As part of a long-term cooperative program to monitor water quality within the Scituate Reservoir drainage area, the U.S. Geological Survey in cooperation with the Providence Water Supply Board collected streamflow and water-quality data at the Scituate Reservoir and tributaries. Streamflow and concentrations of chloride and sodium estimated from records of specific conductance were used to calculate loads of chloride and sodium during water year 2019 (October 1, 2018, through September 30, 2019) for tributaries to the Scituate Reservoir, Rhode Island. Streamflow was measured or estimated by the U.S. Geological Survey following standard methods at 23 streamgages; 14 of these streamgages are equipped with instrumentation capable of continuously monitoring water level, specific conductance, and water temperature. Water-quality samples were collected by the Providence Water Supply Board at 37 sampling stations, which also include the 14 continuous-record streamgages maintained by the U.S. Geological Survey, during water year 2019 as part of a long-term sampling program; all stations are in the Scituate Reservoir drainage area. Water-quality data collected by the Providence Water Supply Board are summarized by using values of central tendency and are used, in combination with measured (or estimated) streamflows, to calculate loads and yields (loads per unit area) of selected water-quality constituents for water year 2019.
The largest tributary to the reservoir, the Ponaganset River, which was monitored by the U.S. Geological Survey, contributed a mean streamflow of 40 cubic feet per second to the reservoir during water year 2019. For the same period, annual mean streamflows measured (or estimated) for the other monitoring stations in this study ranged from about 0.55 to about 26 cubic feet per second. Together, tributaries equipped with instrumentation capable of continuously monitoring specific conductance transported about 3,500 metric tons of chloride and 2,100 metric tons of sodium to the Scituate Reservoir during water year 2019; annual chloride yields for the tributaries ranged from 20 to 180 metric tons per square mile, and annual sodium yields ranged from 14 to 100 metric tons per square mile.
At the stations where water-quality samples were collected by the Providence Water Supply Board, the medians of the median concentrations were 25.1 milligrams per liter for chloride, 0.001 milligram per liter as nitrogen for nitrite, 0.08 milligram per liter as nitrogen for nitrate, 0.03 milligram per liter as phosphate for orthophosphate, 1,000 colony forming units per 100 milliliters for total coliform bacteria, and 10 colony forming units per 100 milliliters for Escherichia coli (E. coli). The medians of the median daily loads of chloride, nitrite, nitrate, orthophosphate, total coliform, and E. coli bacteria were 340 kilograms per day, 18 grams per day, 1,000 grams per day, 410 grams per day, 81,000 million colony forming units per day, and less than 1,800 million colony forming units per day, respectively. The medians of the median yields of chloride, nitrite, nitrate, orthophosphate, total coliform, and E. coli bacteria were 140 kilograms per day per square mile, 6.8 grams per day per square mile, 440 grams per day per square mile, 140 grams per day per square mile, 32,000 million colony forming units per day per square mile, and 660 million colony forming units per day per square mile, respectively.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dr1145","collaboration":"Prepared in cooperation with the Providence Water Supply Board","usgsCitation":"Smith, K.P., 2022, Streamflow, water quality, and constituent loads and yields, Scituate Reservoir drainage area, Rhode Island, water year 2019: U.S. Geological Survey Data Report 1145, 35 p., https://doi.org/10.3133/dr1145.","productDescription":"Report: v, 35 p.; Data release; Dataset","numberOfPages":"35","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-125608","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":394951,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/dr/1145/coverthb.jpg"},{"id":501201,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112157.htm","linkFileType":{"id":5,"text":"html"}},{"id":394956,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","linkHelpText":"- USGS water data for the Nation"},{"id":394955,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WK8N0F","text":"USGS data release","linkHelpText":"Water quality data from the Providence Water Supply Board for tributary streams to the Scituate Reservoir, water year 2018–19"},{"id":394954,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/dr/1145/dr1145.XML"},{"id":394953,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/dr/1145/images/"},{"id":394952,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/dr/1145/dr1145.pdf","text":"Report","size":"1.73 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DR 1145"}],"country":"United States","state":"Rhode Island","otherGeospatial":"Scituate Reservoir Drainage Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.78192138671875,\n 41.71187978193456\n ],\n [\n -71.50177001953125,\n 41.71187978193456\n ],\n [\n -71.50177001953125,\n 41.947234477977766\n ],\n [\n -71.78192138671875,\n 41.947234477977766\n ],\n [\n -71.78192138671875,\n 41.71187978193456\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Direct and indirect measures of individual movement provide valuable knowledge regarding a species’ resiliency to environmental change. Information on patterns of movement can inform species management and conservation but is lacking for many imperiled fishes. The Candy Darter, Etheostoma osburni, is an endangered stream fish with a dramatically reduced distribution in Virginia in the eastern United States, now known from only four isolated populations. We used visual implant elastomer tags and microsatellite DNA markers to directly describe movement patterns in two populations. Parentage analysis based on parent-offspring pairs was used to infer movement patterns of young-of-year and age-1 individuals, as well as the reproductive contribution of certain adults. Direct measurements of movement distances were generally similar between methods, but microsatellite markers revealed greater distances moved, commensurate with greater spatial frames sampled. Parent-offspring pairs were found throughout the species’ 18.8-km distribution in Stony Creek, while most parent-offspring pairs were in 2 km of the 4.25-km distribution in Laurel Creek. Sibship reconstruction allowed us to characterize the mating system and number of spawning years for adults. Our results provide the first measures of movement patterns of Candy Darter as well as the spatial distribution of parent-offspring pairs, which may be useful for selecting collection sites in source populations to be used for translocation or reintroductions. Our results highlight the importance of documenting species movement patterns and spatial distributions of related individuals as steps toward understanding population dynamics and informing translocation strategies. We also demonstrate that the reproductive longevity of this species is greater than previously described, which may be the case for other small stream fishes.
","language":"English","publisher":"MDPI","doi":"10.3390/fishes7010030","usgsCitation":"McBaine, K., Hallerman, E., and Angermeier, P., 2022, Direct and molecular observation of movement and reproduction by Candy Darter, Etheostoma osburni, an endangered benthic stream fish in Virginia, USA: Fishes, v. 7, no. 1, 30, 19 p., https://doi.org/10.3390/fishes7010030.","productDescription":"30, 19 p.","ipdsId":"IP-136240","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":481094,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/fishes7010030","text":"Publisher Index Page"},{"id":480849,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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including from commercial sources. The CAC is operated and staffed by the U.S. Geological Survey on behalf of the U.S. Department of the Interior and its interagency partners. The director of the U.S. Geological Survey is the chair of the committee, and the vice-chair is a non-Department of the Interior senior official. The CAC ensures certain Federal civil agencies have access to these remotely sensed assets to meet their statutory missions in ways that do not threaten the civil rights, civil liberties, and personal privacy of U.S. citizens. To meet its mandate, the CAC hosts various working groups and communities of interest including those focused on thermal issues (wildland fires and volcanoes), environmental security, and historical satellite imagery.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20223002","usgsCitation":"Opstal, D.W., and Rogers, R.T., 2022, Civil Applications Committee (ver. 1.4, January 2026): U.S. Geological Survey Fact Sheet 2022–3002, 2 p., https://doi.org/10.3133/fs20223002.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-126482","costCenters":[{"id":36171,"text":"National Civil Applications Center","active":true,"usgs":true}],"links":[{"id":394944,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2022/3002/coverthb5.jpg"},{"id":394945,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2022/3002/fs20223002.pdf","text":"Report","size":"1.37 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2022-3002"},{"id":395432,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/fs/2022/3002/versionHist.txt","size":"1.43 KB","linkFileType":{"id":2,"text":"txt"}}],"edition":"Version 1.0: January 27, 2022; Version 1.1: February 4, 2022; Version 1.2: March 7, 2023; Version 1.3: March 4, 2025; Version 1.4: January 14, 2026","contact":"CAC Secretariat
National Land Imaging Program
U.S. Geological Survey
12201 Sunrise Valley Drive, MS 562
Reston, VA 20192
The Southcentral Alaska (SCAK) sea otter (Enhydra lutris) stock is the northernmost stock of sea otters, a keystone predator known for structuring nearshore marine ecosystems. We conducted aerial surveys within the range of the SCAK sea otter stock to provide recent estimates of sea otter abundance and distribution. We defined three survey regions: (1) Eastern Cook Inlet (2017), (2) Outer Kenai Peninsula (2019), and (3) Prince William Sound (2014 and 2017). Combined, the three regional estimates yielded an overall abundance estimate of 21,617 sea otters (standard error [SE] = 2,190) with an average density of 1.96 sea otters per square kilometer (km2; SE = 0.55). Sea otters were distributed unevenly across the survey regions and densities varied from 0.52 sea otters/km2 (SE = 0.18) in the deep rock-walled glacial fjords along parts of the Outer Kenai Peninsula to nearly 20 sea otters/km2 (SE = 6.70) in shallow soft-bottom communities such as those in Orca Inlet and Kachemak Bay. These survey results represent the best available contemporary information concerning the distribution, density, and abundance of sea otters across the range of the SCAK stock. Survey data files have been standardized and formatted in data releases associated with this report so that they can be queried and displayed with standard geographic information system and database management software. In addition to providing contemporary information on sea otter populations, this report details how an observer-based aerial survey method has been applied in Alaska over 2 decades.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211122","collaboration":"Prepared in cooperation with U.S. Fish and Wildlife Service","usgsCitation":"Esslinger, G.G., Robinson, B.H., Monson, D.H., Taylor, R.L., Esler, D., Weitzman, B.P., and Garlich-Miller, J., 2021, Abundance and distribution of sea otters (Enhydra lutris) in the southcentral Alaska stock, 2014, 2017, and 2019: U.S. Geological Survey Open-File Report 2021–1122, 19 p., https://doi.org/10.3133/ofr20211122.","productDescription":"Report: iv, 19 p.; 4 Data Releases","numberOfPages":"19","onlineOnly":"Y","ipdsId":"IP-125417","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":394901,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TTJVBC","linkHelpText":"Sea otter aerial survey data from the outer Kenai Peninsula, Alaska, 2019"},{"id":394902,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KNKOG1","linkHelpText":"Sea otter aerial survey data from western Prince William Sound, Alaska, 2017"},{"id":394904,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/p9OG6SR5","linkHelpText":"Sea otter aerial survey data from northern and eastern Prince William Sound, Alaska, 2014"},{"id":394903,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Q4DA3T","linkHelpText":"Sea otter aerial survey data from lower Cook Inlet, Alaska, 2017"},{"id":435988,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9OG6SR5","text":"USGS data release","linkHelpText":"Sea Otter Aerial Survey Data from Northern and Eastern Prince William Sound, Alaska, 2014"},{"id":394895,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1122/covrthb.jpg"},{"id":394896,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1122/ofr20211122.pdf","text":"Report","size":"26 MB","linkFileType":{"id":1,"text":"pdf"}}],"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 -155.3466796875,\n 57.868131763328826\n ],\n [\n -143.0419921875,\n 57.868131763328826\n ],\n [\n -143.0419921875,\n 61.80428390136847\n ],\n [\n -155.3466796875,\n 61.80428390136847\n ],\n [\n -155.3466796875,\n 57.868131763328826\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Alaska Science Center
U.S. Geological Survey
4210 University Drive
Anchorage, Alaska 99508
Warm water temperatures in the lower Yakima River in central Washington are key limitations to the restoration of Pacific salmon (Onchorhynchus spp.) populations within the Yakima River Basin. Identification of the location and magnitude of cold-water anomalies, which are cooler than ambient river temperatures during summer months, and the processes that create and maintain them is needed to inform salmon restoration efforts within the Yakima River Basin. Longitudinal thermal profiles of nine reaches in the lower Yakima River were surveyed at ambient river velocity during summer 2018 when surface-water temperatures were near their annual maximum and the difference between surface-water and groundwater temperatures was greatest. The profiles were compared to previously published profiles of the same reaches measured in 2001, 2002, 2008, and 2009, and analyzed in the context of hydrologic, geomorphic, and hydrogeologic conditions that may create and maintain cold-water inputs to the river. Cold-water anomalies that departed from expected diurnal increases in water temperature were measured in all nine study reaches and were attributed to diffuse groundwater discharge through the streambed, discrete groundwater discharge at seeps and springs, and cold-water tributaries entering the river. Some cold-water anomalies were measured during repeated surveys in different years, whereas other cold-water anomalies did not persist across surveys. Additionally, some discrete cold-water anomalies were confined to one side of the channel, but others associated with diffuse groundwater discharge were present across the channel for several river miles. Hydrogeologic conditions including the extent and thickness of aquifers connected to the Yakima River, geomorphic conditions including channel gradient, channel geometry, and floodplain extent, and the location of tributaries, irrigation returns, and other surface-water inputs created the large-scale conditions that facilitate the formation and maintenance of cold-water anomalies. Finer-scale geomorphic features such as side channels, gravel-bar alcoves, deep pools, and other locations, where colder water collected and remained relatively unmixed with upstream surface water, were also important factors in the occurrence and distribution of cold-water anomalies. These hydrogeologic and geomorphic conditions, coupled with the alteration of the Yakima River’s hydrologic regime to support irrigation within the Yakima Valley, contributed to the surveyed distribution of cold-water anomalies within the river.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215140","collaboration":"Prepared in cooperation with Benton Conservation District under Washington Department of Ecology Funding Agreement WRYBP-VER1-BentCD-00004 as part of the Yakima Basin Integrated Plan","usgsCitation":"Gendaszek, A.S., and Appel, M., 2021, Thermal heterogeneity and cold-water anomalies within the lower Yakima River, Yakima and Benton Counties, Washington: U.S. Geological Survey Scientific Investigations Report 2021–5140, 45 p., https://doi.org/10.3133/sir20215140.","productDescription":"Report: v, 43 p.; Data Release","numberOfPages":"43","onlineOnly":"Y","ipdsId":"IP-126706","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":394822,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5140/sir20215140.pdf","text":"Report","size":"13 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Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
Many aquatic invertebrates are declining or facing extinction from stressors that compromise physiology, resource consumption, reproduction, and phenology. However, the influence of these common stressors specifically on consumer–resource interactions for aquatic invertebrate consumers is only beginning to be understood. We conducted a field study to investigate Pteronarcys californica (i.e., the “giant salmonfly”), a large-bodied insect that is ecologically and culturally significant to rivers throughout the western United States. We sampled gut contents and polyunsaturated fatty acid composition of salmonflies to compare resource consumption across river (Madison or Gallatin, Montana), sex (male or female), and habitat (rock or woody debris). We found that allochthonous detritus comprised the majority of salmonfly diets in the Gallatin and Madison Rivers, making up 68% of the gut contents on average, followed by amorphous detritus, diatoms, and filamentous algae. Diets showed little variation across river, sex, or length. Minor differences in diets were detected by habitat type, with a higher proportion of diatoms in the diets of salmonflies collected from rocky habitat compared to woody debris. Fatty acid composition generally supported the results of gut content analysis but highlighted the importance of primary producers. The presence of eicosapentaenoic acid (20:5n-3) and alpha linolenic acid (18:3n-3) indicated consumption of diatoms and filamentous green algae, respectively. Our research underscores the importance of a healthy riparian zone that provides allochthonous detritus for invertebrate nutrition as well as the role of algae as an important source of fatty acids.
As part of a long-term cooperative program to monitor water quality within the Scituate Reservoir drainage area, the U.S. Geological Survey in cooperation with the Providence Water Supply Board collected streamflow and water-quality data at the Scituate Reservoir and tributaries. Streamflow and concentrations of chloride and sodium estimated from records of specific conductance were used to calculate loads of chloride and sodium during water year 2018 (October 1, 2017, through September 30, 2018) for tributaries to the Scituate Reservoir, Rhode Island. Streamflow was measured or estimated by the U.S. Geological Survey following standard methods at 23 streamgages; 14 of these streamgages are equipped with instrumentation capable of continuously monitoring water level, specific conductance, and water temperature. Water-quality samples were collected by the Providence Water Supply Board at 36 sampling stations, which also include the 14 continuous-record streamgages maintained by the U.S. Geological Survey, during water year 2018 as part of a long-term sampling program; all stations are in the Scituate Reservoir drainage area. Water-quality data collected by the Providence Water Supply Board are summarized by using values of central tendency and are used, in combination with measured (or estimated) streamflows, to calculate loads and yields (loads per unit area) of selected water-quality constituents for water year 2018.
The largest tributary to the reservoir, the Ponaganset River, which was monitored by the U.S. Geological Survey, contributed a mean streamflow of 33 cubic feet per second to the reservoir during water year 2018. For the same period, annual mean streamflows measured (or estimated) for the other monitoring stations in this study ranged from about 0.34 to about 20 cubic feet per second. Together, tributaries equipped with instrumentation capable of continuously monitoring specific conductance transported about 3,100 metric tons of chloride and 1,900 metric tons of sodium to the Scituate Reservoir during water year 2018; annual chloride yields for the tributaries ranged from 18 to 140 metric tons per square mile, and annual sodium yields ranged from 12 to 80 metric tons per square mile.
At the stations where water-quality samples were collected by the Providence Water Supply Board, the medians of the median concentrations were 25.8 milligrams per liter for chloride, 0.001 milligram per liter as nitrogen for nitrite, 0.11 milligram per liter as nitrogen for nitrate, 0.04 milligram per liter as phosphate for orthophosphate, 1,200 colony forming units per 100 milliliters for total coliform bacteria, and 10 colony forming units per 100 milliliters for Escherichia coli (E. coli). The medians of the median daily loads of chloride, nitrite, nitrate, orthophosphate, total coliform, and E. coli bacteria were 220 kilograms per day, 15 grams per day, less than 890 grams per day, 360 grams per day, 93,000 million colony forming units per day, and less than 700 million colony forming units per day, respectively. The medians of the median yields of chloride, nitrite, nitrate, orthophosphate, total coliform, and E. coli bacteria were 110 kilograms per day per square mile, 5.5 grams per day per square mile, 250 grams per day per square mile, 210 grams per day per square mile, 36,000 million colony forming units per day per square mile, and 410 million colony forming units per day per square mile, respectively.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dr1144","collaboration":"Prepared in cooperation with the Providence Water Supply Board","usgsCitation":"Smith, K.P., 2022, Streamflow, water quality, and constituent loads and yields, Scituate Reservoir drainage area, Rhode Island, water year 2018: U.S. Geological Survey Data Report 1144, 36 p., https://doi.org/10.3133/dr1144.","productDescription":"Report: v, 36 p.; Data release; Dataset","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-120140","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":501199,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112156.htm","linkFileType":{"id":5,"text":"html"}},{"id":394803,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/dr/1144/images/"},{"id":394802,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/dr/1144/dr1144.XML"},{"id":394801,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the Nation"},{"id":394800,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WK8N0F","text":"USGS data release","linkHelpText":"Water quality data from the Providence Water Supply Board for tributary streams to the Scituate Reservoir, water year 2018–19"},{"id":394799,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/dr/1144/dr1144.pdf","text":"Report","size":"1.59 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DR 1144"},{"id":394798,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/dr/1144/coverthb.jpg"}],"country":"United States","state":"Rhode Island","otherGeospatial":"Scituate Reservoir Drainage Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.77642822265625,\n 41.69752591075902\n ],\n [\n -71.54022216796875,\n 41.69752591075902\n ],\n [\n -71.54022216796875,\n 41.92680320648791\n ],\n [\n -71.77642822265625,\n 41.92680320648791\n ],\n [\n -71.77642822265625,\n 41.69752591075902\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Physical processes driving barrier island change during storms are important to understand to mitigate coastal hazards and to evaluate conceptual models for barrier evolution. Spatial variations in barrier island topography, landcover characteristics, and nearshore and back-barrier hydrodynamics can yield complex morphological change that requires models of increasing resolution and physical complexity to predict. Using the Coupled Ocean-Atmosphere-Wave-Sediment Transport (COAWST) modeling system, we investigated two barrier island breaches that occurred on Fire Island, NY during Hurricane Sandy (2012) and at Matanzas, FL during Hurricane Matthew (2016). The model employed a recently implemented infragravity (IG) wave driver to represent the important effects of IG waves on nearshore water levels and sediment transport. The model simulated breaching and other changes with good skill at both locations, resolving differences in the processes and evolution. The breach simulated at Fire Island was 250 m west of the observed breach, whereas the breach simulated at Matanzas was within 100 m of the observed breach. Implementation of the vegetation module of COAWST to allow three-dimensional drag over dune vegetation at Fire Island improved model skill by decreasing flows across the back-barrier, as opposed to varying bottom roughness that did not positively alter model response. Analysis of breach processes at Matanzas indicated that both far-field and local hydrodynamics influenced breach creation and evolution, including remotely generated waves and surge, but also surge propagation through back-barrier waterways. This work underscores the importance of resolving the complexity of nearshore and back-barrier systems when predicting barrier island change during extreme events.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2021JF006307","usgsCitation":"Hegermiller, C., Warner, J.C., Olabarrieta, M., Sherwood, C.R., and Kalra, T., 2022, Modeling of barrier breaching during Hurricanes Sandy and Matthew: JGR-Earth Surface, v. 127, no. 3, e2021JF006307, 20 p., https://doi.org/10.1029/2021JF006307.","productDescription":"e2021JF006307, 20 p.","ipdsId":"IP-130367","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":449023,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1029/2021jf006307","text":"External Repository"},{"id":413242,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida, New York","city":"Matanzas","otherGeospatial":"Fire Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -74.23320426968054,\n 41.082997080822736\n ],\n [\n -74.23320426968054,\n 40.32905270617809\n ],\n [\n -71.43741334729009,\n 40.32905270617809\n ],\n [\n -71.43741334729009,\n 41.082997080822736\n ],\n [\n -74.23320426968054,\n 41.082997080822736\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -80.335863306947,\n 26.295094198443238\n ],\n [\n -78.26241414026661,\n 27.205116096340547\n ],\n [\n -80.7016669317273,\n 31.630079958177035\n ],\n [\n -82.69413025464559,\n 30.949177652812494\n ],\n [\n -80.2897567468504,\n 26.26830908028633\n ],\n [\n -80.335863306947,\n 26.295094198443238\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"127","issue":"3","noUsgsAuthors":false,"publicationDate":"2022-03-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Hegermiller, Christie 0000-0002-6383-7508","orcid":"https://orcid.org/0000-0002-6383-7508","contributorId":241895,"corporation":false,"usgs":true,"family":"Hegermiller","given":"Christie","affiliations":[{"id":36711,"text":"Woods Hole Oceanographic Institution","active":true,"usgs":false}],"preferred":true,"id":864757,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Warner, John C. 0000-0002-3734-8903 jcwarner@usgs.gov","orcid":"https://orcid.org/0000-0002-3734-8903","contributorId":258015,"corporation":false,"usgs":true,"family":"Warner","given":"John","email":"jcwarner@usgs.gov","middleInitial":"C.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":864758,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Olabarrieta, Maitane 0000-0002-7619-7992 molabarrieta@usgs.gov","orcid":"https://orcid.org/0000-0002-7619-7992","contributorId":211373,"corporation":false,"usgs":false,"family":"Olabarrieta","given":"Maitane","email":"molabarrieta@usgs.gov","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":864759,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sherwood, Christopher R. 0000-0001-6135-3553 csherwood@usgs.gov","orcid":"https://orcid.org/0000-0001-6135-3553","contributorId":2866,"corporation":false,"usgs":true,"family":"Sherwood","given":"Christopher","email":"csherwood@usgs.gov","middleInitial":"R.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":864760,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kalra, Tarandeep S. 0000-0001-5468-248X tkalra@usgs.gov","orcid":"https://orcid.org/0000-0001-5468-248X","contributorId":178820,"corporation":false,"usgs":true,"family":"Kalra","given":"Tarandeep S.","email":"tkalra@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":864762,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70256727,"text":"70256727 - 2022 - Influences of channel and floodplain modification on expansion of woody vegetation into Catahoula Lake, Louisiana, USA","interactions":[],"lastModifiedDate":"2024-09-03T16:44:50.779458","indexId":"70256727","displayToPublicDate":"2022-01-26T11:39:54","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1425,"text":"Earth Surface Processes and Landforms","active":true,"publicationSubtype":{"id":10}},"title":"Influences of channel and floodplain modification on expansion of woody vegetation into Catahoula Lake, Louisiana, USA","docAbstract":"Ecosystem structure of wetlands in managed floodplains depends on hydrological processes controlled by geomorphology and water management. Overlapping effects of direct modifications and geomorphic adjustments to management can combine to trigger changes to floodplain ecosystem structure. We examined the case of woody vegetation encroaching into the depressional Catahoula Lake, Louisiana, in the context of regional hydrologic and geomorphic modification in the floodplain of the Mississippi River. Historical aerial photographs indicated woody encroachment into Catahoula Lake for at least 80 years, and the rate of expansion has increased in recent decades. Historical stage analysis revealed that the downstream Red–Atchafalaya–Mississippi River system controls the lower limit of the lake water level when the large rivers are high, but channel enlargement and other hydrological changes there have reduced the frequency of backwater flooding by 42% since 1880. In addition, operation of the water control structure on the lake has altered its hydrological regime to be more regular among years. Historic stage analysis revealed current lake levels are lower in the high-water spring, less variable in the dry period, and lack the extreme high-water events of 100+ years ago, all of which facilitate the expansion of woody vegetation.
","language":"English","publisher":"Wiley","doi":"10.1002/esp.5328","usgsCitation":"Keim, R., Dugue, L., Latuso, K., Joshi, S., King, S.L., and Willis, F., 2022, Influences of channel and floodplain modification on expansion of woody vegetation into Catahoula Lake, Louisiana, USA: Earth Surface Processes and Landforms, v. 47, no. 6, p. 1466-1479, https://doi.org/10.1002/esp.5328.","productDescription":"14 p.","startPage":"1466","endPage":"1479","ipdsId":"IP-130218","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":449025,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/esp.5328","text":"Publisher Index Page"},{"id":433416,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Catahoula Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -92.20285714912983,\n 31.44173705449458\n ],\n [\n -92.12418940417722,\n 31.44557223555043\n ],\n [\n -92.0297881102343,\n 31.532780176376406\n ],\n [\n -92.03877870965712,\n 31.576832357365504\n ],\n [\n -92.0803602319895,\n 31.574917477714266\n ],\n [\n -92.13655147838381,\n 31.541400717897048\n ],\n [\n -92.17925682564407,\n 31.505955624529022\n ],\n [\n -92.21521922333639,\n 31.45899413301514\n ],\n [\n -92.20285714912983,\n 31.44173705449458\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"47","issue":"6","noUsgsAuthors":false,"publicationDate":"2022-02-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Keim, R.F.","contributorId":264646,"corporation":false,"usgs":false,"family":"Keim","given":"R.F.","affiliations":[{"id":54524,"text":"Lousiiana State University","active":true,"usgs":false}],"preferred":false,"id":908787,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dugue, L.","contributorId":341705,"corporation":false,"usgs":false,"family":"Dugue","given":"L.","email":"","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":908788,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Latuso, K.D.","contributorId":341706,"corporation":false,"usgs":false,"family":"Latuso","given":"K.D.","affiliations":[{"id":5115,"text":"Louisiana State University","active":true,"usgs":false}],"preferred":false,"id":908789,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Joshi, S.","contributorId":341707,"corporation":false,"usgs":false,"family":"Joshi","given":"S.","email":"","affiliations":[{"id":13314,"text":"Columbia River Inter-Tribal Fish Commission","active":true,"usgs":false}],"preferred":false,"id":908790,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"King, Sammy L. 0000-0002-5364-6361 sking@usgs.gov","orcid":"https://orcid.org/0000-0002-5364-6361","contributorId":557,"corporation":false,"usgs":true,"family":"King","given":"Sammy","email":"sking@usgs.gov","middleInitial":"L.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908791,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Willis, F.L.","contributorId":341708,"corporation":false,"usgs":false,"family":"Willis","given":"F.L.","email":"","affiliations":[{"id":81776,"text":"Willis Engineering and Scientific","active":true,"usgs":false}],"preferred":false,"id":908792,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70227681,"text":"70227681 - 2022 - The potential of wave energy conversion to mitigate coastal erosion from hurricanes","interactions":[],"lastModifiedDate":"2022-01-26T17:12:54.664026","indexId":"70227681","displayToPublicDate":"2022-01-26T11:03:34","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2380,"text":"Journal of Marine Science and Engineering","active":true,"publicationSubtype":{"id":10}},"title":"The potential of wave energy conversion to mitigate coastal erosion from hurricanes","docAbstract":"Wave energy conversion technologies have recently attracted more attention as part of global efforts to replace fossil fuels with renewable energy resources. While ocean waves can provide renewable energy, they can also be destructive to coastal areas that are often densely populated and vulnerable to coastal erosion. There have been a variety of efforts to mitigate the impacts of wave- and storm-induced erosion; however, they are either temporary solutions or approaches that are not able to adapt to a changing climate. This study explores a green and sustainable approach to mitigating coastal erosion from hurricanes through wave energy conversion. A barrier island, Dauphin Island, off the coast of Alabama, is used as a test case. The potential use of wave energy converter farms to mitigate erosion due to hurricane storm surges while simultaneously generating renewable energy is explored through simulations that are forced with storm data using the XBeach model. It is shown that wave farms can impact coastal morphodynamics and have the potential to reduce dune and beach erosion, predominantly in the western portion of the island. The capacity of wave farms to influence coastal morphodynamics varies with the storm intensity.
","language":"English","publisher":"MDPI AG","doi":"10.3390/jmse10020143","usgsCitation":"Ozkan, C., Mayo, T., and Passeri, D., 2022, The potential of wave energy conversion to mitigate coastal erosion from hurricanes: Journal of Marine Science and Engineering, v. 10, no. 2, p. 1-26, https://doi.org/10.3390/jmse10020143.","productDescription":"143, 26 p.","startPage":"1","endPage":"26","ipdsId":"IP-126398","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":449028,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/jmse10020143","text":"Publisher Index Page"},{"id":394882,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alabama","otherGeospatial":"Dauphin Island, Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.35411071777344,\n 30.22317846163011\n ],\n [\n -88.06777954101562,\n 30.22317846163011\n ],\n [\n -88.06777954101562,\n 30.355397662121728\n ],\n [\n -88.35411071777344,\n 30.355397662121728\n ],\n [\n -88.35411071777344,\n 30.22317846163011\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"2","noUsgsAuthors":false,"publicationDate":"2022-01-21","publicationStatus":"PW","contributors":{"editors":[{"text":"Morales, Rafael","contributorId":272228,"corporation":false,"usgs":false,"family":"Morales","given":"Rafael","email":"","affiliations":[],"preferred":false,"id":831787,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Ozkan, Cigdem","contributorId":272200,"corporation":false,"usgs":false,"family":"Ozkan","given":"Cigdem","email":"","affiliations":[{"id":18879,"text":"University of Central Florida","active":true,"usgs":false}],"preferred":false,"id":831708,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mayo, Talea","contributorId":272201,"corporation":false,"usgs":false,"family":"Mayo","given":"Talea","email":"","affiliations":[{"id":40432,"text":"Emory University","active":true,"usgs":false}],"preferred":false,"id":831709,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Passeri, Davina 0000-0002-9760-3195 dpasseri@usgs.gov","orcid":"https://orcid.org/0000-0002-9760-3195","contributorId":166889,"corporation":false,"usgs":true,"family":"Passeri","given":"Davina","email":"dpasseri@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":831710,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70227682,"text":"70227682 - 2022 - Guidelines for volcano-observatory operations during crises: Recommendations from the 2019 Volcano Observatory Best Practices meeting","interactions":[],"lastModifiedDate":"2022-01-26T17:02:08.978401","indexId":"70227682","displayToPublicDate":"2022-01-26T10:22:26","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3841,"text":"Journal of Applied Volcanology","active":true,"publicationSubtype":{"id":10}},"title":"Guidelines for volcano-observatory operations during crises: Recommendations from the 2019 Volcano Observatory Best Practices meeting","docAbstract":"In November 2019, the fourth meeting on Volcano Observatory Best Practices workshop was held in Mexico City as a series of talks, discussions, and panels. Volcanologists from around the world offered suggestions for ways to optimize volcano-observatory crisis operations. By crisis, we mean unrest that may or may not lead to eruption, the eruption itself, or its aftermath, all of which require analysis and communications by the observatory. During a crisis, the priority of the observatory should be to acquire, process, analyze, and interpret data in a timely manner. A primary goal is to communicate effectively with the authorities in charge of civil protection. Crisis operations should rely upon exhaustive planning in the years prior to any actual unrest or eruptions. Ideally, nearly everything that observatories do during a crisis should be envisioned, prepared, and practiced prior to the actual event. Pre-existing agreements and exercises with academic and government collaborators will minimize confusion about roles and responsibilities. In the situation where planning is unfinished, observatories should prioritize close ties and communications with the land and civil-defense authorities near the most threatening volcanoes. \nTo a large extent, volcanic crises become social crises, and any volcano observatory should have a communication strategy, a lead communicator, regular status updates, and a network of colleagues outside the observatory who can provide similar messaging to a public that desires consistent and authoritative information. Checklists permit tired observatory staff to fulfill their duties without forgetting key communications, data streams, or protocols that need regular fulfilment (Bretton et al. 2018; Newhall et al. 2020). Observatory leaders need to manage staff workload to prevent exhaustion and ensure that expertise is available as needed. Event trees and regular group discussions encourage multi-disciplinary thinking, consideration of disparate viewpoints, and documentation of all group decisions and consensus. Though regulations, roles and responsibilities differ around the world, scientists can justify their actions in the wake of an eruption if they document their work, are thoughtful and conscientious in their deliberations, and carry out protocols and procedures developed prior to volcanic unrest. This paper also contains six case studies of volcanic eruptions or observatory actions that illustrate some of the topics discussed herein. Specifically, we discuss Ambae (Vanuatu) in 2017–2018, Kīlauea (USA) in 2018, Etna (Italy) in 2018, Bárðarbunga (Iceland) in 2014, Cotopaxi (Ecuador) in 2015, and global data sharing to prepare for eruptions at Nyiragongo (Democratic Republic of Congo).","language":"English","publisher":"BioMed Central","doi":"10.1186/s13617-021-00112-9","usgsCitation":"Lowenstern, J.B., Wallace, K.L., Barsotti, S., Sandri, L., Stovall, W., Bernard, B., Privitera, E., Komorowski, J., Fournier, N., Baligizi, C., and Gareabiti, E., 2022, Guidelines for volcano-observatory operations during crises: Recommendations from the 2019 Volcano Observatory Best Practices meeting: Journal of Applied Volcanology, v. 11, p. 1-24, https://doi.org/10.1186/s13617-021-00112-9.","productDescription":"3, 24 p.","startPage":"1","endPage":"24","ipdsId":"IP-123190","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":449031,"rank":0,"type":{"id":40,"text":"Open Access Publisher 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waves of emerging vegetation coinciding with rising daily mean temperatures initiating snowmelt across the landscape. Snowmelt also causes rivers and streams draining these regions to swell, a process referred to as to as the ‘spring pulse.’ Networks of streamgages measuring streamflow in these regions often have long-term and continuous periods of record available in real-time and at the daily time step, and thus produce data with potential to predict temporal migration patterns for species exploiting green waves. We tested the potential of models informed by streamflow data to predict timing of spring migration of mule deer (Odocoileus hemionus) herds in a headwater basin of the Colorado River. Models using streamflow data were compared with those informed by traditional temperature-derived measures of the onset of spring. Non-parametric linear-regression techniques were used to test for temporal stationarity in each variable, and logistic-regression models were used to produce probabilities of migration initiation. Our analysis indicates that models using daily streamflow data can perform as well as those using temperature-derived data to predict past-migration patterns, and nearly as well in potential to forecast future migrations. The best performing model was used to generate probabilities of onset of migration for mule deer herds over the 69-year period-of-record from a streamgage. That model indicated spring migration has been trending toward earlier initiations, with modeled median initiations shifting from a Julian day of 123 in the mid 20th century to Julian day 115 over the most recent two decades. The period of 1960 to 1979 had the latest modeled median initiations with Julian day of 128. The analyses demonstrate promise for merging existing hydrologic and biological data collection platforms in these regions to explore timing of past migration patterns and predict migration onsets in real-time.
","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0262078","usgsCitation":"Alexander, J.S., Murr, M.L., and Eddy-Miller, C.A., 2022, Testing the potential of streamflow data to predict spring migration of an ungulate herds: PLoS ONE, v. 17, no. 1, p. 1-18, https://doi.org/10.1371/journal.pone.0262078.","productDescription":"e0262078, 18 p.","startPage":"1","endPage":"18","ipdsId":"IP-125176","costCenters":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":449034,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0262078","text":"Publisher Index Page"},{"id":394871,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Wyoming","otherGeospatial":"Little Snake River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.45703125,\n 40.45321727150385\n ],\n [\n -108.00933837890625,\n 40.70562793820589\n ],\n [\n -107.46826171874999,\n 40.84913799774759\n ],\n [\n -107.0892333984375,\n 40.86991083161536\n ],\n [\n -107.05078125,\n 41.00477542222947\n ],\n [\n -107.490234375,\n 41.539421883822854\n ],\n [\n -108.446044921875,\n 41.54764462357737\n ],\n [\n -108.8031005859375,\n 41.20552261955812\n ],\n [\n -108.45703125,\n 40.45321727150385\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"17","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-01-21","publicationStatus":"PW","contributors":{"editors":[{"text":"Grignolio, Stefano","contributorId":272227,"corporation":false,"usgs":false,"family":"Grignolio","given":"Stefano","email":"","affiliations":[{"id":35987,"text":"Department of Life Sciences and Biotechnology, University of Ferrara, Ferrara, Italy","active":true,"usgs":false}],"preferred":false,"id":831783,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Alexander, Jason S. 0000-0002-1602-482X jalexand@usgs.gov","orcid":"https://orcid.org/0000-0002-1602-482X","contributorId":261330,"corporation":false,"usgs":true,"family":"Alexander","given":"Jason","email":"jalexand@usgs.gov","middleInitial":"S.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":831739,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Murr, Marissa L.","contributorId":252938,"corporation":false,"usgs":false,"family":"Murr","given":"Marissa","email":"","middleInitial":"L.","affiliations":[{"id":50476,"text":"Department of Geology and Geophysics, University of Wyoming, Laramie, Wyoming","active":true,"usgs":false}],"preferred":false,"id":831740,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eddy-Miller, Cheryl A. 0000-0002-4082-750X","orcid":"https://orcid.org/0000-0002-4082-750X","contributorId":195780,"corporation":false,"usgs":true,"family":"Eddy-Miller","given":"Cheryl","email":"","middleInitial":"A.","affiliations":[{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"preferred":false,"id":831741,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70227686,"text":"70227686 - 2022 - Oxygen isotopes of land snail shells in high latitude regions","interactions":[],"lastModifiedDate":"2022-01-26T15:51:22.676505","indexId":"70227686","displayToPublicDate":"2022-01-26T09:41:08","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3219,"text":"Quaternary Science Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Oxygen isotopes of land snail shells in high latitude regions","docAbstract":"The present study investigates the environmental significance of the oxygen isotopic composition of several modern land snail species collected along two north-to-south transects in Alaska and Scandinavia at latitudes between 60 and 70 °N. We tested the hypothesis that land snail shell δ18O values primarily track precipitation δ18O. The results show that shell δ18O values from Scandinavia were ∼5.1‰ enriched in 18O with respect to snails from Alaska, equivalent to differences in precipitation δ18O values between the two regions. Within the Alaskan transect, shell δ18O values increased with observed increasing air temperature and precipitation δ18O, whereas shell δ18O values from Scandinavia did not correlate to instrumental climate data because of a reduced climatic gradient across the locations sampled. In addition, shell δ18O values differed significantly among sympatric species, with larger species consistently exhibiting higher δ18O values, which implies that species-level isotopic variations should be considered at the local and microhabitat scale. However, when snail shell δ18O values from this study are combined with previously published data from North America and Europe, we see evidence that shell δ18O values track precipitation δ18O across latitudes, even when different species are combined because climate gradients are greater than variations among taxa.
This article investigates methods to improve earthquake early warning (EEW) predictions of shaking levels for residents of tall buildings. In the current U.S. Geological Survey ShakeAlert EEW system, regions far from an epicenter will not receive alerts due to low predicted ground‐shaking intensities. However, residents of tall buildings in those areas may still experience significant shaking due to the acceleration amplification caused by tall buildings’ dynamic behavior, as recently experienced by residents of the 52‐story building in downtown Los Angeles (DTLA) during the 2019 M 7.1 Ridgecrest earthquake. Using more than 400 recorded response data acquired from 77 instrumented buildings in California, here we compare the Federal Emergency Management Agency (FEMA) P‐58 and American Society of Civil Engineers (ASCE) 7‐16 simplified equations for peak floor acceleration (PFA), finding that the ASCE estimation is close to the median of data recorded in large and long‐distance events, whereas the current FEMA estimation is not suitable. In the second part of this article, four instrumented tall buildings in DTLA are extensively studied, and the performance of the simplified and response spectrum (RS) methods giving both an estimation of the free‐field horizontal peak ground acceleration (PGA) and pseudospectral acceleration is evaluated. The results show that the RS method is as accurate as the response history analysis as long as the ground‐motion RS is accurate, whereas the ASCE 7‐16 prediction is conservative. However, when ground‐motion RS or PGA is estimated for DTLA using a ground‐motion model (GMM), the performance of the RS method significantly degrades due to underestimation by the GMM at long periods. The results of this study imply that a nonergodic GMM, which may give more accurate prediction in Los Angeles, could improve the results for PFA when the building’s behavior is dominated by a few long‐period fundamental modes, as is the case for the 52‐story building in DTLA.
In the United States, the Bald and Golden Eagle Protection Act prohibits take of golden eagles (Aquila chrysaetos) unless authorized by permit, and stipulates that all permitted take must be sustainable. Golden eagles are unintentionally killed in conjunction with many lawful activities (e.g., electrocution on power poles, collision with wind turbines). Managers who issue permits for incidental take of golden eagles must determine allowable take levels and manage permitted take accordingly. To aid managers in making these decisions in the western United States, we used an integrated population model to obtain estimates of golden eagle vital rates and population size, and then used those estimates in a prescribed take level (PTL) model to estimate the allowable take level. Estimated mean annual survival rates for golden eagles ranged from 0.70 (95% credible interval = 0.66–0.74) for first-year birds to 0.90 (0.88–0.91) for adults. Models suggested a high proportion of adult female golden eagles attempted to breed and breeding pairs fledged a mean of 0.53 (0.39–0.72) young annually. Population size in the coterminous western United States has averaged ~31,800 individuals for several decades, with λ = 1.0 (0.96–1.05). The PTL model estimated a median allowable take limit of ~2227 (708–4182) individuals annually given a management objective of maintaining a stable population. We estimate that take averaged 2572 out of 4373 (59%) deaths annually, based on a representative sample of transmitter-tagged golden eagles. For the subset of golden eagles that were recovered and a cause of death determined, anthropogenic mortality accounted for an average of 74% of deaths after their first year; leading forms of take over all age classes were shooting (~670 per year), collisions (~611), electrocutions (~506), and poisoning (~427). Although observed take overlapped the credible interval of our allowable take estimate and the population overall has been stable, our findings indicate that additional take, unless mitigated for, may not be sustainable. Our analysis demonstrates the utility of the joint application of integrated population and prescribed take level models to management of incidental take of a protected species.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.2544","usgsCitation":"Milsap, B., Zimmerman, G.S., Kendall, W.L., Barnes, J., Braham, M., Bedrosian, B.E., Bell, D.A., Bloom, P.H., Crandall, R.H., Domenech, R., Driscoll, D., Duerr, A.E., Gerhardt, R., Gibbs, S.E., Harmata, A.R., Jacobson, K., Katzner, T., Knight, R., Lockhart, J.M., McIntyre, C., Murphy, R.K., Slater, S.J., Smith, B.W., Smith, J., Stahlecker, D.W., and Watson, J.W., 2022, Age-specific survival rates, causes of death, and allowable take of golden eagles in the western United States: Ecological Applications, v. 32, no. 3, e2544, 22 p., https://doi.org/10.1002/eap.2544.","productDescription":"e2544, 22 p.","ipdsId":"IP-125525","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"links":[{"id":449040,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index 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Bioremediation of RDX is feasible through biostimulation of native microbes with an organic carbon donor but may be less efficient, or not occur at all, in the presence of the common co-contaminants perchlorate and nitrate. Laboratory tests compared biostimulation with bioaugmentation to achieve anaerobic degradation of RDX, perchlorate, and nitrate; a field pilot test was then conducted in a fractured rock aquifer with the selected bioaugmentation approach. Insignificant reduction of RDX, perchlorate, or nitrate was observed by the native microbes in microcosms, with or without biostimulation by addition of lactate. Tests of the RDX-degrading ability of the microbial consortium WBC-2, originally developed for dehalogenation of chlorinated volatile organic compounds, showed first-order biodegradation rate constants ranging from 0.57 to 0.90 per day (half-lives 1.2 to 0.80 days). WBC-2 sustained degradation without daughter product accumulation when repeatedly amended with RDX and lactate for a year. In microcosms with groundwater containing perchlorate and nitrate, RDX degradation began without delay when bioaugmented with 10% WBC-2. Slower RDX degradation occurred with 3% or 5% WBC-2 amendment, indicating a direct relation with cell density. Transient RDX daughter compounds included methylene dinitramine, MNX, and DNX. With WBC-2 amendment, nitrate concentrations immediately decreased to near or below detection, and perchlorate degradation occurred with half-lives of 25 to 34 days. Single-well injection tests with WBC-2 and lactate showed that the onset of RDX degradation coincided with the onset of sulfide production, which was affected by the initial perchlorate concentration. Bioegradation rates in the pilot injection tests agreed well with those measured in the microcosms. These results support bioaugmentation with an anaerobic culture as a remedial strategy for sites contaminated with RDX, nitrate, and perchlorate.","language":"English","publisher":"Elsevier","doi":"10.1016/j.chemosphere.2022.133674","usgsCitation":"Lorah, M.M., Vogler, E., Gebhardt, F.E., Graves, D., and Grabowski, J., 2022, Enhanced bioremediation of RDX and co-contaminants perchlorate and nitrate using an anaerobic dehalogenating consortium in a fractured rock aquifer: Chemosphere, v. 294, p. 1-12, https://doi.org/10.1016/j.chemosphere.2022.133674.","productDescription":"133674, 12 p.","startPage":"1","endPage":"12","ipdsId":"IP-133155","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true},{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":449043,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1016/j.chemosphere.2022.133674","text":"External Repository"},{"id":394864,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Hazardous Test Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.60926818847656,\n 33.55970664841198\n ],\n [\n -106.34422302246094,\n 33.55970664841198\n ],\n [\n -106.34422302246094,\n 33.63234403356961\n ],\n [\n -106.60926818847656,\n 33.63234403356961\n ],\n [\n -106.60926818847656,\n 33.55970664841198\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"294","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"editors":[{"text":"Yoon, Y. Yeomin","contributorId":272225,"corporation":false,"usgs":false,"family":"Yoon","given":"Y.","email":"","middleInitial":"Yeomin","affiliations":[],"preferred":false,"id":831779,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Lorah, Michelle M. 0000-0002-9236-587X","orcid":"https://orcid.org/0000-0002-9236-587X","contributorId":224040,"corporation":false,"usgs":true,"family":"Lorah","given":"Michelle","middleInitial":"M.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":831767,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vogler, Eric","contributorId":272221,"corporation":false,"usgs":false,"family":"Vogler","given":"Eric","email":"","affiliations":[{"id":56372,"text":"Stantec","active":true,"usgs":false}],"preferred":false,"id":831768,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gebhardt, Fredrick E.","contributorId":272222,"corporation":false,"usgs":true,"family":"Gebhardt","given":"Fredrick","email":"","middleInitial":"E.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":831769,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Graves, Duane","contributorId":172428,"corporation":false,"usgs":false,"family":"Graves","given":"Duane","email":"","affiliations":[{"id":27037,"text":"Geosyntec Consultants, Inc., Knoxville, TN","active":true,"usgs":false}],"preferred":false,"id":831770,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Grabowski, Jennifer","contributorId":272223,"corporation":false,"usgs":false,"family":"Grabowski","given":"Jennifer","email":"","affiliations":[{"id":56373,"text":"U.S. Pharmacopeia","active":true,"usgs":false}],"preferred":false,"id":831771,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70230378,"text":"70230378 - 2022 - A landscape approach for identifying potential reestablishment sites for extirpated stream fishes: an example with Arctic grayling (Thymallus arcticus) in Michigan","interactions":[],"lastModifiedDate":"2022-04-11T13:30:07.813676","indexId":"70230378","displayToPublicDate":"2022-01-26T08:26:13","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1919,"text":"Hydrobiologia","onlineIssn":"1573-5117","printIssn":"0018-8158","active":true,"publicationSubtype":{"id":10}},"displayTitle":"A landscape approach for identifying potential reestablishment sites for extirpated stream fishes: an example with Arctic grayling (Thymallus arcticus) in Michigan","title":"A landscape approach for identifying potential reestablishment sites for extirpated stream fishes: an example with Arctic grayling (Thymallus arcticus) in Michigan","docAbstract":"Habitat degradation combined with climate change increases the threat of extinction for stream fishes. In response to these threats, efforts to reestablish species within formerly occupied streams or translocation to suitable areas may be effective conservation strategies. In the absence of historic species presence data, identifying locations where suitable habitat exists across many fluvial habitats may limit the effectiveness of reestablishments. We present an approach that ranks habitat for stream fish reestablishment over large areas using best available information. Using the locally extirpated Arctic grayling (Thymallus arcticus) in Michigan, USA as an example, we integrate information on species preferences and relationships between species with similar habitat requirements and landscape predictors of habitat to rank stream suitability. We find that unfragmented streams throughout the historical range of Arctic grayling and areas previously unoccupied by the species are potential locations for conservation action. However, we note that projected increases in summer water temperatures may reduce the amount of thermally suitable habitat in some top-ranked locations by up to 30%. Given its inherent flexibility in data requirements, our landscape-level approach may be a valuable tool that supports planning for species reestablishment.
","language":"English","publisher":"Springer","doi":"10.1007/s10750-021-04791-8","usgsCitation":"Tingley, R.W., Infante, D.M., Dean, E., Schemske, D.W., Cooper, A.R., Ross, J., and Daniel, W., 2022, A landscape approach for identifying potential reestablishment sites for extirpated stream fishes: an example with Arctic grayling (Thymallus arcticus) in Michigan: Hydrobiologia, v. 849, p. 1397-1415, https://doi.org/10.1007/s10750-021-04791-8.","productDescription":"19 p.","startPage":"1397","endPage":"1415","ipdsId":"IP-125422","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":398463,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"849","noUsgsAuthors":false,"publicationDate":"2022-01-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Tingley, Ralph William 0000-0002-1689-2133","orcid":"https://orcid.org/0000-0002-1689-2133","contributorId":258043,"corporation":false,"usgs":true,"family":"Tingley","given":"Ralph","email":"","middleInitial":"William","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":840119,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Infante, Dana M.","contributorId":146114,"corporation":false,"usgs":false,"family":"Infante","given":"Dana","email":"","middleInitial":"M.","affiliations":[{"id":16583,"text":"Department of Fisheries and Wildlife, 480 Wilson Rd. 13 Natural Resources Building, Michigan State University, East Lansing, MI 48824","active":true,"usgs":false}],"preferred":false,"id":840120,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dean, Emily M.","contributorId":289990,"corporation":false,"usgs":false,"family":"Dean","given":"Emily M.","affiliations":[{"id":6590,"text":"Department of Fisheries and Wildlife, Michigan State University","active":true,"usgs":false}],"preferred":false,"id":840121,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schemske, Douglas W.","contributorId":171953,"corporation":false,"usgs":false,"family":"Schemske","given":"Douglas","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":840122,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cooper, Arthur R. 0000-0002-0557-8560","orcid":"https://orcid.org/0000-0002-0557-8560","contributorId":220307,"corporation":false,"usgs":false,"family":"Cooper","given":"Arthur","email":"","middleInitial":"R.","affiliations":[{"id":7266,"text":"Michigan State University, Department of Fisheries and Wildlife","active":true,"usgs":false}],"preferred":false,"id":840123,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ross, Jared 0000-0002-0582-3589","orcid":"https://orcid.org/0000-0002-0582-3589","contributorId":289993,"corporation":false,"usgs":false,"family":"Ross","given":"Jared","email":"","affiliations":[{"id":6590,"text":"Department of Fisheries and Wildlife, Michigan State University","active":true,"usgs":false}],"preferred":false,"id":840124,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Daniel, Wesley M. 0000-0002-7656-8474","orcid":"https://orcid.org/0000-0002-7656-8474","contributorId":219320,"corporation":false,"usgs":true,"family":"Daniel","given":"Wesley M.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":840125,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70227651,"text":"sir20215118 - 2022 - Hydrology of the Yucaipa groundwater subbasin: Characterization and integrated numerical model, San Bernardino and Riverside Counties, California","interactions":[{"subject":{"id":70228448,"text":"sir20215118A - 2022 - Hydrogeologic characterization of the Yucaipa groundwater subbasin","indexId":"sir20215118A","publicationYear":"2022","noYear":false,"chapter":"A","displayTitle":"Hydrogeologic Characterization of the Yucaipa Groundwater Subbasin","title":"Hydrogeologic characterization of the Yucaipa groundwater subbasin"},"predicate":"IS_PART_OF","object":{"id":70227651,"text":"sir20215118 - 2022 - Hydrology of the Yucaipa groundwater subbasin: Characterization and integrated numerical model, San Bernardino and Riverside Counties, California","indexId":"sir20215118","publicationYear":"2022","noYear":false,"title":"Hydrology of the Yucaipa groundwater subbasin: Characterization and integrated numerical model, San Bernardino and Riverside Counties, California"},"id":1},{"subject":{"id":70228449,"text":"sir20215118B - 2022 - Yucaipa 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Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-5118","displayTitle":"Hydrology of the Yucaipa Groundwater Subbasin: Characterization and Integrated Numerical Model, San Bernardino and Riverside Counties, California","title":"Hydrology of the Yucaipa groundwater subbasin: Characterization and integrated numerical model, San Bernardino and Riverside Counties, California","docAbstract":"Water management in the Santa Ana River watershed in San Bernardino and Riverside Counties in southern California is a complex task with various water purveyors navigating geographic, geologic, hydrologic, and political challenges to provide a reliable water supply to stakeholders. As the population has increased throughout southern California, so has the demand for water. The Yucaipa groundwater subbasin (hereafter referred to as “Yucaipa subbasin”), one of nine groundwater subbasins in what the California Department of Water Resources (DWR) refers to as the Upper Santa Ana Valley groundwater basin (California Department of Water Resources, 2016; the DWR naming convention is used within this report), is no exception; steady population growth since the 1940s and changes in water use has forced local water purveyors to regularly adapt their water infrastructure to meet demand. Groundwater has historically been the dominant source of water in the Yucaipa subbasin although recently, imported water via the California State Water Project has augmented the total water supply. Despite the influx of imported water, overall demand for groundwater continues to rise, and there is concern by local water managers that groundwater levels may adversely impact water supply and (or) decline to a point where it will be uneconomical to produce water, severely limiting the ability of local agencies to meet water-supply demand.
To better understand the hydrogeology and water resources in the Yucaipa subbasin, the U.S. Geological Survey (USGS) and the San Bernardino Valley Municipal Water District initiated a cooperative study to understand the hydrogeologic system of the Yucaipa subbasin and in the encompassing Yucaipa Valley watershed (YVW). A three-dimensional hydrogeologic framework model was constructed to quantify the structure and extent of hydrogeologic units. Historical and present-day groundwater conditions were characterized to evaluate the groundwater-flow system. Lastly, the Yucaipa Integrated Hydrological Model (YIHM) was developed to simulate the integrated surface-water and groundwater systems, including natural and anthropogenic (that is, human influenced) recharge and discharge throughout the study area from 1947 to 2014.
The Yucaipa subbasin is an inland groundwater basin located about 12 miles (mi) southeast of the City of San Bernardino and about 75 mi east of Los Angeles, California. The subbasin encompasses about 39 square miles (mi2), including the City of Yucaipa. The geographic extent of the Yucaipa subbasin was established by the California Department of Water Resources, who defined the boundaries of the subbasin based on hydrogeologic transitions between crystalline rock and basin-fill sediments, active fault strands, surface-water drainage divides, and a portion of an adjudicated groundwater management boundary. Two groundwater subbasins of the Upper Santa Ana Valley groundwater basin are adjacent to the Yucaipa subbasin, the San Bernardino groundwater subbasin to the west and the San Timoteo groundwater subbasin to the south.
The Yucaipa subbasin is encompassed by the YVW, which is in turn comprised of three sub-watersheds that represent surface-water flow across and within the Yucaipa subbasin. Although the Yucaipa subbasin is the specific area of interest for this study, the entire YVW was considered for the purposes of characterizing the hydrogeology of the Yucaipa subbasin and for development of the YIHM.
The purposes of this report are to (1) describe the hydrologic and hydrogeologic settings of the Yucaipa subbasin and aquifer system, (2) describe the construction and calibration of the fully coupled groundwater and surface-water flow model for the Yucaipa subbasin and the encompassing YVW, referred to as the YIHM, and (3) present numerical results, including water budgets and hydraulic heads, and the effect of pumping and climate stresses (precipitation and temperature) on water-budget components.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215118","collaboration":"Prepared in cooperation with San Bernardino Valley Municipal Water District","usgsCitation":"Cromwell, G., and Alzraiee, A., eds., 2022, Hydrology of the Yucaipa groundwater subbasin: Characterization and integrated numerical model, San Bernardino and Riverside Counties, California: U.S. Geological Survey Scientific Investigations Report 2021–5118, 4 p., https://doi.org/10.3133/sir20215118.","productDescription":"Executive Summary: vi, 4 p.; Chapter A: viii, 81 p.; Chapter B: xii, 76 p.; 2 Data Releases","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-123424","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":394827,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5118/images"},{"id":394823,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9F7OYQR","text":"Data release of hydrogeologic data of the Yucaipa groundwater subbasin, San Bernardino and Riverside Counties, California"},{"id":394776,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5118/covrthb.jpg"},{"id":394777,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5118/sir20215118.pdf","text":"Executive Summary","size":"10 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":502121,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112154.htm","linkFileType":{"id":5,"text":"html"}},{"id":394835,"rank":8,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5118/sir20215118b.xml"},{"id":394834,"rank":7,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5118/sir20215118a.xml"},{"id":394826,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5118/sir20215118.xml"},{"id":394825,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9K540DV","text":"GSFLOW model to evaluate the effect of groundwater pumpage and climate stresses on the integrated hydrologic system of the Yucaipa subbasin, Yucaipa Valley watershed, San Bernardino and Riverside Counties, California"}],"country":"United States","state":"California","county":"Riverside County, San Bernardino County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.257080078125,\n 33.899486813913285\n ],\n [\n -116.87736511230469,\n 33.899486813913285\n ],\n [\n -116.87736511230469,\n 34.098159345215535\n ],\n [\n -117.257080078125,\n 34.098159345215535\n ],\n [\n -117.257080078125,\n 33.899486813913285\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
Global Navigation Satellite Systems (GNSSs) have undergone notable advancement in the last few decades, leading to the availability of a dataset with capabilities well beyond its original intended purpose. The proliferation of high‐rate (1 Hz or greater) GNSS receivers in areas of seismological interest now allows for routine consideration of dynamic earthquake ground motions, with centimeter‐level displacement accuracy via precise point positioning methods. Real‐time (RT) GNSS observations, from stations that are both telemetered and processed to displacement with minimal latency, have lower accuracy compared to post‐processed (PP) GNSS displacements due to imprecise knowledge of atmospheric conditions, satellite clocks, and satellite orbits in RT. Whether the quality of RT high‐rate GNSS is sufficient for use in rapid response products remains to be thoroughly examined. Here, we highlight RT GNSS displacement time series processed during the 2019
We present a kinematic slip model of the July 8, 2021 Antelope Valley earthquake from a finite-source inversion based on regional seismic waveforms and static offsets from GPS and InSAR. Seismic waveforms are employed at 6s dominant period out to 100 km from the epicenter, and the combined GPS and InSAR datasets cover the near field and far field out to ∼ 100 km and constrain the overall rupture size. The aftershock pattern defines a nearly north-striking, 50◦ east-dipping fault plane. We find a unilateral rupture along this fault plane propagating southward and updip with predominantly normal slip up to ∼ 1.5m. The estimated seismic moment of 8.47 × 10 22 17 Nm is equivalent to Mw 5.92. A finite-source inversion that retains seismic waveforms and GPS static offsets but omits InSAR range changes yields a seismic moment of 1.08 × 10 25 18 Nm (Mw 5.99). Despite vigorous aftershock activity between 10 km and Earth’s surface, coseismic slip is concentrated in the depth interval 7 - 10 km.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0320210043","usgsCitation":"Pollitz, F., Wicks, C., and Hammond, W.M., 2022, Kinematic slip model of the July 8, 2021 M6.0 Antelope Valley, California, earthquake: The Seismic Record, v. 2, no. 1, p. 20-28, https://doi.org/10.1785/0320210043.","productDescription":"9 p.","startPage":"20","endPage":"28","ipdsId":"IP-133557","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":449047,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1785/0320210043","text":"Publisher Index Page"},{"id":421846,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Antelope Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -120.00,\n 39.00\n ],\n [\n -120.00,\n 38.00\n ],\n [\n -119.00,\n 38.00\n ],\n [\n -119.00,\n 39.00\n ],\n [\n -120.00,\n 39.00\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"2","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-01-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Pollitz, Frederick 0000-0002-4060-2706 fpollitz@usgs.gov","orcid":"https://orcid.org/0000-0002-4060-2706","contributorId":139578,"corporation":false,"usgs":true,"family":"Pollitz","given":"Frederick","email":"fpollitz@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":885944,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wicks, Charles 0000-0002-0809-1328","orcid":"https://orcid.org/0000-0002-0809-1328","contributorId":9023,"corporation":false,"usgs":true,"family":"Wicks","given":"Charles","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":885945,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hammond, William M","contributorId":292777,"corporation":false,"usgs":false,"family":"Hammond","given":"William","email":"","middleInitial":"M","affiliations":[{"id":36221,"text":"University of Florida","active":true,"usgs":false}],"preferred":false,"id":885946,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70262545,"text":"70262545 - 2022 - Redundancy analysis reveals complex den use patterns by eastern spotted skunks, a conditional specialist","interactions":[],"lastModifiedDate":"2025-01-22T18:32:02.773642","indexId":"70262545","displayToPublicDate":"2022-01-26T00:00:00","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Redundancy analysis reveals complex den use patterns by eastern spotted skunks, a conditional specialist","docAbstract":"Wildlife managers tasked with understanding habitat and resource selection at the population level attempt to characterize patterns in nature that aid and inform conservation. Resource selection functions (RSFs), such as discrete choice analyses, are the standard convention to characterize the effects of habitat attributes on resource selection patterns. These tools are invaluable for wildlife management and conservation and have proven successful in numerous studies. However, the analysis of small datasets using RSF becomes problematic when attempting to account for complex sources of variation, and the inclusion of factors such as weather or intrinsic variation on target species' response may produce models with poor predictive ability. We compared the application of generalized linear mixed-effects modeling (GLMM) and redundancy analysis (RDA) on Appalachian spotted skunk (Spilogale putorius putorius) den selection data at four study sites within the George Washington, Jefferson, and Monongahela National Forests, and surrounding private lands in the Appalachian Mountains of western Virginia and northeastern West Virginia. We assessed the need for the inclusion of alternative sources of variation (i.e., weather conditions and individual intrinsic variation) in addition to standard habitat attributes to better identify sources of variation in den selection. The RDA elucidated complex and opposing relationships, whereby den type use was based on reproductive status or weather condition, which were not evident in the GLMM model that relied solely on habitat measures. Our results demonstrated the importance of examining resource selection data using multivariate techniques in addition to conventional discrete choice analyses to better understand intricate habitat–species relationships, especially for small datasets. Furthermore, from our analyses, we proposed that spotted skunks are neither a true generalist nor specialist species. We introduced and define the term “conditional specialist” to represent a species that is conditionally selective of a given resource in response to one or more current environmental or intrinsic conditions.
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Mark","email":"wford@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":924521,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70227465,"text":"sir20215135 - 2022 - Groundwater hydrology in the area of Savannah and Gunstocker Creeks in northeastern Hamilton, southern Meigs, and northwestern Bradley Counties, Tennessee, 2007–09","interactions":[],"lastModifiedDate":"2026-04-08T16:26:04.962799","indexId":"sir20215135","displayToPublicDate":"2022-01-25T13:59:52","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":"2021-5135","displayTitle":"Groundwater Hydrology in the Area of Savannah and Gunstocker Creeks in Northeastern Hamilton, Southern Meigs, and Northwestern Bradley Counties, Tennessee, 2007–09","title":"Groundwater hydrology in the area of Savannah and Gunstocker Creeks in northeastern Hamilton, southern Meigs, and northwestern Bradley Counties, Tennessee, 2007–09","docAbstract":"The U.S. Geological Survey, in cooperation with the Savannah Valley Utility District, evaluated the groundwater hydrology of the Valley and Ridge carbonate rock aquifer in northeastern Hamilton, southern Meigs, and northwestern Bradley Counties, Tennessee, from 2007 through 2009. The evaluation included, and built on, the results of test drilling conducted in the area in 1974 to determine the potential for groundwater as a source of public supply for the utility and the results of an investigation conducted to define recharge areas for wells used by groundwater-source public-supply water systems throughout Hamilton County in the early 1990s.
Groundwater-level data collected from wells open to the aquifer in the study area were used to prepare potentiometric-surface maps for fall 1992, spring and fall 1993, summer 2008, and spring 2009 conditions. Two primary groundwater basins were delineated from the maps—the larger of which coincides with the watershed of Savannah Creek in the southern part of the study area and the smaller of which coincides with the watershed of Gunstocker Creek in the northern part of the study area. Both basins are characterized by potentiometric surfaces that contain a central area of low-altitude groundwater levels and low gradients relative to the basin margins that reflect the orientation of enhanced permeability along dissolution-enlarged features that have developed parallel to strike in the aquifer. The recharge area of the Savannah Creek groundwater basin is estimated to be about 31 square miles, and the recharge area of the Gunstocker Creek groundwater basin is estimated to be about 17 square miles.
Recharge to the aquifer in the Savannah Creek and Gunstocker Creek groundwater basins primarily occurs in the uplands area along White Oak Mountain in the eastern part of the study area and along the western boundaries of the basins. Groundwater flows toward the potentiometric lows in each basin, discharging as base flow to the streams and to springs locally. Groundwater withdrawals for public supply by the utility influence the potentiometric low in the north-central part of the Savannah Creek groundwater basin and disrupt flow in the creek and nearby Anderson Spring, particularly during the summer and fall seasons. No large groundwater withdrawals currently occur in the Gunstocker Creek basin, but there is potential for groundwater supply development in the basin.
A conceptual model of the groundwater hydrology of the area developed from the evaluation indicates that Chickamauga Lake is the base-level control on groundwater discharge from the Savannah Creek and Gunstocker Creek basins and that lake stage affects the potentiometric surfaces and groundwater discharge in the most downgradient parts of the basins as a result of inferred hydraulic connection between the aquifer and the lake. The model also infers that captured surface water from sections of Savannah Creek and the Hiwassee River that are embayed by the lake could recharge the aquifer and serve as a source of water withdrawn by wells in each basin if the potentiometric surfaces were lowered to altitudes less than the stage of the lake, particularly under potential future groundwater-development scenarios in the Gunstocker Creek basin.
Geochemical analysis of samples collected from six wells for the study indicate that groundwater in the Valley and Ridge aquifer in the area generally is a calcium-magnesium-bicarbonate type, and although the water generally is hard, it is suitable for most uses. Trace-element concentrations were less than primary drinking-water criteria in all the samples.
Results of the investigation indicate that options are available for additional groundwater withdrawal in the study area. Water-level data collected since 1975 at the Savannah Valley Utility District Smith Road well site indicate that some additional amount of groundwater is available for withdrawal from the aquifer in the Savannah Creek groundwater basin. The potentiometric low within the Gunstocker Creek groundwater basin indicates that an area with enhanced permeability is present as a northeastern counterpart to the potentiometric low within the Savannah Creek basin. Because the Gunstocker Creek basin is about one-half the total area of the Savannah Creek basin, a commensurate decrease in available groundwater storage is likely. Furthermore, groundwater withdrawal locations in the Gunstocker Creek basin would be closer to—and possibly connected hydraulically to—the Hiwassee River, thus increasing the potential for induced surface-water recharge in the basin if sustained drawdown from pumping lowered groundwater levels to altitudes less than the stage of the river.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215135","isbn":"978-1-4113-4435-8","collaboration":"Prepared in cooperation with the Savannah Valley Utility District","programNote":"Water Availability and Use Science Program","usgsCitation":"Carmichael, J.K., 2022, Groundwater hydrology in the area of Savannah and Gunstocker Creeks in northeastern Hamilton, southern Meigs, and northwestern Bradley Counties, Tennessee, 2007–09: U.S. Geological Survey Scientific Investigations Report 2021–5135, 31 p., 5 pls., https://doi.org/10.3133/sir20215135.","productDescription":"Report: vii, 31 p.; Data Release; 5 Plates: 20.00 x 30.00 inches or smaller","numberOfPages":"44","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-104265","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science 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2009"},{"id":394457,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2021/5135/sir20215135_plates.pdf","text":"Plates 1–5","size":"2.29 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2021–5135 Plates"}],"country":"United States","state":"Tennessee","county":"Bradley County, Meigs 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Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
640 Grassmere Park, Suite 100
Nashville, TN 37211
Fluvial systems provide a variety of habitats that support thousands of species including many that are threatened or endangered. Moreover, these habitats, which range from aquatic and riparian to floodplain, are important for the variety of ecosystem services they provide. In addition to water temperature and streamflow change, geomorphic change is important and warrants consideration as one of the several potential threats to these habitats posed by climate change. The geomorphic response of fluvial systems to global warming in temperate environments, for example, caused by an increase in the frequency and magnitude of floods, is important because geomorphology is a primary determinant of habitat availability and quality. Possible geomorphic responses include increased erosion and (or) deposition in the river channel, riparian zone, and floodplain with associated habitat implications. Geomorphic changes caused by global warming can be beneficial (e.g., increased habitat complexity) or detrimental (e.g., mortality caused by scour or burial) to biota. The ability of a species to respond to and survive disturbances, including geomorphic changes, will depend on the nature of the disturbances and the sensitivity and adaptive capabilities of the species. Post-flood recovery often is rapid; however, for certain species (e.g., periphyton, macroinvertebrates), changes in community composition may persist. Increased flood frequency, sediment mobility, and associated geomorphic changes potentially will result in more frequent and persistent changes in habitat and community composition in the affected fluvial systems.
","language":"English","publisher":"Wiley","doi":"10.1002/rra.3938","usgsCitation":"Juracek, K.E., and Fitzpatrick, F., 2022, Geomorphic responses of fluvial systems to climate change: A habitat perspective: River Research and Applications, v. 38, no. 4, p. 757-775, https://doi.org/10.1002/rra.3938.","productDescription":"19 p.","startPage":"757","endPage":"775","ipdsId":"IP-127640","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":396338,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"38","issue":"4","noUsgsAuthors":false,"publicationDate":"2022-01-25","publicationStatus":"PW","contributors":{"authors":[{"text":"Juracek, Kyle E. 0000-0002-2102-8980 kjuracek@usgs.gov","orcid":"https://orcid.org/0000-0002-2102-8980","contributorId":2022,"corporation":false,"usgs":true,"family":"Juracek","given":"Kyle","email":"kjuracek@usgs.gov","middleInitial":"E.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":835745,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fitzpatrick, Faith A. 0000-0002-9748-7075","orcid":"https://orcid.org/0000-0002-9748-7075","contributorId":209612,"corporation":false,"usgs":true,"family":"Fitzpatrick","given":"Faith A.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":835746,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70227634,"text":"dr1146 - 2022 - Alaska Volcano Observatory archive of seismic drum records of eruptions of Augustine Volcano (1986), Redoubt Volcano (1989–90), Mount Spurr (1992), and Pavlof Volcano (1996), and the 1996 earthquake swarm at Akutan Peak","interactions":[],"lastModifiedDate":"2026-03-16T19:57:25.979118","indexId":"dr1146","displayToPublicDate":"2022-01-24T12:58:39","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":"1146","displayTitle":"Alaska Volcano Observatory Archive of Seismic Drum Records of Eruptions of Augustine Volcano (1986), Redoubt Volcano (1989–90), Mount Spurr (1992), and Pavlof Volcano (1996), and the 1996 Earthquake Swarm at Akutan Peak","title":"Alaska Volcano Observatory archive of seismic drum records of eruptions of Augustine Volcano (1986), Redoubt Volcano (1989–90), Mount Spurr (1992), and Pavlof Volcano (1996), and the 1996 earthquake swarm at Akutan Peak","docAbstract":"The advent of continuous digital recording of seismograph stations in Alaska did not occur until the fall of 2002. Continuous records of seismic waveforms prior to 2002 were recorded only in analog form. The Alaska Volcano Observatory (AVO) has a substantial archive of continuous analog records made on helicorders in a collection maintained by the University of Alaska Fairbanks Geophysical Institute. As part of the response to the 2006 Augustine Volcano eruption, the AVO scanned analog drum records of the 1986 Augustine eruption to aid in comparing the progression of volcanic seismicity in 2006 with the seismic record of the 1986 eruption. The scanned records proved useful, prompting subsequent efforts to preserve records from other notable episodes of volcanic unrest as readily available scanned images. The data archive accompanying this report contains scanned images of select drum records for the eruptions at Augustine Volcano (1986), Redoubt Volcano (1989–90), Mount Spurr (1992), and Pavlof Volcano (1996), as well as for the 1996 earthquake swarm at Akutan Peak.
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U.S. Geological Survey
4210 University Drive
Anchorage, AK 99508
The West Napa Fault has previously been mapped as extending ~45 kilometers (km) from northern Vallejo to southern Saint Helena, California, dominantly running along the western edge of Napa Valley. A zone of fault strands (some previously unmapped) along a ~15-km section of the fault ruptured during the 2014 magnitude 6.0 South Napa earthquake, illustrating the need for further investigation of this little-studied structure. Based on light detection and ranging (lidar) topography and field examination, the fault zone likely extends an additional 10 km or more northward past Saint Helena. In this vicinity, geomorphology suggests two fault strands, one along the range front and another associated with a line of rounded hills that rise 5–10 meters above the middle of the valley. In 2017, we excavated two trenches across an apparent fault scarp on the east side of one elongate hill near Ehlers Lane north of Saint Helena. Examination of the walls revealed three main sedimentary packages. The oldest package, weakly lithified alluvial fan gravels with local sand and silt layers, is tilted 25°–35° to the west. Overlying these tilted strata are two younger sets of strata. On the west side, underlying the crest of the scarp, are alluvial fan gravels with local sand and silt lenses, potentially tilted a few degrees to the west. On the east side, deposited against the scarp, are much finer grained (dominantly fine sand to silt) subhorizontal fluvial strata, likely overbank deposits from the Napa River. We obtained age control on the two younger units through a combination of radiocarbon, infrared-stimulated luminescence, and obsidian hydration dating, establishing that they are latest Pleistocene to modern in age. Although there are no prominent unconformities within the alluvial fan sediments, sample dating indicates there are two generations, one in the 10–20 thousand year (ka) age range and one in the <3 ka age range. Owing to a general lack of well-defined laterally continuous alluvial fan units, it is difficult to distinguish contacts between the two generations except in the immediate proximity of dated samples. The river sediments approximately span the Holocene. No faults were apparent in either trench, indicating that any fault related to the observed surface deformation has not ruptured to the surface at this site during the Holocene and is likely blind.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221002","usgsCitation":"Philibosian, B.E., Sickler, R.R., Prentice, C.S., Pickering, A.J., Gannon, P., Broudy, K.N., Mahan, S.A., Titular, J.N., Turner, E.A., Folmar, C., Patterson, S.F., and Bowman, E.E., 2022, Photomosaics and logs associated with study of West Napa Fault at Ehlers Lane, north of Saint Helena, California: U.S. Geological Survey Open-File Report 2022–1002, 1 sheet, pamphlet 8 p., https://doi.org/10.3133/ofr20221002.","productDescription":"Report: iv, 8 p.; 1 Sheet: 82.00 x 43.00 inches","numberOfPages":"8","additionalOnlineFiles":"Y","ipdsId":"IP-114127","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":501537,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112153.htm","linkFileType":{"id":5,"text":"html"}},{"id":394764,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2022/1002/ofr20221002_sheet.pdf","size":"80 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":394763,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1002/ofr20221002_pamphlet.pdf","text":"Pamphlet","size":"300 KB","linkFileType":{"id":1,"text":"pdf"}},{"id":394762,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1002/covrthb.jpg"}],"country":"United States","state":"California","city":"Saint Helena","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.58407592773438,\n 38.47294404791815\n ],\n [\n -122.38494873046875,\n 38.47294404791815\n ],\n [\n -122.38494873046875,\n 38.586820096127674\n ],\n [\n -122.58407592773438,\n 38.586820096127674\n ],\n [\n -122.58407592773438,\n 38.47294404791815\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information, Menlo Park, Calif.
Office—Earthquake Science Center
U.S. Geological Survey
345 Middlefield Road, MS 977
Menlo Park, CA 94025