Globally, migration phenologies of numerous avian species have shifted over the past half-century. Despite North American waterfowl being well researched, published data on shifts in waterfowl migration phenologies remain scarce. Understanding shifts in waterfowl migration phenologies along with potential drivers is critical for guiding future conservation efforts. Therefore, we utilized historical (1955–2008) nonbreeding waterfowl survey data collected at 21 National Wildlife Refuges in the mid- to lower portion of the Central Flyway to summarize changes in spring and autumn migration phenology. We examined changes in the timing of peak abundance from survey data at monthly intervals for each refuge and species (or species group; n = 22) by year and site-specific temperature for spring (Jan–Mar) and autumn (Oct–Dec) migration periods. For spring (n = 187) and autumn (n = 194) data sets, 13% and 9% exhibited statistically significant changes in the timing of peak migration across years, respectively, while the corresponding numbers for increasing temperatures were 4% and 9%. During spring migration, ≥80% of significant changes in the timing of spring peak indicated advancements, while 67% of significant changes in autumn peak timing indicated delays both across years and with increasing temperatures. Four refuges showed a consistent pattern across species of advancing spring migration peaks over time. Advancements in spring peak across years became proportionally less common among species with increasing latitude, while delays in autumn peak with increasing temperature became proportionally more common. Our study represents the first comprehensive summary of changes in spring and autumn migration phenology for Central Flyway waterfowl and demonstrates significant phenological changes during the latter part of the twentieth century.
","language":"English","publisher":"PLoS","doi":"10.1371/journal.pone.0266785","usgsCitation":"Andersson, K., Craig A. Davis, Grant Harris, and Haukos, D.A., 2022, Changes in waterfowl migration phenologies in central North America: Implications for future waterfowl conservation: PLoS ONE, v. 17, no. 5, e0266785, 19 p., https://doi.org/10.1371/journal.pone.0266785.","productDescription":"e0266785, 19 p.","ipdsId":"IP-135751","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":447749,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0266785","text":"Publisher Index Page"},{"id":433367,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kansas, Nebraska, New Mexico, Oklahoma, 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\"}}]}","volume":"17","issue":"5","noUsgsAuthors":false,"publicationDate":"2022-05-18","publicationStatus":"PW","contributors":{"authors":[{"text":"Andersson, Kent","contributorId":341552,"corporation":false,"usgs":false,"family":"Andersson","given":"Kent","email":"","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":908601,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Craig A. 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Davis","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":908602,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grant Harris","contributorId":341554,"corporation":false,"usgs":false,"family":"Grant Harris","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":908603,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haukos, David A. 0000-0001-5372-9960 dhaukos@usgs.gov","orcid":"https://orcid.org/0000-0001-5372-9960","contributorId":3664,"corporation":false,"usgs":true,"family":"Haukos","given":"David","email":"dhaukos@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":908604,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70231595,"text":"ofr20221024 - 2022 - Continuous stream discharge, salinity, and associated data collected in the lower St. Johns River and its tributaries, Florida, 2020","interactions":[],"lastModifiedDate":"2026-03-27T20:03:48.787042","indexId":"ofr20221024","displayToPublicDate":"2022-05-17T14:31:30","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-1024","displayTitle":"Continuous Stream Discharge, Salinity, and Associated Data Collected in the Lower St. Johns River and Its Tributaries, Florida, 2020","title":"Continuous stream discharge, salinity, and associated data collected in the lower St. Johns River and its tributaries, Florida, 2020","docAbstract":"The U.S. Army Corps of Engineers, Jacksonville District, is deepening the St. Johns River channel in Jacksonville, Florida, from 40 to 47 feet along 13 miles of the river channel beginning at the mouth of the river at the Atlantic Ocean, in order to accommodate larger, fully loaded cargo vessels. The U.S. Geological Survey, in cooperation with the U.S. Army Corps of Engineers, monitored stage, discharge, and (or) water temperature and salinity at 26 continuous data collection stations in the St. Johns River and its tributaries.
This is the fifth annual report by the U.S. Geological Survey on data collection for the Jacksonville Harbor deepening project. The report contains information pertinent to data collection during the 2020 water year, from October 2019 to September 2020. The addition of water-quality data collection at St. Johns River at Buffalo Bluff near Satsuma was the only modification to the previously installed network.
Discharge and salinity varied widely during the data collection period, which included above-average rainfall for 3 of the 5 counties in the study area. Total annual rainfall for all counties ranked third among the annual totals computed for the 5 years considered for this study. Annual mean discharge at Clapboard Creek was highest among the tributaries, followed by Ortega River, Durbin Creek, Pottsburg Creek at U.S. 90, Cedar River, Trout River, Julington Creek, Pottsburg Creek near South Jacksonville, Dunn Creek, and Broward River, whose annual mean was lowest. Annual mean discharge at 8 of the 10 tributary monitoring sites was higher for the 2020 water year than for the 2019 water year, and the computed annual mean flow at Clapboard Creek was the highest over the 5 years considered for this study. The annual mean discharge for each of the main-stem sites was higher for the 2020 water year than for the 2019 water year except for Buffalo Bluff, which remained the same.
Among the tributary sites, annual mean salinity was highest at Clapboard Creek, the site closest to the Atlantic Ocean, and was lowest at Durbin Creek, the site farthest from the ocean. Annual mean salinity data from the main-stem sites on the St. Johns River indicate that salinity decreased with distance upstream from the ocean, which was expected. Relative to annual mean salinity calculated for the 2019 water year, annual mean salinity at all monitoring locations was higher for the 2020 water year except at the tributary sites of Trout River, Dunn Creek, and Clapboard Creek, which were lower, and Durbin Creek, which remained the same. The 2020 annual mean salinity on the main-stem of the St. Johns River was the highest since the beginning of the study in 2016 at Dancy Point, Racy Point, Shands Bridge, below Shands Bridge, above Buckman Bridge, and Jacksonville (Acosta Bridge). Among the tributary sites, annual mean salinity rankings for 2020 were highest for Julington Creek and Ortega River, which were the second-highest on record for those sites.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221024","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Ryan, P.J., 2022, Continuous stream discharge, salinity, and associated data collected in the lower St. Johns River and its tributaries, Florida, 2020: U.S. Geological Survey Open-File Report 2022–1024, 48 p., https://doi.org/10.3133/ofr20221024.","productDescription":"Report: ix, 48 p.; Dataset","numberOfPages":"62","onlineOnly":"Y","ipdsId":"IP-133884","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":400657,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1024/coverthb.jpg"},{"id":400658,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1024/ofr20221024.pdf","text":"Report","size":"3.73 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1024"},{"id":400659,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1024/ofr20221024.XML"},{"id":400660,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1024/images"},{"id":400661,"rank":5,"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":401171,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/ofr20221024/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":501767,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113057.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Florida","otherGeospatial":"St. Johns River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.27935791015625,\n 29.14736383122664\n ],\n [\n -80.38970947265625,\n 29.14736383122664\n ],\n [\n -80.38970947265625,\n 30.56226095049944\n ],\n [\n -82.27935791015625,\n 30.56226095049944\n ],\n [\n -82.27935791015625,\n 29.14736383122664\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
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Lutz, FL 33559
Groundwater-quality data collected from 1997 through 2018 from 68 monitoring locations open to the Missouri River alluvial aquifer (hereafter referred to as the “alluvial aquifer”) near the Independence, Missouri, well field were analyzed by the U.S. Geological Survey, in cooperation with the City of Independence, Missouri. This analysis was done to assess the quality of the water in the alluvial aquifer near the well field, identify trends in water quality in the alluvial aquifer from 1997 through 2018, assess hydraulic interaction between the Missouri River and the groundwater system, identify potential threats to the potability of the water extracted from the well field, and identify ways to improve the monitoring effort. Water-quality data indicate that water from the Missouri River recharges the alluvial aquifer. Recharge is exacerbated by pumping from the well field so that the quality of the water pumped from the well field is similar to that of the river for many constituents. Water-quality data indicate that the alluvial aquifer is under oxygen- and nitrate-reducing conditions, and iron- and manganese-reducing conditions are present in most of the alluvial aquifer. Sulfate-reducing conditions are present along the northern and western parts of the monitoring network north of the Missouri River. Maximum contaminant levels for antimony, arsenic, barium, lead, selenium, and uranium were exceeded in at least one sample, and the median concentrations of arsenic exceeded the maximum contaminant level in several monitoring wells on the periphery of the well field. Secondary maximum contaminant levels were exceeded for iron, manganese, and sulfate in multiple wells. Low concentrations of a variety of organic compounds, primarily derived from recharge from the Missouri River with lesser amounts potentially derived from application at land surface in the study area, are present in the alluvial aquifer and in water extracted from the well field.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225027","collaboration":"Prepared in cooperation with the City of Independence, Missouri","usgsCitation":"Kay, R.T., Krempa, H.M., and Hulsey, K.M., 2022, Water quality in the Missouri River alluvial aquifer near the Independence, Missouri, well field, 1997–2018: U.S. Geological Survey Scientific Investigations Report 2022–5027, 63 p., https://doi.org/10.3133/sir20225027.","productDescription":"Report: vi, 63 p.; Appendixes; Dataset","numberOfPages":"74","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-113521","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":400723,"rank":10,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20225027/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":400537,"rank":9,"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":400536,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2022/5027/sir20225027_appendix2.zip","text":"Appendix 2","size":"16 kB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"—Tables 2.1 to 2.30"},{"id":400535,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2022/5027/sir20225027_appendix2.xlsx","text":"Appendix 2","size":"68.8 kB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"—Tables 2.1 to 2.30"},{"id":400534,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2022/5027/sir20225027_appendix1.zip","text":"Appendix 1","size":"61 kB","linkFileType":{"id":7,"text":"csv"},"linkHelpText":"—Tables 1.1 to 1.70"},{"id":400533,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2022/5027/sir20225027_appendix1.xlsx","text":"Appendix 1","size":"204 kB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"—Tables 1.1 to 1.70"},{"id":400530,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5027/sir20225027.XML"},{"id":400529,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5027/sir20225027.pdf","text":"Report","size":"3.89 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5027"},{"id":400528,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5027/coverthb.jpg"},{"id":400531,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5027/images"}],"country":"United States","state":"Missouri","city":"Independence","otherGeospatial":"Missouri River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.46765899658203,\n 39.08876842889136\n ],\n [\n -94.37633514404297,\n 39.08876842889136\n ],\n [\n -94.37633514404297,\n 39.165471994238374\n ],\n [\n -94.46765899658203,\n 39.165471994238374\n ],\n [\n -94.46765899658203,\n 39.08876842889136\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
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1400 Independence Road
Rolla, MO 65401
A cooperative study between the National Park Service (NPS) and the U.S. Geological Survey (USGS) characterized groundwater quality and hydrogeology in parts of Pinnacles National Park. The water-quality investigation assessed the geochemistry of springs, wells, surface water, and precipitation and analyzed geochemistry of rock formations that affect the water chemistry through water-rock interaction. The hydrogeology investigation used geophysical and groundwater level data to characterize groundwater-flow processes in the alluvial deposits of Bear Valley and the Chalone Creek watershed.
Analysis of aqueous geochemical parameters in water samples from perennial springs, water-supply wells, and surface waters was conducted for samples collected after the dry season (autumnal) and after the wet season (vernal) to assess changes in geochemistry due to changes in groundwater levels or flow resulting from precipitation. The chemistry of bulk precipitation collected during the wet season was also analyzed. Bedrock samples were analyzed for geochemical parameters to help constrain groundwater sources, flow paths, and weathering. The geochemical investigations show a correspondence between the source rock and the spring-water chemistry that can be attributed to the mineralogy of the source rock. The narrow range of strontium isotopes in water samples, sourced in geochemically and mineralogically disparate rocks, indicates that the bedrock groundwater is relatively old and has reached quasi-steady state with respect to weathering of susceptible minerals.
Groundwater-level monitoring indicated that the water table is shallow—from 0 to 10 meters (m) below land surface. In southern Bear Valley and in the Chalone Creek alluvium, water levels rose and declined by several meters over each annual cycle of this study. In northern Bear Valley, water levels rose modestly over two wet seasons but declined during a third wet season. In Bear Valley, groundwater/surface-water interaction occurs along the perennial reach of Sandy Creek. Groundwater discharges to the upstream part of the reach, becomes surface water and is partly consumed by evapotranspiration, and infiltrates farther downstream. In the Chalone Creek alluvium, runoff-generated surface-water flow in intermittent stream reaches is a major component of groundwater recharge. After the onset of significant streamflow, creek water rapidly recharges groundwater until water levels rise to nearly the creek level. Groundwater levels generally remain high throughout the wet season, then gradually decline after the creek becomes dry.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221026","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Scheiderich, K., Tiedeman, C.R., Hsieh, P.A., 2022, Aqueous geochemistry of waters and hydrogeology of alluvial deposits, Pinnacles National Park, California: U.S. Geological Survey Open-File Report 2022-1026, 39 p., https://doi.org/10.3133/ofr20221026.","productDescription":"Report: viii, 39 p.; 3 Data Releases","numberOfPages":"39","onlineOnly":"Y","ipdsId":"IP-129434","costCenters":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"links":[{"id":400733,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9IZXRC0","text":"Streamflow data collected by the wading method, Pinnacles National Park, California, 2018","description":"Tiedeman, C.R., Ingebritsen, S.E., and Hsieh, P.A., 2021, Streamflow data collected by the wading method, Pinnacles National Park, California, 2018: U.S. Geological Survey data release, https://doi.org/10.5066/P9IZXRC0."},{"id":400732,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9AMDH71","text":"Passive Seismic Data Collected for the Horizontal-to-Vertical Spectral Ratio (HVSR) Method, Pinnacles National Park, California, 2018-2020","description":"Tiedeman, C.R., and Hsieh, P.A., 2021, Passive Seismic Data Collected for the Horizontal-to-Vertical Spectral Ratio (HVSR) Method, Pinnacles National Park, California, 2018-2020: U.S. Geological Survey data release, https://doi.org/10.5066/P9AMDH71."},{"id":400435,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1026/covrthb.jpg"},{"id":400731,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9BMM0XG","text":"Geochemistry of rocks, precipitation, and water sources from Pinnacles National Park, California, 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36.51060196931051\n ],\n [\n -121.24528884887695,\n 36.51046399690832\n ],\n [\n -121.24563217163087,\n 36.50273714986985\n ],\n [\n -121.23258590698242,\n 36.502323189870765\n ],\n [\n -121.22777938842772,\n 36.49473353098341\n ],\n [\n -121.22571945190428,\n 36.494871531420934\n ],\n [\n -121.22434616088866,\n 36.48962734192797\n ],\n [\n -121.21885299682617,\n 36.48879927955005\n ],\n [\n -121.21267318725585,\n 36.49017937859546\n ],\n [\n -121.21129989624022,\n 36.494319528195426\n ],\n [\n -121.20872497558592,\n 36.49100742621996\n ],\n [\n -121.2118148803711,\n 36.486177023622\n ],\n [\n -121.21730804443358,\n 36.48507288930754\n ],\n [\n -121.21644973754881,\n 36.47306441258654\n ],\n [\n -121.20666503906249,\n 36.4729263733008\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
WMA- Laboratory & Analytical Services Division
U.S. Geological Survey
USGS Headquarters
12201 Sunrise Valley Drive
Reston, VA 20192
Mercury (Hg) contamination has been a persistent concern in the Florida Everglades for over three decades due to elevated atmospheric deposition and the system's propensity for methylation and rapid bioaccumulation. Given declines in atmospheric Hg concentrations in the conterminous United States and efforts to mitigate nutrient release to the greater Everglades ecosystem, it was vital to assess how Hg dynamics responded on temporal and spatial scales. This study used a multimedia approach (water and biota) to examine Hg and methylmercury (MeHg) dynamics across a 76-site network within the southernmost portion of the region, Everglades National Park (ENP), from 2008 to 2018. Atmospheric Hg deposition was evaluated over time using a long-term monitoring station. Hg concentrations across matrices showed that air, water, and biota from the system were inextricably linked. Temporal patterns across matrices were driven primarily by hydrologic and climatic changes in the park and no evidence of a decline in atmospheric Hg deposition from 2008 to 2018 was observed, unlike other regions of the United States. In the Shark River Slough (SRS), excess dissolved organic carbon and sulfate were also consistently delivered from upgradient canals and showed no evidence of decline over the study period. Within the SRS a strong positive correlation was observed between MeHg concentrations in surface water and resident fish. Within distinct geographic regions of ENP (SRS, Marsh, Coastal), the geochemical controls on MeHg dynamics differed and highlighted regions susceptible to higher MeHg bioaccumulation, particularly in the SRS and Coastal regions. This study demonstrates the strong influence that dissolved organic carbon and sulfate loads have on spatial and temporal distributions of MeHg across the ENP. Importantly, improved water quality and flow rates are two key restoration targets of the nearly 30-year Everglades restoration program, which if achieved, this study suggests would lead to reduced MeHg production and exposure.
Desert riverscape rehabilitation practitioners must contend with compounding effects of increasing human water demand, persistent drought, non-native species establishment, and climate change, which further stress desert riverine ecosystems such as rivers in the Colorado River basin, United States. Herein, we provide our perspective on the importance of natural flows, large floods in particular, for successful conservation and rehabilitation of riverscapes. We present ideas developed from our experience with rehabilitation projects across multiple desert tributary rivers with varying levels of habitat degradation and water abstraction. We propose spatially extensive measures such as protection of in-stream flows, tailoring rehabilitation efforts to available annual water availability, and working with nature using low-tech process-based techniques to more completely address the mechanisms of habitat degradation, such as flow reduction and vegetation-induced channel narrowing. Traditionally, rehabilitation efforts in the Colorado River basin take place at relatively small spatial extents, at convenient locations and, largely focus on reducing non-native plant and fish species. We suggest that we need to think more broadly and creatively, and that conservation or recovery of natural flow regimes is crucial to long-term success of almost all management efforts for both in-stream and riparian communities.
","language":"English","publisher":"Frontiers Media","doi":"10.3389/fenvs.2022.870488","usgsCitation":"Pennock, C., Budy, P., and Macfarlane, W., 2022, Effective conservation of desert riverscapes requires protection and restoration of in-stream flows with rehabilitation approaches tailored to water availability: Frontiers in Environmental Science, v. 10, 870488, 7 p., https://doi.org/10.3389/fenvs.2022.870488.","productDescription":"870488, 7 p.","ipdsId":"IP-138466","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":447774,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fenvs.2022.870488","text":"Publisher Index Page"},{"id":429773,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","noUsgsAuthors":false,"publicationDate":"2022-05-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Pennock, Casey A.","contributorId":337824,"corporation":false,"usgs":false,"family":"Pennock","given":"Casey A.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":902715,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Budy, Phaedra E. 0000-0002-9918-1678","orcid":"https://orcid.org/0000-0002-9918-1678","contributorId":228930,"corporation":false,"usgs":true,"family":"Budy","given":"Phaedra E.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":902716,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Macfarlane, William W.","contributorId":337701,"corporation":false,"usgs":false,"family":"Macfarlane","given":"William W.","affiliations":[{"id":6682,"text":"Utah State University","active":true,"usgs":false}],"preferred":false,"id":902717,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70231614,"text":"70231614 - 2022 - A collaborative agenda for archaeology and fire science","interactions":[],"lastModifiedDate":"2022-07-08T13:34:47.693082","indexId":"70231614","displayToPublicDate":"2022-05-16T08:39:13","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":6505,"text":"Nature Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"A collaborative agenda for archaeology and fire science","docAbstract":"Humans have influenced global fire activity for millennia and will continue to do so into the future. Given the long-term interaction between humans and fire, we propose a collaborative research agenda linking archaeology and fire science that emphasizes the socioecological histories and consequences of anthropogenic fire in the development of fire management strategies today.
","language":"English","publisher":"Nature","doi":"10.1038/s41559-022-01759-2","usgsCitation":"Snitker, G.J., Roos, C., Sullivan, A., Maezumi, S.Y., Bird, D., Coughlan, M., Derr, K., Gassaway, L., Klimaszewski-Patterson, A., and Loehman, R.A., 2022, A collaborative agenda for archaeology and fire science: Nature Ecology and Evolution, v. 6, p. 835-839, https://doi.org/10.1038/s41559-022-01759-2.","productDescription":"5 p.","startPage":"835","endPage":"839","ipdsId":"IP-137105","costCenters":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":400695,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"6","noUsgsAuthors":false,"publicationDate":"2022-05-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Snitker, Grant J.","contributorId":221493,"corporation":false,"usgs":false,"family":"Snitker","given":"Grant","email":"","middleInitial":"J.","affiliations":[{"id":12697,"text":"University of Georgia","active":true,"usgs":false}],"preferred":false,"id":843121,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roos, Christopher","contributorId":251699,"corporation":false,"usgs":false,"family":"Roos","given":"Christopher","affiliations":[{"id":20300,"text":"Southern Methodist University","active":true,"usgs":false}],"preferred":false,"id":843122,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sullivan, Allen","contributorId":291811,"corporation":false,"usgs":false,"family":"Sullivan","given":"Allen","email":"","affiliations":[{"id":7159,"text":"University of Cincinnati","active":true,"usgs":false}],"preferred":false,"id":843123,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Maezumi, S. Yoshi","contributorId":291813,"corporation":false,"usgs":false,"family":"Maezumi","given":"S.","email":"","middleInitial":"Yoshi","affiliations":[{"id":37958,"text":"University of Amsterdam","active":true,"usgs":false}],"preferred":false,"id":843124,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bird, Douglas","contributorId":291815,"corporation":false,"usgs":false,"family":"Bird","given":"Douglas","email":"","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":843125,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Coughlan, Michael","contributorId":168920,"corporation":false,"usgs":false,"family":"Coughlan","given":"Michael","email":"","affiliations":[{"id":25390,"text":"Department of Anthropology, University of Georgia, Athens, Georgia, USA","active":true,"usgs":false}],"preferred":false,"id":843126,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Derr, Kelly","contributorId":291819,"corporation":false,"usgs":false,"family":"Derr","given":"Kelly","email":"","affiliations":[{"id":62760,"text":"Historical Research Associates","active":true,"usgs":false}],"preferred":false,"id":843127,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Gassaway, Linn","contributorId":291821,"corporation":false,"usgs":false,"family":"Gassaway","given":"Linn","email":"","affiliations":[{"id":36400,"text":"US Forest Service","active":true,"usgs":false}],"preferred":false,"id":843128,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Klimaszewski-Patterson, Anna 0000-0001-7765-8802","orcid":"https://orcid.org/0000-0001-7765-8802","contributorId":288490,"corporation":false,"usgs":false,"family":"Klimaszewski-Patterson","given":"Anna","email":"","affiliations":[{"id":39151,"text":"California State University Sacramento","active":true,"usgs":false}],"preferred":false,"id":843129,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Loehman, Rachel A. 0000-0001-7680-1865 rloehman@usgs.gov","orcid":"https://orcid.org/0000-0001-7680-1865","contributorId":187605,"corporation":false,"usgs":true,"family":"Loehman","given":"Rachel","email":"rloehman@usgs.gov","middleInitial":"A.","affiliations":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":false,"id":843130,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70231664,"text":"70231664 - 2022 - Assessing private well contamination in Grant, Iowa, and Lafayette Counties, Wisconsin: The southwest Wisconsin groundwater and geology study","interactions":[],"lastModifiedDate":"2022-05-19T13:21:52.585221","indexId":"70231664","displayToPublicDate":"2022-05-16T08:14:15","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":4,"text":"Other Government Series"},"title":"Assessing private well contamination in Grant, Iowa, and Lafayette Counties, Wisconsin: The southwest Wisconsin groundwater and geology study","docAbstract":"Rural residents of Grant, Iowa, and Lafayette Counties in Wisconsin rely on private wells for their water. Contaminants like nitrate and bacteria from septic systems, fertilizer, and manure can contaminate the groundwater that residents use. Groundwater is vulnerable to contamination where the soil layer is thin and the bedrock is fractured, which is the case for much of the study region. This study includes five objectives that were designed to assess and understand private well water contamination in the three counties.
","language":"English","publisher":"Extension Iowa County, University of Wisconsin-Madison","usgsCitation":"Stokdyk, J.P., Borchardt, M.A., Firnstahl, A.D., Bradbury, K., Muldoon, M., and Kieke, B.A., 2022, Assessing private well contamination in Grant, Iowa, and Lafayette Counties, Wisconsin: The southwest Wisconsin groundwater and geology study, 66 p.","productDescription":"66 p.","ipdsId":"IP-139234","costCenters":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":400805,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":400796,"type":{"id":15,"text":"Index Page"},"url":"https://iowa.extension.wisc.edu/natural-resources/swigg"}],"country":"United States","state":"Wisconsin","county":"Grant County, Iowa County, Lafayette 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classification using low frequency tracking data and automated modelling pipelines: Application to North American waterfowl","docAbstract":"Identifying animal behaviors, life history states, and movement patterns is a prerequisite for many animal behavior analyses and effective management of wildlife and habitats. Most approaches classify short-term movement patterns with high frequency location or accelerometry data. However, patterns reflecting life history across longer time scales can have greater relevance to species biology or management needs, especially when available in near real-time. Given limitations in collecting and using such data to accurately classify complex behaviors in the long-term, we used hourly GPS data from 5 waterfowl species to produce daily activity classifications with machine-learned models using “automated modelling pipelines”.
Automated pipelines are computer-generated code that complete many tasks including feature engineering, multi-framework model development, training, validation, and hyperparameter tuning to produce daily classifications from eight activity patterns reflecting waterfowl life history or movement states. We developed several input features for modeling grouped into three broad categories, hereafter “feature sets”: GPS locations, habitat information, and movement history. Each feature set used different data sources or data collected across different time intervals to develop the “features” (independent variables) used in models.
Automated modelling pipelines rapidly developed easily reproducible data preprocessing and analysis steps, identification and optimization of the best performing model and provided outputs for interpreting feature importance. Unequal expression of life history states caused unbalanced classes, so we evaluated feature set importance using a weighted F1-score to balance model recall and precision among individual classes. Although the best model using the least restrictive feature set (only 24 hourly relocations in a day) produced effective classifications (weighted F1 = 0.887), models using all feature sets performed substantially better (weighted F1 = 0.95), particularly for rarer but demographically more impactful life history states (i.e., nesting).
Automated pipelines generated models producing highly accurate classifications of complex daily activity patterns using relatively low frequency GPS and incorporating more classes than previous GPS studies. Near real-time classification is possible which is ideal for time-sensitive needs such as identifying reproduction. Including habitat and longer sequences of spatial information produced more accurate classifications but incurred slight delays in processing.
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0000-0003-3657-5941","orcid":"https://orcid.org/0000-0003-3657-5941","contributorId":222610,"corporation":false,"usgs":true,"family":"Lorenz","given":"Austen","email":"","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":857613,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Mott, Andrea 0000-0001-9586-9590","orcid":"https://orcid.org/0000-0001-9586-9590","contributorId":299367,"corporation":false,"usgs":false,"family":"Mott","given":"Andrea","affiliations":[{"id":64822,"text":"USGS WERC (name not found)","active":true,"usgs":false}],"preferred":false,"id":857614,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Herzog, Mark P. 0000-0002-5203-2835 mherzog@usgs.gov","orcid":"https://orcid.org/0000-0002-5203-2835","contributorId":131158,"corporation":false,"usgs":true,"family":"Herzog","given":"Mark","email":"mherzog@usgs.gov","middleInitial":"P.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":857615,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Ackerman, Joshua T. 0000-0002-3074-8322","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":202848,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":857616,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70237692,"text":"70237692 - 2022 - Evaluating aromatization of solid bitumen generated in the presence and absence of water: Implications for solid bitumen reflectance as a thermal proxy","interactions":[],"lastModifiedDate":"2022-10-19T13:22:32.108904","indexId":"70237692","displayToPublicDate":"2022-05-13T08:20:18","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2033,"text":"International Journal of Coal Geology","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating aromatization of solid bitumen generated in the presence and absence of water: Implications for solid bitumen reflectance as a thermal proxy","docAbstract":"Geological models for petroleum generation suggest thermal conversion of oil-prone sedimentary organic matter in the presence of water promotes increased liquid saturate yield, whereas absence of water causes formation of an aromatic, cross-linked solid bitumen residue. To test the influence of hydrogen from water, organic-rich (22 wt% total organic carbon, TOC) mudrock samples from the Eocene lacustrine Green River Formation Mahogany zone oil shale were pyrolyzed under hydrous and anhydrous conditions in closed system batch reactors at temperatures between 300 and 370 °C for 72 h. Pre- and post-pyrolysis samples were characterized using petrographic approaches including optical microscopy, reflectance, Raman spectroscopy, and scanning electron and transmission electron microscopy to quantify differences in relative appearance, abundance, and composition of solid bitumen newly generated during the pyrolysis experiments. Petrographic analyses were supplemented by geochemical screening measurements (TOC content and programmed temperature pyrolysis). Results show post-hydrous pyrolysis residues contain lower TOC, are comprised of solid bitumen with greater aromaticity, and have textures indicative of lower viscosities, relative to anhydrous residues from the same temperature pyrolysis conditions. These observations suggest solid bitumen forming from thermal conversion of oil-prone sedimentary organic matter under anhydrous conditions may be less aromatic, although more cross-linked, than solid bitumen forming under hydrous conditions at the same time-temperature combination. To explain these results, we suggest that a radical disproportionation mechanism is favored in the presence of hydrogen donated from water, and that this disproportionation promotes aromatization in the solid residue with concomitant expulsion of saturated hydrocarbons.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.coal.2022.104016","usgsCitation":"Hackley, P.C., Jubb, A., Smith, P.L., McAleer, R.J., Valentine, B.J., Hatcherian, J.J., Botterell, P.J., and Birdwell, J.E., 2022, Evaluating aromatization of solid bitumen generated in the presence and absence of water: Implications for solid bitumen reflectance as a thermal proxy: International Journal of Coal Geology, v. 258, 104016, 16 p., https://doi.org/10.1016/j.coal.2022.104016.","productDescription":"104016, 16 p.","ipdsId":"IP-136449","costCenters":[{"id":49175,"text":"Geology, Energy & Minerals Science Center","active":true,"usgs":true}],"links":[{"id":447793,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.coal.2022.104016","text":"Publisher Index Page"},{"id":408537,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"258","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hackley, Paul C. 0000-0002-5957-2551 phackley@usgs.gov","orcid":"https://orcid.org/0000-0002-5957-2551","contributorId":592,"corporation":false,"usgs":true,"family":"Hackley","given":"Paul","email":"phackley@usgs.gov","middleInitial":"C.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":855030,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jubb, Aaron M. 0000-0001-6875-1079","orcid":"https://orcid.org/0000-0001-6875-1079","contributorId":201978,"corporation":false,"usgs":true,"family":"Jubb","given":"Aaron M.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":855031,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Patrick L.","contributorId":298071,"corporation":false,"usgs":false,"family":"Smith","given":"Patrick","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":855032,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McAleer, Ryan J. 0000-0003-3801-7441 rmcaleer@usgs.gov","orcid":"https://orcid.org/0000-0003-3801-7441","contributorId":215498,"corporation":false,"usgs":true,"family":"McAleer","given":"Ryan","email":"rmcaleer@usgs.gov","middleInitial":"J.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":855033,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Valentine, Brett J. 0000-0002-8678-2431 bvalentine@usgs.gov","orcid":"https://orcid.org/0000-0002-8678-2431","contributorId":3846,"corporation":false,"usgs":true,"family":"Valentine","given":"Brett","email":"bvalentine@usgs.gov","middleInitial":"J.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":855034,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hatcherian, Javin J. 0000-0001-9151-6798 jhatcherian@usgs.gov","orcid":"https://orcid.org/0000-0001-9151-6798","contributorId":195770,"corporation":false,"usgs":true,"family":"Hatcherian","given":"Javin","email":"jhatcherian@usgs.gov","middleInitial":"J.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":855035,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Botterell, Palma J. 0000-0001-7140-0915 pjarboe@usgs.gov","orcid":"https://orcid.org/0000-0001-7140-0915","contributorId":5805,"corporation":false,"usgs":true,"family":"Botterell","given":"Palma","email":"pjarboe@usgs.gov","middleInitial":"J.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":855036,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Birdwell, Justin E. 0000-0001-8263-1452 jbirdwell@usgs.gov","orcid":"https://orcid.org/0000-0001-8263-1452","contributorId":3302,"corporation":false,"usgs":true,"family":"Birdwell","given":"Justin","email":"jbirdwell@usgs.gov","middleInitial":"E.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":855037,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70240914,"text":"70240914 - 2022 - Temperature explains the formation of a metalimnetic oxygen minimum in a deep mesotrophic lake","interactions":[],"lastModifiedDate":"2023-03-01T14:10:49.606498","indexId":"70240914","displayToPublicDate":"2022-05-13T07:06:07","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1999,"text":"Inland Waters","active":true,"publicationSubtype":{"id":10}},"title":"Temperature explains the formation of a metalimnetic oxygen minimum in a deep mesotrophic lake","docAbstract":"Green Lake, a deep mesotrophic lake located in a primarily agricultural watershed in central Wisconsin, USA, has experienced annual metalimnetic oxygen minima since the early 20th century. However, the severity of the phenomenon has increased over time, and late-summer dissolved oxygen (DO) concentrations have typically been <3 mg L−1 in recent years. In situ, high-frequency observations of oxygen depletion at multiple depths reveal that while DO consumption during stratification occurs most rapidly in the metalimnion, there is synchrony between DO time series extending into the hypolimnion. A biochemical oxygen demand-based modeling approach suggests that much of the relationship between water depth and respiration rates can be explained by differences in water temperature. The amount of labile organic matter present throughout the water column at the onset of stratification seems to be a primary determinant of the severity of the annual metalimnetic DO minimum in late summer. Productivity has increased in the lake as a result of increased nutrient loading and is the likely driver of the decrease in minimum DO concentrations. In addition, the onset and duration of stratification is an important factor in determining the severity of the DO minimum.
The U.S. Geological Survey (USGS) Central Midwest Water Science Center (CMWSC) includes three States—Illinois, Iowa, and Missouri. USGS water science centers across the Nation provide information on water resources including streamflow, water use, water availability, and the quality of surface water and groundwater (https://www.usgs.gov/mission-areas/water-resources).
The USGS CMWSC Harmful Algal Blooms (HABs) team is dedicated to studying the complexity of HABs and is currently (2021) researching ways to better predict the timing, magnitude, and toxicity of HABs. Updated information about the HABs team including current projects, data releases, and publications are available on the CMWSC website (https://www.usgs.gov/centers/cm-water/science-topics/harmful-algal-blooms).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20223011","usgsCitation":"Summers, K.M., Krempa, H.M., and Garrett, J.D., 2022, Central Midwest Water Science Center— Harmful Algal Blooms team: U.S. Geological Survey Fact Sheet, 2022–3011, 4 p., https://doi.org/10.3133/fs20223011.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"N","ipdsId":"IP-132581","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":400625,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/fs20223011/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":400591,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/fs/2022/3011/images"},{"id":400590,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/fs/2022/3011/fs20223011.XML"},{"id":400589,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2022/3011/fs20223011.pdf","text":"Report","size":"7.79 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2022-3011"},{"id":400588,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2022/3011/coverthb.jpg"}],"contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
405 North Goodwin
Urbana, IL 61801
The alteration of thermal regimes, including increased temperatures and shifts in seasonality, is a key challenge to the health and survival of federally protected cold-water salmonids in streams of the Willamette River basin in northwestern Oregon. To better support threatened fish species, the U.S. Army Corps of Engineers (USACE) and other water managers seek to improve the thermal regime in the Willamette River and key tributaries downstream of USACE dams by utilizing strategically timed flow releases from USACE dams. To inform flow management decisions, regression relations were developed for 12 Willamette River basin locations below USACE dams relating stream temperature with streamflow and air temperature utilizing publicly available datasets spanning 2000–18. The resulting relations provide simple tools to investigate stream temperature responses to changes in streamflow and climatic conditions in the Willamette River system.
Regression relations on the Willamette River and key tributaries show that, at locations sufficiently distant from the direct temperature influence of upstream dam releases, air temperature and streamflow are reasonable proxies to predict the 7-day average of the daily mean (7dADMean) and 7-day average of the daily maximum (7dADMax) water temperature with errors generally ≤1 degrees Celsius (°C). To account for seasonal variations in the relation between air temperature, streamflow, and stream temperature, a transition-smoothed, seasonal regression approach was used. Stream temperature is inversely correlated with streamflow in all seasons except “winter” (January–March), when it is relatively independent. Stream temperature is positively correlated with air temperature in all seasons, but the slope decreases at very low or very high air temperatures. Generally, fit is best for seasonal models “winter” (January–March), “spring” (April–May), “summer” (June–August), and “early autumn” (September–October). Error in “autumn” (November–December) is larger, probably due to variation in the onset timing of winter storms.
Simulated results from a climatological analysis of predicted stream temperature suggest that, excluding extremes and accounting for some seasonal variability, the 7dADMean and 7dADMax stream temperature sensitivity to air temperature and streamflow varies by location on the river. To investigate the potential range of stream temperature variability based on historical air temperature and streamflow conditions, stream temperature predictions were calculated using synthetic time series comprised of daily temperature values representing the 0.10, 0.33, 0.50, 0.67, and 0.90 quantile of air temperature and streamflow from 1954 (the year meaningful streamflow augmentation began) to 2018. Results show that from a “very hot” (0.90 quantile) and “very dry” (0.10 quantile) year to a “very cool” (0.10 quantile) and “very wet” (0.90; all quantiles from 1954 to 2018) year, the stream temperature sensitivity to air temperature and streamflow is about 3 °C at Harrisburg (river mile 161.0) and increases to about 5 °C at Keizer (river mile 82.2). While the number of days exceeding regulatory criteria are fewer in cooler, wetter years than in warmer, dryer years, the models suggest that the Willamette River will likely continue to exceed the State of Oregon maximum water-temperature criterion of 18 °C for sustained periods from late spring to early autumn and that the flow management practices evaluated in this study, while effective at influencing stream temperature, likely cannot prevent many or all such exceedances.
As modeled for 2018, a representative very hot year with normal to below-normal streamflow, stream temperature sensitivity to changes in streamflow of ±100 to ±1000 cubic feet per second produced mean monthly temperature changes from 0.0 to 1.4 °C at Keizer, Albany, and Harrisburg during summer. For a specified change in flow, temperature sensitivity is greater at upstream locations where streamflow is less than that at downstream locations because the change in streamflow is a greater percentage of total streamflow at upstream locations. Similarly, temperature response to a set change in flow is greater in the summer and early autumn low-flow season than in spring when flows are higher. The regression models developed in this study thus indicate that flow management is likely to have a greater effect on stream temperature at upstream locations (such as Harrisburg or Albany) and during the low-flow season than at downstream locations (such as Keizer) or during periods of higher streamflow.
","largerWorkType":{"id":18,"text":"Report"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20215022","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Portland District","usgsCitation":"Stratton Garvin, L.E., Rounds, S.A., and Buccola, N.L., 2022, Estimating stream temperature in the Willamette River Basin, northwestern Oregon—A regression-based approach: U.S. Geological Survey Scientific Investigations Report 2021–5022, 40 p., https://doi.org/10.3133/sir20215022.","productDescription":"Report: viii, 40 p.; Data Release","numberOfPages":"40","onlineOnly":"Y","ipdsId":"IP-119336","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":501948,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113055.htm","linkFileType":{"id":5,"text":"html"}},{"id":400563,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9PALKQZ","text":"USGS Data Release","description":"Stratton Garvin, L.E., 2022, Stream temperature predic tions for the Willamette River Basin, northwestern Oregon estimated from regression equations (1954–2018): U.S. Geological Survey data release, https://doi.org/10.5066/P9PALKQZ.","linkHelpText":"Stream temperature predictions for the Willamette River Basin, northwestern Oregon estimated from regression equations (1954–2018)"},{"id":400560,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2021/5022/sir20215022.pdf","text":"Report","size":"8.5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":400559,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2021/5022/covrthb.jpg"},{"id":400561,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2021/5022/sir20215022.xml"},{"id":400562,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2021/5022/images"}],"country":"United States","state":"Oregon","otherGeospatial":"Willamette River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.64013671874999,\n 43.54854811091286\n ],\n [\n -122.18994140624999,\n 43.54854811091286\n ],\n [\n -122.18994140624999,\n 45.99696161820381\n ],\n [\n -123.64013671874999,\n 45.99696161820381\n ],\n [\n -123.64013671874999,\n 43.54854811091286\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
Cyanobacteria harmful algal blooms (cyanoHABs) negatively affect ecological, human, and animal health. Traditional methods of validating satellite algorithms with data from water samples are often inhibited by the expense of quantifying cyanobacteria indicators in the field and the lack of public data. However, state recreation advisories and other recorded events of cyanoHAB occurrence reported by local authorities can serve as an independent and publicly available dataset for validation. State recreation advisories were defined as a period delimited by a start and end date where a warning was issued due to detections of cyanoHABs over a state's risk threshold. State reported events were defined as any event that was documented with a single date related to cyanoHABs. This study examined the presence-absence agreement between 160 state reported cyanoHAB advisories and 1,343 events and cyanobacteria biomass estimated by a satellite algorithm called the Cyanobacteria Index (CIcyano). The true positive rate of agreement with state recreation advisories was 69% and 60% with state reported events. CIcyano detected a reduction or absence in cyanobacteria after 76% of the recreation advisories ended. CIcyano was used to quantify the magnitude, spatial extent, and temporal frequency of cyanoHABs; each of these three metrics were greater (r > 0.2) during state recreation advisories compared to non-advisory times with effect sizes ranging from small to large. This is the first study to quantitatively evaluate satellite algorithm performance for detecting cyanoHABs with state reported events and advisories and supports informed management decisions with satellite technologies that complement traditional field observations.
The ability of young fish to find and consume food during early life history is an important factor affecting survival and recruitment. While dietary assessments for age-0 Scaphirhynchus sturgeon (shovelnose sturgeon and pallid sturgeon) in the Missouri River, USA have received increased attention over the last 15 years, there is currently limited information available to evaluate long-term trends in prey consumption and body condition. To better understand interannual factors during early-life history, we examined foraging and body condition of age-0 (<12.0 cm) Scaphirhynchus in relation to discharge and the availability of hypothesized foraging and food-producing habitats at a single reach (Lexington) of the Missouri River over a span of five years (2014–2018). Relatively high discharge in 2015 led to concomitant maxima in foraging and lipid levels for age-0 sturgeon. However, lower water levels in 2014 did not see declines in lipid content as would be expected given the low level of foraging observed that year. Additionally, the availability of hypothesized foraging and food-producing habitats had little effect on age-0 sturgeon prey consumption and condition in the Lexington Reach. Our results suggest that other factors in addition to river discharge may affect age-0 sturgeon foraging and condition and more research focused on understanding the flow-habitat relationships would be critical.
Frequent and prolonged military training maneuvers are an intensive type of land use that may disturb land cover, compact soils, and have lasting effects on adjacent stream hydrology and ecosystems. To better understand the potential effect of military training on hydrologic and environmental processes, the U.S. Geological Survey in cooperation with the U.S. Army established hydrologic and water-quality data-collection networks at the U.S. Army Garrison Fort Carson (AGFC) in 1978 and at the Piñon Canyon Maneuver Site (PCMS) in 1982. The purpose of this report is to present precipitation, streamflow, suspended-sediment, and water-quality data collected by the U.S. Geological Survey at the AGFC and PCMS for water years (WYs) 2016–18 and to evaluate those data in relation to long-term data from the AGFC and PCMS. In WYs 2016–18, the U.S. Geological Survey monitored 26 sites on the AGFC and 17 sites on the PCMS for precipitation amount, streamflow, suspended sediment, and (or) water quality.
On the AGFC, total annual precipitation in WYs 2016–18 was larger than the long-term mean for all 3 years at Rod and Gun Meteorologic Station at Fort Carson, CO (Rod and Gun). There were statistically significant upward trends in annual precipitation at Rod and Gun and Young Hollow Meteorologic Station at Fort Carson, CO (Young Hollow) with slopes of 1.25 and 0.66 inches per year (in/yr), respectively. The precipitation totals for WY 2017 were either the largest on record or in the top three for both sites and at Sullivan Park Meteorologic Station at Fort Carson, CO. On the PCMS, total annual precipitation was larger than the long-term mean in WYs 2016–18 at Brown Sheep Camp Meteorologic Station near Tyrone, CO; CIG Pipeline South Meteorologic Station near Simpson, CO; Bear Springs Hills Meteorologic Station near Houghton, CO (Bear Springs); and Upper Red Rock Canyon Meteorologic Station near Houghton, CO (Upper Red Rock). There were statistically significant upward trends in precipitation at Bear Springs and Upper Red Rock with slopes of 0.16 and 0.19 in/yr, respectively. The precipitation totals for WY 2017 were the largest on record for all sites except for Upper Bent Canyon Meteorological Station near Delhi, CO.
Streamflow was calculated at 18 sites on the AGFC and 7 sites on the PCMS in at least 1 of WYs 2016–18. At AGFC, mean annual (or seasonal) streamflow in WYs 2016–18 was less than the long-term mean at 7 sites and greater than the long-term mean at 3 sites. There were statistically significant downward trends in mean annual or seasonal streamflow at Womack Ditch from Little Fountain Creek near Fort Carson, CO, and Ripley Ditch from Little Fountain Creek at Fort Carson, CO, with slopes of −0.036 and −0.028 cubic feet per second per year (ft3/s/y), respectively; and a significant upward trend in streamflow at Turkey Creek West Seepage below Teller Reservoir near Stone City, CO, with a slope of less than 0.001 ft3/s/y. Unlike for precipitation, the mean annual or seasonal streamflow for WY 2017 was not in the top 3 for any of the 12 sites with measured flow.
At the PCMS, mean annual (or seasonal) streamflow was less than the long-term mean streamflow in WYs 2016–18 at the Taylor Arroyo below Rock Crossing near Thatcher, CO, and Bent Canyon Creek at Mouth near Timpas, CO, sites; and in WYs 2016 and 2018 at the Purgatoire River near Thatcher, CO (Purgatoire Thatcher), and Purgatoire River at Rock Crossing near Timpas, CO (Purgatoire Rock Crossing). There were no statistically significant trends in mean annual (or seasonal) streamflow at sites on the PCMS, and unlike for precipitation, the mean streamflow for WY 2017 was not in the top three for any sites except Purgatoire Rock Crossing. In WYs 2016–18, streamflow from sites on the AGFC and PCMS represented only a small fraction of streamflow in Fountain Creek or the Purgatoire River, and changes in streamflow that resulted from military maneuvers on the AGFC and PCMS were not likely to be detected in the downstream receiving waters.
Suspended-sediment concentrations, loads, and yields for WYs 2016–18, were analyzed at two sites on the AGFC and five sites on the PCMS. On the AGFC, mean seasonal suspended-sediment concentrations ranged from 3.10 to 155 milligrams per liter (mg/L), mean seasonal suspended-sediment loads ranged from 0.04 to 27.1 tons per day (t/d), and seasonal suspended-sediment yields ranged from 0.28 to 216 tons per season per square mile (t/s/mi2). Suspended-sediment yields at the two AGFC sites in WYs 2016–18 were all less than the long-term means. On the PCMS, mean seasonal suspended-sediment concentrations (at sites with some streamflow during a WY) ranged from 1.12 to 41.8 mg/L, mean suspended-sediment loads ranged from 0.01 to 13.1 t/d, and seasonal suspended-sediment yields ranged from 0.06 to 57.4 t/s/mi2. Suspended-sediment yields at the five PCMS sites in WYs 2016–18 were all less than the long-term means. In WYs 2016–18, mean daily suspended-sediment loads at Little Fountain were 1.3, 2.5, and 7.6 percent, respectively, of the mean daily suspended-sediment load at Fountain Creek at Security, Colorado. Likewise, the total of mean daily suspended-sediment loads from the five tributary sites to the Purgatoire River in WYs 2016–18 were about 0.25, 0.17, and 3.2 percent, respectively, of the historical mean daily suspended-sediment load at Purgatoire Thatcher.
Spearman’s rank correlation coefficient was used to evaluate the strength and form of the relations between daily total precipitation and daily mean streamflow and between daily mean streamflow and suspended-sediment concentration and load for WYs 2016–18. For the sites on the AGFC and PCMS, there were weak or statistically insignificant positive correlations between precipitation and streamflow at nearby streamgauges, but strong statistically significant positive correlations between streamflow and suspended-sediment concentration and load. The ephemeral nature of the streams, quantity and timing of precipitation, air temperature, seasonal soil-moisture deficits, and effective runoff detention in erosion-control ponds could all contribute to inconsistent conversion of precipitation to streamflow.
Water-quality data were analyzed for as many as 43 parameters from 9 samples collected from 3 sites on the AGFC and from 37 samples collected from 4 sites on PCMS during WYs 2016–18. The concentrations of selected water-quality parameters were compared to regulatory standards for aquatic life from the Colorado Department of Public Health and Environment (CDPHE) or aquatic-life criteria from the U.S. Environmental Protection Agency (EPA). There is at least 1 CDPHE standard or EPA criterion for 30 of the 43 water-quality parameters.
For all samples from both the AGFC and the PCMS in WYs 2016–18, the concentrations of most water-quality parameters were compliant with the associated standards or criteria. However, there were some exceedances of standards or criteria: 11 samples exceeded the CDPHE recreational class standard for Escherichia coli concentration, 9 samples exceeded the CDPHE chronic unfiltered phosphorus aquatic-life standard, 36 samples exceeded the CDPHE chronic sulfate aquatic-life standard, 5 samples exceeded the EPA criterion for selenium, 7 samples exceeded the EPA criterion for aluminum, 2 samples exceeded the CDPHE chronic standard for iron, and 15 samples exceeded the CDPHE chronic standard for manganese.
Identifying potential effects of military training on water quality in adjacent streams on the AGFC and PCMS is difficult due to the ephemeral nature of streamflow, limited number of sampling locations and samples, and limited access to the study areas. At the PCMS, pairs of water-quality samples were collected in March and May 2017 before and after an April–May 2017 military training event. At the Purgatoire Rock Crossing site, streamflow at the time of the May sample was approximately 35 times larger than streamflow for the March sample. The absolute percent differences of concentrations for 27 parameters ranged from −71.7 to 183 percent, and 7 parameters had increases in concentration whereas 22 parameters had no change or decreases in concentrations. The absolute percent differences of loads for 24 parameters ranged from 141 to 198 percent. The generally lower concentrations and higher loads were expected given the higher streamflows at the time of collection of the May compared to the March samples.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225018","collaboration":"Prepared in cooperation with the U.S. Department of the Army","usgsCitation":"Battaglin, W.A., and Kisfalusi, Z.D., 2022, Characterization of and relations among precipitation, streamflow, suspended-sediment, and water-quality data at the U.S. Army Garrison Fort Carson and Piñon Canyon Maneuver Site, Colorado, water years 2016–18: U.S. Geological Survey Scientific Investigations Report 2022–5018, 94 p., https://doi.org/10.3133/sir20225018.","productDescription":"Report: ix, 94 p.; Database; Data Release","onlineOnly":"Y","ipdsId":"IP-115539","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":400092,"rank":4,"type":{"id":9,"text":"Database"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System—","linkHelpText":"USGS water data for the Nation: U.S. Geological 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U.S. Geological Survey
Box 25046, MS-415
Denver, CO 80225
Science has played a mixed role in guiding conservation and sustainability-oriented decision-making by individuals, policymakers, institutions, and governments. Not all science-based conservation and sustainability initiatives that address issues facing humanity and ecosystems and global problems have gained public support. Conservation decisions and policy prescriptions are and may be based on perceptions about and experiences with the environment, local land use, and ecosystems that may not align with or be grounded in science or evidence from experts in the field. Values, beliefs, and perceptions associated with nature play a critical role in how individuals view biodiversity conservation, sustainability, and natural resource management. This study first examines the gap between experts (scientists and other field experts) and the public (farmers and non-farmers) about the state of water and land resources, wildlife and associated habitats, and aquatic biodiversity in the Smoky Hill River Watershed in western Kansas. Second, the study examines the role that values and beliefs play in shaping environmental perceptions for farmers and non-farmers. Analysis confirms that a gap between experts and farmers/non-farmers does exist, especially with respect to the state of the Ogallala Aquifer, playas, rivers and streams, lakes and reservoirs, native grasslands, wildlife habitats, farmland, native fish populations, and wildlife species. Ordered-logistic regression analyses, meanwhile, indicate that farmer and non-farmer perceptions about the state of the local environment are influenced by traditional and self-interested values, as well as environmental values and beliefs, but less so by religiosity and political ideology. Despite broad takeaways, results exhibited heterogeneity across the farmer and non-farmer subpopulations. If environmental professionals cannot align ecological data, stakeholders’ values/perceptions, and policies, then the existing body of technical research and management on sustainability in natural and social sciences may be of little value.
Marbled murrelets (Brachyramphus marmoratus) have been listed as “endangered” by the State of California and “threatened” by the U.S. Fish and Wildlife Service since 1992 in California, Oregon, and Washington. Information regarding marbled murrelet abundance, distribution, population trends, and habitat associations is critical for risk assessment, effective management, evaluation of conservation efficacy, and ultimately, to meet federal- and state-mandated recovery efforts for this species. During June–August 2020 and 2021, the U.S. Geological Survey Western Ecological Research Center continued previously established, long-term (1999–present), at-sea surveys to estimate abundance and productivity of marbled murrelets in U.S. Fish and Wildlife Service Conservation Zone 6 (San Francisco Bay to Point Sur in central California). The abundance estimated for the entire study area was 470 birds (95-percent confidence interval, 313–707 birds) in 2020 and 402 birds (95-percent confidence interval, 219–737 birds) in 2021. Estimated abundances for both years are comparable with most prior years of study. We estimated reproductive productivity (calculated as the hatch-year to after-hatch-year ratio) after date-correcting hatch-year and after-hatch-year counts to account for birds expected to be absent from the water while inland at nests. The date-corrected juvenile ratio was 0.018±0.011 standard error in 2020 and 0.041±0.024 standard error in 2021. We updated a comprehensive database of all Zone 6 marbled murrelet survey data since 1999 with 2020–21 data to allow scientists and managers to evaluate established survey methods and assess trends in abundance and productivity estimates.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/dr1157","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","programNote":"Ecosystems Mission Area—Species Management Research Program","usgsCitation":"Felis, J.J., Adams, J., Horton, C.A., Kelsey, E.C., and White, L.M., 2022, Abundance and productivity of Marbled Murrelets (Brachyramphus marmoratus) off central California during the 2020 and 2021 breeding seasons: U.S. Geological Survey Data Report 1157, 12 p., https://doi.org/10.3133/dr1157.","productDescription":"Report: vi, 12 p.; Data Release","numberOfPages":"12","onlineOnly":"Y","ipdsId":"IP-134849","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":400463,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/dr/1157/dr1157.pdf","text":"Report","size":"6 MB"},{"id":400464,"rank":2,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/dr/1157/images"},{"id":400465,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/dr/1157/dr1157.xml"},{"id":400466,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F75B01RW","text":"Annual marbled murrelet abundance and productivity surveys off central California (Zone 6), 1999–2021","description":"Felis, J.J., Adams, J., Peery, M.Z., Henry, R.W., Henkel, L.A., Becker, B.H., and Halbert, P., 2022, Annual marbled murrelet abundance and productivity surveys off central California (Zone 6), 1999–2021: U.S. Geological Survey data release, https://doi.org/10.5066/F75B01RW."},{"id":400473,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/dr/1157/covrthb.jpg"},{"id":400472,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/dr1157/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"DR 1157"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.59918212890626,\n 36.87962060502676\n ],\n [\n -121.717529296875,\n 36.87962060502676\n ],\n [\n -121.717529296875,\n 37.65773212628272\n ],\n [\n -122.59918212890626,\n 37.65773212628272\n ],\n [\n -122.59918212890626,\n 36.87962060502676\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
A cooperative study led by the U.S. Geological Survey and Wake County Environmental Services was initiated to characterize the fractured-rock aquifer system and assess the sustainability of groundwater resources in and around Wake County. This report contributes to the development of a comprehensive groundwater budget for the study area, thereby helping to enable resource managers to make sound and sustainable water-supply and water-use decisions.
Construction information was used to analyze the well depth, casing depth, and reported well yield of more than 7,500 inventoried wells. The median well depth and casing depth were 265 feet (ft) below land surface (bls) and 68 ft bls, respectively, and the median well yield was 10 gallons per minute. Generally, well yield increased with depth to around 200 ft bls and then began to decrease with depth within the fractured-rock aquifer.
Borehole geophysical logging methods were used to characterize the fractured-rock aquifer by mapping the orientation of geologic structures within the subsurface. Structure measurements were made on resulting log data and mapped to observed general spatial trends within the regional groundwater system and more distinct hydrogeologic units. Many of the fractures observed within the borehole logs are steeply dipping across Wake County, although open fractures with shallow dip angles were also observed in most rock classes. Regional geologic structural trends were observed in proximity to the Jonesboro Fault.
Potential groundwater recharge in the study area was estimated using a Soil-Water-Balance (SWB) model, as well as using base flow hydrograph separation. The SWB model calculated net infiltration below the root zone for 1981 through 2019 for a 5,402-square-mile area that extends to the counties surrounding Wake County. The mean annual net infiltration rate for the 39-year period was about 8.6 inches per year for the study area. The mean annual net infiltration results from the SWB model were comparable to annual base flow estimates using the PART hydrograph-separation method at six U.S. Geological Survey streamgages within the study area. Mean annual base flow for all six drainage basins was near 7.5 inches per year and estimates ranged from 2.9 to 8.9 inches. Comparisons of mean annual potential recharge from the SWB model and base flow estimates were generally within 2 inches, except during high flows for most of the drainage basins in the study area.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225041","collaboration":"Prepared in cooperation with Wake County Environmental Services","usgsCitation":"Antolino, D.J., and Gurley, L.N., 2022, Assessment of well yield, dominant fractures, and groundwater recharge in Wake County, North Carolina (ver. 1.1, May 2022) : U.S. Geological Survey Scientific Investigations Report 2022–5041, 35 p., https://doi.org/10.3133/sir20225041.","productDescription":"Report: viii, 35 p.; 3 Data Releases; Database","numberOfPages":"35","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-115494","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":399581,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9C2J23X","text":"USGS data release","linkHelpText":"Groundwater well yield in Wake County, North Carolina"},{"id":435853,"rank":11,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MO793B","text":"USGS data release","linkHelpText":"Soil-Water-Balance (SWB) model data sets for the Greater Wake County area, North Carolina, 1981 - 2070"},{"id":399596,"rank":9,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20225041/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":399578,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5041/images/"},{"id":399575,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5041/coverthb2.jpg"},{"id":400310,"rank":10,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2022/5041/versionHist.txt","size":"508 B","linkFileType":{"id":2,"text":"txt"}},{"id":399582,"rank":8,"type":{"id":9,"text":"Database"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the Nation"},{"id":399580,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96HHBIE","text":"USGS data release","linkHelpText":"National Land Cover Database (NLCD) 2016 products (ver. 2.0, July 2020)"},{"id":399579,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95XKK5V","text":"USGS data release","linkHelpText":"Soil-Water-Balance (SWB) model datasets for the Greater Wake County area, North Carolina, 1981–2019"},{"id":399577,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5041/sir20225041.XML"},{"id":399576,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5041/sir20225041.pdf","text":"Report","size":"13.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5041"}],"country":"United States","state":"North Carolina","county":"Wake County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-78.5465,36.0218],[-78.4307,35.9795],[-78.3969,35.9387],[-78.3567,35.9318],[-78.351,35.909],[-78.3385,35.9052],[-78.3347,35.8997],[-78.3302,35.896],[-78.3245,35.896],[-78.3177,35.8963],[-78.3137,35.8976],[-78.3081,35.8935],[-78.2948,35.8797],[-78.292,35.8792],[-78.2893,35.8741],[-78.2859,35.8713],[-78.2831,35.8681],[-78.2782,35.8631],[-78.2749,35.8567],[-78.2756,35.8494],[-78.2707,35.843],[-78.2657,35.8361],[-78.2652,35.8325],[-78.2613,35.8315],[-78.2591,35.826],[-78.2599,35.8183],[-78.3731,35.7523],[-78.4635,35.7072],[-78.4686,35.7087],[-78.4709,35.7078],[-78.4732,35.7046],[-78.4778,35.7011],[-78.5716,35.6255],[-78.708,35.5191],[-78.9196,35.5857],[-78.9956,35.6104],[-78.9796,35.6656],[-78.9439,35.7515],[-78.9421,35.756],[-78.9403,35.7615],[-78.9337,35.7859],[-78.9191,35.8216],[-78.9096,35.8506],[-78.9076,35.8678],[-78.89,35.8676],[-78.8298,35.8689],[-78.8056,35.9281],[-78.7609,35.9176],[-78.751,35.9307],[-78.7372,35.941],[-78.714,35.9729],[-78.7009,36.0068],[-78.6985,36.0131],[-78.7048,36.0091],[-78.7077,36.0087],[-78.7076,36.0132],[-78.7052,36.0223],[-78.7085,36.0287],[-78.7102,36.0287],[-78.713,36.0278],[-78.7164,36.0283],[-78.7232,36.0334],[-78.726,36.0343],[-78.7272,36.0334],[-78.7278,36.0289],[-78.7324,36.0267],[-78.7353,36.0199],[-78.7422,36.0209],[-78.75,36.026],[-78.7551,36.0283],[-78.7545,36.0301],[-78.7511,36.0323],[-78.7499,36.035],[-78.747,36.0395],[-78.7492,36.0427],[-78.7503,36.0468],[-78.7519,36.0491],[-78.7564,36.0532],[-78.7498,36.0718],[-78.7088,36.0768],[-78.6895,36.0752],[-78.5922,36.0378],[-78.5465,36.0218]]]},\"properties\":{\"name\":\"Wake\",\"state\":\"NC\"}}]}","edition":"Version 1.1: May 2022; Version 1.0: April 2022","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
1770 Corporate Drive
Norcross, GA 30093
Radium (Ra) is a geogenic radioactive contaminant that frequently occurs at elevated levels in the Midwestern Cambrian-Ordovician aquifer system (MCOAS). Geochemical indicators (e.g., redox conditions or total dissolved solids) can broadly characterize conditions associated with elevated Ra levels in groundwater, but do not consistently correlate to elevated Ra within specific stratigraphic horizons. A coupled geochemical and isotopic study of groundwater and aquifer solids for major and trace elements, Ra, and uranium (U) at discrete intervals in the MCOAS was used to elucidate processes that may be responsible for this disconnect, via analysis of groundwater as well as extracted and digested solid aquifer samples. We find that the potential for Ra mobilization varies by stratigraphic unit, as observed by whole-rock 226Ra/238U (dis)equilibrium. Overall, the examined aqueous geochemical characteristics (e.g., redox conditions, total dissolved solids) do not explain Ra concentrations within the system, suggesting that alternative factors, like solid-phase associations or the extent of alpha recoil damage, may be more important. A relation between aqueous 87Sr/86Sr and 226Ra suggests that minerals with radiogenic 87Sr/86Sr are more likely to release 226Ra to the aqueous system. Overall, the release of U and Ra due to water-rock interaction varies with discrete stratigraphy, depending on aqueous geochemistry and available mineral associations. Due to complex Ra-rock interactions and the heterogeneous geology of the MCOAS, aqueous geochemistry does not fully predict the mobilization and concentration of Ra in groundwater. As sources and sinks of Ra within the MCOAS vary across stratigraphy, knowledge of aqueous geochemistry, available solid-phase associations, and nuclide leachability all are important to consider for understanding elevated Ra occurrence in aquifer systems.
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2022 - Age of the late Holocene Bonneville landslide and submerged forest of the Columbia River Gorge, Oregon and Washington, USA, by radiocarbon dating","interactions":[],"lastModifiedDate":"2023-09-27T12:16:30.658314","indexId":"70248943","displayToPublicDate":"2022-05-10T07:13:52","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3218,"text":"Quaternary Research","active":true,"publicationSubtype":{"id":10}},"title":"Age of the late Holocene Bonneville landslide and submerged forest of the Columbia River Gorge, Oregon and Washington, USA, by radiocarbon dating","docAbstract":"The late Holocene Bonneville landslide, a 15.5 km2 rockslide-debris avalanche, descended 1000 m from the north side of the Columbia River Gorge and dammed the Columbia River where it bisects the Cascade Range of Oregon and Washington, USA. The landslide, inundation, and overtopping created persistent geomorphic, ecologic, and cultural consequences to the river corridor, reported by Indigenous narratives and explorer accounts, as well as scientists and engineers. From new dendrochronology and radiocarbon dating of three trees killed by the landslide, one entrained and buried by the landslide and two killed by rising water in the impounded Columbia River upstream of the blockage, we find (1) the two drowned trees and the buried tree died the same year, and (2) the age of tree death, and hence the landslide (determined by combined results of nine radiocarbon analyses of samples from the three trees), falls within AD 1421–1455 (3σ confidence interval). This result provides temporal context for the tremendous physical, ecological, and cultural effects of the landslide, as well as possible triggering mechanisms. The age precludes the last Cascadia Subduction Zone earthquake of AD 1700 as a landslide trigger, but not earlier subduction zone or local crustal earthquakes.
Climate change can act to facilitate or inhibit invasions of non-native species. Here, we address the influence of climate change on control of non-native common carp (hereafter, carp), a species recognized as one of the “world's worst” invaders across the globe. Control of this species is exceedingly difficult, as it exhibits rapid population growth and compensatory density dependence. In many locations where carp have invaded, however, climate change is altering hydrologic regimes and may influence population demography and efficacy of human control efforts. To further evaluate these processes, we employed a modified version of an age-based population model (CarpMOD), to investigate how hydrologic variability (change in lake area) influences carp population dynamics and control efforts in Malheur Lake, southeastern Oregon, USA. We explored how changes in lake area influence carp populations under three control scenarios: (1) no carp removal, (2) carp removal during low water years, and (3) carp removal during all years. Lake area fluctuations strongly influenced carp populations and the efficacy of carp control. Modeled carp biomass peaked when the lake transitioned from high-to-low levels, and carp biomass declined when lake area transitioned from low-to-high. Removing carp during low water periods—when fish were concentrated into a smaller area—reduced carp populations almost as much as removing carp every year. Furthermore, the effectiveness of control efforts increased with the prevalence and severity of low lake conditions (longer durations of very low lake area). These simulations suggest that a drier climate may naturally decrease carp populations and make them easier to control. However, drier conditions may also negatively affect aquatic ecosystems and potentially have a greater impact than non-native species themselves.
Debris flows pose a significant hazard to communities in mountainous areas, and there is a continued need for methods to delineate hazard zones associated with debris-flow inundation. In certain situations, such as scenarios following wildfire, where there could be an abrupt increase in the likelihood and size of debris flows that necessitates a rapid hazard assessment, the computational demands of inundation models play a role in their utility. The inability to efficiently determine the downstream effects of anticipated debris-flow events remains a critical gap in our ability to understand, mitigate, and assess debris-flow hazards. To better understand the downstream effects of debris flows, we introduce a computationally efficient, reduced-complexity inundation model, which we refer to as the Progressive Debris-Flow routing and inundation model (ProDF). We calibrate ProDF against mapped inundation from five watersheds near Montecito, CA, that produced debris flows shortly after the 2017 Thomas Fire. ProDF reproduced 70% of mapped deposits across a 40 km2 study area. While this study focuses on a series of post-wildfire debris flows, ProDF is not limited to simulating debris-flow inundation following wildfire and could be applied to any scenario where it is possible to estimate a debris-flow volume. However, given its ability to reproduce mapped debris-flow deposits downstream of the 2017 Thomas Fire burn scar, and the modest run time associated with a simulation over this 40 km2 study area, results suggest ProDF may be particularly promising for post-wildfire hazard assessment applications.
In the United States, greater attention has been given to developing water supplies and quantifying available waters than determining who uses water, how much they withdraw and consume, and how and where water use occurs. As water supplies are stressed due to an increasingly variable climate, changing land-use, and growing water needs, greater consideration of the demand side of the water balance equation is essential. Data about the spatial and temporal aspects of water use for different purposes are now critical to long-term water supply planning and resource management. We detail the current state of water-use data, the major stakeholders involved in their collection and applications, and the challenges in obtaining high-quality nationally consistent data applicable to a range of scales and purposes. Opportunities to improve access, use, and sharing of water-use data are outlined. We cast a vision for a world-class national water-use data product that is accessible, timely, and spatially detailed. Our vision will leverage the strengths of existing local, state, and federal agencies to facilitate rapid and informed decision-making, modeling, and science for water resources. To inform future decision-making regarding water supplies and uses, we must coordinate efforts to substantially improve our capacity to collect, model, and disseminate water-use data.
Director, Virginia and West Virginia Water Science Center
U.S. Geological Survey
1730 East Parham Road
Richmond, VA 23228