with maximum Sorensen’s coefficient (SC) and Cohen’s kappa (K) values of 0.38 and 0.36, respectively. In contrast, maps of FBFMs derived from unsupervised classification of RAP vegetation cover maps led to much greater simulated-to-observed burned area agreement (SC = 0.70, K = 0.68). The FBFM map that generated the greatest simulated-to-observed burned area agreement for the Soda wildfire was then used to crosswalk FBFMs to another nearby wildfire (2016 Cherry Road), and this FBFM selection led to high FARSITE simulated-to-observed burned area agreement (SC = 0.80, K = 0.79).
Conclusions: Using RAP to inform pre-fire FBFM selection increased the accuracy of FARSITE simulations compared to parameterization with the standard LANDFIRE FBFM maps, in sagebrush steppe. Additionally, the crosswalk method appeared to have regional generalizability. Flanking and backfires were the primary source of disagreements between simulated and observed fire spread in FARSITE, which are sources of error that may require modeling of lateral heterogeneity in fuels and fire processes at finer scales than used here.
","language":"English","publisher":"Springer","doi":"10.1186/s42408-022-00147-2","usgsCitation":"Price, S.J., and Germino, M., 2022, Modeling of fire spread in sagebrush steppe using FARSITE: An approach to improving input data and simulation accuracy: Fire Ecology, v. 18, 23, 16 p., https://doi.org/10.1186/s42408-022-00147-2.","productDescription":"23, 16 p.","ipdsId":"IP-135384","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":446305,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s42408-022-00147-2","text":"Publisher Index Page"},{"id":407453,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Oregon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.333984375,\n 42.85180609584705\n ],\n [\n -116.43310546875,\n 42.85180609584705\n ],\n [\n -116.43310546875,\n 43.67581809328341\n ],\n [\n -117.333984375,\n 43.67581809328341\n ],\n [\n -117.333984375,\n 42.85180609584705\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"18","noUsgsAuthors":false,"publicationDate":"2022-09-24","publicationStatus":"PW","contributors":{"authors":[{"text":"Price, Samuel J. 0000-0003-4172-4139","orcid":"https://orcid.org/0000-0003-4172-4139","contributorId":297001,"corporation":false,"usgs":true,"family":"Price","given":"Samuel","email":"","middleInitial":"J.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":853070,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Germino, Matthew J. 0000-0001-6326-7579","orcid":"https://orcid.org/0000-0001-6326-7579","contributorId":251901,"corporation":false,"usgs":true,"family":"Germino","given":"Matthew J.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":853071,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70236977,"text":"fs20223070 - 2022 - Assessment of undiscovered conventional oil and gas resources of the Volga-Ural Basin and Timan-Pechora Basin Provinces of Russia, 2020","interactions":[],"lastModifiedDate":"2022-09-28T21:12:57.082748","indexId":"fs20223070","displayToPublicDate":"2022-09-27T12:05:00","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-3070","displayTitle":"Assessment of Undiscovered Conventional Oil and Gas Resources of the Volga-Ural Basin and Timan-Pechora Basin Provinces of Russia, 2020","title":"Assessment of undiscovered conventional oil and gas resources of the Volga-Ural Basin and Timan-Pechora Basin Provinces of Russia, 2020","docAbstract":"Using a geology-based assessment methodology, the U.S. Geological Survey estimated undiscovered, technically recoverable mean conventional resources of 4.9 billion barrels of oil and 21 trillion cubic feet of gas within the Volga-Ural Basin Province and technically recoverable mean conventional resources of 1.8 billion barrels of oil and 9.5 trillion cubic of gas in the Timan-Pechora Basin Province, Russia.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston VA","doi":"10.3133/fs20223070","usgsCitation":"Schenk, C.J., Mercier, T.J., Ellis, G.S., Woodall, C.A., Finn, T.M., Tennyson, M.E., Le, P.A., Leathers-Miller, H.M., and Drake, R.M., II, 2022, Assessment of undiscovered conventional oil and gas resources of the Volga-Ural Basin and Timan-Pechora Basin Provinces of Russia, 2020: U.S. Geological Survey Fact Sheet 2022–3070, 2 p., https://doi.org/10.3133/fs20223070.","productDescription":"Report: 2 p.; Data Release","onlineOnly":"Y","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":407292,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P98J8PN3","text":"USGS data release","linkHelpText":"USGS National and Global Oil and Gas Assessment Project-Volga-Ural Basin and Timan-Pechora Basin Provinces of Russia: Assessment Unit Boundaries, Assessment Input Data, and Fact Sheet Data Tables"},{"id":407291,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2022/3070/fs20223070.pdf","text":"Report","size":"9.03 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2022-3070"},{"id":407290,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2022/3070/coverthb.jpg"}],"country":"Russia","otherGeospatial":"Timan-Pechora Basin, Volga-Ural Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 72,\n 46\n ],\n [\n 34,\n 46\n ],\n [\n 34,\n 72\n ],\n [\n 72,\n 72\n ],\n [\n 72,\n 46\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
The characteristic pattern of variation in flow magnitude, frequency, duration, timing, and rate of change defines the flow regime of rivers and streams and is a key driver of ecosystem processes in fluvial ecosystems. Understanding how freshwater biotic assemblages change across gradients of hydrology and anthropogenic-source disturbance in different streamflow regimes is crucial to managing for sustainable environmental flows and watershed conservation. We compiled long-term (1916–2016) occurrence records for fishes collected in the Ouachita-Ozark Interior Highlands and West Gulf Coastal Plain streams, together with hydrologic metrics calculated from daily streamflow data measured at USGS stream gauging stations (n = 111), to examine important drivers and thresholds for fish assemblage turnover in groundwater (GW), runoff (RO), and intermittent (INT) flow regimes. We also examined the importance of spatial gradients (latitude, longitude, elevation, drainage area) and anthropogenic-source stressors (Hydrologic Disturbance Index; HDI) for fish assemblage turnover using a gradient forest modeling approach. Watershed fragmentation was of high importance for fish assemblage turnover in RO and INT streams, while changes in dam storage were more important for fishes in GW streams. Hydrologic metrics describing seasonal and stochastic properties of daily streamflow (Mag6) were most important for fish assemblage turnover in INT streams. Timing of high flow events had significantly higher importance compared to flow magnitude, duration, and frequency metrics, especially for fish assemblages in GW and INT streams. The frequency and timing of low flow events had high importance for fish assemblage turnover across all stream flow classes, while the magnitude of low flows and the magnitude and rate of change of average flows was most important for INT stream fish assemblages. In addition to benefiting multi-species conservation and management actions through identification of local and regional flow-ecology relationships generalized across different flow regimes, the results of this study provide a better understanding of complex nonlinear threshold effects, which is critical to anticipating changes in aquatic ecosystems and communities.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2022.109500","usgsCitation":"Fox, J.T., and Magoulick, D.D., 2022, Hydrologic and environmental thresholds in stream fish assemblage structure across flow regimes: Ecological Indicators, v. 144, 109500, 12 p., https://doi.org/10.1016/j.ecolind.2022.109500.","productDescription":"109500, 12 p.","ipdsId":"IP-141446","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":446307,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolind.2022.109500","text":"Publisher Index Page"},{"id":433199,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas, Missouri, Oklahoma","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -94.0072909145776,\n 32.996331346931214\n ],\n [\n -91.86367305364405,\n 32.95089330614236\n ],\n [\n -91.50751795508893,\n 33.152929696557536\n ],\n [\n -91.43542283894192,\n 33.983279606945345\n ],\n [\n -91.88620071539745,\n 34.66359118761602\n ],\n [\n -90.24911433667984,\n 36.41777106986588\n ],\n [\n -89.39173105840047,\n 37.127658750904004\n ],\n [\n -90.27870353794154,\n 38.050842204957206\n ],\n [\n -92.57312445398881,\n 38.27074078230794\n ],\n [\n -94.07764032833012,\n 38.04668122401986\n ],\n [\n -94.69043619691729,\n 36.83802911087706\n ],\n [\n -96.4642878616655,\n 35.22823697686589\n ],\n [\n -96.5088412530875,\n 33.78407715154462\n ],\n [\n -95.25898895253292,\n 33.910484415403275\n ],\n [\n -94.09522136802627,\n 33.61028174407495\n ],\n [\n -94.0072909145776,\n 32.996331346931214\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"144","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Fox, John Tyler","contributorId":341398,"corporation":false,"usgs":false,"family":"Fox","given":"John","email":"","middleInitial":"Tyler","affiliations":[{"id":6623,"text":"University of Arkansas","active":true,"usgs":false}],"preferred":false,"id":908351,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Magoulick, Daniel D. 0000-0001-9665-5957 danmag@usgs.gov","orcid":"https://orcid.org/0000-0001-9665-5957","contributorId":2513,"corporation":false,"usgs":true,"family":"Magoulick","given":"Daniel","email":"danmag@usgs.gov","middleInitial":"D.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908352,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70236979,"text":"ofr20221077 - 2022 - Field investigation of sub-isokinetic sampling by the US D-96-type suspended-sediment sampler and its effect on suspended-sediment measurements","interactions":[],"lastModifiedDate":"2026-03-30T20:32:00.626998","indexId":"ofr20221077","displayToPublicDate":"2022-09-27T09:04:33","publicationYear":"2022","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":"2022-1077","displayTitle":"Field Investigation of Sub-Isokinetic Sampling by the US D-96-Type Suspended-Sediment Sampler and its Effect on Suspended-Sediment Measurements","title":"Field investigation of sub-isokinetic sampling by the US D-96-type suspended-sediment sampler and its effect on suspended-sediment measurements","docAbstract":"Collection of accurate suspended-sediment data using depth-integrating samplers requires that they operate isokinetically, that is, that they sample at the local stream velocity unaffected by the presence of the suspended-sediment sampler. Sub-isokinetic suspended-sediment sampling causes grain-size dependent positive biases in the suspended-sediment concentration measured by the suspended-sediment sampler. Collapsible bag suspended-sediment samplers like the US D-96 and the lighter US D-96-A1 depth-integrating samplers have shown a tendency to sample sub-isokinetically under low stream velocities (below ~3.5 feet per second), colder water temperatures, and longer sampling durations. Previous work concluded that the time-dependent decrease in the intake efficiency of the US D-96-type sampler could be partially overcome by increasing the venting of water from the sampler cavity by shortening the sampler tray. The standard-length sampler tray partially blocks the rear vent hole; shortening the sampler tray effectively increases the area of the sampler-cavity rear vent hole. This previous work showed that removing the partial blockage of the rear vent hole caused by the sampler tray resulted in both an increase in intake efficiency and a decrease in the positive bias in measured suspended-sand concentration.
Herein, a series of tests were conducted on the Colorado River in Arizona using different modifications to a US D-96-A1 sampler to see if physical enlargement of the rear vent hole would produce further improvements in intake efficiency. Results from these tests show that physical enlargement of the rear vent hole, beyond that already effectively achieved by shortening the sampler tray, did not result in any further improvement in intake efficiency. However, these tests also indicated that physically increasing the area of the rear vent hole did not affect the suspended-sediment data collected by the US D-96-A1 sampler. Furthermore, comparisons of suspended-sediment data collected using the US D-96-A1 sampler and the isokinetic US P-61-A1 point-integrating sampler show that the suspended-sediment data collected by the US D-96-type sampler can be accurate in certain circumstances despite the tendency of this sampler to sample sub-isokinetically over the entire depth of a sampling vertical. We surmise that this result could arise from the US D-96-A1 sampler collecting sample isokinetically when the water-sediment mixture enters the nozzle, but that the water-sediment mixture only enters the nozzle intermittently while the sampler transits a sampling vertical.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221077","usgsCitation":"Sabol, T.A., Topping, D.J., Griffiths, R.E., and Dramais, G., 2022, Field investigation of sub-isokinetic sampling by the US D-96-type suspended-sediment sampler and its effect on suspended-sediment measurements: U.S. Geological Survey Open-File Report 2022-1077, 14 p., https://doi.org/10.3133/ofr20221077.","productDescription":"v, 14 p.","numberOfPages":"14","onlineOnly":"Y","ipdsId":"IP-127691","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":501827,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113586.htm","linkFileType":{"id":5,"text":"html"}},{"id":407352,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1077/ofr20221077.pdf","text":"Report","size":"4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1077"},{"id":407351,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1077/covrthb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Colorado River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.58950805664062,\n 36.830722025409784\n ],\n [\n -111.54144287109375,\n 36.830722025409784\n ],\n [\n -111.54144287109375,\n 36.88236678807325\n ],\n [\n -111.58950805664062,\n 36.88236678807325\n ],\n [\n -111.58950805664062,\n 36.830722025409784\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.38714599609375,\n 35.755149755962755\n ],\n [\n -113.33358764648438,\n 35.755149755962755\n ],\n [\n -113.33358764648438,\n 35.777435736805614\n ],\n [\n -113.38714599609375,\n 35.777435736805614\n ],\n [\n -113.38714599609375,\n 35.755149755962755\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Passive membrane samplers—semipermeable membrane devices and polar organic chemical integrative samplers—were deployed for 22 continuous days at 7 sites along the West Maui, Hawaiʻi, coastline in February and March 2017 to assess organic contaminants at shallow coral reef ecosystems from diverse upstream inputs. The distribution of organic compounds observed at these coastal sites showed considerable variability; high concentrations of microbially sourced organic compounds observed at all sites, with pentadecane as the predominant normal alkane, showed the relative importance of marine and microbial organic matter to the coastal carbon pool. Pharmaceuticals and personal care products, as well as flame retardants, were also detected at all sites. Of the seven sites sampled, the Kahekili Beach Park site had the highest number of unique contaminants and the Honokōwai Stream site had the highest concentrations of compounds. Two individual compounds, a flame retardant and a fragrance, were ubiquitous across the studied West Maui reefs, including at the least-developed site. A direct correlation to upstream land-use practices or legacy agricultural inputs was not readily observed since polychlorinated biphenyls, pesticides, herbicides, or insecticides were not detected. Results provide a snapshot of relative contaminant abundances as well as inputs to select nearshore environments along the West Maui coastline captured during the 2017 wet season, which was drier than expected. These data can be useful for understanding the range of stressors potentially affecting nearshore ecosystems, such as groundwater inputs and watershed runoff.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221065","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency and the State of Hawai‘i Department of Health","usgsCitation":"Campbell, P.L., Prouty, N.G., and Storlazzi, C.D., 2022, Pharmaceuticals and personal care products in passive samplers at seven coastal sites off West Maui, Hawaiʻi: U.S. Geological Survey Open-File Report 2022–1065, 14 p., https://doi.org/10.3133/ofr20221065.","productDescription":"Report: vii, 12 p.; Data Release","numberOfPages":"14","onlineOnly":"Y","ipdsId":"IP-132890","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":501819,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113585.htm","linkFileType":{"id":5,"text":"html"}},{"id":435674,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZFE0OP","text":"USGS data release","linkHelpText":"Pharmaceuticals and personal care products measured in passive samplers at seven coastal sites off West Maui during February and March 2017"},{"id":407356,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1065/ofr20221065.pdf","text":"Report","size":"3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1065"},{"id":407355,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1065/covrthb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Maui","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -156.708984375,\n 20.78693059257028\n ],\n [\n -156.5826416015625,\n 20.78693059257028\n ],\n [\n -156.5826416015625,\n 21.04349121680354\n ],\n [\n -156.708984375,\n 21.04349121680354\n ],\n [\n -156.708984375,\n 20.78693059257028\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Pacific Coastal and Marine Science Center
U.S. Geological Survey
2885 Mission St.
Santa Cruz, CA 95060
Tungurahua volcano (Ecuador) intermittently emitted ash between 1999 and 2016, enduringly affecting the surrounding rural area and its population, but its health impact remains poorly documented. We aim to assess the respiratory health hazard posed by the 16–17 August 2006 most intense eruptive phase of Tungurahua. We mapped the spatial distribution of the health-relevant ash size fractions produced by the eruption in the area impacted by ash fallout. We quantified the mineralogy, composition, surface texture, and morphology of a respirable ash sample isolated by aerodynamic separation. We then assessed the cytotoxicity and pro-inflammatory potential of this respirable ash toward lung tissues in-vitro using A549 alveolar epithelial cells, by electron microscopy and biochemical assays. The eruption produced a high amount of inhalable and respirable ash (12.0–0.04 kg/m2 of sub-10 μm and 5.3–0.02 kg/m2 of sub-4 μm ash deposited). Their abundance and proportion vary greatly across the deposit within the first 20 km from the volcano. The respirable ash is characteristic of an andesitic magma and no crystalline silica is detected. Morphological features and surface textures are complex and highly variable, with few fibers observed. In-vitro experiments show that respirable volcanic ash is internalized by A549 cells and processed in the endosomal pathway, causing little cell damage, but resulting in changes in cell morphology and membrane texture. The ash triggers a weak pro-inflammatory response. These data provide the first understanding of the respirable ash hazard near Tungurahua and the extent to which it varies spatially in a fallout deposit.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2022GH000680","usgsCitation":"Eychenne, J., Gurioli, L., Damby, D., Belville, C., Schiavi, F., Marceau, G., Szczepaniak, C., Blavignac, C., Laumonier, M., Gardes, E., Le Pennec, J., Nedelec, J., Blanchon, L., and Sapin, V., 2022, Spatial distribution and physicochemical properties of respirable volcanic ash from the 16-17 August 2006 Tungurahua eruption (Ecuador), and alveolar epithelium response in-vitro: GeoHealth, v. 6, no. 12, e2022GH000680, 21 p., https://doi.org/10.1029/2022GH000680.","productDescription":"e2022GH000680, 21 p.","ipdsId":"IP-142222","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":446315,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2022gh000680","text":"Publisher Index Page"},{"id":418584,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Ecuador","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -78.26112606583433,\n -1.2298836523803232\n ],\n [\n -79.4800078645985,\n -1.2298836523803232\n ],\n [\n -79.4800078645985,\n -2.1006015647003693\n ],\n [\n -78.26112606583433,\n -2.1006015647003693\n ],\n [\n -78.26112606583433,\n -1.2298836523803232\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"6","issue":"12","noUsgsAuthors":false,"publicationDate":"2022-12-17","publicationStatus":"PW","contributors":{"authors":[{"text":"Eychenne, Julia","contributorId":168818,"corporation":false,"usgs":false,"family":"Eychenne","given":"Julia","email":"","affiliations":[{"id":25364,"text":"Univ. Hawai`i","active":true,"usgs":false}],"preferred":false,"id":876427,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gurioli, Lucia","contributorId":218540,"corporation":false,"usgs":false,"family":"Gurioli","given":"Lucia","email":"","affiliations":[{"id":39864,"text":"Laboratoire Magmas et Volcans, Université Blaise Pascal","active":true,"usgs":false}],"preferred":false,"id":876428,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Damby, David 0000-0002-3238-3961","orcid":"https://orcid.org/0000-0002-3238-3961","contributorId":206614,"corporation":false,"usgs":true,"family":"Damby","given":"David","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":876429,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Belville, Corinne","contributorId":315388,"corporation":false,"usgs":false,"family":"Belville","given":"Corinne","email":"","affiliations":[{"id":68301,"text":"Université Clermont Auvergne, France","active":true,"usgs":false}],"preferred":false,"id":876430,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schiavi, Federica","contributorId":315389,"corporation":false,"usgs":false,"family":"Schiavi","given":"Federica","email":"","affiliations":[{"id":68301,"text":"Université Clermont Auvergne, France","active":true,"usgs":false}],"preferred":false,"id":876431,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Marceau, Geoffroy","contributorId":315390,"corporation":false,"usgs":false,"family":"Marceau","given":"Geoffroy","email":"","affiliations":[{"id":68301,"text":"Université Clermont Auvergne, France","active":true,"usgs":false}],"preferred":false,"id":876432,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Szczepaniak, Claire","contributorId":315391,"corporation":false,"usgs":false,"family":"Szczepaniak","given":"Claire","email":"","affiliations":[{"id":68301,"text":"Université Clermont Auvergne, France","active":true,"usgs":false}],"preferred":false,"id":876433,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Blavignac, Christelle","contributorId":315392,"corporation":false,"usgs":false,"family":"Blavignac","given":"Christelle","email":"","affiliations":[{"id":68301,"text":"Université Clermont Auvergne, France","active":true,"usgs":false}],"preferred":false,"id":876434,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Laumonier, Mickael","contributorId":315393,"corporation":false,"usgs":false,"family":"Laumonier","given":"Mickael","email":"","affiliations":[{"id":68301,"text":"Université Clermont Auvergne, France","active":true,"usgs":false}],"preferred":false,"id":876435,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Gardes, Emmanuel","contributorId":315417,"corporation":false,"usgs":false,"family":"Gardes","given":"Emmanuel","email":"","affiliations":[],"preferred":false,"id":876474,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Le Pennec, Jean-Luc","contributorId":315394,"corporation":false,"usgs":false,"family":"Le Pennec","given":"Jean-Luc","affiliations":[{"id":68303,"text":"CNRS, France","active":true,"usgs":false}],"preferred":false,"id":876436,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Nedelec, Jean-Marie","contributorId":315395,"corporation":false,"usgs":false,"family":"Nedelec","given":"Jean-Marie","email":"","affiliations":[{"id":68301,"text":"Université Clermont Auvergne, France","active":true,"usgs":false}],"preferred":false,"id":876437,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Blanchon, Loic","contributorId":315396,"corporation":false,"usgs":false,"family":"Blanchon","given":"Loic","email":"","affiliations":[{"id":68301,"text":"Université Clermont Auvergne, France","active":true,"usgs":false}],"preferred":false,"id":876438,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Sapin, Vincent","contributorId":315397,"corporation":false,"usgs":false,"family":"Sapin","given":"Vincent","email":"","affiliations":[{"id":68301,"text":"Université Clermont Auvergne, France","active":true,"usgs":false}],"preferred":false,"id":876439,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70238019,"text":"70238019 - 2022 - Understanding the role of initial soil moisture and precipitation magnitude in flood forecast using a hydrometeorological modelling system","interactions":[],"lastModifiedDate":"2022-11-04T12:10:15.277815","indexId":"70238019","displayToPublicDate":"2022-09-27T07:07:05","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Understanding the role of initial soil moisture and precipitation magnitude in flood forecast using a hydrometeorological modelling system","docAbstract":"We adapted the WRF-Hydro modelling system to Hurricane Florence (2018) and performed a series of diagnostic experiments to assess the influence of initial soil moisture and precipitation magnitude on flood simulation over the Cape Fear River basin in the United States. Model results suggest that: (1) The modulation effect of initial soil moisture on the flood peak is non-linear and weakens as precipitation magnitude increases. There is a threshold value of the soil saturation, below and above which the sensitivity of flood peak to the soil moisture differentiates substantially; (2) For model spin-up, streamflow needs longer time to reach the ‘practical’ equilibrium (10%) than the soil moisture and latent heat flux. The model uncertainty from spin-up can propagate through the hydrometeorological modelling chain and get amplified into the flood peak; (3) For ensemble flood modelling with a hydrometeorological system, modelling uncertainty is dominated by the precipitation forecast. Spin-up induced uncertainty can be minimized once the model reaches the ‘practical’ equilibrium.
Natural resource management is often challenged with a mismatch between the scale of decision-making and the scale of the biological, ecological, and physical processes that control a system. Bioregional approaches to adaptive management have emerged as an approach to inform natural resource management at ecologically relevant scales and across multi-level governance structures. The implementation of adaptive management requires the determination of ecological and social priorities that can inform a desired system state across multiple governing bodies. We use the Northern Gulf of Mexico, United States, as a case study for a bioregional approach to adaptive management and illustrate a method for developing objectives and management priorities across programs and jurisdictions. Through this synthesis, using qualitative coding methods to develop a shared vocabulary across the diverse dataset, we identified commonalities and differences in ecological and human community priorities across the five states which line the Northern Gulf of Mexico. Using these shared priorities, we conceptualize a network of priority-focused objectives as a starting point for further stakeholder engagement and effectively monitoring and evaluating progress across boundaries. This approach serves as a framework for cross-program adaptive management by illustrating a desired system state that reflects the shared priorities among decision-making authorities in this region and offering individual programs or projects a method to articulate their contributions to the broader set of shared priorities Gulf-wide. This method can be used by restoration managers in any region of the world to align project objectives within cross-jurisdictional boundaries and illustrate the value of a bioregional approach to restoration.
Bottom-simulating reflections (BSRs) that sometimes mark the base of the gas hydrate stability zone in marine sediments are often identified based on the reverse polarity reflections that cut across stratigraphic layering in seismic amplitude data. On the northern U.S. Atlantic margin (USAM) between Cape Hatteras and Hudson Canyon, legacy seismic data have revealed pronounced BSRs south of the deepwater extension of Hudson Canyon and more subtle ones from offshore Delaware south to Cape Hatteras, where the reflections sometimes follow stratigraphic layering. Using high-resolution seismic data acquired during the 2018 Mid-Atlantic Resource Imaging Experiment and a supervised neural net, we identify seismic features associated with gas hydrates and/or the top of gas between Hudson Canyon and Cape Hatteras. Using seismic attributes especially sensitive to the presence of gas, we train a neural network algorithm on seismic data from an area with strong BSRs and then apply the model to the rest of the data set. The results indicate that gas hydrate and/or shallow free gas are significantly more widespread on the northern part of the USAM than previously known. Seismic indicators of gas extend landward from the 2000 m isobath to the upper continental slope in sectors with (offshore Virginia) and, to a lesser extent, without (offshore New Jersey) pervasive upper slope methane seeps. Higher sand content and intermediate sediment thickness, factors related to the container size and gas charge in a petroleum systems framework, are associated with more robust gas indicators.
Black Carp (Mylopharyngodon piceus) was imported to the USA to control aquaculture pond snails. This species has escaped captivity and occurs in parts of the Mississippi River, several tributaries, and floodplain lakes, which is concerning due to potential competition with native fishes and predation on native mussels, many of which are imperiled. However, Black Carp captures have primarily been incidental by commercial fishers, and evidence of reproduction in the wild is limited. The objectives of this study were to assess relative abundance of aquaculture-origin and wild Black Carp using ploidy and otolith stable isotope analysis, identify spatial extent of natural reproduction using otolith microchemistry, assess age distributions of wild and aquaculture-source Black Carp to infer years in which natural reproduction occurred and timing of aquaculture escapement or introductions, and estimate size and age at maturation to assess whether recruitment to adulthood has occurred. Results revealed that Black Carp are established in parts of the Mississippi River basin based on findings that: (1) non-captive Black Carp primarily consist of fertile, naturally-reproduced fish, (2) reproduction has occurred in several rivers, (3) multiple year classes of wild fish are present, and (4) wild fish have recruited to adulthood. Multiple introductions or escapements of aquaculture-source fish into the wild, including both fertile and functionally sterile individuals, were also inferred. Individual growth appears to be rapid, although considerable variation was observed among fish. Additional study is suggested to refine understanding of where and when Black Carp reproduction is occurring in the Mississippi River basin.
We used a representative of one of the oldest extant vertebrate lineages (jawless fish or agnathans) to investigate the early evolution and function of the growth hormone (GH)/prolactin (PRL) family. We identified a second member of the GH/PRL family in an agnathan, the sea lamprey (Petromyzon marinus). Structural, phylogenetic, and synteny analyses supported the identification of this hormone as prolactin-like (PRL-L), which has led to added insight into the evolution of the GH/PRL family. At least two ancestral genes were present in early vertebrates, which gave rise to distinct GH and PRL-L genes in lamprey. A series of gene duplications, gene losses, and chromosomal rearrangements account for the diversity of GH/PRL-family members in jawed vertebrates. Lamprey PRL-L is produced in the proximal pars distalis of the pituitary and is preferentially bound by the lamprey PRL receptor, whereas lamprey GH is preferentially bound by the lamprey GH receptor. Pituitary PRL-L messenger RNA (mRNA) levels were low in larvae, then increased significantly in mid-metamorphic transformers (stage 3); thereafter, levels subsided in final-stage transformers and metamorphosed juveniles. The abundance of PRL-L mRNA and immunoreactive protein increased in the pituitary of juveniles under hypoosmotic conditions, and treatment with PRL-L blocked seawater-associated inhibition of freshwater ion transporters. These findings clarify the origin and divergence of GH/PRL family genes in early vertebrates and reveal a function of PRL-L in osmoregulation of sea lamprey, comparable to a role of PRLs that is conserved in jawed vertebrates.
","language":"English","publisher":"National Academy of Sciences","doi":"10.1073/pnas.2212196119","usgsCitation":"Gong, N., Ferreira-Martins, D., Norstog, J.L., McCormick, S.D., and Sheridan, M., 2022, Discovery of prolactin-like in lamprey: Role in osmoregulation and new insight into the evolution of the growth hormone/prolactin family: PNAS, v. 119, no. 40, e2212196119, 11 p., https://doi.org/10.1073/pnas.2212196119.","productDescription":"e2212196119, 11 p.","ipdsId":"IP-133495","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":446325,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1073/pnas.2212196119","text":"Publisher Index Page"},{"id":408263,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"119","issue":"40","noUsgsAuthors":false,"publicationDate":"2022-09-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Gong, Ningping","contributorId":228919,"corporation":false,"usgs":false,"family":"Gong","given":"Ningping","email":"","affiliations":[{"id":41526,"text":"Univ of Texas, Lubbock","active":true,"usgs":false}],"preferred":false,"id":854461,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ferreira-Martins, Diogo","contributorId":228920,"corporation":false,"usgs":false,"family":"Ferreira-Martins","given":"Diogo","email":"","affiliations":[{"id":37062,"text":"UMASS","active":true,"usgs":false}],"preferred":false,"id":854462,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Norstog, Jessica L. 0000-0002-5495-5131","orcid":"https://orcid.org/0000-0002-5495-5131","contributorId":295345,"corporation":false,"usgs":false,"family":"Norstog","given":"Jessica","email":"","middleInitial":"L.","affiliations":[{"id":6932,"text":"University of Massachusetts, Amherst","active":true,"usgs":false}],"preferred":false,"id":854463,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McCormick, Stephen D. 0000-0003-0621-6200 smccormick@usgs.gov","orcid":"https://orcid.org/0000-0003-0621-6200","contributorId":139214,"corporation":false,"usgs":true,"family":"McCormick","given":"Stephen","email":"smccormick@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":854464,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sheridan, Mark","contributorId":228921,"corporation":false,"usgs":false,"family":"Sheridan","given":"Mark","affiliations":[{"id":41527,"text":"Univ of Texas Lubbock","active":true,"usgs":false}],"preferred":false,"id":854465,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70236960,"text":"dr1163 - 2022 - Groundwater and surface-water data collection for the Walla Walla River Basin, Washington, 2018–22","interactions":[],"lastModifiedDate":"2026-03-18T19:34:40.771206","indexId":"dr1163","displayToPublicDate":"2022-09-26T10:33:29","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":9318,"text":"Data Report","code":"DR","onlineIssn":"2771-9448","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1163","displayTitle":"Groundwater and Surface-Water Data Collection for the Walla Walla River Basin, Washington, 2018–22","title":"Groundwater and surface-water data collection for the Walla Walla River Basin, Washington, 2018–22","docAbstract":"The semi-arid Walla Walla River Basin (WWRB) spans 1777 square miles in the states of Washington and Oregon and supports a diverse agricultural region as well as cities and rural communities that are partially reliant on groundwater. Historically, surface water and groundwater data have been collected in the WWRB by several entities including federal, state, local, and tribal governments; irrigation districts; universities; and non-profits. This report describes the surface and groundwater data collection by the U.S. Geological Survey from February 2018 to April 2022 to provide the Washington State Department of Ecology and other stakeholders basic knowledge of existing water resources in the WWRB, Washington. Additionally, the data were collected to build a long-term groundwater dataset, with the intent to provide data for better understanding to assist in informed decisions about groundwater use, management, and conservation throughout the basin, and for future inclusion in a conceptual model of the groundwater-flow system (conceptual model). Data were collected and compiled for 237 sites—191 wells and 46 surface-water discharge sites. A small annual network of deep basalt wells was established in February 2018 to commence the data collection. In March 2020 and April 2021, additional field inventories were performed by locating and measuring groundwater wells in the WWRB. A subset of the inventoried wells were selected for an annual or a quarterly water level network to be measured until July 2024. In August 2020, field reconnaissance identified 46 surface-water sites to be measured for discharge, estimating gaining and losing reaches in streams for groundwater influences.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dr1163","collaboration":"Prepared in cooperation with Washington Department of Ecology","usgsCitation":"Fasser, E.T., and Dunn, S.B., 2022, Groundwater and surface-water data collection for the Walla Walla River Basin, Washington, 2018–22: Data Report 1163, 8 p., https://doi.org/10.3133/dr1163.","productDescription":"Report: vi, 8 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-140692","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":407252,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/dr/1163/coverthb.jpg"},{"id":407253,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/dr/1163/dr1163.pdf","text":"Report","size":"3.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DR 1163"},{"id":407254,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/dr/1163/images"},{"id":407255,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/dr/1163/dr1163.XML"},{"id":407256,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9D2C2DK","text":"USGS data release","description":"USGS data release","linkHelpText":"Dataset of groundwater and surface water data collection for the Walla Walla Basin in Washington, 2018–2022"},{"id":407257,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/dr1163/full","text":"Report"},{"id":501271,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113584.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Oregon, Washington","otherGeospatial":"Walla Walla River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.21264648437499,\n 45.62172169252446\n ],\n [\n -117.191162109375,\n 45.62172169252446\n ],\n [\n -117.191162109375,\n 47.092565552235705\n ],\n [\n -119.21264648437499,\n 47.092565552235705\n ],\n [\n -119.21264648437499,\n 45.62172169252446\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Washington Water Science Center
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In the United States (US), private-supply tapwater (TW) is rarely monitored. This data gap undermines individual/community risk-management decision-making, leading to an increased probability of unrecognized contaminant exposures in rural and remote locations that rely on private wells. We assessed point-of-use (POU) TW in three northern plains Tribal Nations, where ongoing TW arsenic (As) interventions include expansion of small community water systems and POU adsorptive-media treatment for Strong Heart Water Study participants. Samples from 34 private-well and 22 public-supply sites were analyzed for 476 organics, 34 inorganics, and 3 in vitro bioactivities. 63 organics and 30 inorganics were detected. Arsenic, uranium (U), and lead (Pb) were detected in 54%, 43%, and 20% of samples, respectively. Concentrations equivalent to public-supply maximum contaminant level(s) (MCL) were exceeded only in untreated private-well samples (As 47%, U 3%). Precautionary health-based screening levels were exceeded frequently, due to inorganics in private supplies and chlorine-based disinfection byproducts in public supplies. The results indicate that simultaneous exposures to co-occurring TW contaminants are common, warranting consideration of expanded source, point-of-entry, or POU treatment(s). This study illustrates the importance of increased monitoring of private-well TW, employing a broad, environmentally informative analytical scope, to reduce the risks of unrecognized contaminant exposures.
","language":"English","publisher":"American Chemical Society","doi":"10.1021/acsestwater.2c00293","usgsCitation":"Bradley, P., Romanok, K., Smalling, K., Focazio, M.J., Charboneau, R., George, C.M., Navas-Acien, A., O’Leary, M., Red Cloud, R., Zacher, T., Breitmeyer, S.E., Cardon, M.C., Cuny, C.K., Ducheneaux, G., Enright, K., Evans, N., Gray, J., Harvey, D.E., Hladik, M.L., Kanagy, L.K., Loftin, K.A., McCleskey, R., Medlock-Kakaley, E., Meppelink, S.M., Valder, J., and Weis, C.P., 2022, Tapwater exposures, effects potential, and residential risk management in Northern Plains Nations: Environmental Science and Technology Water, v. 2, no. 10, p. 1772-1788, https://doi.org/10.1021/acsestwater.2c00293.","productDescription":"17 p.","startPage":"1772","endPage":"1788","ipdsId":"IP-117867","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":446328,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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Inc.","active":true,"usgs":false}],"preferred":false,"id":855583,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Ducheneaux, Guthrie","contributorId":298426,"corporation":false,"usgs":false,"family":"Ducheneaux","given":"Guthrie","email":"","affiliations":[{"id":64575,"text":"Missouri Breaks Industries Research Inc.","active":true,"usgs":false}],"preferred":false,"id":855584,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Enright, Kendra","contributorId":298427,"corporation":false,"usgs":false,"family":"Enright","given":"Kendra","email":"","affiliations":[{"id":64575,"text":"Missouri Breaks Industries Research Inc.","active":true,"usgs":false}],"preferred":false,"id":855585,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Evans, 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It generated oil found in Prudhoe Bay and other accumulations and is a prospective self-sourced resource play on Alaska’s North Slope. Its distal, deeper-water equivalent—the Otuk Formation—consists largely of radiolarian chert, mudstone, and limestone and contains potential gas accumulations in the Brooks Range foothills to the south. New petrographic, fossil, geochemical, spectral gamma-ray, and zircon U-Pb data yield insights into facies changes in these units, which were deposited across a shallowly dipping shelf margin in a high-latitude setting. Samples come from four localities along a transect that extends ~410 km from present-day northeast (proximal) to southwest (distal) in northwest Alaska. Proximal Shublik facies (Brontosaurus 1 well) contain abundant siliciclastic detritus and local phosphate. Shublik-Otuk transitional facies occur in the probable onshore extension of the Hanna Trough (Surprise Creek); new zircon U-Pb data indicate an early Norian age for a bentonite bed in this section. Distal Otuk facies (Red Dog district, Cape Lisburne) are fine grained, biosiliceous, and organic rich. New detrital zircon U-Pb data from a distinctive sandstone member in the Otuk Formation at Cape Lisburne reinforce previous interpretations of a provenance to the present-day northwest and indicate a protracted history of Triassic magmatism for this source area. Triassic facies patterns in northwestern Alaska were shaped by sea-level change, climate, and regional tectonism. Organic-rich facies developed best at times (Ladinian–middle Norian) and/or in settings (distal shelf, Hanna Trough) with minimal dilution of organic matter by other detritus.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Understanding the Monterey Formation and similar biosiliceous units across space and time","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"Geological Society of America","doi":"10.1130/2022.2556(11)","usgsCitation":"Dumoulin, J.A., Whidden, K.J., Rouse, W.A., Lease, R.O., Boehlke, A., and O’Sullivan, P., 2022, Biosiliceous, organic-rich, and phosphatic facies of Triassic strata of northwest Alaska: Transect across a high-latitude, low-angle continental margin, chap. of Understanding the Monterey Formation and similar biosiliceous units across space and time, v. 556, p. 243-271, https://doi.org/10.1130/2022.2556(11).","productDescription":"29 p.","startPage":"243","endPage":"271","ipdsId":"IP-113618","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":446332,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1130/spe.s.20387097","text":"External Repository"},{"id":435677,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P924FY7V","text":"USGS data release","linkHelpText":"Geochemical, Geochronologic, Rock-Eval, and Spectral Gamma Ray Data for Selected Triassic Rocks in Northwestern Alaska"},{"id":408478,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -168.134765625,\n 66.8265202749748\n ],\n [\n -141.240234375,\n 66.8265202749748\n ],\n [\n -141.240234375,\n 71.41317683396566\n ],\n [\n -168.134765625,\n 71.41317683396566\n ],\n [\n -168.134765625,\n 66.8265202749748\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"556","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Dumoulin, Julie A. 0000-0003-1754-1287 dumoulin@usgs.gov","orcid":"https://orcid.org/0000-0003-1754-1287","contributorId":203209,"corporation":false,"usgs":true,"family":"Dumoulin","given":"Julie","email":"dumoulin@usgs.gov","middleInitial":"A.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":854909,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Whidden, Katherine J. 0000-0002-7841-2553 kwhidden@usgs.gov","orcid":"https://orcid.org/0000-0002-7841-2553","contributorId":3960,"corporation":false,"usgs":true,"family":"Whidden","given":"Katherine","email":"kwhidden@usgs.gov","middleInitial":"J.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":854910,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rouse, William A. 0000-0002-0790-370X wrouse@usgs.gov","orcid":"https://orcid.org/0000-0002-0790-370X","contributorId":4172,"corporation":false,"usgs":true,"family":"Rouse","given":"William","email":"wrouse@usgs.gov","middleInitial":"A.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":854911,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lease, Richard O. 0000-0003-2582-8966 rlease@usgs.gov","orcid":"https://orcid.org/0000-0003-2582-8966","contributorId":5098,"corporation":false,"usgs":true,"family":"Lease","given":"Richard","email":"rlease@usgs.gov","middleInitial":"O.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":854912,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Boehlke, Adam 0000-0003-4980-431X aboehlke@usgs.gov","orcid":"https://orcid.org/0000-0003-4980-431X","contributorId":3470,"corporation":false,"usgs":true,"family":"Boehlke","given":"Adam","email":"aboehlke@usgs.gov","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":854913,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"O’Sullivan, Paul 0000-0002-7247-5107","orcid":"https://orcid.org/0000-0002-7247-5107","contributorId":254377,"corporation":false,"usgs":false,"family":"O’Sullivan","given":"Paul","email":"","affiliations":[{"id":51089,"text":"Geosep Services","active":true,"usgs":false}],"preferred":false,"id":854914,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ]}