Ecological studies indicate that impervious cover (IC) greater than approximately 5%–20% may have adverse effects on receiving-stream ecology. It is difficult to separate the effects of runoff quality from other effects of urbanization on receiving streams. This study presents the results of a numerical experiment to assess the effects of increasing IC on water quality using the Stochastic Empirical Loading and Dilution Model (SELDM). Hydrologic and physiographic variables representative of southern New England were used to simulate receiving water quality in a basin with IC ranging from 0.1% to 30%. Simulation results mirror the results of ecological studies; event mean concentrations (EMCs) of total phosphorus (TP) increase proportionally to the logarithms of imperviousness for a given risk percentile. Simulation results indicated that commonly used stormwater treatment methods may be insufficient for mitigating the effects of imperviousness. Therefore, disconnection, rather than treatment, may be needed to protect water quality, and efforts to preserve undeveloped stream basins may be more effective than efforts to remediate conditions in highly developed basins. Results also indicate that commonly used water-quality criteria may be too restrictive for stormwater because TP EMCs frequently exceed these criteria, even in minimally developed basins.
Groundwater-level conditions, generalized groundwater potentiometric surfaces, and generalized flow directions at the decommissioned Naval Air Warfare Center in West Trenton, New Jersey, were evaluated for calendar year 2018. Groundwater levels measured continuously in five on-site wells and one nearby off-site well were plotted as hydrographs for January 1, 2018, through December 31, 2018. Groundwater levels measured in 110 wells on June 18, 2018, were contoured as generalized potentiometric surfaces on maps and sections. Generalized groundwater-flow directions inferred from the June 2018 data are shown in the maps and sections.
Groundwater levels in six monitoring wells fluctuated in response to seasonal changes, precipitation, and pumping from “pump-and-treat” (P&T) wells. Record high precipitation totals in November, combined with a shutdown of three P&T wells in November, resulted in annual high water levels in late November for five of the six wells monitored. Annual high groundwater levels that occur during the fall are uncharacteristic of the typical timing of annual high water levels, which usually occur in the spring following low evapotranspiration during the winter months, compared to annual low water levels, which usually occur in fall because of high evapotranspiration during the summer months. The annual high water levels occurred following a 3-day precipitation event totaling 3.50 inches from November 24-26, which also caused the largest 1-day water-level increase for five of the six wells in 2018.
The groundwater-level contour maps and sections include generalized flow directions. Given the heterogeneity of the site’s fractured rock aquifers, contours and associated groundwater-flow directions shown on the maps and sections should be considered as broad conceptualizations. A nearly vertical fault striking southwest to northeast separates the northwestern part of the site underlain by the Lockatong Formation from the southeastern part, which is underlain by the Stockton Formation. In the Lockatong Formation, general groundwater-flow directions were toward P&T wells. The P&T wells limited the flow of groundwater in the Lockatong Formation from the site into the adjacent areas and contained most groundwater contamination within the site. A groundwater divide bisected the site; groundwater in the western part generally flowed to P&T wells 8BR, 15BR, 20BR, 29BR, 56BR, 91BR, and BRP-2, and groundwater in the eastern part generally flowed to P&T well 48BR. A groundwater divide also was present in the Stockton Formation. Groundwater west of the divide in the Stockton Formation generally flowed toward P&T well 22BR, and groundwater east of the divide generally flowed south and southeast, away from the site. Saprolite and fill from land surface to depths of 25 feet below land surface exhibit similar properties to those of porous media, and water levels in surficial wells were contoured using a porous media aquifer approach. Water levels in these surficial wells indicate that groundwater in the saprolite and fill flowed predominantly toward Gold Run and, to a lesser extent, the West Ditch spring that drains to Gold Run. In addition, some shallow groundwater was captured by the cone of depression in the fractured bedrock and was attributed to P&T well 48BR.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201016","collaboration":"Prepared in cooperation with the U.S. Navy","usgsCitation":"Fiore, A.R., and Lacombe, P.J., 2020, Groundwater levels and generalized potentiometric surfaces, former Naval Air Warfare Center, West Trenton, New Jersey, 2018: U.S. Geological Survey Open-File Report 2020–1016, 28 p., https://doi.org/10.3133/ofr20201016.","productDescription":"Report: v, 28 p.; Data Release","numberOfPages":"28","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-104199","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":375290,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1016/ofr20201016.pdf","text":"Report","size":"10.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1016"},{"id":375285,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1016/coverthb.jpg"},{"id":375288,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P98N1GWV","text":"USGS data release","linkHelpText":"Reported groundwater levels and groundwater pump-and-treat withdrawals, former Naval Air Warfare Center, West Trenton, New Jersey, 2018"}],"country":"United States","state":"New Jersey","city":"West Trenton","otherGeospatial":"Former Naval Air Warfare Center","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.81613278388977,\n 40.26694411855267\n ],\n [\n -74.80834364891052,\n 40.26694411855267\n ],\n [\n -74.80834364891052,\n 40.27319835024231\n ],\n [\n -74.81613278388977,\n 40.27319835024231\n ],\n [\n -74.81613278388977,\n 40.26694411855267\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Jersey Water Science Center
U.S. Geological Survey
3450 Princeton Pike, Suite 110
Lawrenceville, NJ 08648
The hydrogeology below large surface water features such as rivers and estuaries is universally under-informed at the long reach to basin scales (tens of km+). This challenge inhibits the accurate modeling of fresh/saline groundwater interfaces and groundwater/surface water exchange patterns at management-relevant spatial extents. Here we introduce a towed, floating transient electromagnetic (TEM) system (i.e. FloaTEM) for rapid (up to 15 km/h) high resolution electrical mapping of the subsurface below large water bodies to depths often a factor of 10 greater than other towed instruments. The novel FloaTEM system is demonstrated at a range of diverse 4th through 6th-order riverine settings across the United States including 1) the Farmington River, near Hartford, Connecticut; 2) the Upper Delaware River near Barryville, New York; 3) the Tallahatchie River near Shellmound, Mississippi; and, 4) the Eel River estuary, on Cape Cod, near Falmouth, Massachusetts. Airborne frequency-domain electromagnetic and land-based towed TEM data are also compared at the Tallahatchie River site, and streambed geologic scenarios are explored with forward modeling. A range of geologic structures and pore water salinity interfaces were identified. Process-based interpretation of the case study data indicated FloaTEM can resolve varied sediment-water interface materials, such as the accumulation of fines at the bottom of a reservoir and permeable sand/gravel riverbed sediments that focus groundwater discharge. Bedrock layers were mapped at several sites, and aquifer confining units were defined at comparable resolution to airborne methods. Terrestrial fresh groundwater discharge with flowpaths extending hundreds of meters from shore was also imaged below the Eel River estuary, improving on previous hydrogeological characterizations of that nutrient-rich coastal exchange zone. In summary, the novel FloaTEM system fills a critical gap in our ability to characterize the hydrogeology below surface water features and will support more accurate prediction of groundwater/surface water exchange dynamics and fresh-saline groundwater interfaces.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2020.140074","usgsCitation":"Lane, J.W., Briggs, M., Maurya, P., White, E.A., Pedersen, J., Auken, E., Terry, N., Minsley, B.J., Kress, W., LeBlanc, D.R., Adams, R.F., and Johnson, C., 2020, Characterizing the diverse hydrogeology underlying rivers and estuaries using new floating transient electromagnetic methodology: Science of the Total Environment, v. 740, 140074, 14 p., https://doi.org/10.1016/j.scitotenv.2020.140074.","productDescription":"140074, 14 p.","ipdsId":"IP-119384","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":456460,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2020.140074","text":"Publisher Index Page"},{"id":436936,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9E5JBAF","text":"USGS data release","linkHelpText":"Floating and Towed Transient Electromagnetic Surveys used to Characterize Hydrogeology underlying Rivers and Estuaries: March - December 2018"},{"id":385330,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"740","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Lane, John W. 0000-0002-3558-243X","orcid":"https://orcid.org/0000-0002-3558-243X","contributorId":219742,"corporation":false,"usgs":true,"family":"Lane","given":"John","email":"","middleInitial":"W.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":814802,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Briggs, Martin A. 0000-0003-3206-4132","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":257637,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin A.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"preferred":true,"id":814803,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Maurya, PK","contributorId":257644,"corporation":false,"usgs":false,"family":"Maurya","given":"PK","affiliations":[{"id":37318,"text":"Aarhus University","active":true,"usgs":false}],"preferred":false,"id":814804,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"White, Eric A. 0000-0002-7782-146X eawhite@usgs.gov","orcid":"https://orcid.org/0000-0002-7782-146X","contributorId":1737,"corporation":false,"usgs":false,"family":"White","given":"Eric","email":"eawhite@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":814805,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pedersen, JB","contributorId":257645,"corporation":false,"usgs":false,"family":"Pedersen","given":"JB","email":"","affiliations":[{"id":37318,"text":"Aarhus University","active":true,"usgs":false}],"preferred":false,"id":814806,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Auken, Esben","contributorId":193991,"corporation":false,"usgs":false,"family":"Auken","given":"Esben","email":"","affiliations":[],"preferred":false,"id":814807,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Terry, Neil 0000-0002-3965-340X nterry@usgs.gov","orcid":"https://orcid.org/0000-0002-3965-340X","contributorId":192554,"corporation":false,"usgs":true,"family":"Terry","given":"Neil","email":"nterry@usgs.gov","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":true,"id":814808,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Minsley, Burke J. 0000-0003-1689-1306","orcid":"https://orcid.org/0000-0003-1689-1306","contributorId":248573,"corporation":false,"usgs":true,"family":"Minsley","given":"Burke","email":"","middleInitial":"J.","affiliations":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":814809,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kress, Wade 0000-0002-6833-028X","orcid":"https://orcid.org/0000-0002-6833-028X","contributorId":203539,"corporation":false,"usgs":true,"family":"Kress","given":"Wade","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":814810,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"LeBlanc, Denis R. 0000-0002-4646-2628","orcid":"https://orcid.org/0000-0002-4646-2628","contributorId":219907,"corporation":false,"usgs":true,"family":"LeBlanc","given":"Denis","email":"","middleInitial":"R.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":38175,"text":"Toxics Substances Hydrology Program","active":true,"usgs":true}],"preferred":true,"id":814811,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Adams, Ryan F. 0000-0001-7299-329X rfadams@usgs.gov","orcid":"https://orcid.org/0000-0001-7299-329X","contributorId":5499,"corporation":false,"usgs":true,"family":"Adams","given":"Ryan","email":"rfadams@usgs.gov","middleInitial":"F.","affiliations":[{"id":5064,"text":"Southeast Regional Director's Office","active":true,"usgs":true},{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":814812,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Johnson, Carole D. 0000-0001-6941-1578","orcid":"https://orcid.org/0000-0001-6941-1578","contributorId":245365,"corporation":false,"usgs":true,"family":"Johnson","given":"Carole D.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":814813,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70210535,"text":"70210535 - 2020 - Acris blanchardi (Blanchard's Cricket Frog), Predation","interactions":[],"lastModifiedDate":"2020-12-15T20:28:40.109354","indexId":"70210535","displayToPublicDate":"2020-06-09T11:16:57","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1898,"text":"Herpetological Review","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Acris blanchardi (Blanchard's Cricket Frog), Predation","title":"Acris blanchardi (Blanchard's Cricket Frog), Predation","docAbstract":"Invertebrates are well-known predators of amphibians with many documented cases of spiders preying upon anurans (reviewed in Toledo 2005. Herpetol. Rev. 36:395–400). Wolf spiders are known to feed on a variety of frogs, including those in the genus Acris (Blackburn et al. 2002. Herpetol. Rev. 33:299). Although typically terrestrial, wolf spiders have been found feeding on arboreal frogs ca. 1 m above the ground (Aucone and Card 2002. Herpetol. Rev. 33:48). To our knowledge, no records exist of a wolf spider feeding on a terrestrial frog at an elevated height. At 0113 h on 30 April 2019, we observed an adult female wolf spider (Tigrosa georgicola: Lycosidae) feeding on an adult Acris blanchardi ca. 1.5 m high on the trunk of a small tree at the edge of a pond in Sherburne Wildlife Management Area, St. Martin Parish, Louisiana, USA (30.424°N, 91.663°W; WGS 84; Fig. 1). The spider was positioned facing the ground and the partially digested frog was hanging from its mouthparts. The spider likely captured the frog on the ground near the edge of the water and retreated up the tree with its meal (Fig. 1B). Movement of spiders with prey from an initial point of capture is documented in wolf spiders (Aucone and Card 2002, op. cit.) and other large terrestrial spiders (Maffei et al. 2010. Herpetol. Notes 3:167–170). This behavior may minimize the vulnerability of the spider to predators. We thank Zack Lemann, Curator of Animal Collections at the Audubon Butterfly Garden and Insectarium, for spider identification.
","language":"English","publisher":"Society for the Study of Amphibians and Reptiles","usgsCitation":"Maldonado, B.R., Glorioso, B., and Kidder, R.P., 2020, Acris blanchardi (Blanchard's Cricket Frog), Predation: Herpetological Review, v. 51, no. 2.","productDescription":"1 p.","startPage":"296","ipdsId":"IP-112194","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":375469,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":375441,"type":{"id":15,"text":"Index Page"},"url":"https://ssarherps.org/herpetological-review-pdfs/"}],"country":"United States","state":"Louisiana","county":"St Martin Parish","otherGeospatial":"Sherburne Wildlife Management Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.73468112945557,\n 30.445306929719315\n ],\n [\n -91.70335292816162,\n 30.445306929719315\n ],\n [\n -91.70335292816162,\n 30.469685487622733\n ],\n [\n -91.73468112945557,\n 30.469685487622733\n ],\n [\n -91.73468112945557,\n 30.445306929719315\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"51","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Maldonado, Brittany R. 0000-0002-9737-6922","orcid":"https://orcid.org/0000-0002-9737-6922","contributorId":225150,"corporation":false,"usgs":true,"family":"Maldonado","given":"Brittany","email":"","middleInitial":"R.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":790559,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Glorioso, Brad 0000-0002-5400-7414","orcid":"https://orcid.org/0000-0002-5400-7414","contributorId":204397,"corporation":false,"usgs":true,"family":"Glorioso","given":"Brad","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":790560,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kidder, Raymond P. II 0000-0002-7102-788X","orcid":"https://orcid.org/0000-0002-7102-788X","contributorId":225151,"corporation":false,"usgs":true,"family":"Kidder","given":"Raymond","suffix":"II","email":"","middleInitial":"P.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":790561,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70211027,"text":"70211027 - 2020 - Changes in climate and land cover affect seasonal streamflow forecasts in the Rio Grande headwaters","interactions":[],"lastModifiedDate":"2023-03-27T17:19:48.95791","indexId":"70211027","displayToPublicDate":"2020-06-09T09:51:16","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Changes in climate and land cover affect seasonal streamflow forecasts in the Rio Grande headwaters","docAbstract":"Seasonal streamflow forecast bias, changes in climate, snowpack, and land cover, and the effects of these changes on relations between basin‐wide snowpack, SNOw TELemetry (SNOTEL) station snowpack, and seasonal streamflow were evaluated in the headwaters of the Rio Grande, Colorado. Results indicate that shifts in the seasonality of precipitation and changing climatology are consistent with periods of overprediction and underprediction in streamflow forecasts. Multiple linear regression of SNOTEL data, postcedent precipitation, and land‐cover changes explained 2%–18% more variability in streamflow prediction than using SNOTEL station data alone. Simulated basin‐wide snowpack from a physically based model had significant negative trends in snow water equivalent (−4.33 mm/yr) and snow‐covered area (−0.05%/yr) during the melt period April–June. Simulated streamflow from a precipitation‐runoff model increased an average 5% when the effects of bark beetle‐induced tree mortality were compared to a baseline simulation with static vegetation. The effects of a 2013 wildfire increased simulated seasonal streamflow an average 35% for 1–4 years postfire. The combined effects of climate and land‐cover changes on snowpack‐streamflow relations highlight the difficulty in seasonal streamflow forecasting, which has important implications for water‐resource management.
","language":"English","publisher":"American Water Resources Association","doi":"10.1111/1752-1688.12863","usgsCitation":"Penn, C.A., Clow, D.W., Sexstone, G.A., and Murphy, S.F., 2020, Changes in climate and land cover affect seasonal streamflow forecasts in the Rio Grande headwaters: Journal of the American Water Resources Association, v. 56, no. 5, p. 882-902, https://doi.org/10.1111/1752-1688.12863.","productDescription":"21 p.","startPage":"882","endPage":"902","ipdsId":"IP-109042","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":436937,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9B08S5N","text":"USGS data release","linkHelpText":"Model input and output for hydrologic simulations in the Rio Grande Headwaters, Colorado, using the Precipitation-Runoff Modeling System (PRMS)"},{"id":376258,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Rio Grande","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108,\n 37.25\n ],\n [\n -106,\n 37.25\n ],\n [\n -106,\n 38.25\n ],\n [\n -108,\n 38.25\n ],\n [\n -108,\n 37.25\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"56","issue":"5","noUsgsAuthors":false,"publicationDate":"2020-06-09","publicationStatus":"PW","contributors":{"authors":[{"text":"Penn, Colin A. 0000-0002-5195-2744 cpenn@usgs.gov","orcid":"https://orcid.org/0000-0002-5195-2744","contributorId":5336,"corporation":false,"usgs":true,"family":"Penn","given":"Colin","email":"cpenn@usgs.gov","middleInitial":"A.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":792475,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Clow, David W. 0000-0001-6183-4824 dwclow@usgs.gov","orcid":"https://orcid.org/0000-0001-6183-4824","contributorId":1671,"corporation":false,"usgs":true,"family":"Clow","given":"David","email":"dwclow@usgs.gov","middleInitial":"W.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":792476,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sexstone, Graham A. 0000-0001-8913-0546 sexstone@usgs.gov","orcid":"https://orcid.org/0000-0001-8913-0546","contributorId":5159,"corporation":false,"usgs":true,"family":"Sexstone","given":"Graham","email":"sexstone@usgs.gov","middleInitial":"A.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":792477,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Murphy, Sheila F. 0000-0002-5481-3635 sfmurphy@usgs.gov","orcid":"https://orcid.org/0000-0002-5481-3635","contributorId":1854,"corporation":false,"usgs":true,"family":"Murphy","given":"Sheila","email":"sfmurphy@usgs.gov","middleInitial":"F.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":792478,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70210525,"text":"70210525 - 2020 - Observations on the structure of Surtsey","interactions":[],"lastModifiedDate":"2020-06-15T17:33:02.052439","indexId":"70210525","displayToPublicDate":"2020-06-09T07:44:09","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3500,"text":"Surtsey Research","active":true,"publicationSubtype":{"id":10}},"title":"Observations on the structure of Surtsey","docAbstract":"Comparison of investigations of the 1979 and 2017 cored boreholes coupled with continued observations of the dynamic surface of Surtsey has modified our concepts of the subsurface structure of the volcano. A geometrical analysis of the 2017 vertical and inclined cores indicates that near-surface layering dips westerly, indicating that the boreholes are located inside the Surtur crater. In subaerial deposits, as well as in deep deposits below sea level and below the pre-Surtsey seafloor, there are zones of porous tuff that contain abundant pyroclasts with narrow rims of fine ash. These features, typical of near-surface deposits, could have been carried down the vent by downslumping during fluctuating explosive activity. They support the hypothesis that a broad diatreme underlies the Surtur vent. No major intrusions were encountered in the 2017 drilling except for coherent basalt in deep sub-seafloor deposits below the center of Surtur crater. The 2017 borehole temperature measurements indicate that the peak temperature in the vertical boreholes was 124 °C at 105 meters below the surface (m.b.s.) and that in the inclined hole it was 127 °C at 115 m.b.s. immediately after drilling. These peak temperatures are 72 meters apart horizontally yet closely resemble each other in shape and magnitude, suggesting a broad heat source. In addition, measurements in the inclined hole from 200 to 290 m.b.s. indicate a temperature of 60±2 °C. This is apparently residual heat from the volcanic action that created the diatreme. These facts cast doubt on the previous concept that the heat anomaly in the 1979 borehole was due to a nearby intrusion. Instead they suggest that heat would have been conducted down from the 85-meter-thick hot lava shield within the Surtur crater into a warm diatreme substrate containing original volcanic heat. As the conducted heat moved down into the water-saturated substrate it would have elevated the temperature above the boiling point curve, baked out water, and created a vapor-dominated system below sea level. Eventually loss of heat by boiling and rise of steam caused the vapor-dominated system to retreat upward. The resulting steam rose and warmed the tephra adjacent to the lava shields where it produced broad areas of palagonitized tuff.","language":"English","publisher":"European Geosciences Union","doi":"10.33112/surtsey.14.3","usgsCitation":"Moore, J.G., and Jackson, M.D., 2020, Observations on the structure of Surtsey: Surtsey Research, v. 14, p. 33-45, https://doi.org/10.33112/surtsey.14.3.","productDescription":"13 p.","startPage":"33","endPage":"45","ipdsId":"IP-113720","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":488754,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.33112/surtsey.14.3","text":"Publisher Index Page"},{"id":375458,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Iceland","otherGeospatial":"Surtsey","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -20.63953399658203,\n 63.29139621002748\n ],\n [\n -20.569496154785156,\n 63.29139621002748\n ],\n [\n -20.569496154785156,\n 63.31391630233039\n ],\n [\n -20.63953399658203,\n 63.31391630233039\n ],\n [\n -20.63953399658203,\n 63.29139621002748\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"14","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Moore, James G. 0000-0002-7543-2401 jmoore@usgs.gov","orcid":"https://orcid.org/0000-0002-7543-2401","contributorId":2892,"corporation":false,"usgs":true,"family":"Moore","given":"James","email":"jmoore@usgs.gov","middleInitial":"G.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":790522,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jackson, Marie D.","contributorId":225145,"corporation":false,"usgs":false,"family":"Jackson","given":"Marie","email":"","middleInitial":"D.","affiliations":[{"id":13028,"text":"Department of Geology and Geophysics, University of Utah","active":true,"usgs":false}],"preferred":false,"id":790523,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70211289,"text":"70211289 - 2020 - Nowcasting methods for determining microbiological water quality at recreational beaches and drinking-water source waters","interactions":[],"lastModifiedDate":"2020-07-22T15:05:33.044537","indexId":"70211289","displayToPublicDate":"2020-06-06T10:03:16","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2390,"text":"Journal of Microbiological Methods","active":true,"publicationSubtype":{"id":10}},"title":"Nowcasting methods for determining microbiological water quality at recreational beaches and drinking-water source waters","docAbstract":"Nowcasts are tools used to provide timely and accurate water-quality assessments of threats to drinking-water and recreational resources from fecal contamination or cyanobacterial harmful algal blooms. They use mathematical models and techniques to provide near-real-time estimates of fecal-indicator bacteria (FIB) and cyanotoxin concentrations. Techniques include logic-based thresholds, decision trees (built with machine learning), multiple linear and binary logistic regression, artificial neural networks, and process-based deterministic models. The type of site (freshwater, marine, or river) and dependent variable (FIB or cyanotoxin) dictate which explanatory variables are used in models. Nowcast systems notify the public of associated public-health risks and can also be used to manage data for FIB models; work is ongoing to incorporate cyanotoxin models into some nowcasts. The Great Lakes NowCast in the USA has been operational since 2010 and includes 25 lake beaches and one recreational river site. Examples of other operational FIB nowcasts are described for locations in the USA and around the world. In many cases, models predicted exceedances of FIB standards with accuracies as good as or better than using the previous measured FIB concentration (persistence method). Accuracy and timeliness are vital to beach management decisions that protect public health and support the local recreation-driven economy. Nowcasts benefit the public by providing estimates of water-quality conditions in near-real-time. Managers can use nowcasts at recreational and drinking-water treatment plant sites when FIB or cyanotoxins are projected to be elevated to target sample collection, to provide near-real-time recreational advisories to the public, or to preemptively optimize drinking-water treatments or change intake options to mitigate possible adverse effects on drinking-water quality.","language":"English","publisher":"Elsevier","doi":"10.1016/j.mimet.2020.105970","usgsCitation":"Francy, D.S., Brady, A.M., Cicale, J.R., Dalby, H.D., and Stelzer, E., 2020, Nowcasting methods for determining microbiological water quality at recreational beaches and drinking-water source waters: Journal of Microbiological Methods, v. 175, 105970, 11 p., https://doi.org/10.1016/j.mimet.2020.105970.","productDescription":"105970, 11 p.","ipdsId":"IP-117123","costCenters":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":456480,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.mimet.2020.105970","text":"Publisher Index Page"},{"id":376634,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"175","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Francy, Donna S. 0000-0001-9229-3557 dsfrancy@usgs.gov","orcid":"https://orcid.org/0000-0001-9229-3557","contributorId":1853,"corporation":false,"usgs":true,"family":"Francy","given":"Donna","email":"dsfrancy@usgs.gov","middleInitial":"S.","affiliations":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":793533,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brady, Amie M.G. 0000-0002-7414-0992 amgbrady@usgs.gov","orcid":"https://orcid.org/0000-0002-7414-0992","contributorId":2544,"corporation":false,"usgs":true,"family":"Brady","given":"Amie","email":"amgbrady@usgs.gov","middleInitial":"M.G.","affiliations":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":793534,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cicale, Jessica R. 0000-0002-0008-4051","orcid":"https://orcid.org/0000-0002-0008-4051","contributorId":208157,"corporation":false,"usgs":true,"family":"Cicale","given":"Jessica","email":"","middleInitial":"R.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":793535,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dalby, Harrison D 0000-0001-6048-3217","orcid":"https://orcid.org/0000-0001-6048-3217","contributorId":228841,"corporation":false,"usgs":true,"family":"Dalby","given":"Harrison","email":"","middleInitial":"D","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":793536,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stelzer, Erin A. 0000-0001-7645-7603","orcid":"https://orcid.org/0000-0001-7645-7603","contributorId":220549,"corporation":false,"usgs":true,"family":"Stelzer","given":"Erin A.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":793537,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70220875,"text":"70220875 - 2020 - Occurrence and geochemistry of lead-210 and polonium-210 radionuclides in public-drinking-water supplies from principal aquifers of the United States","interactions":[],"lastModifiedDate":"2021-05-27T12:38:43.595169","indexId":"70220875","displayToPublicDate":"2020-06-05T07:29:25","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":7760,"text":"Environmental Science Technology","active":true,"publicationSubtype":{"id":10}},"title":"Occurrence and geochemistry of lead-210 and polonium-210 radionuclides in public-drinking-water supplies from principal aquifers of the United States","docAbstract":"On the basis of lifetime cancer risks, lead-210 (210Pb) and polonium-210 (210Po) ≥ 1.0 and 0.7 pCi/L (picocuries per liter), respectively, in drinking-water supplies may pose human-health concerns. 210Pb and 210Po were detected at concentrations greater than these thresholds at 3.7 and 1.5%, respectively, of filtered untreated groundwater samples from 1263 public-supply wells in 19 principal aquifers across the United States. Nationally, 72% of samples with radon-222 (222Rn) concentrations > 4000 pCi/L had 210Pb ≥ 1.0 pCi/L. 210Pb is mobilized by alpha recoil associated with the decay of 222Rn and short-lived progeny. 210Pb concentrations ≥ 1.0 pCi/L occurred most frequently where acidic groundwaters inhibited 210Pb readsorption (felsic-crystalline rocks) and where reducing alkaline conditions favored dissolution of iron–manganese- (Fe–Mn-) oxyhydroxides (which adsorb 210Pb) and formation of lead–carbonate complexes (enhancing lead (Pb) mobility). 210Po concentrations ≥ 0.7 pCi/L occurred almost exclusively in confined Coastal Plain aquifers where old (low percent-modern carbon-14) groundwaters were reducing, with high pH (>7.5) and high sodium/chloride (Na/Cl) ratios resulting from cation exchange. In high-pH environments, aqueous polonium (Po) is poorly sorbed, occurring as dihydrogen polonate (H2PoO3(aq)) or, under strongly reducing conditions, as a hydrogen-polonide anion (HPo–). Fe–Mn- and sulfate-reduction and cation-exchange processes may mobilize polonium from mineral surfaces. Po2+ occurrence in low-to-neutral-pH waters is attenuated by adsorption.
Prior to emergence as fry, salmonid embryos incubating within gravel nests called “redds” are vulnerable to substrate mobilization and lowering of the streambed, a process termed “streambed scour,” during floods. Water managers regulating discharge in salmonid-bearing rivers need information about the magnitude of discharge during which the scour of substrate surrounding salmonid redds occurs. The time when scour occurs, however, is difficult to measure and usually poorly constrained. The South Fork Tolt River in western Washington supplies the City of Seattle with hydroelectric power and about 40 percent of its municipal water needs, while providing spawning habitat for two salmonid species listed under the Endangered Species Act: Chinook salmon (Oncorhynchus tshawytscha) and steelhead trout (O. mykiss). The U.S. Geological Survey, in cooperation with Seattle City Light and Seattle Public Utilities, began a study in 2015 using accelerometer scour monitors (ASM) to characterize the timing of and hydrologic conditions associated with streambed scour at the depth of incubating salmonid embryos in the South Fork Tolt River. Prior to this study, operational thresholds for peak discharge on the South Fork Tolt River were 350 cubic feet per second (cfs) in the upper part of the river and 550 cfs in the lower part of the river as measured at USGS streamgages 12148000 and 12148300, respectively. These thresholds were developed from the peak discharge associated with observations of the flattening of redd structure and not from direct measurement of scour at the depth of egg pockets within redds. Accelerometer scour monitors were deployed at the level of salmonid egg pockets in spawning habitat of the South Fork Tolt River to record the temporal pattern of streambed scour at the depth of incubating salmon eggs during fall and winter flood seasons of water years (WY) 2016 and 2017. Thirteen of 48 ASMs deployed during the WY 2016 flood season recorded scour attributed to high streamflow when discharge measured at USGS streamgage 12148300 (the lower river streamgage used as an index gage) was between 969 and 1,360 cfs. Local discharge at individual scour sites varied depending on the timing of tributary inputs and downstream transport of water. During the subsequent flood season in WY 2017, peak discharge at the index gage reached 809 cfs. None of the 38 ASMs deployed recorded scour attributed to streamflow alone, although 10 ASMs recorded localized bed movement attributed to spawning activity of fish. Most scour at the depth of redds measured during WY 2016 occurred at or before peak flood discharge consistent with previous redd scour studies. The lack of scour measured in WY 2017 when peak discharge (809 cfs) was less than the minimum discharge when scour occurred in WY 2016 (969 cfs) suggests minimal to no scour of egg pockets in salmonid redds when discharge is less than 809 cfs.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205044","collaboration":"Prepared in cooperation with Seattle City Light and Seattle Public Utilities","usgsCitation":"Gendaszek, A.S., Ablow, E., and Marks, D., 2020, Streambed scour of salmon (Oncorhynchus spp.) and steelhead (Oncorhynchus mykiss) redds in the South Fork Tolt River, King County, Washington: U.S. Geological Survey Scientific Investigations Report 2020–5044, 20 p., https://doi.org/10.3133/sir20205044.","productDescription":"iv, 20 p.","onlineOnly":"Y","ipdsId":"IP-110809","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":375381,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5044/coverthb.jpg"},{"id":375382,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5044/sir20205044.pdf","text":"Report","size":"3 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Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
Hyperpigmented melanistic skin lesions (HPMLs) of smallmouth bass Micropterus dolomieu are observed in the Potomac and Susquehanna rivers, Chesapeake Bay watershed, USA. Routine, nonlethal population surveys were conducted at 8 sites on the mainstem Susquehanna River and 9 on the Juniata River, a tributary of the Susquehanna River, between 2012 and 2018, and the prevalence of HPMLs was documented. A total of 4078 smallmouth bass were collected from the mainstem Susquehanna River and 6478 from the Juniata River. Lesions were primarily seen in bass greater than 200 mm, and prevalence in the Susquehanna River (8%) was higher (p < 0.001) than in the Juniata River (2%). As part of ongoing fish health monitoring projects, smallmouth bass were collected at additional sites, primarily tributaries of the Susquehanna (n = 758) and Potomac (n = 545) rivers between 2013 and 2018. Prevalence in the Susquehanna River (13%) was higher (p < 0.001) than the Potomac (3%). Microscopically, HPMLs were characterized by an increased number of melanocytes in the epidermis or within the dermis and epidermis. RNAseq analyses of normal and melanistic skin identified 3 unique sequences in HPMLs. Two were unidentified and the third was a viral helicase (E1). Transcript abundance in 16 normal skin samples and 16 HPMLs showed upregulation of genes associated with melanogenesis and cell proliferation in HPMLs. The E1 transcript was detected in 12 of the 16 melanistic areas but in no samples from normal skin. Further research will be necessary to identify the putative new virus and determine its role in melanocyte proliferation.
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Georgia","active":true,"usgs":false}],"preferred":false,"id":794679,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smith, Geoffrey D.","contributorId":224595,"corporation":false,"usgs":false,"family":"Smith","given":"Geoffrey D.","affiliations":[{"id":40898,"text":"Pennsylvania Fish & Boat Commission","active":true,"usgs":false}],"preferred":false,"id":794680,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sperry, Adam 0000-0002-4815-3730","orcid":"https://orcid.org/0000-0002-4815-3730","contributorId":203243,"corporation":false,"usgs":true,"family":"Sperry","given":"Adam","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":794681,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Iwanowicz, Luke R. 0000-0002-1197-6178 liwanowicz@usgs.gov","orcid":"https://orcid.org/0000-0002-1197-6178","contributorId":190787,"corporation":false,"usgs":true,"family":"Iwanowicz","given":"Luke","email":"liwanowicz@usgs.gov","middleInitial":"R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":794682,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70211202,"text":"70211202 - 2020 - Four-dimensional surface motions of the Slumgullion landslide and quantification of hydrometeorological forcing","interactions":[],"lastModifiedDate":"2020-07-17T17:25:42.112539","indexId":"70211202","displayToPublicDate":"2020-06-03T12:18:06","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2842,"text":"Nature Communications","active":true,"publicationSubtype":{"id":10}},"title":"Four-dimensional surface motions of the Slumgullion landslide and quantification of hydrometeorological forcing","docAbstract":"Landslides modify the natural landscape and cause fatalities and property damage worldwide. Quantifying landslide dynamics is challenging due to the stochastic nature of the environment. With its large area of ~1 km2 and perennial motions at ~10–20 mm per day, the Slumgullion landslide in Colorado, USA, represents an ideal natural laboratory to better understand landslide behavior. Here, we use hybrid remote sensing data and methods to recover the four-dimensional surface motions during 2011–2018. We refine the boundaries of an area of ~0.35 km2 below the crest of the prehistoric landslide. We construct a mechanical framework to quantify the rheology, subsurface channel geometry, mass flow rate, and spatiotemporally dependent pore-water pressure feedback through a joint analysis of displacement and hydrometeorological measurements from ground, air and space. Our study demonstrates the importance of remotely characterizing often inaccessible, dangerous slopes to better understand landslides and other quasi-static mass fluxes in natural and industrial environments, which will ultimately help reduce associated hazards.
","language":"English","publisher":"Nature","doi":"10.1038/s41467-020-16617-7","usgsCitation":"Hu, X., Bürgmann, R., Schulz, W.H., and Fielding, E.J., 2020, Four-dimensional surface motions of the Slumgullion landslide and quantification of hydrometeorological forcing: Nature Communications, v. 11, 2792, 9 p., https://doi.org/10.1038/s41467-020-16617-7.","productDescription":"2792, 9 p.","ipdsId":"IP-117085","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":456500,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41467-020-16617-7","text":"Publisher Index Page"},{"id":436941,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TCQDD5","text":"USGS data release","linkHelpText":"Data from in-situ displacement monitoring, Slumgullion landslide, Hinsdale County, Colorado"},{"id":376466,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Slumgullion landslide","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107.30132102966309,\n 37.97600347500009\n ],\n [\n -107.22647666931152,\n 37.97600347500009\n ],\n [\n -107.22647666931152,\n 38.01212375706868\n ],\n [\n -107.30132102966309,\n 38.01212375706868\n ],\n [\n -107.30132102966309,\n 37.97600347500009\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","noUsgsAuthors":false,"publicationDate":"2020-06-03","publicationStatus":"PW","contributors":{"authors":[{"text":"Hu, Xie","contributorId":177306,"corporation":false,"usgs":false,"family":"Hu","given":"Xie","email":"","affiliations":[],"preferred":false,"id":793138,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bürgmann, Roland","contributorId":195087,"corporation":false,"usgs":false,"family":"Bürgmann","given":"Roland","affiliations":[],"preferred":false,"id":793139,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schulz, William H. 0000-0001-9980-3580 wschulz@usgs.gov","orcid":"https://orcid.org/0000-0001-9980-3580","contributorId":942,"corporation":false,"usgs":true,"family":"Schulz","given":"William","email":"wschulz@usgs.gov","middleInitial":"H.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":793140,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fielding, Eric J.","contributorId":218096,"corporation":false,"usgs":false,"family":"Fielding","given":"Eric","email":"","middleInitial":"J.","affiliations":[{"id":39742,"text":"Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA.","active":true,"usgs":false}],"preferred":false,"id":793141,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70228370,"text":"70228370 - 2020 - Granular measures of agricultural land use influence lake nitrogen and phosphorus differently at macroscales","interactions":[],"lastModifiedDate":"2022-02-09T17:32:13.635678","indexId":"70228370","displayToPublicDate":"2020-06-02T11:20:12","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Granular measures of agricultural land use influence lake nitrogen and phosphorus differently at macroscales","docAbstract":"Agricultural land use is typically associated with high stream nutrient concentrations and increased nutrient loading to lakes. For lakes, evidence for these associations mostly comes from studies on individual lakes or watersheds that relate concentrations of nitrogen (N) or phosphorus (P) to aggregate measures of agricultural land use, such as the proportion of land used for agriculture in a lake’s watershed. However, at macroscales (i.e., in hundreds to thousands of lakes across large spatial extents), there is high variability around such relationships and it is unclear whether considering more granular (or detailed) agricultural data, such as fertilizer application, planting of specific crops, or the extent of near-stream cropping, would improve prediction and inform understanding of lake nutrient drivers. Furthermore, it is unclear whether lake N and P would have different relationships to such measures and whether these relationships would vary by region, since regional variation has been observed in prior studies using aggregate measures of agriculture. To address these knowledge gaps, we examined relationships between granular measures of agricultural activity and lake total phosphorus (TP) and total nitrogen (TN) concentrations in 928 lakes and their watersheds in the Northeastern and Midwest U.S. using a Bayesian hierarchical modeling approach. We found that both lake TN and TP concentrations were related to these measures of agriculture, especially near-stream agriculture. The relationships between measures of agriculture and lake TN concentrations were more regionally variable than those for TP. Conversely, TP concentrations were more strongly related to lake-specific measures like depth and watershed hydrology relative to TN. Our finding that lake TN and TP concentrations have different relationships with granular measures of agricultural activity has implications for the design of effective and efficient policy approaches to maintain and improve water quality.
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M.","contributorId":275322,"corporation":false,"usgs":false,"family":"Cobourn","given":"K.","email":"","middleInitial":"M.","affiliations":[{"id":36967,"text":"Virginia Tech University","active":true,"usgs":false}],"preferred":false,"id":833992,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Wagner, Tyler 0000-0003-1726-016X twagner@usgs.gov","orcid":"https://orcid.org/0000-0003-1726-016X","contributorId":1050,"corporation":false,"usgs":true,"family":"Wagner","given":"Tyler","email":"twagner@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":833987,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Weathers, K. C.","contributorId":275323,"corporation":false,"usgs":false,"family":"Weathers","given":"K. 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A.","contributorId":275324,"corporation":false,"usgs":false,"family":"Soranno","given":"P.","email":"","middleInitial":"A.","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":833994,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70210353,"text":"ofr20201039 - 2020 - Dye-tracing plan for verifying the Kansas River time-of-travel model","interactions":[],"lastModifiedDate":"2020-06-04T15:33:07.235685","indexId":"ofr20201039","displayToPublicDate":"2020-06-02T10:13:06","publicationYear":"2020","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":"2020-1039","displayTitle":"Dye-Tracing Plan for Verifying the Kansas River Time-of-Travel Model","title":"Dye-tracing plan for verifying the Kansas River time-of-travel model","docAbstract":"The Kansas River provides drinking water for multiple cities in northeastern Kansas and is used for recreational purposes. Thus, improving the scientific knowledge of streamflow velocities and traveltimes will greatly aid in water-treatment plans and response to critical events and threats to water supplies. Dye-tracer studies are usually done to enhance knowledge of transport characteristics, which include streamflow velocities, traveltimes, and dispersion rates, within a river system. To achieve this in the Kansas River, rhodamine water-tracing dye is planned to be injected into the Kansas River during three different flow ranges at three locations: Manhattan, Topeka, and Eudora. The primary purpose of doing a dye-tracer study in the Kansas River is to calibrate a time-of-travel model used for estimating streamflow velocities and traveltimes, which can be used by the public as well as drinking water suppliers to protect water resources and public-water supplies.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201039","collaboration":"Prepared in cooperation with the Kansas Water Office, Kansas Department of Health and Environment, The Nature Conservancy, City of Topeka, Johnson County WaterOne, City of Manhattan, and City of Olathe","usgsCitation":"Davis, C.A., Lukasz, B.S., and May, M.R., 2020, Dye-tracing plan for verifying the Kansas River time-of-travel model: U.S. Geological Survey Open-File Report 2020–1039, 10 p., https://doi.org/10.3133/ofr20201039.","productDescription":"iv, 10 p.","numberOfPages":"18","onlineOnly":"Y","ipdsId":"IP-107718","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":375197,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1039/ofr20201039.pdf","text":"Report","size":"1.58 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020–1039"},{"id":375196,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1039/coverthb.jpg"}],"country":"United States","state":"Kansas","otherGeospatial":"Kansas River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.1630859375,\n 38.53097889440024\n ],\n [\n -94.4384765625,\n 38.53097889440024\n ],\n [\n -94.4384765625,\n 39.926588421909436\n ],\n [\n -97.1630859375,\n 39.926588421909436\n ],\n [\n -97.1630859375,\n 38.53097889440024\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Kansas Water Science Center
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1217 Biltmore Drive
Lawrence, KS 66049
This paper outlines the development and demonstration of a new tool, TOUGH2–ChemPlugin (T2CPI) for predicting rock–water–CO2 interaction following injection of supercritical CO2 into a heterogeneous carbonate system. Specifically, modeling capabilities of TOUGH2, which examines multiphase flow and supercritical CO2 behavior, were combined with the geochemical modeling capabilities of The Geochemist’s Workbench® (GWB), using ChemPluginTM. ChemPlugin is a self-linking re-entrant software object that, when coupled to a transport simulator, retains the flow and transport capabilities of the simulator but enables incorporation of reactive chemistry via GWB. To test and assess the capabilities of T2CPI, results from T2CPI simulations were compared to those of TOUGHREACT, using the same carbonate reservoir parameters (based on the Dollar Bay Formation of the South Florida Basin). Overall, results of simulations from TOUGHREACT and T2CPI were very similar for nearly all evaluated parameters. Dissimilarities between the two programs included qualitative differences in how TOUGHREACT and T2CPI predicted calcite dissolution and the subsequent spatial pattern of the porosity gain caused by how each handles evaporation of water near the injection point. The TOUGHREACT program is a proven, widely used tool for evaluating CO2–brine–rock interaction following supercritical CO2 injection. The T2CPI tool offers similar capabilities and strengths of TOUGHREACT, with the ability to read in and use databases for a wide range of activity coefficient types. This program also has abilities to use a wide range of kinetic constraints, define those kinetic constraints with scripts or compiled libraries, account for colloidal transport, and/or account for a wide range of surface sorption models.
","language":"English","publisher":"AAPG","doi":"10.1306/eg.08061919003","collaboration":"None","usgsCitation":"Roberts-Ashby, T., Berger, P.M., Cunningham, J.A., Kumar, R., and Blondes, M., 2020, Modeling geologic sequestration of carbon dioxide in a deep saline carbonate reservoir with TOUGH2–ChemPlugin, a new tool for reactive transport modeling: Environmental Geosciences, v. 27, no. 2, p. 103-116, https://doi.org/10.1306/eg.08061919003.","productDescription":"14 p.","startPage":"103","endPage":"116","ipdsId":"IP-098127","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":375280,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Dollar Bay Formation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.18298339843749,\n 24.297040469311558\n ],\n [\n -79.73876953125,\n 24.297040469311558\n ],\n [\n -79.73876953125,\n 27.81478637667891\n ],\n [\n -83.18298339843749,\n 27.81478637667891\n ],\n [\n -83.18298339843749,\n 24.297040469311558\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"27","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Roberts-Ashby, Tina L. 0000-0003-2940-1740","orcid":"https://orcid.org/0000-0003-2940-1740","contributorId":205925,"corporation":false,"usgs":true,"family":"Roberts-Ashby","given":"Tina L.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":785375,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Berger, Peter M.","contributorId":223538,"corporation":false,"usgs":false,"family":"Berger","given":"Peter","email":"","middleInitial":"M.","affiliations":[{"id":40735,"text":"Illionois State Geological Survey","active":true,"usgs":false}],"preferred":false,"id":785376,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cunningham, Jeffrey A.","contributorId":223539,"corporation":false,"usgs":false,"family":"Cunningham","given":"Jeffrey","email":"","middleInitial":"A.","affiliations":[{"id":40736,"text":"Dept of Civil and Environmental Engineering, University of South Florida","active":true,"usgs":false}],"preferred":false,"id":785377,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kumar, Ram","contributorId":223540,"corporation":false,"usgs":false,"family":"Kumar","given":"Ram","email":"","affiliations":[{"id":40737,"text":"Dept. of Chemical and Biomedical Engineering, Univ. of South Florida","active":true,"usgs":false}],"preferred":false,"id":790254,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Blondes, Madalyn S. 0000-0003-0320-0107 mblondes@usgs.gov","orcid":"https://orcid.org/0000-0003-0320-0107","contributorId":3598,"corporation":false,"usgs":true,"family":"Blondes","given":"Madalyn S.","email":"mblondes@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":785378,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70211970,"text":"70211970 - 2020 - Laboratory trials to evaluate carbon dioxide as a potential behavioral control method for invasive red swamp (Procambarus clarkii) and rusty crayfish (Faxonius rusticus)","interactions":[],"lastModifiedDate":"2020-08-12T20:41:03.507096","indexId":"70211970","displayToPublicDate":"2020-06-01T15:39:20","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Laboratory trials to evaluate carbon dioxide as a potential behavioral control method for invasive red swamp (Procambarus clarkii) and rusty crayfish (Faxonius rusticus)","title":"Laboratory trials to evaluate carbon dioxide as a potential behavioral control method for invasive red swamp (Procambarus clarkii) and rusty crayfish (Faxonius rusticus)","docAbstract":"Few effective strategies are available to control invasive crayfishes. Carbon dioxide (CO2) acts as a behavioral deterrent for invasive fishes and could be a useful crayfish control tool. The objective of this laboratory study was to quantify CO2 concentrations that caused red swamp crayfish (RSC; Procambarus clarkii) and rusty crayfish (RYC; Faxonius rusticus) avoidance behavior, altered emergence behavior, and caused loss of equilibrium. Behavioral endpoints were quantified under light and dark conditions and at 10 and 24 °C. Avoidance responses from both species varied widely. Under light conditions, 35 mg/L CO2 was needed to induce the first avoidance shuttle in both crayfish species at 10 °C. CO2 concentrations of 42 mg/L for RYC and 46 mg/L for RSC were required for first shuttle at 24 °C. The first avoidance shuttle was induced at 37 mg/L CO2 for RYC and 54 mg/L CO2 for RSC at 10 °C in the dark. At 24 °C, 44 mg/L CO2 was required for first shuttle for both species. Less CO2 was needed to cause the last avoidance shuttle in RYC compared to RSC at both temperatures and under both lighting conditions. RSC emergence occurred at 418 ± 77 mg/L CO2, and loss of equilibrium occurred for both species at 1,231 ± 201 mg/L CO2. RYC appeared to be more sensitive than RSC to CO2, but behavior did not differ among light and water temperature treatments. These results demonstrate that CO2 alters crayfish behavior. The CO2 concentrations identified during this study may inform field testing to develop CO2 as a potential control tool for invasive crayfishes.
","language":"English","publisher":"REABIC","doi":"10.3391/mbi.2020.11.2.06","usgsCitation":"Fredricks, K.T., Tix, J., Smerud, J.R., and Cupp, A.R., 2020, Laboratory trials to evaluate carbon dioxide as a potential behavioral control method for invasive red swamp (Procambarus clarkii) and rusty crayfish (Faxonius rusticus): Biological Invasions, v. 11, no. 2, p. 259-278, https://doi.org/10.3391/mbi.2020.11.2.06.","productDescription":"20 p.","startPage":"259","endPage":"278","ipdsId":"IP-102493","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":456537,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3391/mbi.2020.11.2.06","text":"Publisher Index Page"},{"id":436946,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9R7AQVM","text":"USGS data release","linkHelpText":"Evaluation of dissolved carbon dioxide (CO2) as a non-physical deterrent to invasive Red Swamp Crayfish (Procambarus clarkii) and Rusty Crayfish (Faxonius rusticus): Data"},{"id":377437,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"11","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Fredricks, Kim T. 0000-0003-2363-7891 kfredricks@usgs.gov","orcid":"https://orcid.org/0000-0003-2363-7891","contributorId":173994,"corporation":false,"usgs":true,"family":"Fredricks","given":"Kim","email":"kfredricks@usgs.gov","middleInitial":"T.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":796020,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tix, John A.","contributorId":126766,"corporation":false,"usgs":false,"family":"Tix","given":"John A.","affiliations":[{"id":6602,"text":"Great Lakes Science Center, Hammond Bay Biological Station","active":true,"usgs":false}],"preferred":false,"id":796021,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Smerud, Justin R. 0000-0003-4385-7437 jrsmerud@usgs.gov","orcid":"https://orcid.org/0000-0003-4385-7437","contributorId":5031,"corporation":false,"usgs":true,"family":"Smerud","given":"Justin","email":"jrsmerud@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":796022,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cupp, Aaron R. 0000-0001-5995-2100 acupp@usgs.gov","orcid":"https://orcid.org/0000-0001-5995-2100","contributorId":5162,"corporation":false,"usgs":true,"family":"Cupp","given":"Aaron","email":"acupp@usgs.gov","middleInitial":"R.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":796023,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70209091,"text":"sir20205026 - 2020 - Application of the Precipitation-Runoff Modeling System (PRMS) to simulate near-native streamflow in the Upper Rio Grande Basin","interactions":[],"lastModifiedDate":"2020-09-01T12:26:51.639849","indexId":"sir20205026","displayToPublicDate":"2020-06-01T14:36:39","publicationYear":"2020","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":"2020-5026","displayTitle":"Application of the Precipitation-Runoff Modeling System (PRMS) To Simulate Near-Native Streamflow in the Upper Rio Grande Basin","title":"Application of the Precipitation-Runoff Modeling System (PRMS) to simulate near-native streamflow in the Upper Rio Grande Basin","docAbstract":"The U.S. Geological Survey’s Precipitation-Runoff Modeling System (PRMS) is widely used to simulate the effects of climate, topography, land cover, and soils on landscape-level hydrologic response and streamflow. This study developed, calibrated, and assessed a PRMS model that simulates near-native or naturalized streamflow conditions in the Upper Rio Grande Basin. A PRMS model framework of 1,021 hydrologic response units was constructed for the basin. Subbasins within the larger Upper Rio Grande Basin range from snow-dominated northern basins to monsoon driven southern basins. The 1,021 hydrologic response units were grouped into 133 subareas within the basin, and solar radiation and potential evapotranspiration data were used to calibrate corresponding PRMS parameters in each subarea independently. Nine subbasins with streamgages distributed across the basin were identified as “near-native” subbasins, or those basins with low anthropogenic disturbance. Model parameters that affect streamflow were calibrated for the near-native subbasins, and the calibrated parameters were distributed to the remaining hydrologic response units on the basis of terrain, soil, and vegetation conditions linked to a distribution and weighting algorithm developed for this study. The parameter distribution method was validated in three of the nine near-native subbasins. Calibration results demonstrated that the PRMS model developed in this study with distributed model parameters for the entire Upper Rio Grande Basin was successful in applying local information to improve model performance over the National Hydrologic Model, and that the new model is appropriate to use to simulate near-native conditions throughout the basin. The result is a model that can simulate naturalized flow and other variables that affect the water budget (including soil moisture, evapotranspiration, recharge) at the daily time step for current and future climate conditions, and that can also be used in conjunction with other models developed for the basin.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20205026","collaboration":"U.S. Geological Survey National Water Census and Water Availability and Use Science Program","usgsCitation":"Chavarria, S.B., Moeser, C.D., and Douglas-Mankin, K.R., 2020, Application of the Precipitation-Runoff Modeling System (PRMS) to simulate near-native streamflow in the Upper Rio Grande Basin: U.S. Geological Survey Scientific Investigations Report 2020–5026, 38 p., https://doi.org/10.3133/sir20205026.","productDescription":"Report: vi, 38 p.; Data Release","numberOfPages":"48","onlineOnly":"Y","ipdsId":"IP-111974","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":436948,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ML93QB","text":"USGS data release","linkHelpText":"Hydrologic simulations using projected climate data as input to the Precipitation-Runoff Modeling System (PRMS) in the Upper Rio Grande Basin"},{"id":375137,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YOPYW7","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Input and output data for the application of the Precipitation-Runoff Modeling System (PRMS) to simulate near-native streamflow in the Upper Rio Grande Basin"},{"id":375136,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2020/5026/sir20205026.pdf","text":"Report","size":"15.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2020–5026"},{"id":375135,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2020/5026/coverthb.jpg"}],"country":"United States","otherGeospatial":"Upper Rio Grande Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.74316406249999,\n 31.466153715024294\n ],\n [\n -106.0400390625,\n 31.052933985705163\n ],\n [\n -105.380859375,\n 30.90222470517144\n ],\n [\n -105.0732421875,\n 31.12819929911196\n ],\n [\n -105.5126953125,\n 32.175612478499325\n ],\n [\n -105.2490234375,\n 32.80574473290688\n ],\n [\n -105.732421875,\n 33.211116472416855\n ],\n [\n -105.16113281249999,\n 33.797408767572485\n ],\n [\n -104.8974609375,\n 34.66935854524543\n ],\n [\n -105.380859375,\n 35.460669951495305\n ],\n [\n -104.5458984375,\n 36.80928470205937\n ],\n [\n -104.94140625,\n 38.03078569382294\n ],\n [\n -106.34765625,\n 38.54816542304656\n ],\n [\n -107.314453125,\n 37.92686760148135\n ],\n [\n -106.8310546875,\n 37.33522435930639\n ],\n [\n -108.06152343749999,\n 35.99578538642032\n ],\n [\n -107.75390625,\n 34.488447837809304\n ],\n [\n -108.19335937499999,\n 33.61461929233378\n ],\n [\n -108.984375,\n 32.65787573695528\n ],\n [\n -108.80859375,\n 31.541089879585808\n ],\n [\n -108.45703125,\n 31.27855085894653\n ],\n [\n -107.7978515625,\n 32.287132632616384\n ],\n [\n -107.05078125,\n 32.39851580247402\n ],\n [\n -106.74316406249999,\n 31.466153715024294\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Mexico Water Science Center
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This project was funded by the Louisiana Trustee Implementation Group (LA TIG) to support decisions related to investments in long-term monitoring. The LA TIG seeks to ensure long-term monitoring informs coastal restoration activities with the goal of sustaining and improving fisheries impacted by the Deepwater Horizon (DWH) Oil Spill. The project objective was to compare nekton catch across an estuarine gradient using different sampling gear with the goal of identifying trade-offs among nekton sampling approaches. To accomplish this objective, Louisiana Department of Wildlife and Fisheries (LDWF), The Water Institute of the Gulf (the Institute), Dynamic Solutions, LLC, Louisiana State University Agricultural Center (LSU AgCenter), and the U.S. Geological Survey (USGS) completed a field gear comparison study from 2018 to 2019. This work compared electrofisher and seine sampling at 12 fixed stations in Barataria Basin using data collected by LDWF. In addition, and in conjunction with LDWF monthly sampling, the same 12 fixed stations were sampled in May 2019 using a throw trap to compare nekton catch and assemblages collected with the throw trap, seine and electrofisher. LDWF has been conducting seine sampling since 1986, and seine data are used by the State of Louisiana to assess juvenile shrimp, crab and fish abundances, sizes and overall assemblages. In 2018, LDWF began conducting electrofisher sampling at 12 Barataria Basin seine stations in order to determine if the two gear types sample similar species and assemblages for potential future replacement of long-term seine sampling with electrofishing. Throw traps were included as they provide density estimates, which are ultimately the desired statistic used in modeling trophic webs, and are used in assessing habitat restoration outcomes.
The project compared the nekton catch and assemblages collected using seine, electrofisher, and throw trap data from marsh edge habitats located across the estuarine gradient in Barataria Basin. Specifically, catch per unit effort (CPUE), species richness, species-specific total length (mm) distribution and nekton assemblages were compared between gear types. The first dataset was collected in May 2019 with throw trap (Appendix A), seine (LDWF data), and electrofisher (LDWF data) gear, and the second dataset (collected by LDWF) spanned 14 months of seine and electrofisher monthly sampling occurring from May 2018 through June 2019 at 12 stations in Barataria Basin.
Key findings include that gear bias was not evident across the range of water quality conditions (salinity, temperature, o C, dissolved oxygen, mg L-1 , turbidity, NTU; Appendix B: scatter plots) captured during this pilot study, but differences in nekton catch per unit effort (CPUE) and assemblages were evident between gear types. However, those differences largely depended on the parameter examined. For example, the overall CPUE was highest for electrofishing, followed by seine, and then throw trap. When grass shrimp (the most abundant taxon collected) were removed from CPUE, the electrofisher and seine results were similar in CPUE. When CPUE was corrected for gear efficiency and total area sampled, the throw trap had the highest reported density of nekton sampled, followed by electrofisher and seine results. Electrofishing captured the highest number of species, which included more unique species compared to seine or throw trap catches, though all gear types captured at least one unique species. These highlight a need for caution in interpreting assemblage and density data when comparing datasets derived from different sampling methodologies.
These key findings can help inform implementation and interpretation of long-term monitoring data in Louisiana as management decisions are made about coastal restoration projects to sustain and improve fisheries. There are trade-offs in selecting gear types for estuarine nekton monitoring of density, abundance, species richness, and assemblages. The table below (Table 1) summarizes some considerations when selecting gear types for long-term monitoring of estuarine nekton. In addition to biological and ecological considerations, other important considerations include cost, the labor required to conduct sampling, logistics, and potential uncertainties related to how effective each gear type is for sampling the wide variety of conditions found across Louisiana’s coastal habitats. For example, although electrofishing may capture higher CPUE, the equipment is more expensive to obtain and maintain compared to the other gear types. Most importantly, this table highlights differences in the nekton assemblages sampled by each gear type; this consideration is critical when designing the goals of a long-term monitoring program as it will inform how the data can be used and interpreted in the future.
This report provides caveats, assumptions, and recommendations that can help support the Louisiana Coastal Protection and Restoration Authority (CPRA), LDWF and the LA TIG in comparing data from different gear types, and in making decisions for future monitoring. Findings from this study are limited to the range of water quality conditions occurring during these data collection events; these data and analyses could benefit from sampling across a wider range of water quality conditions, and collection of habitat structure and bottom type data which are not routinely collected but critically influence nekton. Further investigation examining how relative differences detected in key species abundances between gear types might impact ecosystem indicators and energetics in a modeled food web would provide valuable input to understand outputs of the Comprehensive Aquatic System Model for Barataria Basin, including the potential impacts of nekton monitoring decisions on food web models.
","language":"English","publisher":"NOAA","usgsCitation":"Taylor, C., La Peyre, M., Sable, S., Kiskaddon, E.P., and Baustian, M., 2020, Gear comparison study for sampling nekton in Barataria Basin marshes: Technical Report Administrative Summary, 67 p.","productDescription":"67 p.","ipdsId":"IP-118449","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":395893,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":395891,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://www.gulfspillrestoration.noaa.gov/sites/default/files/2020-08%20LA%20TO65_GearCompReport_final_June2020.pdf"}],"country":"United States","state":"Louisiana","otherGeospatial":"Barataria Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.20599365234375,\n 29.106576445680258\n ],\n [\n -89.2694091796875,\n 29.14496502116881\n ],\n [\n -89.40948486328125,\n 29.346269551093652\n ],\n [\n -89.48089599609375,\n 29.336692606945483\n ],\n [\n -89.637451171875,\n 29.432421529604852\n ],\n [\n -89.82696533203125,\n 29.58540020340835\n ],\n [\n -90.09063720703124,\n 29.738147333955528\n ],\n [\n -90.2252197265625,\n 29.654642479663647\n ],\n [\n -90.42022705078125,\n 29.649868677972304\n ],\n [\n -90.22796630859375,\n 29.27442054681336\n ],\n [\n -90.20599365234375,\n 29.106576445680258\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Taylor, Caleb","contributorId":278588,"corporation":false,"usgs":false,"family":"Taylor","given":"Caleb","affiliations":[],"preferred":false,"id":834706,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"La Peyre, Megan K. 0000-0001-9936-2252","orcid":"https://orcid.org/0000-0001-9936-2252","contributorId":264343,"corporation":false,"usgs":true,"family":"La Peyre","given":"Megan K.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":834707,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sable, Shaye","contributorId":147275,"corporation":false,"usgs":false,"family":"Sable","given":"Shaye","affiliations":[{"id":16816,"text":"Dynamic Solutions, Baton Rouge, LA","active":true,"usgs":false}],"preferred":false,"id":834708,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kiskaddon, Erin P.","contributorId":272886,"corporation":false,"usgs":false,"family":"Kiskaddon","given":"Erin","email":"","middleInitial":"P.","affiliations":[{"id":13499,"text":"The Water Institute of the Gulf","active":true,"usgs":false}],"preferred":false,"id":834709,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Baustian, Melissa M.","contributorId":189569,"corporation":false,"usgs":false,"family":"Baustian","given":"Melissa M.","affiliations":[],"preferred":false,"id":834818,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70210873,"text":"70210873 - 2020 - Combining physical and species‐based approaches improves refugia identification","interactions":[],"lastModifiedDate":"2020-06-30T15:38:25.331939","indexId":"70210873","displayToPublicDate":"2020-06-01T10:36:07","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1701,"text":"Frontiers in Ecology and the Environment","active":true,"publicationSubtype":{"id":10}},"title":"Combining physical and species‐based approaches improves refugia identification","docAbstract":"Climate‐change refugia – locations likely to facilitate species persistence under climate change – are increasingly important components of conservation planning. Recent approaches for identifying refugia at broad scales include identifying regions that are projected to experience less severe changes (climatic exposure), that contain a diversity of physical and topographic features (environmental diversity), and that either retain or remain close to suitable climatic conditions (climate tracking, including both “species‐neutral” and species‐based approaches). We compared the degree of agreement between these approaches – with respect to their spatial coverage and other characteristics – across much of North America. This analysis found that approaches based on environmental diversity and species‐neutral climatic gradients both favored topographically complex regions, whereas climatic exposure and species‐based approaches identified regions with a range of topographic characteristics. Species‐based approaches targeting specific habitat groups identified unique regions missed by other approaches, emphasizing the importance of asking the question “refugia for what?” when prioritizing refugia. Our results highlight the necessity of including climatic exposure and species‐based information in addition to topographic diversity and climatic gradients in refugia analyses.
","language":"English","publisher":"Wiley","doi":"10.1002/fee.2207","usgsCitation":"Michalak, J., Stralberg, D., Cartwright, J.M., and Lawler, J.J., 2020, Combining physical and species‐based approaches improves refugia identification: Frontiers in Ecology and the Environment, v. 18, no. 5, p. 254-260, https://doi.org/10.1002/fee.2207.","productDescription":"7 p.","startPage":"254","endPage":"260","ipdsId":"IP-105568","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":456545,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/fee.2207","text":"Publisher Index Page"},{"id":376025,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"18","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Michalak, Julia 0000-0002-2524-8390","orcid":"https://orcid.org/0000-0002-2524-8390","contributorId":210589,"corporation":false,"usgs":false,"family":"Michalak","given":"Julia","email":"","affiliations":[{"id":6934,"text":"University of Washington","active":true,"usgs":false}],"preferred":false,"id":791901,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stralberg, Diana","contributorId":187413,"corporation":false,"usgs":false,"family":"Stralberg","given":"Diana","email":"","affiliations":[],"preferred":false,"id":791902,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cartwright, Jennifer M. 0000-0003-0851-8456 jmcart@usgs.gov","orcid":"https://orcid.org/0000-0003-0851-8456","contributorId":5386,"corporation":false,"usgs":true,"family":"Cartwright","given":"Jennifer","email":"jmcart@usgs.gov","middleInitial":"M.","affiliations":[{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":791903,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lawler, Joshua J.","contributorId":73327,"corporation":false,"usgs":false,"family":"Lawler","given":"Joshua","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":791904,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70210874,"text":"70210874 - 2020 - Disturbance refugia within mosaics of forest fire, drought, and insect outbreaks","interactions":[],"lastModifiedDate":"2020-06-30T15:35:29.994854","indexId":"70210874","displayToPublicDate":"2020-06-01T10:32:33","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1701,"text":"Frontiers in Ecology and the Environment","active":true,"publicationSubtype":{"id":10}},"title":"Disturbance refugia within mosaics of forest fire, drought, and insect outbreaks","docAbstract":"Disturbance refugia – locations that experience less severe or frequent disturbances than the surrounding landscape – provide a framework to highlight not only where and why these biological legacies persist as adjacent areas change but also the value of those legacies in sustaining biodiversity. Recent studies of disturbance refugia in forest ecosystems have focused primarily on fire, with a growing recognition of important applications to land management. Given the wide range of disturbance processes in forests, developing a broader understanding of disturbance refugia is important for scientists and land managers, particularly in the context of anthropogenic climate change. We illustrate the framework of disturbance refugia through the individual and interactive effects of three prominent forest disturbance agents: fire, drought, and insect outbreaks. We provide examples of disturbance refugia and related applications to natural resource management in western North America, demonstrate methods for characterizing refugia, identify research priorities, and discuss why a more comprehensive definition of disturbance refugia is relevant to conservation globally.
","language":"English","publisher":"Wiley","doi":"10.1002/fee.2190","usgsCitation":"Krawchuk, M.A., Meigs, G., Cartwright, J.M., Coop, J.D., Davis, R.J., Holz, A., Kolden, C.A., and Meddens, A.J., 2020, Disturbance refugia within mosaics of forest fire, drought, and insect outbreaks: Frontiers in Ecology and the Environment, v. 18, no. 5, p. 235-244, https://doi.org/10.1002/fee.2190.","productDescription":"10 p.","startPage":"235","endPage":"244","ipdsId":"IP-105563","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":456547,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/fee.2190","text":"Publisher Index Page"},{"id":376024,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"18","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Krawchuk, Meg A.","contributorId":187425,"corporation":false,"usgs":false,"family":"Krawchuk","given":"Meg","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":791905,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Meigs, Garrett","contributorId":192344,"corporation":false,"usgs":false,"family":"Meigs","given":"Garrett","affiliations":[],"preferred":false,"id":791906,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cartwright, Jennifer M. 0000-0003-0851-8456 jmcart@usgs.gov","orcid":"https://orcid.org/0000-0003-0851-8456","contributorId":5386,"corporation":false,"usgs":true,"family":"Cartwright","given":"Jennifer","email":"jmcart@usgs.gov","middleInitial":"M.","affiliations":[{"id":581,"text":"Tennessee Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":791909,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Coop, Jonathan D.","contributorId":187427,"corporation":false,"usgs":false,"family":"Coop","given":"Jonathan","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":791910,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Davis, Raymond J.","contributorId":150574,"corporation":false,"usgs":false,"family":"Davis","given":"Raymond","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":791911,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Holz, Andres","contributorId":225619,"corporation":false,"usgs":false,"family":"Holz","given":"Andres","affiliations":[{"id":6929,"text":"Portland State University","active":true,"usgs":false}],"preferred":false,"id":791912,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kolden, Crystal A.","contributorId":196909,"corporation":false,"usgs":false,"family":"Kolden","given":"Crystal","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":791908,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Meddens, Arjan J.H.","contributorId":140349,"corporation":false,"usgs":false,"family":"Meddens","given":"Arjan","email":"","middleInitial":"J.H.","affiliations":[{"id":13466,"text":"Univ. of Idaho","active":true,"usgs":false}],"preferred":false,"id":791907,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70210738,"text":"70210738 - 2020 - Impacts of hydrothermal plume processes on oceanic metal cycles and transport","interactions":[],"lastModifiedDate":"2020-06-23T14:59:50.64286","indexId":"70210738","displayToPublicDate":"2020-06-01T09:58:16","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2845,"text":"Nature Geoscience","active":true,"publicationSubtype":{"id":10}},"title":"Impacts of hydrothermal plume processes on oceanic metal cycles and transport","docAbstract":"Chemical, physical and biological processes in hydrothermal plumes control the flux of elements from hydrothermal vents to the global oceans. The timescales of these processes range from less than a second, as the hydrothermal fluid mixes with seawater at the seafloor, to decades, as the plume disperses over thousands of kilometers. Integrating hydrothermal geochemistry throughout the lifetime of the plume reveals some well constrained processes, along with many surprises. For instance, contrary to the idea that metals are removed from the hydrothermal plume via oxidation, a survey of recent datasets reveals that oxidation of iron and manganese does not consistently result in their removal from the plume, and that manganese may be lost from the water column more rapidly than iron. These observations suggest that the understanding of element transport in hydrothermal plumes is incomplete, partly due to the change in removal processes as the plume disperses from less than 1 km from the vent to more than 4,000 km. We suggest that characterizing the plume based on regions that retain some reduced components versus those that are fully oxidized, in addition to buoyancy, will illuminate the nature of the dominant processes and allow a more complete understanding of the ultimate fate of hydrothermally derived metals.","language":"English","publisher":"Nature","doi":"10.1038/s41561-020-0579-0","usgsCitation":"Gartman, A., and Findlay, A.J., 2020, Impacts of hydrothermal plume processes on oceanic metal cycles and transport: Nature Geoscience, v. 13, p. 396-402, https://doi.org/10.1038/s41561-020-0579-0.","productDescription":"7 p.","startPage":"396","endPage":"402","ipdsId":"IP-112031","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":375808,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","noUsgsAuthors":false,"publicationDate":"2020-06-01","publicationStatus":"PW","contributors":{"authors":[{"text":"Gartman, Amy 0000-0001-9307-3062 agartman@usgs.gov","orcid":"https://orcid.org/0000-0001-9307-3062","contributorId":177057,"corporation":false,"usgs":true,"family":"Gartman","given":"Amy","email":"agartman@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":791186,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Findlay, Alyssa J.","contributorId":215547,"corporation":false,"usgs":false,"family":"Findlay","given":"Alyssa","email":"","middleInitial":"J.","affiliations":[{"id":37318,"text":"Aarhus University","active":true,"usgs":false}],"preferred":false,"id":791187,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70236144,"text":"70236144 - 2020 - Basinwide hydroclimatic drought in the Colorado River basin","interactions":[],"lastModifiedDate":"2022-08-30T13:55:23.296854","indexId":"70236144","displayToPublicDate":"2020-06-01T08:50:02","publicationYear":"2020","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1421,"text":"Earth Interactions","active":true,"publicationSubtype":{"id":10}},"title":"Basinwide hydroclimatic drought in the Colorado River basin","docAbstract":"The Colorado River basin (CRB) supplies water to approximately 40 million people and is essential to hydropower generation, agriculture, and industry. In this study, a monthly water balance model is used to compute hydroclimatic water balance components (i.e., potential evapotranspiration, actual evapotranspiration, and runoff) for the period 1901–2014 across the entire CRB. The time series of monthly runoff is aggregated to compute water-year runoff and then used to identify drought periods in the basin. For the 1901–2014 period, eight basinwide drought periods were identified. The driest drought period spanned years 1901–04, whereas the longest drought period occurred during 1943–56. The eight droughts were primarily driven by winter precipitation deficits rather than warm temperature anomalies. In addition, an analysis of prehistoric drought for the CRB—computed using tree-ring-based reconstructions of the Palmer drought severity index—indicates that during some past centuries drought frequency was higher than during the twentieth century and that some centuries experienced droughts that were much longer than those during the twentieth century. More frequent or longer droughts than those that occurred during the twentieth century, combined with continued warming associated with climate change, may lead to substantial future water deficits in the CRB.
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