Atlantic salmon (Salmo salar) return to rivers in spring for an energetically costly upstream migration for spawning. These fish are often delayed in the lower river below dams, subjecting them to warmer waters than occur in upstream sections of river, that may increase metabolic costs. We sought to quantify the energetic cost of dam-mediated delays in migrating adults in the Penobscot and Kennebec rivers, ME. We radio-tagged fish at the lower most dams, released them downstream (18 and 14 km), and tracked their movements back upstream. We used a Distell Fish Fatmeter as a noninvasive measurement of full-body energy at tagging and then again after re-ascending the fish-way at the dams. We found that adults (n = 99) experienced average delays of 16–23 days at dams, losing 11%–22% of initial fat reserves. Using linear regressions, we showed thermal experience as a strong predictor of fat loss. Delay time was also a contributing factor. Extensive delays at dams expose migrating Atlantic salmon to warmer temperatures and increase the depletion rate of energy reserves required for spawning and post-spawn survival.
","language":"English","publisher":"Canadian Science Publishing","doi":"10.1139/cjfas-2022-0008","usgsCitation":"Rubenstein, S., Peterson, E., Christman, P., and Zydlewski, J.D., 2022, Adult Atlantic salmon (Salmo salar) delayed below dams rapidly deplete energy stores: Canadian Journal of Fisheries and Aquatic Sciences, v. 80, no. 1, p. 170-182, https://doi.org/10.1139/cjfas-2022-0008.","productDescription":"13 p.","startPage":"170","endPage":"182","ipdsId":"IP-137191","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":481000,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maine","otherGeospatial":"Lockwood Dam, Milford Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -70.36478332126005,\n 44.873642207371006\n ],\n [\n -70.36478332126005,\n 44.06312690380926\n ],\n [\n -67.77061776241788,\n 44.06312690380926\n ],\n [\n -67.77061776241788,\n 44.873642207371006\n ],\n [\n -70.36478332126005,\n 44.873642207371006\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"80","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Rubenstein, Sarah R.","contributorId":349051,"corporation":false,"usgs":false,"family":"Rubenstein","given":"Sarah R.","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":923956,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peterson, Erin","contributorId":349052,"corporation":false,"usgs":false,"family":"Peterson","given":"Erin","affiliations":[{"id":7063,"text":"University of Maine","active":true,"usgs":false}],"preferred":false,"id":923957,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Christman, Paul","contributorId":349053,"corporation":false,"usgs":false,"family":"Christman","given":"Paul","affiliations":[{"id":68617,"text":"Maine Department of Marine Resources","active":true,"usgs":false}],"preferred":false,"id":923958,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zydlewski, Joseph D. 0000-0002-2255-2303 jzydlewski@usgs.gov","orcid":"https://orcid.org/0000-0002-2255-2303","contributorId":2004,"corporation":false,"usgs":true,"family":"Zydlewski","given":"Joseph","email":"jzydlewski@usgs.gov","middleInitial":"D.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":923959,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70238761,"text":"sir20225110 - 2022 - Water quality of sand and gravel aquifers in McHenry County, Illinois, 2020 and comparisons to conditions in 2010","interactions":[],"lastModifiedDate":"2022-12-09T20:49:58.848528","indexId":"sir20225110","displayToPublicDate":"2022-12-07T14:27:26","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2022-5110","displayTitle":"Water Quality of Sand and Gravel Aquifers in McHenry County, Illinois, 2020 and Comparisons to Conditions in 2010","title":"Water quality of sand and gravel aquifers in McHenry County, Illinois, 2020 and comparisons to conditions in 2010","docAbstract":"McHenry County, Illinois, obtains most of its drinking water from shallow sand and gravel aquifers (groundwater). To evaluate this groundwater resource, the U.S. Geological Survey, in cooperation with McHenry County, Illinois, collected water-quality samples from 41 of 42 monitoring wells in the McHenry County Groundwater Monitoring Network and 4 monitoring wells from the U.S. Geological Survey National Water-Quality Assessment Project. Additionally, a subset of 12 monitoring wells was sampled and analyzed for pharmaceuticals and wastewater indicator compounds (WICs), collectively referred to as “contaminants of emerging concern” (CECs). Results from this 2020 study were compared to the 2010 results to assess changes in groundwater quality. Statistical analyses and chloride-bromide ratio analyses also were completed to assess changes in water quality.
Health-based benchmarks were exceeded for arsenic (about 24 percent; 11 of 45 monitoring wells), sodium (40 percent, 18 of 45), and manganese (about 2 percent, 1 of 45). Aesthetically based benchmarks were exceeded for dissolved solids (about 29 percent, 13 of 45), chloride (about 4 percent, 2 of 45), iron (about 87 percent, 39 of 45), and manganese (about 29 percent, 13 of 45). CECs were detected at low or estimated concentrations in 8 of the 12 (about 67 percent) monitoring wells analyzed.
In addition to sampling the groundwater monitoring wells, three surface-water-quality monitoring sites also were sampled and analyzed for pharmaceuticals and WICs to provide a preliminary assessment of the presence of CECs in the surface waters. CECs were detected in all three of the surface-water-quality monitoring samples collected, and WICs were more prevalent and more frequently detected than pharmaceutical compounds. These results provided a cursory understanding of the presence of CECs in surface waters and do not constitute a robust analysis of sources, seasonality, range of concentrations, persistence, or effects.
The 2020 groundwater-quality results had measurements of field properties, and concentrations of major ions, trace metals, and nutrients that were consistent with 2010 results with statistically significant increases for calcium, magnesium, and silica, and decreases for aluminum, ammonia, arsenic, barium, bromide, calcium, molybdenum, phosphate, specific conductance, sulfate, and dissolved solids. Increases generally were detected in the intermediate and deep parts of the sand and gravel aquifer, and decreases were detected in the shallow parts of the sand and gravel aquifer. The mixed distribution of increases and decreases among the various constituents and aquifer-depth groups could be reflecting dissolution and mobility of some of the redox sensitive constituents and dilution of some constituents in the shallow aquifer depths. These changes may be attributed to a combination of stable population of the past decade (2010–20), land-use management practices, and the recent wet years of 2017 through 2019 causing a dilution of the major ions in the shallow parts of the aquifer.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225110","collaboration":"Prepared in cooperation with McHenry County, Illinois","usgsCitation":"Gahala, A.M., Gruhn, L.R., Murphy, J.C., and Matson, L.A., 2022, Water quality of sand and gravel aquifers in McHenry County, Illinois, 2020 and comparisons to conditions in 2010: U.S. Geological Survey Scientific Investigations Report 2022–5110, 53 p., https://doi.org/10.3133/sir20225110.","productDescription":"Report: viii, 53 p.; Data Release; Dataset","numberOfPages":"66","onlineOnly":"Y","ipdsId":"IP-137120","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":435599,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9W1TPNF","text":"USGS data release","linkHelpText":"Reconnaissance of Per- and Polyfluoroalkyl Substances (PFAS) in Selected Groundwater and Surface Water Sites in McHenry County, Illinois, 2020"},{"id":410159,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5110/coverthb.jpg"},{"id":410160,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5110/sir20225110.pdf","text":"Report","size":"4.21 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022–5110"},{"id":410161,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5110/sir20225110.XML"},{"id":410162,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5110/images"},{"id":410163,"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":410164,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RBXV53","text":"USGS data release","linkHelpText":"Quality-assurance and quality-control data for discrete water-quality samples collected in McHenry County, Illinois, 2020"},{"id":410218,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20225110/full","text":"Report","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Illinois","county":"McHenry County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-88.3016,42.4979],[-88.1971,42.4981],[-88.1979,42.4562],[-88.1974,42.4167],[-88.1966,42.3286],[-88.1994,42.2432],[-88.1992,42.1555],[-88.2382,42.155],[-88.3539,42.1547],[-88.4703,42.1552],[-88.5891,42.1556],[-88.7061,42.1564],[-88.7057,42.2418],[-88.7041,42.329],[-88.705,42.4167],[-88.7059,42.4972],[-88.6737,42.4977],[-88.6288,42.4985],[-88.5047,42.4981],[-88.4099,42.4977],[-88.3016,42.4979]]]},\"properties\":{\"name\":\"McHenry\",\"state\":\"IL\"}}]}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
405 North Goodwin
Urbana, IL 61801
The McMurdo Dry Valleys, Antarctica, are a polar desert populated with numerous closed-watershed, perennially ice-covered lakes primarily fed by glacial melt. Lake levels have varied by as much as 8 m since 1972 and are currently rising after a decade of decreasing. Precipitation falls as snow, so lake hydrology is dominated by energy available to melt glacier ice and to sublimate lake ice. To understand the energy and hydrologic controls on lake level changes and to explain the variability between neighboring lakes, only a few kilometers apart, we model the hydrology for the three largest lakes in Taylor Valley. We apply a physically based hydrological model that includes a surface energy balance model to estimate glacial melt and lake sublimation to constrain mass fluxes to and from the lakes. Results show that lake levels are very sensitive to small changes in glacier albedo, air temperature, and wind speed. We were able to balance the hydrologic budget in two watersheds using meltwater inflow and sublimation loss from the ice-covered lake alone. A third watershed, closest to the coast, required additional inflow beyond model uncertainties. We hypothesize a shallow groundwater system within the active layer, fed by dispersed snow patches, contributes 23% of the inflow to this watershed. The lakes are out of equilibrium with the current climate. If the climate of our study period (1996-2013) persists into the future, the lakes will reach equilibrium starting in 2300, with levels 2-17 m higher, depending on the lake, relative to the 2020 level.
Skipped spawning, or variation in spawning periodicity, occurs in many annual spawning fish species and is an important consideration for population management. We assessed plasma sex steroid concentrations and measured gonad size and ovarian follicle diameter as metrics to nonlethally identify mass ovarian follicular atresia, which may contribute to skipped spawning in Burbot Lota lota. We maintained wild fish in captivity and exposed them to increasing water temperatures during a 3-wk period before the spawning season to induce mass ovarian follicular atresia. We collected ovarian follicles, blood plasma, and gonadal sonograms from fish weekly between January 28, 2018, and March 25, 2018. We histologically analyzed ovarian follicles to confirm stage of maturity. We measured concentrations of plasma sex steroids testosterone (T) and estradiol-17β (E2) by radioimmunoassay. We measured gonad diameter and circumference by ultrasonography and ovarian follicle diameter by image analysis. Mean plasma T concentration decreased from 8.94 ng/mL during late vitellogenesis to 1.83 ng/mL during atresia, suggesting that plasma T concentrations may be used to identify mass ovarian follicular atresia. We do not recommend using plasma E2 concentrations to identify mass ovarian follicular atresia because E2 concentrations rapidly decreased during the completion of vitellogenesis and the initiation of atresia in Burbot; therefore, plasma E2 may not accurately identify mass ovarian follicular atresia. Mean gonad diameter measured by ultrasonography decreased from 4.05 cm during late vitellogenesis to 3.65 cm during atresia. Mean diameter of ovarian follicles decreased during the final week of the study, suggesting that ovarian follicle diameter may be used to identify advanced mass ovarian follicular atresia. The nonlethal tools assessed—plasma sex steroid concentrations, ultrasonography, and ovarian follicle diameter—enable fisheries biologists to determine the occurrence and frequency of mass ovarian follicular atresia among Burbot in Lake Roosevelt and may be applied to other Burbot populations.
This study focused on optimizing the placement of shortwave infrared (SWIR) bands for pixel-level estimation of fractional crop residue cover (fR) for the upcoming Landsat Next mission. We applied an iterative wavelength shift approach to a database of crop residue field spectra collected in Beltsville, Maryland, USA (n = 916) and computed generalized two- and three-band spectral indices for all wavelength combinations between 2000 and 2350 nm, then used these indices to model field-measured fR. A subset of the full dataset with a Normalized Difference Vegetation Index (NDVI) < 0.3 threshold (n = 643) was generated to evaluate green vegetation impacts on fR estimation. For the two-band wavelength shift analyses applied to the NDVI < 0.3 dataset, a generalized normalized difference using 2226 nm and 2263 nm bands produced the top fR estimation performance (R2 = 0.8222; RMSE = 0.1296). These findings were similar to the established two-band Shortwave Infrared Normalized Difference Residue Index (SINDRI) (R2 = 0.8145; RMSE = 0.1324). Performance of the two-band generalized normalized difference and SINDRI decreased for the full-NDVI dataset (R2 = 0.5865 and 0.4144, respectively). For the three-band wavelength shift analyses applied to the NDVI < 0.3 dataset, a generalized ratio-based index with a 2031–2085–2216 nm band combination, closely matching established Cellulose Absorption Index (CAI) bands, was top performing (R2 = 0.8397; RMSE = 0.1231). Three-band indices with CAI-type wavelengths maintained top fR estimation performance for the full-NDVI dataset with a 2036–2111–2217 nm band combination (R2 = 0.7581; RMSE = 0.1548). The 2036–2111–2217 nm band combination was also top performing in fR estimation (R2 = 0.8690; RMSE = 0.0970) for an additional analysis assessing combined green vegetation cover and surface moisture effects. Our results indicate that a three-band configuration with band centers and wavelength tolerances of 2036 nm (±5 nm), 2097 nm (±14 nm), and 2214 (±11 nm) would optimize Landsat Next SWIR bands for fR estimation.
","language":"English","publisher":"MDPI","doi":"10.3390/rs14236128","usgsCitation":"Lamb, B.T., Dennison, P., Hively, W.D., Kokaly, R.F., Serbin, G., Wu, Z., Dabney, P.W., Masek, J.G., Campbell, M., and Daughtry, C.S., 2022, Optimizing Landsat Next shortwave infrared bands for crop residue characterization: Remote Sensing, v. 14, no. 23, 6128, 29 p., https://doi.org/10.3390/rs14236128.","productDescription":"6128, 29 p.","ipdsId":"IP-144753","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":445721,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs14236128","text":"Publisher Index Page"},{"id":410537,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","issue":"23","noUsgsAuthors":false,"publicationDate":"2022-12-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Lamb, Brian T. 0000-0001-7957-5488","orcid":"https://orcid.org/0000-0001-7957-5488","contributorId":291893,"corporation":false,"usgs":true,"family":"Lamb","given":"Brian","middleInitial":"T.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":859052,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dennison, Phillip 0000-0002-0241-1917","orcid":"https://orcid.org/0000-0002-0241-1917","contributorId":266031,"corporation":false,"usgs":false,"family":"Dennison","given":"Phillip","email":"","affiliations":[{"id":54865,"text":"Dept. Geography, Utah State University","active":true,"usgs":false}],"preferred":false,"id":859053,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hively, W. Dean 0000-0002-5383-8064","orcid":"https://orcid.org/0000-0002-5383-8064","contributorId":201565,"corporation":false,"usgs":true,"family":"Hively","given":"W.","email":"","middleInitial":"Dean","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":859054,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kokaly, Raymond F. 0000-0003-0276-7101","orcid":"https://orcid.org/0000-0003-0276-7101","contributorId":205165,"corporation":false,"usgs":true,"family":"Kokaly","given":"Raymond","email":"","middleInitial":"F.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":5078,"text":"Southwest Regional Director's Office","active":true,"usgs":true}],"preferred":true,"id":859055,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Serbin, Guy 0000-0001-9345-1772","orcid":"https://orcid.org/0000-0001-9345-1772","contributorId":266030,"corporation":false,"usgs":false,"family":"Serbin","given":"Guy","email":"","affiliations":[{"id":54864,"text":"EOAnalytics","active":true,"usgs":false}],"preferred":false,"id":859056,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wu, Zhuoting 0000-0001-7393-1832 zwu@usgs.gov","orcid":"https://orcid.org/0000-0001-7393-1832","contributorId":4953,"corporation":false,"usgs":true,"family":"Wu","given":"Zhuoting","email":"zwu@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":498,"text":"Office of Land Remote Sensing (Geography)","active":true,"usgs":true}],"preferred":true,"id":859057,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dabney, Philip W.","contributorId":214572,"corporation":false,"usgs":false,"family":"Dabney","given":"Philip","email":"","middleInitial":"W.","affiliations":[{"id":38788,"text":"NASA","active":true,"usgs":false}],"preferred":false,"id":859058,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Masek, Jeffery G.","contributorId":294418,"corporation":false,"usgs":false,"family":"Masek","given":"Jeffery","email":"","middleInitial":"G.","affiliations":[{"id":38788,"text":"NASA","active":true,"usgs":false}],"preferred":false,"id":859059,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Campbell, Michael","contributorId":299937,"corporation":false,"usgs":false,"family":"Campbell","given":"Michael","email":"","affiliations":[{"id":13252,"text":"University of Utah","active":true,"usgs":false}],"preferred":false,"id":859060,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Daughtry, Craig S. T.","contributorId":211093,"corporation":false,"usgs":false,"family":"Daughtry","given":"Craig","email":"","middleInitial":"S. T.","affiliations":[{"id":38179,"text":"USDA Agricultural Research Service, Hydrology and Remote Sensing Laboratory","active":true,"usgs":false}],"preferred":false,"id":859061,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70238667,"text":"ofr20221100 - 2022 - Verification of multiple phosphorus analyzers for use in surface-water applications","interactions":[],"lastModifiedDate":"2026-03-30T20:49:48.631242","indexId":"ofr20221100","displayToPublicDate":"2022-12-02T13:49:32","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":"2022-1100","displayTitle":"Verification of Multiple Phosphorus Analyzers for Use in Surface-Water Applications","title":"Verification of multiple phosphorus analyzers for use in surface-water applications","docAbstract":"The U.S. Geological Survey (USGS) completed a verification study of selected commercially available phosphorus analyzers for their applicability to scientific surface-water applications. In this study, the analyzers were the Hach EZ7800 TOPHO, Hach Phosphax sc, Sea-Bird Scientific HydroCycle-PO4, and the YSI Inc. Alyza IQ PO4. Verification tests included laboratory trials comparing analyzer results to known standards with several known concentrations of dissolved organic matter and waste production estimates. Field trials were completed at the Vermilion River near Danville, Illinois (U.S. Geological Survey station 03339000), where analyzer-measured concentrations were compared against discrete samples across a wide range of environmental conditions from November 2020 to August 2021. Data coverage was closely tracked for analyzer malfunctions and operator errors that caused missing data. Laboratory and field trials indicated that each analyzer is a viable option for scientific surface-water studies depending on environmental conditions. Because of the complexity of the analyzers, a substantial time investiture was required to get maximum data coverage including considerable site infrastructure investments and well-trained technicians. Data coverage was closely related to each analyzer’s ability to handle elevated turbidity levels.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221100","collaboration":"Prepared in cooperation with the Next Generation Water Observing System","programNote":"Groundwater and Streamflow Information Program","usgsCitation":"Peake, C.S., 2022, Verification of multiple phosphorus analyzers for use in surface-water applications: U.S. Geological Survey Open-File Report 2022–1100, 23 p., https://doi.org/10.3133/ofr20221100.","productDescription":"Report: viii, 23 p.; Dataset","numberOfPages":"36","onlineOnly":"Y","ipdsId":"IP-139337","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":410009,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221100/full","text":"Report"},{"id":409997,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1100/ofr20221100.XML"},{"id":409995,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1100/coverthb.jpg"},{"id":501839,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113882.htm","linkFileType":{"id":5,"text":"html"}},{"id":409998,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1100/images"},{"id":409996,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1100/ofr20221100.pdf","text":"Report","size":"1.42 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022–1100"},{"id":409999,"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"}],"country":"United States","state":"Illinois, Indiana","otherGeospatial":"Vermilion River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -87.41449158849616,\n 39.979211528524246\n ],\n [\n -87.41449158849616,\n 40.79889755055865\n ],\n [\n -88.38087805821512,\n 40.79889755055865\n ],\n [\n -88.38087805821512,\n 39.979211528524246\n ],\n [\n -87.41449158849616,\n 39.979211528524246\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
405 North Goodwin
Urbana, IL 61801
This study used the complete set of continuous water-quality (WQ) data and discrete measurements of total ammonia collected by the U.S. Geological Survey from 2005 to 2019 at the four core sites in Upper Klamath Lake, Oregon, to examine relations between variables and extreme conditions that may be harmful for endemic Lost River suckers (Deltistes luxatus) and shortnose suckers (Chasmistes brevirostris). Several graphical and tabular approaches were used to compare variables, sites, and years to better understand the factors contributing to and timing of extreme WQ in the lake. Extreme WQ thresholds were defined as the 1st or 99th percentiles of the daily average dataset of water temperature, pH, and dissolved oxygen (DO) concentration, and the weekly estimated un-ionized ammonia (NH3) from 2005 to 2019. Extreme WQ days were defined as those when at least 12 hours of measurements exceeded the extreme WQ threshold. The core site at Mid-Trench, which was also the deepest measurement site with a full-pool depth of 15 meters and at which water-quality sondes were deployed at the top and bottom of the water column, had the most extreme conditions of high water temperature, low DO, and high NH3. The upper sonde at Mid-Trench represented 40 percent of all days of extremely high water temperature (days with at least 12 hours exceeding 24.38 degrees Celsius) in the lake and 71 percent of all weekly estimates of extremely high NH3 (greater than 264 micrograms per liter) in the lake. The lower sonde at Mid-Trench represented 85 percent of all days of extremely low DO (days with at least 12 hours of DO concentrations less than 1.76 milligrams per liter) in the lake. In each of the study years, poor water quality at Mid-Trench, as represented by several metrics, lasted for multiple days. The shallowest site at the Williamson River outlet represented 54 percent of all days of extremely high pH (days with at least 12 hours of pH measurements exceeding 10.04) in the lake. The seasonality of extreme WQ during the summer sampling period (limited to June through September) was evaluated and most days of extremely high water temperature (83 percent) and extremely high pH (54 percent) occurred in July, whereas most days of extremely low DO (57 percent) and extremely high NH3 (57 percent) occurred in August. The years with the most days of extreme WQ accumulated for all variables (high water temperature, low DO, high pH, and high NH3) were 2012–15 and 2017, which all occurred in the latter half of the study period. The years with the fewest accumulated days of extreme WQ were 2010 and 2011.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221080","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Wherry, S.A., 2022, Summary of extreme water-quality conditions in Upper Klamath Lake, Oregon, 2005–19: U.S. Geological Survey Open-File Report 2022–1080, 29 p., https://doi.org/10.3133/ofr20221080.","productDescription":"vii, 29 p.","onlineOnly":"Y","ipdsId":"IP-128098","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":501831,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113883.htm","linkFileType":{"id":5,"text":"html"}},{"id":410005,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1080/ofr20221080.XML"},{"id":410002,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1080/ofr20221080.pdf","text":"Report","size":"6.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1080"},{"id":410001,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1080/coverthb.jpg"},{"id":410004,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1080/images"},{"id":410003,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/ofr20221080/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1080"}],"country":"United States","state":"Oregon","otherGeospatial":"Upper Klamath Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.11865576927013,\n 42.623699726465674\n ],\n [\n -122.11865576927013,\n 42.185824493728575\n ],\n [\n -121.73017939010751,\n 42.185824493728575\n ],\n [\n -121.73017939010751,\n 42.623699726465674\n ],\n [\n -122.11865576927013,\n 42.623699726465674\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
The Chesapeake Bay is a region along the eastern coast of the United States where sea-level rise is confounded with poorly resolved rates of land subsidence, thus new constraints on vertical land motions (VLM) in the region are warranted. In this paper, we provide a description of two campaign-style Global Positioning System (GPS) datasets, explain the methods used in data collection and validation, and present the experiment designed to quantify a new baseline of VLM in the Chesapeake Bay region of eastern North America. Data from GPS campaigns in 2019 and 2020 are presented as ASCII RINEX2.11 files and logsheets for each observation from the campaigns. Data were quality checked using the open-source program TEQC, resulting in average multipath 1 and 2 values of 0.68 and 0.57, respectively. All data are archived and publicly available for open access at the geodesy facility UNAVCO to abide by Findable, Accessible, Interoperable, Reusable (FAIR) data principles.
","language":"English","publisher":"Nature","doi":"10.1038/s41597-022-01864-8","usgsCitation":"Troia, G., Stamps, S., Lotspeich, R., Duda, J.M., McCoy, K., Moore, W., Hensel, P., Hippenstiel, R., McKenna, T., Andreasen, D.C., Geoghegan, C., Ulizo, T.P., Kronebusch, M., Carr, J., Walters, D., and Winn, N., 2022, GPS data from 2019 and 2020 campaigns in the Chesapeake Bay region towards quantifying vertical land motions: Scientific Data, v. 9, no. 1, 744, 9 p., https://doi.org/10.1038/s41597-022-01864-8.","productDescription":"744, 9 p.","ipdsId":"IP-122566","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true}],"links":[{"id":445723,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41597-022-01864-8","text":"Publisher Index Page"},{"id":410538,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Chesapeake Bay area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -77.29568067904435,\n 40.12967557474843\n ],\n [\n -77.29568067904435,\n 36.768971760646394\n ],\n [\n -75.43832592966815,\n 36.768971760646394\n ],\n [\n -75.43832592966815,\n 40.12967557474843\n ],\n [\n -77.29568067904435,\n 40.12967557474843\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"9","issue":"1","noUsgsAuthors":false,"publicationDate":"2022-12-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Troia, Gabrielle 0000-0001-6566-4623","orcid":"https://orcid.org/0000-0001-6566-4623","contributorId":299921,"corporation":false,"usgs":false,"family":"Troia","given":"Gabrielle","email":"","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":859036,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stamps, Sarah 0000-0002-3531-1752","orcid":"https://orcid.org/0000-0002-3531-1752","contributorId":299923,"corporation":false,"usgs":false,"family":"Stamps","given":"Sarah","email":"","affiliations":[{"id":12694,"text":"Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":859037,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lotspeich, R. Russell 0000-0002-5572-9064 rlotspei@usgs.gov","orcid":"https://orcid.org/0000-0002-5572-9064","contributorId":194107,"corporation":false,"usgs":true,"family":"Lotspeich","given":"R. 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2022 - Analog field-scale acoustic study of volcanic eruption directivity using a tiltable liquid nitrogen-charged water cannon","interactions":[],"lastModifiedDate":"2023-02-24T13:00:00.092972","indexId":"70240837","displayToPublicDate":"2022-12-02T06:57:37","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1430,"text":"Earth, Planets and Space","active":true,"publicationSubtype":{"id":10}},"title":"Analog field-scale acoustic study of volcanic eruption directivity using a tiltable liquid nitrogen-charged water cannon","docAbstract":"Laterally directed explosive eruptions are responsible for multiple fatalities over the past decade and are an increasingly important volcanology problem. To understand the energy dynamics for these events, we collected field-scale explosion data from nine acoustic sensors surrounding a tiltable cannon as part of an exploratory experimental design. For each cannon discharge, the blast direction was varied systematically at 0°, 12°, and 24° from vertical, capturing acoustic wavefield directivity related to the tilt angle. While each event was similar in energy discharge potential, the resulting acoustic signal features were variable event-to-event, producing non-repetitious waveforms and spectra. Systematic features were observed in a subset of individual events for vertical and lateral discharges. For vertical discharges, the acoustic energy had a uniform radiation pattern. The lateral discharges showed an asymmetric radiation pattern with higher frequencies in the direction of the blast and depletion of those frequencies behind the cannon. Results suggest that, in natural volcanic systems, near-field blast directionality may be elucidated from acoustic sensors in absence of visual data, with implications for volcano monitoring and hazard assessment.
","language":"English","publisher":"Springer","doi":"10.1186/s40623-022-01732-0","usgsCitation":"Jolly, A., Kennedy, B., Matoza, R.S., Iezzi, A., Christensen, B.W., Johnson, R., Sork, A., and Fee, D., 2022, Analog field-scale acoustic study of volcanic eruption directivity using a tiltable liquid nitrogen-charged water cannon: Earth, Planets and Space, v. 74, 177, 16 p., https://doi.org/10.1186/s40623-022-01732-0.","productDescription":"177, 16 p.","ipdsId":"IP-138530","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":445729,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1186/s40623-022-01732-0","text":"Publisher Index Page"},{"id":413396,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"74","noUsgsAuthors":false,"publicationDate":"2022-12-02","publicationStatus":"PW","contributors":{"authors":[{"text":"Jolly, A.D. 0000-0003-1020-9062","orcid":"https://orcid.org/0000-0003-1020-9062","contributorId":296487,"corporation":false,"usgs":true,"family":"Jolly","given":"A.D.","email":"","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":865016,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kennedy, Benjamin","contributorId":302666,"corporation":false,"usgs":false,"family":"Kennedy","given":"Benjamin","email":"","affiliations":[{"id":37172,"text":"University of Canterbury","active":true,"usgs":false}],"preferred":false,"id":865017,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Matoza, Robin S.","contributorId":257265,"corporation":false,"usgs":false,"family":"Matoza","given":"Robin","email":"","middleInitial":"S.","affiliations":[{"id":36524,"text":"University of California, Santa Barbara","active":true,"usgs":false}],"preferred":false,"id":865018,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Iezzi, Alexandra M. 0000-0002-6782-7681","orcid":"https://orcid.org/0000-0002-6782-7681","contributorId":196436,"corporation":false,"usgs":false,"family":"Iezzi","given":"Alexandra M.","affiliations":[],"preferred":false,"id":865019,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Christensen, Bruce W.","contributorId":196298,"corporation":false,"usgs":false,"family":"Christensen","given":"Bruce","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":865020,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Johnson, Richard","contributorId":190189,"corporation":false,"usgs":false,"family":"Johnson","given":"Richard","email":"","affiliations":[],"preferred":false,"id":865021,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sork, Amilea","contributorId":302667,"corporation":false,"usgs":false,"family":"Sork","given":"Amilea","email":"","affiliations":[{"id":37172,"text":"University of Canterbury","active":true,"usgs":false}],"preferred":false,"id":865022,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Fee, David 0000-0002-0936-9977","orcid":"https://orcid.org/0000-0002-0936-9977","contributorId":267231,"corporation":false,"usgs":false,"family":"Fee","given":"David","affiliations":[{"id":13097,"text":"Geophysical Institute, University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":865023,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70236050,"text":"70236050 - 2022 - Wetland ecosystem health and biodiversity","interactions":[],"lastModifiedDate":"2024-03-27T20:46:12.939206","indexId":"70236050","displayToPublicDate":"2022-12-01T15:45:15","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"chapter":"14","title":"Wetland ecosystem health and biodiversity","docAbstract":"• Cropland expansion from 2008 to 2016 was mostly from losses of grassland (88%), with 3% losses from wetlands (a total of nearly 275,000 acres of wetlands, concentrated in the Prairie Pothole Region). Given the lack of national or regional datasets to track changes in RFS acreage, the extent of wetland losses directly attributable to the RFS cannot be more accurately estimated in the RtC3.
• Wetlands gains and losses are not distributed evenly across wetland types or sizes. Since 2007, the nation has lost 120.3 thousand acres of palustrine (marsh-like) wetlands and gained 205.9 thousand acres of lacustrine (lake-like) habitats in the conterminous United States. The diverse wetlands within these classes support different species and perform different ecosystem functions, including loss of functions that impact watershed hydrology, water quality, and water quantity.
• Small, seasonal wetlands are being lost at the fastest rate. The loss and consolidation of small wetlands to promote crop production has negatively impacted amphibians, invertebrates, and other aquatic species that depend on shallow water depths for reproduction. Shifts to longer hydroperiods in large or consolidated wetlands have more uniform (less diverse) invertebrate communities and can support fish that prey on insects and amphibians.
• Small wetlands and ponds are primary sources of water for aquifer recharge in the Northern Prairies. Recent studies in the Canadian portion of the Prairie Pothole Region found that while permanent ponds and wetlands are sources for recharge to aquifers, wetlands with surface water ponds that dry out every year play the dominant role in groundwater replenishment.
• While some Endangered Species Act-listed and other waterbirds have declined, waterfowl (ducks, geese, swans) as a group have not experienced declines over the past decade, possibly due to availability of food (grains), increased precipitation, and the interspersion of ponded waters and agricultural fields along migration routes.
• Shifts to corn and soybean production have resulted in more frequent application of chemicals, including pesticides and fertilizers. Increased usage of neonicotinoid insecticides is of particular concern because of their high toxicity to invertebrates, which are important food sources for wetland-dependent taxa.
• Evidence from the Prairie Pothole Region suggests that trends in larger wetland size, shifts to lakes and ponds (vs. vegetated wetlands), and prolonged and more frequent flooding are due to the combined effects of climate change and increased wetland ditching and consolidation. These trends are highly correlated with increased annual precipitation, which is projected to continue.
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Seabirds are highly mobile, with species-specific seasonal migrations that result in variable patterns of distribution in space and time. In remote offshore marine areas, obtaining useful and current information on resources is difficult to achieve and maintain, both fiscally and logistically, necessitating collaborative effort (Danielson et al. 2022). We used seabird at-sea survey data (2007-2021) and new modeling techniques to develop spatio-temporal models of seasonal abundance and distribution of species in waters of the Pacific Arctic. For six species groups selected as model test cases, we identified fine-scale distributions for each year, using data collected during summer to early fall (June through September). Our approach uses the best available data and can be updated as new data are generated, providing up-to-date information for regions with existing or potential future oil and gas development.
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A study area, including a centrally located rain garden and the surrounding paved surfaces and green space, was instrumented during both a preconstruction and a postconstruction period to (1) develop water budgets to improve understanding of the rain garden hydrology and (2) determine the quantity of stormwater runoff that was diverted and retained by the green infrastructure instead of reaching the combined storm and sanitary sewer. The study was focused on warm-season precipitation and was monitored during spring, summer, and fall of 2016, 2017 and 2018.
Before construction of the rain garden in the parking lot of Gary City Hall in 2017, nearly all precipitation was conveyed away from the parking lot by underground drains, discharged to the sewer, and treated as sanitary waste at the Gary Sanitary District’s treatment plant or discharged directly to local waterways if stormflow exceeded capabilities of the sewage treatment plant. A goal of the Great Lakes Restoration Initiative is the reduction of sewer overflows to local waterways to improve the quality of water entering the Great Lakes. Cities such as Gary benefit financially and environmentally by reducing discharges of stormwater runoff to the sewer system, eliminating the need for treatment. Before implementation of green infrastructure at Gary City Hall, approximately 25 percent of precipitation (approximately 10,200 cubic feet) discharged as stormwater to the sewers through the parking lot drain. After implementation, 2 percent of precipitation discharged to the sewers. For the spring, summer, and fall seasons of 2017 and 2018, 21–24 percent (about 10,700–19,700 cubic feet) of precipitation was captured by the newly installed rain garden. Stormwater discharged to the rain garden infiltrated the sandy soil and was later evaporated from the soil surface, was transpired by plants, or recharged the underlying groundwater aquifer. The percent reduction in stormwater discharged to the storm sewer after the construction of the rain garden was 80.3 percent, equating to approximately 21,400 and 39,300 gallons of stormwater in 2017 and 2018, respectively.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20225101","collaboration":"Prepared in cooperation with the Great Lakes Restoration Initiative","usgsCitation":"Lampe, D.C., Bayless, E.R., and Follette, D.D., 2022, Stormwater reduction and water budget for a rain garden on sandy soil, Gary, Indiana, 2016–18: U.S. Geological Survey Scientific Investigations Report 2022–5101, 39 p., https://doi.org/10.3133/sir20225101.","productDescription":"Report: viii, 39 p.; Data Release","numberOfPages":"39","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-126798","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":409550,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9H5RNNE","text":"USGS data release","linkHelpText":"Groundwater recharge estimates for a green infrastructure installation at Gary City Hall, Gary, Indiana 2016–18"},{"id":409545,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2022/5101/coverthb.jpg"},{"id":409546,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2022/5101/sir20225101.pdf","text":"Report","size":"7.73 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2022-5101"},{"id":409548,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2022/5101/sir20225101.XML"},{"id":409549,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2022/5101/images/"}],"country":"United States","state":"Indiana","city":"Gary","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -87.33719284301965,\n 41.60392762249708\n ],\n [\n -87.33719284301965,\n 41.602552401500475\n ],\n [\n -87.33581350339763,\n 41.602552401500475\n ],\n [\n -87.33581350339763,\n 41.60392762249708\n ],\n [\n -87.33719284301965,\n 41.60392762249708\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Ohio-Kentucky-Indiana Water Science Center
U.S. Geological Survey
5957 Lakeside Boulevard
Indianapolis, IN 46278
The PHREEQ-N-AMDTreat+REYs water-quality modeling tools have the fundamental capability to simulate aqueous chemical reactions and predict the formation of metal-rich solids during the treatment of acid mine drainage (AMD). These new user-friendly, publicly available tools were expanded from the PHREEQ-N-AMDTreat tools to include the precipitation of rare-earth elements plus yttrium (REYs) and the adsorption of REYs onto hydrous Fe, Al, and Mn oxides. The tool set consists of a caustic titration model that indicates equilibrium surface and aqueous speciation of REYs as functions of pH and caustic agent, and a kinetics+adsorption model that simulates progressive changes in pH, major ions, and REYs in water and solids during sequential steps through passive and/or active treatment. Each model has a user interface (UI) that facilitates the input of water-quality data and adjustment to geochemical or treatment system variables; for example, retention time and aeration rate are adjustable parameters in the kinetics model. On-screen graphs display results of changes in metals and associated solute concentrations as functions of pH or retention time; details are summarized in output tables. A goal of such modeling is to identify strategies that could produce a concentrated REYs extract from AMD or mine waste leachate. For example, if REYs could be concentrated after first removing substantial Fe and Al, the final REYs-bearing phase(s) could be more efficiently processed for REYs recovery and, therefore, may represent a more valuable commodity. Preliminary modeling supports the hypothesis that Fe and Al can be removed at pH < 5.5 using conventional sequential oxidation and neutralization treatment processes without removing REYs, and that further increasing pH can promote the adsorption of REYs by hydrous Mn oxides. Alternatively, chemicals such as oxalate or phosphate may be added to precipitate REYs compounds following initial steps to decrease Fe and Al concentrations. The aqueous geochemical model framework is comprehensive and permits evaluation of effects from interactive chemical and physical variables. Field studies that demonstrate REYs attenuation from AMD and corresponding solid-phase formation during specific treatment steps plus laboratory studies of aqueous/solid interactions are helpful to corroborate, refine, and constrain modelin parameters.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 12th International Conference on Acid Mine Drainage","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"12th International Conference on Acid Mine Drainage","conferenceDate":"September 18-24, 2022","language":"English","publisher":"University of Queensland","usgsCitation":"Cravotta, C., 2022, PHREEQ-N-AMDTreat+REYs water-quality modeling tools to evaluate acid mine drainage treatment strategies for recovery of rare-earth elements, in Proceedings of the 12th International Conference on Acid Mine Drainage, September 18-24, 2022, p. 788-804.","productDescription":"7 p.","startPage":"788","endPage":"804","ipdsId":"IP-137202","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":410097,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://smi.uq.edu.au/conferences/international-conference-acid-rock-drainage-2022","linkFileType":{"id":5,"text":"html"}},{"id":425945,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Cravotta, Charles A. 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The presence of soil supports vegetation, and substantially reduces runoff and erosion. Soil enhances other processes such as infiltration of water and aquifer recharge. Soils can be damaged by a warming climate. Loss of vegetation in the Northwest High Desert and Eastern Plains, where soils are not well developed and easily damaged, will lead to dustier conditions in much of the state. On mountain hillslopes, the loss of vegetation cover in response to ongoing climate change will increase soil erosion, which then increases hillslope runoff. This, in turn, causes additional increases in soil erosion and bedrock exposure, which can largely prevent widespread recolonization by most plants, including trees. Soils on mountain hillslopes that face south, which are typically hotter and drier, will be damaged sooner by a warming climate than those on generally north-facing hillslopes that are slightly cooler and moister. Soils take many thousands of years to form, so these hillslopes will increasingly support sparse forests, or, in some circumstances, be entirely deforested. 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State Wildlife Actions Plans and other Management Plans aims to help state fish and wildlife agencies incorporate climate change adaptation for fish and wildlife and their habitats into State Wildlife Action Plans (SWAPs) and other natural resource management plans. This update to the original 2009 Voluntary Guidance reflects the advancements in climate science and in our understanding and implementation of climate adaptation developed over the past 13 years. The document provides principles and tools that can be used to plan for and implement climate change adaptation, voluntary guidance for incorporating climate change into the existing required elements of SWAPs, and case studies to demonstrate adaptation strategies deployed by states in their management efforts.
Climate change continues to be a significant issue for wildlife and natural systems and for the people who rely on the ecosystem services they provide. There is now a well-established and growing scientific literature on the impacts of climate change on wildlife and their habitats, including climate-driven range shifts, population changes, and even species extinctions. At the same time, efforts to address climate change impacts can be made in cooperation with efforts to address other threats, including habitat loss/fragmentation from development, introduction of invasive species, water pollution, and wildlife diseases, many of which may be exacerbated by climate change. Since climate change is a complex and often politically charged issue, it is understood that the decision to revise SWAPs, or other plans, to address climate change rests solely with each state fish and wildlife agency.
All states are required to update their SWAPs by 2025 to qualify for federal funding. Although consideration of climate change is not a requirement for this revision of SWAPs, assessing the impacts of climate change and identifying species and habitats vulnerable to those impacts can help states meet the required eight elements for the revision and prepare for funding opportunities that can support climate adaptation efforts. The Inflation Reduction Act of 2022 and the Recovering America’s Wildlife Act, if passed by the Senate, would provide billions of dollars to states to implement SWAPs, including addressing climate change impacts on fish and wildlife.
The Voluntary Guidance Document introduces and explains seven overarching principles for incorporating climate adaptation into SWAPs. These principles (found in Chapter 2) are: 1. Fully integrate climate change into SWAPs 2. Adopt forward-looking goals 3. Explicitly link actions to climate vulnerabilities 4. Manage for change, not just persistence 5. Consider broader landscapes and longer timeframes 6. Address uncertainty by considering future scenarios and use of adaptive management 7. Engage diverse partners with climate experience and expertise
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Leona","contributorId":299975,"corporation":false,"usgs":false,"family":"Svancara","given":"Leona","affiliations":[{"id":36224,"text":"Idaho Department of Fish and Game","active":true,"usgs":false}],"preferred":false,"id":859194,"contributorType":{"id":1,"text":"Authors"},"rank":14},{"text":"Thurman, Lindsey 0000-0003-3142-4909","orcid":"https://orcid.org/0000-0003-3142-4909","contributorId":269425,"corporation":false,"usgs":true,"family":"Thurman","given":"Lindsey","email":"","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":859174,"contributorType":{"id":1,"text":"Authors"},"rank":15},{"text":"Benedict, Logan","contributorId":299965,"corporation":false,"usgs":false,"family":"Benedict","given":"Logan","email":"","affiliations":[{"id":64991,"text":"Florida Wildlife Commission","active":true,"usgs":false}],"preferred":false,"id":859175,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Ernest Johnson, Maggie","contributorId":248477,"corporation":false,"usgs":false,"family":"Ernest Johnson","given":"Maggie","email":"","affiliations":[{"id":49927,"text":"Association of Fish and Wildlife Agencies","active":true,"usgs":false}],"preferred":false,"id":897583,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Humpert, Mark","contributorId":299969,"corporation":false,"usgs":false,"family":"Humpert","given":"Mark","email":"","affiliations":[{"id":49927,"text":"Association of Fish and Wildlife Agencies","active":true,"usgs":false}],"preferred":false,"id":897584,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Cross, Molly S. 0000-0002-4238-9208","orcid":"https://orcid.org/0000-0002-4238-9208","contributorId":149216,"corporation":false,"usgs":false,"family":"Cross","given":"Molly","middleInitial":"S.","affiliations":[{"id":17674,"text":"Wildlife Conservation Society, Bozeman, MT","active":true,"usgs":false}],"preferred":false,"id":859178,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Quinones, Rebecca M.","contributorId":172968,"corporation":false,"usgs":false,"family":"Quinones","given":"Rebecca","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":859191,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Newman, Robert","contributorId":248514,"corporation":false,"usgs":false,"family":"Newman","given":"Robert","affiliations":[],"preferred":false,"id":859190,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Mangham, Roger","contributorId":299973,"corporation":false,"usgs":false,"family":"Mangham","given":"Roger","email":"","affiliations":[{"id":37007,"text":"Arkansas Game and Fish Commission","active":true,"usgs":false}],"preferred":false,"id":859189,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Seamster, Ginny","contributorId":299974,"corporation":false,"usgs":false,"family":"Seamster","given":"Ginny","email":"","affiliations":[{"id":24672,"text":"New Mexico Department of Game and Fish","active":true,"usgs":false}],"preferred":false,"id":859192,"contributorType":{"id":1,"text":"Authors"},"rank":23}]}} ,{"id":70238719,"text":"70238719 - 2022 - Determination and prediction of rare earth element eeochemical associations in acid mine drainage treatment wastes","interactions":[],"lastModifiedDate":"2024-02-23T15:37:15.333066","indexId":"70238719","displayToPublicDate":"2022-12-01T09:36:32","publicationYear":"2022","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Determination and prediction of rare earth element eeochemical associations in acid mine drainage treatment wastes","docAbstract":"Acid mine drainage (AMD) has been proposed by various researchers as a novel source of rare earth elements (REE), a group of elements that include critical metals for clean energy and modern technologies. REE tend to be sequestered in the Fe-Al-Mn-rich solids produced during the treatment of AMD. These solids are typically managed as waste, but could be a low-cost, readily available REE source. Here, results from field sampling, solids characterization, and geochemical modeling are presented to identify the mechanism(s) of REE attenuation and determine the minerals/solid phases in AMD solids that are enriched in REE.
This study reveals that solids produced from low-pH AMD that was passively treated by limestone contain elevated concentrations of REE with Al, Fe, and/or Mn. AMD solid characterization via sequential extraction demonstrated that Al and Mn oxides were more abundant than Fe oxides and that the REEs are mainly associated with Al/Mn phases. Additionally, sequential extractions demonstrate that for the AMD solids evaluated, acidic and/or reducing extractions are required to mobilize the REE. Finally, the “CausticTitrationREYs.exe” geochemical equilibrium model demonstrated in this study indicates that the observed dissolved REE attenuation can be explained via surface complexation on Fe, Al, and Mn oxides/hydroxides and not by REE compound precipitation. The model accurately predicts the pH dependent removal of dissolved REE and that Al and Mn oxides/hydroxides are largely responsible for dissolved REE removal for the systems evaluated. The modeling results are consistent with the characterization results that show that Al and Mn hydroxides are important hosting phases of REEs in AMD treatment systems.
The results presented here can be used to identify conditions favorable for accumulation of REE-enriched AMD solids and possible chemical treatment(s) to mobilize REE. The geochemical model can be applied to active and/or passive AMD treatment systems to predict REE attenuation with Fe, Al, and Mn during treatment and what phases may be enriched in REE. This information can be used to engineer AMD systems to produce specific phases enriched in REE. The recovery of REE from AMD solids is an opportunity to transform the environmental and economical challenge of polluted mine drainage into an asset.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the 12th International Conference on Acid Rock Drainage","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"12th International Conference on Acid Rock Drainage","conferenceDate":"September 18-24, 2022","language":"English","publisher":"University of Queensland","usgsCitation":"Hedin, B., Cravotta, C., Stuckman, M., Lopano, C., Capo, R., and Hedin, R., 2022, Determination and prediction of rare earth element eeochemical associations in acid mine drainage treatment wastes, in Proceedings of the 12th International Conference on Acid Rock Drainage, September 18-24, 2022, p. 626-633.","productDescription":"8 p.","startPage":"626","endPage":"633","ipdsId":"IP-141129","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":425944,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":410096,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://smi.uq.edu.au/conferences/international-conference-acid-rock-drainage-2022"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Hedin, B.C.","contributorId":299679,"corporation":false,"usgs":false,"family":"Hedin","given":"B.C.","email":"","affiliations":[{"id":64931,"text":"Hedin Environmental Inc.","active":true,"usgs":false}],"preferred":false,"id":858353,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cravotta, Charles A. III 0000-0003-3116-4684","orcid":"https://orcid.org/0000-0003-3116-4684","contributorId":207249,"corporation":false,"usgs":true,"family":"Cravotta","given":"Charles A.","suffix":"III","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":true,"id":858354,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Stuckman, M.Y.","contributorId":299680,"corporation":false,"usgs":false,"family":"Stuckman","given":"M.Y.","affiliations":[{"id":64933,"text":"National Energy Technology Laboratory","active":true,"usgs":false}],"preferred":false,"id":858355,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lopano, C.L.","contributorId":299681,"corporation":false,"usgs":false,"family":"Lopano","given":"C.L.","affiliations":[{"id":64933,"text":"National Energy Technology Laboratory","active":true,"usgs":false}],"preferred":false,"id":858356,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Capo, R.C.","contributorId":299682,"corporation":false,"usgs":false,"family":"Capo","given":"R.C.","affiliations":[{"id":12465,"text":"University of Pittsburgh","active":true,"usgs":false}],"preferred":false,"id":858357,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hedin, R.S.","contributorId":299683,"corporation":false,"usgs":false,"family":"Hedin","given":"R.S.","email":"","affiliations":[{"id":64931,"text":"Hedin Environmental Inc.","active":true,"usgs":false}],"preferred":false,"id":858358,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70263284,"text":"70263284 - 2022 - Maintaining wetland ecosystem services in a changing climate","interactions":[],"lastModifiedDate":"2025-02-05T14:20:14.921023","indexId":"70263284","displayToPublicDate":"2022-12-01T09:17:54","publicationYear":"2022","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"10","title":"Maintaining wetland ecosystem services in a changing climate","docAbstract":"A changing climate is causing challenges for soil and water management in many parts of the world. Current soil management practices need to be redesigned to effectively address present and future fluctuating climates.\n\nSoil Hydrology in a Changing Climate explores how soil management practices impact soil hydrological characteristics, and how we can improve our understanding of soil and water management under changing conditions. Soil hydrology includes water infiltration and soil water storage, which are critical for agricultural plant and animal production. With our future climate predicted to include hotter, drier conditions, increases in evapotranspiration as well as fewer, more intense storms, improved soil management and soil hydrology are critical to ensuring our agriculture production can meet human demand.\n\nThis comprehensive book is a valuable resource for land managers, soil conservationists, researchers and others who wish to understand how different management practices affect soil and water dynamics and how these practices can be adjusted to enhance agricultural sustainability and environmental quality.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Soil hydrology in a changing climate","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"CSIRO","doi":"10.1071/9781486313785","usgsCitation":"Johnson, W.C., and Guntenspergen, G.R., 2022, Maintaining wetland ecosystem services in a changing climate, chap. 10 of Soil hydrology in a changing climate, p. 207-232, https://doi.org/10.1071/9781486313785.","productDescription":"26 p.","startPage":"207","endPage":"232","ipdsId":"IP-124331","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":481666,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Johnson, W. Carter","contributorId":189219,"corporation":false,"usgs":false,"family":"Johnson","given":"W.","email":"","middleInitial":"Carter","affiliations":[],"preferred":false,"id":926156,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Guntenspergen, Glenn R. 0000-0002-8593-0244 glenn_guntenspergen@usgs.gov","orcid":"https://orcid.org/0000-0002-8593-0244","contributorId":2885,"corporation":false,"usgs":true,"family":"Guntenspergen","given":"Glenn","email":"glenn_guntenspergen@usgs.gov","middleInitial":"R.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":926157,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70239795,"text":"70239795 - 2022 - Osmoregulation and acid-base balance.","interactions":[],"lastModifiedDate":"2023-01-20T14:50:53.947059","indexId":"70239795","displayToPublicDate":"2022-12-01T08:49:30","publicationYear":"2022","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"chapter":"9","title":"Osmoregulation and acid-base balance.","docAbstract":"Maintaining relatively constant levels of internal cellular ions is critical to the normal function of all animals. For many organisms this is achieved primarily by regulating the ion and acid-base composition of the blood within narrow limits. This understanding of the importance of “le milieu interior,” first espoused by Claude Bernard in the mid-1800s and later described as “homeostasis” by Walter Cannon, is a cornerstone of modern physiology. “It was Bernard’s view that we achieve a free and independent life, physically and mentally, because of the constancy of the composition of our internal environment” (Smith 1961:1). Direct contact between the gills and water makes ion, water, and acid-base balance especially challenging and important to fish and, in turn, makes fish important subjects for understanding the evolution and control of all of these homeostatic processes.
Several strategies exist within fishes for regulating ion concentrations in the blood relative to external (environmental) salt concentrations. Hagfishes, which are one extant group representing the ancestral jawless condition of vertebrates, are restricted to seawater (SW) and have an osmoconforming strategy in which the internal (blood) and external osmotic concentrations are very similar (Currie and Edwards 2010), but important differences do exist (Sardella et al. 2009). Lampreys are the other group of extant jawless fishes and either live wholly in freshwater (FW) or are anadromous. Lampreys have an osmoregulatory strategy in which the internal concentrations of ions are approximately one-third that of SW (Reis-Santos et al. 2008). Their underlying mechanisms of ion transport and osmoregulation appear to be nearly identical to those of the more recently evolved ray-finned fishes (Figure 9.1), which have adopted a similar osmoregulatory strategy. Elasmobranchs and coelacanths in SW retain high levels of urea in their plasma and are osmoconformers (Figure 9.2), whereas in the relatively rare instances elasmobranchs are found in FW, they are hyperosmoregulators, maintaining plasma ion levels in excess of environmental levels via mechanisms similar to FW ray-finned fishes (Ballantyne and Robinson 2010).
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Methods for fish biology","largerWorkSubtype":{"id":15,"text":"Monograph"},"language":"English","publisher":"American Fisheries Society","doi":"10.47886/9781934874615.ch9","usgsCitation":"McCormick, S.D., Schultz, E., and Brauner, C., 2022, Osmoregulation and acid-base balance., chap. 9 of Methods for fish biology, p. 275-308, https://doi.org/10.47886/9781934874615.ch9.","productDescription":"34 p.","startPage":"275","endPage":"308","ipdsId":"IP-108481","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":412128,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"edition":"2nd edition","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McCormick, Stephen D. 0000-0003-0621-6200 smccormick@usgs.gov","orcid":"https://orcid.org/0000-0003-0621-6200","contributorId":139214,"corporation":false,"usgs":true,"family":"McCormick","given":"Stephen","email":"smccormick@usgs.gov","middleInitial":"D.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":861975,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schultz, Eric T.","contributorId":298956,"corporation":false,"usgs":false,"family":"Schultz","given":"Eric T.","affiliations":[{"id":64738,"text":"University of CT, Storrs","active":true,"usgs":false}],"preferred":false,"id":861976,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brauner, Colin","contributorId":301092,"corporation":false,"usgs":false,"family":"Brauner","given":"Colin","affiliations":[{"id":36484,"text":"UBC","active":true,"usgs":false}],"preferred":false,"id":861977,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70240308,"text":"70240308 - 2022 - Modeling risk dynamics of contaminants of emerging concern in a temperate-region wastewater effluent-dominated stream","interactions":[],"lastModifiedDate":"2023-02-03T14:45:16.85921","indexId":"70240308","displayToPublicDate":"2022-12-01T08:24:40","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5112,"text":"Environmental Science: Water Research & Technology","active":true,"publicationSubtype":{"id":10}},"title":"Modeling risk dynamics of contaminants of emerging concern in a temperate-region wastewater effluent-dominated stream","docAbstract":"Wastewater effluent-dominated streams are becoming increasingly common worldwide, including in temperate regions, with potential impacts on ecological systems and drinking water sources. We recently quantified the occurrence/spatiotemporal dynamics of pharmaceutical mixtures in a representative temperate-region wastewater effluent-dominated stream (Muddy Creek, Iowa) under baseflow conditions and characterized relevant fate processes. Herein, we quantified the ecological risk quotients (RQs) of 19 effluent-derived contaminants of emerging concern (CECs; including: 14 pharmaceuticals, 2 industrial chemicals, and 3 neonicotinoid insecticides) and 1 run-off-derived compound (atrazine) in the stream under baseflow conditions, and estimated the probabilistic risks of effluent-derived CECs under all-flow conditions (i.e., including runoff events) using stochastic risk modeling. We determined that 11 out of 20 CECs pose medium-to-high risks to local ecological systems (i.e., algae, invertebrates, fish) based on literature-derived acute effects under measured baseflow conditions. Stochastic risk modeling indicated decreased, but still problematic, risk of effluent-derived CECs (i.e., RQ ≥ 0.1) under all-flow conditions when runoff events were included. Dilution of effluent-derived chemicals from storm flows thus only minimally decreased risk to aquatic biota in the effluent-dominated stream. We also modeled in-stream transport. Thirteen out of 14 pharmaceuticals persisted along the stream reach (median attenuation rate constant k < 0.1 h−1) and entered the Iowa River at elevated concentrations. Predicted and measured concentrations in the drinking water treatment plant were below the human health benchmarks. This study demonstrates the application of probabilistic risk assessments for effluent-derived CECs in a representative effluent-dominated stream under variable flow conditions (when measurements are less practical) and provides an enhanced prediction tool transferable to other effluent-dominated systems.
","language":"English","publisher":"Royal Society of Chemistry","doi":"10.1039/D2EW00157H","usgsCitation":"Zhi, H., Webb, D.T., Schnoor, J.L., Kolpin, D., Klaper, R.D., Iwanowicz, L., and LeFevre, G.H., 2022, Modeling risk dynamics of contaminants of emerging concern in a temperate-region wastewater effluent-dominated stream: Environmental Science: Water Research & Technology, v. 8, p. 1408-1422, https://doi.org/10.1039/D2EW00157H.","productDescription":"15 p.","startPage":"1408","endPage":"1422","ipdsId":"IP-129637","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":445736,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9431852","text":"External Repository"},{"id":412670,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa","otherGeospatial":"Muddy Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -91.55039606554381,\n 41.6953124183122\n ],\n [\n -91.54728310759076,\n 41.69428009738749\n ],\n [\n -91.54749768431226,\n 41.69891044541674\n ],\n [\n -91.54924385578545,\n 41.702072402012334\n ],\n [\n -91.55714027912532,\n 41.702649141061755\n ],\n [\n -91.56618604571608,\n 41.7030279445506\n ],\n [\n -91.57101402194326,\n 41.7076096051033\n ],\n [\n -91.57273063571196,\n 41.710039104793736\n ],\n [\n -91.57322128207477,\n 41.717143169348276\n ],\n [\n -91.57813508899014,\n 41.72124335103547\n ],\n [\n -91.57377171356345,\n 41.727892495681544\n ],\n [\n -91.57581019241506,\n 41.72987822163276\n ],\n [\n 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L","contributorId":302047,"corporation":false,"usgs":false,"family":"Schnoor","given":"Jerald","email":"","middleInitial":"L","affiliations":[{"id":6768,"text":"University of Iowa","active":true,"usgs":false}],"preferred":false,"id":863355,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kolpin, Dana W. 0000-0002-3529-6505","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":204154,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana W.","affiliations":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"preferred":true,"id":863356,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Klaper, Rebecca D.","contributorId":218114,"corporation":false,"usgs":false,"family":"Klaper","given":"Rebecca","email":"","middleInitial":"D.","affiliations":[{"id":18038,"text":"University of Wisconsin, Milwaukee","active":true,"usgs":false}],"preferred":false,"id":863357,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Iwanowicz, Luke 0000-0002-1197-6178 liwanowicz@usgs.gov","orcid":"https://orcid.org/0000-0002-1197-6178","contributorId":302048,"corporation":false,"usgs":true,"family":"Iwanowicz","given":"Luke","email":"liwanowicz@usgs.gov","affiliations":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":863358,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"LeFevre, Gregory H.","contributorId":211880,"corporation":false,"usgs":false,"family":"LeFevre","given":"Gregory","email":"","middleInitial":"H.","affiliations":[{"id":6768,"text":"University of Iowa","active":true,"usgs":false}],"preferred":true,"id":863359,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70238615,"text":"70238615 - 2022 - Atmospheric circulation drivers of extreme high water level events at Foggy Island Bay, Alaska","interactions":[],"lastModifiedDate":"2022-12-01T14:28:00.803404","indexId":"70238615","displayToPublicDate":"2022-12-01T08:20:04","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5634,"text":"Atmosphere","active":true,"publicationSubtype":{"id":10}},"title":"Atmospheric circulation drivers of extreme high water level events at Foggy Island Bay, Alaska","docAbstract":"The northern coast of Alaska is experiencing significant climatic change enhancing hazards from reduced sea ice and increased coastal erosion. This same region is home to offshore oil/gas activities. Foggy Island Bay is one region along the Beaufort Sea coast with planned offshore oil/gas development that will need to account for the changing climate. High water levels impact infrastructure through coastal erosion and flooding hazards. In this study, 21 high water level events exceeding the top 95th percentile were identified at the gauge in Prudhoe Bay, Alaska (adjacent to Foggy Island Bay) over 1990-2018. All events were associated with strong westerly winds according to weather station records. Low pressure storm systems were found to be a key driver of westerly winds in the region according to downscaled reanalysis and storm track data. A dynamically downscaled global climate model projection from CMIP5 indicates that days with westerly wind events will become frequent by 2100 in the Foggy Island Bay region. Coupled with the anticipated continued decline in sea ice, the northern coast of Alaska may experience more frequent high water events over the next ~80 years.","language":"English","publisher":"MDPI","doi":"10.3390/atmos13111791","usgsCitation":"Bieniek, P., Erikson, L.H., and Kasper, J., 2022, Atmospheric circulation drivers of extreme high water level events at Foggy Island Bay, Alaska: Atmosphere, v. 13, 1791, 17 p., https://doi.org/10.3390/atmos13111791.","productDescription":"1791, 17 p.","ipdsId":"IP-144924","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":445740,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/atmos13111791","text":"Publisher Index Page"},{"id":409922,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Beaufort Sea, Foggy Island Bay, Prudhoe Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -148.80741465739465,\n 70.39723931268995\n ],\n [\n -148.70029566028296,\n 70.4000035945075\n ],\n [\n -148.54373712604283,\n 70.3677303272334\n ],\n [\n -148.4970442298659,\n 70.33540601843683\n ],\n [\n -148.5245106393817,\n 70.31321124176867\n ],\n [\n -148.5217639984302,\n 70.29284489806011\n ],\n [\n -148.3404856956258,\n 70.29377107971973\n ],\n [\n -148.1015279328383,\n 70.39816078157423\n ],\n [\n -148.37344538704474,\n 70.47541577367042\n ],\n [\n -148.7222687878956,\n 70.46715246793207\n ],\n [\n -148.80741465739465,\n 70.39723931268995\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"13","noUsgsAuthors":false,"publicationDate":"2022-10-29","publicationStatus":"PW","contributors":{"authors":[{"text":"Bieniek, Peter A.","contributorId":209850,"corporation":false,"usgs":false,"family":"Bieniek","given":"Peter A.","affiliations":[{"id":38014,"text":"Alaska Climate Science Center, University of Alaska, Fairbanks, AK","active":true,"usgs":false}],"preferred":false,"id":858103,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Erikson, Li H. 0000-0002-8607-7695 lerikson@usgs.gov","orcid":"https://orcid.org/0000-0002-8607-7695","contributorId":149963,"corporation":false,"usgs":true,"family":"Erikson","given":"Li","email":"lerikson@usgs.gov","middleInitial":"H.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":858104,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kasper, Jeremy L. 0000-0003-0975-6114","orcid":"https://orcid.org/0000-0003-0975-6114","contributorId":208630,"corporation":false,"usgs":false,"family":"Kasper","given":"Jeremy L.","affiliations":[{"id":37850,"text":"University of Alaska Fairbanks, Fairbanks, Alaska, UNITED STATES","active":true,"usgs":false}],"preferred":false,"id":858105,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70239124,"text":"70239124 - 2022 - Effects of release techniques on parent-reared whooping cranes in the eastern migratory population","interactions":[],"lastModifiedDate":"2022-12-28T13:42:34.222167","indexId":"70239124","displayToPublicDate":"2022-12-01T07:40:38","publicationYear":"2022","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":12807,"text":"Proceedings of the North American Crane Workshop","active":true,"publicationSubtype":{"id":10}},"title":"Effects of release techniques on parent-reared whooping cranes in the eastern migratory population","docAbstract":"Reintroduction of an Eastern Migratory Population (EMP) of whooping cranes (Grus americana) in the United States by release of captive-reared individuals began in 2001. As of 2020, the EMP has approximately 21 breeding pairs and has had limited recruitment of wild-hatched individuals, thus captive-reared juveniles continue to be released into breeding areas in Wisconsin to maintain the population. We investigated the effects of release techniques on survival, behavior, site fidelity, and conspecific associations of 42 captive-parent-reared whooping cranes released during 2013-2019 into the EMP. Individuals were monitored intensively post-release, then as a part of a long-term monitoring program, locational, behavioral, and habitat use data were collected and analyzed. Most cranes roosted in water post-release; however, we documented 4 parent-reared cranes roosting on dry land. Most cranes eventually associated with other whooping cranes; however, juveniles released near single adult cranes were less likely to associate with other whooping cranes during their first migration or winter than juveniles released near other types of whooping crane pairs or groups. Parent-reared and costume-reared whooping cranes had similar rates of survival 1 year post-release (69.0% and 64.4%, respectively). The highest risk of mortality was within the first 100 days post-release, and the leading known causes of death were predation and impact trauma due to powerline or vehicle collisions. Both costume- and parent-reared cranes had strong fidelity to release sites. We advise releasing parent-reared cranes near pairs or groups of whooping cranes and taking measures to reduce the risk of mortality during the immediate period after release (e.g., predator aversion training, marking powerlines).
Laura K. Lautz is a premier mentor, collaborator, and researcher at the intersection of natural hydrologic systems and humans. Her research has shifted the paradigm around measuring and understanding the impacts of surface water and groundwater interactions across spatial and temporal scales. She has done this by testing and refining new methods and by collaborating with, training, supporting, and mentoring diverse scientists. Here, we review her research across five themes, summarizing the prior status of the field, what Lautz contributed, as well as new directions in the field inspired by her work. Lautz’s research expanded our understanding of the impacts of stream restoration on surface water-groundwater interactions, where she tested new field methods and showed that restoration structures increase hyporheic exchange, locally altering biogeochemical function of the streambed. She refined novel methods for measuring surface water-groundwater exchanges and worked to make these methods easily accessible through freely available software. Her research group greatly expanded the use of heat as a quantitative tracer of hydrologic processes via the well-used VFLUX and HFLUX programs. Her research evaluated the impacts of surface water-groundwater interactions in urban streams, showing the substantial fluxes of nutrients and chloride that can move through those exchanges and the potential for groundwater to help buffer contamination. To assess groundwater impacts on streamflow below tropical glaciers, she used a wide range of field methods to reveal the sensitivity of these systems to climate change. Finally, she built tools to quantify natural brine contamination of drinking water wells in areas that may later be subject to high-volume hydraulic fracturing, creating a needed ‘pre-fracking’ dataset. Through this process, she identified multiple sources of salinity that are already reaching wells in these systems. Overall, this research has been done with a focus on mentoring and training the next generation of hydrologists, including work to specifically train for careers beyond academia, and facilitating early career scientists to realize their innate potentials. With former trainees in careers across industry, government, and academia, Dr. Laura K. Lautz is now working to build cross-disciplinary research at even larger scales, across federal research units, guaranteeing that an even larger impact on hydrology is still to come.
The lack of consistent, accurate information on evapotranspiration (ET) and consumptive use of water by irrigated agriculture is one of the most important data gaps for water managers in the western United States (U.S.) and other arid agricultural regions globally. The ability to easily access information on ET is central to improving water budgets across the West, advancing the use of data-driven irrigation management strategies, and expanding incentive-driven conservation programs. Recent advances in remote sensing of ET have led to the development of multiple approaches for field-scale ET mapping that have been used for local and regional water resource management applications by U.S. state and federal agencies. The OpenET project is a community-driven effort that is building upon these advances to develop an operational system for generating and distributing ET data at a field scale using an ensemble of six well-established satellite-based approaches for mapping ET. Key objectives of OpenET include: Increasing access to remotely sensed ET data through a web-based data explorer and data services; supporting the use of ET data for a range of water resource management applications; and development of use cases and training resources for agricultural producers and water resource managers. Here we describe the OpenET framework, including the models used in the ensemble, the satellite, meteorological, and ancillary data inputs to the system, and the OpenET data visualization and access tools. We also summarize an extensive intercomparison and accuracy assessment conducted using ground measurements of ET from 139 flux tower sites instrumented with open path eddy covariance systems. Results calculated for 24 cropland sites from Phase I of the intercomparison and accuracy assessment demonstrate strong agreement between the satellite-driven ET models and the flux tower ET data. For the six models that have been evaluated to date (ALEXI/DisALEXI, eeMETRIC, geeSEBAL, PT-JPL, SIMS, and SSEBop) and the ensemble mean, the weighted average mean absolute error (MAE) values across all sites range from 13.6 to 21.6 mm/month at a monthly timestep, and 0.74 to 1.07 mm/day at a daily timestep. At seasonal time scales, for all but one of the models the weighted mean total ET is within ±8% of both the ensemble mean and the weighted mean total ET calculated from the flux tower data. Overall, the ensemble mean performs as well as any individual model across nearly all accuracy statistics for croplands, though some individual models may perform better for specific sites and regions. We conclude with three brief use cases to illustrate current applications and benefits of increased access to ET data, and discuss key lessons learned from the development of OpenET.