The U.S. Geological Survey, in cooperation with the International Joint Commission, compiled historical data on regulated streamflows and lake levels and estimated unregulated streamflows and lake levels on Forest City Stream at Forest City, Maine, and East Grand Lake on the United States-Canada border between Maine and New Brunswick to study the effects on streamflows and lake levels if two or all three dam gates are left open. Historical regulated monthly mean streamflows in Forest City Stream at the outlet of East Grand Lake (referred to as Grand Lake by Environment Canada) fluctuated between 114 cubic feet per second (ft3 /s) (3.23 cubic meters per second [m3 /s]) in November and 318 ft3 /s (9.01 m3 /s) in September from 1975 to 2015 according to Environment Canada streamgaging data. Unregulated monthly mean streamflows at this location estimated from regression equations for unregulated sites range from 59.2 ft3 /s (1.68 m3 /s) in September to 653 ft3 /s (18.5 m3 /s) in April. Historical lake levels in East Grand Lake fluctuated between 431.3 feet (ft) (131.5 meters [m]) in October and 434.0 ft (132.3 m) in May from 1969 to 2016 according to Environment Canada lake level data for East Grand Lake. Average monthly lake levels modeled by using the estimated hydrology for unregulated flows, and an outflow rating built from a hydraulic model with all gates at the dam open, range from 427.7 ft (130.4 m) in September to 431.1 ft (131.4 m) in April. Average monthly lake levels would likely be from 1.8 to 5.4 ft (0.55 to 1.6 m) lower with the gates at the dam opened than they have been historically. The greatest lake level changes would be from June through September.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185044","collaboration":"Prepared in cooperation with the International Joint Commission","usgsCitation":"Lombard, P.J., 2018, Estimation of unregulated monthly, annual, and peak streamflows in Forest City Stream and lake levels in East Grand Lake, United States-Canada border between Maine and New Brunswick: U.S. Geological Survey Scientific Investigations Report 2018–5044, 8 p., https://doi.org/10.3133/sir20185044.","productDescription":"Report: iv, 8 p.; Data release","numberOfPages":"16","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-092951","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":353763,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7PN94VN","text":"USGS data release","description":"USGS data release","linkHelpText":"Bathymetric data for St. Croix River at outlet to East Grand Lake and Forest City Dam Survey, United States-Canadian border between Maine and New Brunswick"},{"id":353745,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5044/sir20185044.pdf","text":"Report","size":"873 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5044"},{"id":353744,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5044/coverthb.jpg"}],"country":"Canada, United States","state":"Maine, New Brunswick","otherGeospatial":"East Grand Lake, Forest City Stream","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -67.884521484375,\n 45.60587170876381\n ],\n [\n -67.68951416015625,\n 45.60587170876381\n ],\n [\n -67.68951416015625,\n 45.82066487514085\n ],\n [\n -67.884521484375,\n 45.82066487514085\n ],\n [\n -67.884521484375,\n 45.60587170876381\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
196 Whitten Road
Augusta, ME 04330
Feral pigs (Sus scrofa L.) are perhaps the most abundant, widespread, and economically significant large introduced vertebrate across the Pacific island region. Unlike many other nonnative invasive species, feral pigs have both cultural and recreational importance in the region, complicating their management. Today, Pacific island feral pigs are a mixture of several strains of domestic swine, Asiatic wild boar, and European wild boar. Due to their generalist diet and rooting behavior, feral pigs alter soils and watersheds and negatively impact native and nonnative flora and fauna. As a result, feral pigs have played a role in the extinction of several species of plants and animals on Pacific islands and have negative effects on both ecotourism and agricultural industries in the region. Despite numerous published studies on feral pigs in the Pacific island region, of which the majority include systematic analyses of original empirical data, some fundamental aspects of feral pig ecology remain poorly characterized, at least partly due to the remote and inaccessible environments that they often inhabit. To address these knowledge gaps, effort should be made to integrate research conducted outside the Pacific island region into local management strategies. This review summarizes the origins, history, ecology, environmental effects, and current management of feral pigs in the Pacific island region; integrates regional scientific findings with those of other insular and continental systems; and identifies current knowledge gaps requiring further research to inform the ecology and management of this impactful invasive species.
","language":"English ","publisher":"University of Hawai'i Press","doi":"10.2984/72.2.1","usgsCitation":"Wehr, N., Hess, S.C., and Litton, C.M., 2018, Biology and impacts of Pacific Islands invasive species. 14. Sus scrofa the feral pig (Artiodactyla: Suidae): Pacific Science, v. 72, no. 2, p. 177-198, https://doi.org/10.2984/72.2.1.","productDescription":"22 p.","startPage":"177","endPage":"198","numberOfPages":"22","ipdsId":"IP-080121","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":354773,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawai'i","otherGeospatial":"Pacific Islands","volume":"72","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e58ee4b060350a15d1da","contributors":{"authors":[{"text":"Wehr, Nathaniel H. ","contributorId":205455,"corporation":false,"usgs":false,"family":"Wehr","given":"Nathaniel H. ","affiliations":[{"id":33542,"text":"Department of Natural Resources and Environmental Management, University of Hawai‘i at Mānoa, Honolulu, Hawaii","active":true,"usgs":false}],"preferred":false,"id":737354,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hess, Steven C. 0000-0001-6403-9922 shess@usgs.gov","orcid":"https://orcid.org/0000-0001-6403-9922","contributorId":3156,"corporation":false,"usgs":true,"family":"Hess","given":"Steven","email":"shess@usgs.gov","middleInitial":"C.","affiliations":[{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":false,"id":737352,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Litton, Creighton M.","contributorId":58534,"corporation":false,"usgs":true,"family":"Litton","given":"Creighton","email":"","middleInitial":"M.","affiliations":[{"id":34391,"text":"Department of Natural Resources and Environmental Management, University of Hawai‘i at Mānoa, Honolulu, Hawaii 96822","active":true,"usgs":false}],"preferred":false,"id":737353,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70196456,"text":"ofr20181062 - 2018 - Measurements of erosion potential using Gust chamber in Yolo Bypass near Sacramento, California","interactions":[],"lastModifiedDate":"2018-10-17T09:39:35","indexId":"ofr20181062","displayToPublicDate":"2018-04-27T00:00:00","publicationYear":"2018","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":"2018-1062","title":"Measurements of erosion potential using Gust chamber in Yolo Bypass near Sacramento, California","docAbstract":"Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, CA 95819
A whole lake eutrophication (WLE) model approach for phosphorus and cyanobacterial biomass in Upper Klamath Lake, south-central Oregon, is presented here. The model is a successor to a previous model developed to inform a Total Maximum Daily Load (TMDL) for phosphorus in the lake, but is based on net primary production (NPP), which can be calculated from dissolved oxygen, rather than scaling up a small-scale description of cyanobacterial growth and respiration rates. This phase 3 WLE model is a refinement of the proof-of-concept developed in phase 2, which was the first attempt to use NPP to simulate cyanobacteria in the TMDL model. The calibration of the calculated NPP WLE model was successful, with performance metrics indicating a good fit to calibration data, and the calculated NPP WLE model was able to simulate mid-season bloom decreases, a feature that previous models could not reproduce.
In order to use the model to simulate future scenarios based on phosphorus load reduction, a multivariate regression model was created to simulate NPP as a function of the model state variables (phosphorus and chlorophyll a) and measured meteorological and temperature model inputs. The NPP time series was split into a low- and high-frequency component using wavelet analysis, and regression models were fit to the components separately, with moderate success.
The regression models for NPP were incorporated in the WLE model, referred to as the “scenario” WLE (SWLE), and the fit statistics for phosphorus during the calibration period were mostly unchanged. The fit statistics for chlorophyll a, however, were degraded. These statistics are still an improvement over prior models, and indicate that the SWLE is appropriate for long-term predictions even though it misses some of the seasonal variations in chlorophyll a.
The complete whole lake SWLE model, with multivariate regression to predict NPP, was used to make long-term simulations of the response to 10-, 20-, and 40-percent reductions in tributary nutrient loads. The long-term mean water column concentration of total phosphorus was reduced by 9, 18, and 36 percent, respectively, in response to these load reductions. The long-term water column chlorophyll a concentration was reduced by 4, 13, and 44 percent, respectively. The adjustment to a new equilibrium between the water column and sediments occurred over about 30 years.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185042","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Wherry, S.A., and Wood, T.M., 2018, A metabolism-based whole lake eutrophication model to estimate the magnitude and time scales of the effects of restoration in Upper Klamath Lake, south-central Oregon: U.S. Geological Survey Scientific Investigations Report 2018–5042, 43 p., https:/doi.org/10.3133/sir20185042.","productDescription":"vii, 43 p.","onlineOnly":"Y","ipdsId":"IP-081297","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":353789,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5042/coverthb.jpg"},{"id":353790,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5042/sir20185042.pdf","text":"Report","size":"6.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5042"}],"country":"United States","state":"Oregon","otherGeospatial":"Upper Klamath Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.10273742675781,\n 42.22750046697999\n ],\n [\n -121.79374694824219,\n 42.22750046697999\n ],\n [\n -121.79374694824219,\n 42.595554553719204\n ],\n [\n -122.10273742675781,\n 42.595554553719204\n ],\n [\n -122.10273742675781,\n 42.22750046697999\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
The environmental fate of polyoxyethylene tallow amine (POEA), an additive in glyphosate herbicide formulations, has not been studied. This study examined the dissipation of POEA; glyphosate; and aminomethylphosphonic acid (AMPA), a degradation product of glyphosate, in the top 45 cm of soil from an agricultural field where glyphosate was applied. The concentration of these compounds was also analyzed in bed sediment samples from watersheds in agricultural and urban areas from six states (Georgia, Hawaii, Iowa, Mississippi, North Carolina, South Carolina). The field studies show that POEA, glyphosate, and AMPA persist on the soil from planting season to planting season but dissipate over time with little migration into deeper soil. POEA, glyphosate, and AMPA were found on the bed sediment samples in urban and agricultural watersheds.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2018.04.246","usgsCitation":"Tush, D.L., Maksimowicz, M.M., and Meyer, M., 2018, Dissipation of polyoxyethylene tallow amine (POEA) and glyphosate in an agricultural field and their co-occurrence on streambed sediments: Science of the Total Environment, v. 636, p. 212-219, https://doi.org/10.1016/j.scitotenv.2018.04.246.","productDescription":"8 p.","startPage":"212","endPage":"219","ipdsId":"IP-079506","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":488908,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2018.04.246","text":"Publisher Index Page"},{"id":484240,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Georgia, Hawaii, Iowa, Mississippi, North Carolina, South 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T.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":932739,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70196707,"text":"70196707 - 2018 - Open hydrology courseware using the United States Geological Survey’s National Water Census Data Portal","interactions":[],"lastModifiedDate":"2018-04-26T11:32:22","indexId":"70196707","displayToPublicDate":"2018-04-26T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5679,"text":"Open Water Journal","active":true,"publicationSubtype":{"id":10}},"title":"Open hydrology courseware using the United States Geological Survey’s National Water Census Data Portal","docAbstract":"The U.S. Geological Survey (USGS) is the primary U.S. Government agency for water data collection and dissemination. In this role, the USGS has recently created and deployed a National Water Census Data Portal (NWC-DP) which provides access to streamflow, evapotransporation, precipitation, aquatic biology and other data at the national level. Recognizing the value of these data sets for hydrologic science education, this paper presents an effort to bridge the gap between pencil–and-paper-based hydrology curriculum and the USGS NWC-DP resource. Specifically, we have developed an R package, National Water Census Education (NWCEd), and five associated laboratory exercises that integrate R- and web-services-based access to the NWC-DP data sets. Using custom functions built into the NWCEd, students are able to access unprecedented amounts of hydrologic data from the NWC-DP, which can be applied to current hydrology curriculum and analyzed using NWCEd and a number of other open-source R tools.
","language":"English","publisher":"BYU","usgsCitation":"Nelson, J., Ames, D.P., and Blodgett, D.L., 2018, Open hydrology courseware using the United States Geological Survey’s National Water Census Data Portal: Open Water Journal, v. 5, no. 1, p. 1-14.","productDescription":"Article 1; 14 p.","startPage":"1","endPage":"14","ipdsId":"IP-086854","costCenters":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"links":[{"id":353730,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":353724,"type":{"id":15,"text":"Index Page"},"url":"https://scholarsarchive.byu.edu/openwater/vol5/iss1/1/"}],"volume":"5","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6cfe4b0da30c1bfbe42","contributors":{"authors":[{"text":"Nelson, Jake","contributorId":204467,"corporation":false,"usgs":false,"family":"Nelson","given":"Jake","email":"","affiliations":[{"id":6681,"text":"Brigham Young University","active":true,"usgs":false}],"preferred":false,"id":734059,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ames, Daniel P.","contributorId":204468,"corporation":false,"usgs":false,"family":"Ames","given":"Daniel","email":"","middleInitial":"P.","affiliations":[{"id":6681,"text":"Brigham Young University","active":true,"usgs":false}],"preferred":false,"id":734060,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Blodgett, David L. 0000-0001-9489-1710 dblodgett@usgs.gov","orcid":"https://orcid.org/0000-0001-9489-1710","contributorId":3868,"corporation":false,"usgs":true,"family":"Blodgett","given":"David","email":"dblodgett@usgs.gov","middleInitial":"L.","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":734058,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70196005,"text":"sir20185009 - 2018 - Public-supply water use and self-supplied industrial water use in Tennessee, 2010","interactions":[],"lastModifiedDate":"2018-09-25T05:58:29","indexId":"sir20185009","displayToPublicDate":"2018-04-26T00:00:00","publicationYear":"2018","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":"2018-5009","title":"Public-supply water use and self-supplied industrial water use in Tennessee, 2010","docAbstract":"The U.S. Geological Survey (USGS), in cooperation with the Tennessee Department of Environment and Conservation, Division of Water Resources, prepared this report and displayed and analyzed water use by self-supplied industrial and public-supply water systems in Tennessee for 2010. Public-supply water systems in Tennessee provide water for domestic, industrial, and commercial uses and for municipal services. In 2010, 474 public-supply water systems distributed 917 million gallons per day (Mgal/d) of surface water (67 percent, 617 Mgal/d) and groundwater (33 percent, 300 Mgal/d) to a population of 5.7 million in Tennessee. Gross per capita water use in Tennessee during 2010 was 162 gallons per day.
Since 1950, water withdrawals by public-supply water systems in Tennessee have increased from 160 Mgal/d to 917 Mgal/d in 2010. Each of the 95 counties in Tennessee was served by at least 1 public-supply water system in 2010. Tennessee public-supply water systems withdraw less groundwater than surface water, and surface-water use has increased at a faster rate than groundwater use. Since 2005, surface-water withdrawals have increased by 26 Mgal/d, and groundwater withdrawals have decreased by 29 Mgal/d, which is the first decrease in groundwater withdrawals since 1950; however, 29 systems reported increased groundwater withdrawals during 2010, and 12 of these 29 systems reported increases of 1 Mgal/d or more. Davidson County had the largest surface-water withdrawal rate (136 Mgal/d) in 2010. The largest groundwater withdrawal rate (151 Mgal/d) by a single public-supply water system was reported by Memphis Light, Gas and Water, which served more than 669,000 people in Shelby County in 2010.
Self-supplied industrial water use includes water for such purposes as fabrication, processing, washing, diluting, cooling, or transporting a product; incorporating water into a product; or for sanitation needs in facilities that manufacture various products. Water withdrawals for self-supplied industrial water use during 2010 were about 776 Mgal/d. This quantity represented a decrease of 7 Mgal/d since 2005. In Tennessee, self-supplied industrial water withdrawals were primarily for chemical and allied products (555 Mgal/d), paper and allied products (107 Mgal/d), aeronautical products (71.5 Mgal/d), concrete and glass products (9.74 Mgal/d), and primary metal products (4.49 Mgal/d); and these products accounted for 96 percent (747 Mgal/d) of the self-supplied industrial water withdrawals in 2010. Surface water supplied 94 percent of the water (728 Mgal/d) for self-supplied industrial purposes, and groundwater supplied 6 percent (47.6 Mgal/d). Self-supplied industrial water withdrawals in Sullivan County were 488 Mgal/d and accounted for 61 percent of the self-supplied industrial water withdrawals. The largest groundwater withdrawal, 14.9 Mgal/d, by a single self-supplied industry was in Memphis, Tennessee, for the production of chemicals and allied products.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185009","collaboration":"Prepared in cooperation with the Tennessee Department of Environment and Conservation, Division of Water Resources","usgsCitation":"Robinson, J.A., 2018, Public-supply water use and self-supplied industrial water use in Tennessee, 2010: U.S. Geological Survey Scientific Investigation Report 2018–5009, 30 p., https://doi.org/10.3133/sir20185009.","productDescription":"Report: v, 29 p.; 7 Appendixes; Data Release","numberOfPages":"40","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-059935","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":353717,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2018/5009/sir20185009_appendixes1-7.xlsx","text":"Appendixes 1 to 7","size":"162 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2018–5009 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U.S. Geological Survey
640 Grassmere Park, Suite 100
Nashville, TN 37211
Twenty papers on the study of tsunamis are included in Volume III of the PAGEOPH topical issue “Global Tsunami Science: Past and Future”. Volume I of this topical issue was published as PAGEOPH, vol. 173, No. 12, 2016 and Volume II as PAGEOPH, vol. 174, No. 8, 2017. Two papers in Volume III focus on specific details of the 2009 Samoa and the 1923 northern Kamchatka tsunamis; they are followed by three papers related to tsunami hazard assessment for three different regions of the world oceans: South Africa, Pacific coast of Mexico and the northwestern part of the Indian Ocean. The next six papers are on various aspects of tsunami hydrodynamics and numerical modelling, including tsunami edge waves, resonant behaviour of compressible water layer during tsunamigenic earthquakes, dispersive properties of seismic and volcanically generated tsunami waves, tsunami runup on a vertical wall and influence of earthquake rupture velocity on maximum tsunami runup. Four papers discuss problems of tsunami warning and real-time forecasting for Central America, the Mediterranean coast of France, the coast of Peru, and some general problems regarding the optimum use of the DART buoy network for effective real-time tsunami warning in the Pacific Ocean. Two papers describe historical and paleotsunami studies in the Russian Far East. The final set of three papers importantly investigates tsunamis generated by non-seismic sources: asteroid airburst and meteorological disturbances. Collectively, this volume highlights contemporary trends in global tsunami research, both fundamental and applied toward hazard assessment and mitigation.
","language":"English","publisher":"Springer","doi":"10.1007/s00024-018-1851-8","usgsCitation":"Rabinovich, A.B., Fritz, H.M., Tanioka, Y., and Geist, E.L., 2018, Introduction to “Global tsunami science: Past and future, Volume III”: Pure and Applied Geophysics, v. 175, no. 4, p. 1231-1237, https://doi.org/10.1007/s00024-018-1851-8.","productDescription":"7 p.","startPage":"1231","endPage":"1237","ipdsId":"IP-096461","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":353757,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"175","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-04-19","publicationStatus":"PW","scienceBaseUri":"5afee6cee4b0da30c1bfbe3c","contributors":{"authors":[{"text":"Rabinovich, Alexander B.","contributorId":177506,"corporation":false,"usgs":false,"family":"Rabinovich","given":"Alexander","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":734130,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fritz, Hermann M.","contributorId":194830,"corporation":false,"usgs":false,"family":"Fritz","given":"Hermann","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":734131,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tanioka, Yuichiro","contributorId":177507,"corporation":false,"usgs":false,"family":"Tanioka","given":"Yuichiro","email":"","affiliations":[],"preferred":false,"id":734132,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Geist, Eric L. 0000-0003-0611-1150 egeist@usgs.gov","orcid":"https://orcid.org/0000-0003-0611-1150","contributorId":1956,"corporation":false,"usgs":true,"family":"Geist","given":"Eric","email":"egeist@usgs.gov","middleInitial":"L.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":734133,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70196714,"text":"70196714 - 2018 - Temperature-influenced energetics model for migrating waterfowl","interactions":[],"lastModifiedDate":"2018-04-26T16:18:45","indexId":"70196714","displayToPublicDate":"2018-04-26T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1458,"text":"Ecological Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Temperature-influenced energetics model for migrating waterfowl","docAbstract":"Climate and weather affect avian migration by influencing when and where birds fly, the energy costs and risks of flight, and the ability to sense cues necessary for proper navigation. We review the literature of the physiology of avian migration and the influence of climate, specifically temperature, on avian migration dynamics. We use waterfowl as a model guild because of the ready availability of empirical physiological data and their enormous economic value, but our discussion and expectations are broadly generalizable to migratory birds in general. We detail potential consequences of an increasingly warm climate on avian migration, including the possibility of the cessation of migration by some populations and species. Our intent is to lay the groundwork for including temperature effects on energetic gains and losses of migratory birds with the expected consequences of increasing temperatures into a predictive modeling framework. To this end, we provide a simulation of migration progression exclusively focused on the influence of temperature on the physiological determinants of migration. This simulation produced comparable results to empirically derived and observed values for different migratory factors (e.g., body fat content, flight range, departure date). By merging knowledge from the arenas of avian physiology and migratory theory we have identified a clear need for research and have developed hypotheses for a path forward.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2018.04.001","usgsCitation":"Aagaard, K., Thogmartin, W.E., and Lonsdorg, E.V., 2018, Temperature-influenced energetics model for migrating waterfowl: Ecological Modelling, v. 378, p. 46-58, https://doi.org/10.1016/j.ecolmodel.2018.04.001.","productDescription":"13 p.","startPage":"46","endPage":"58","ipdsId":"IP-084841","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":468806,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolmodel.2018.04.001","text":"Publisher Index Page"},{"id":353754,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"378","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6cee4b0da30c1bfbe38","contributors":{"authors":[{"text":"Aagaard, Kevin 0000-0003-0756-2172 kaagaard@usgs.gov","orcid":"https://orcid.org/0000-0003-0756-2172","contributorId":147393,"corporation":false,"usgs":true,"family":"Aagaard","given":"Kevin","email":"kaagaard@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":734081,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thogmartin, Wayne E. 0000-0002-2384-4279 wthogmartin@usgs.gov","orcid":"https://orcid.org/0000-0002-2384-4279","contributorId":2545,"corporation":false,"usgs":true,"family":"Thogmartin","given":"Wayne","email":"wthogmartin@usgs.gov","middleInitial":"E.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":734082,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lonsdorg, Eric V.","contributorId":204474,"corporation":false,"usgs":false,"family":"Lonsdorg","given":"Eric","email":"","middleInitial":"V.","affiliations":[{"id":6626,"text":"University of Minnesota","active":true,"usgs":false}],"preferred":false,"id":734083,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70196709,"text":"70196709 - 2018 - Mechanisms of wave‐driven water level variability on reef‐fringed coastlines","interactions":[],"lastModifiedDate":"2018-07-03T11:25:32","indexId":"70196709","displayToPublicDate":"2018-04-26T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2315,"text":"Journal of Geophysical Research C: Oceans","active":true,"publicationSubtype":{"id":10}},"title":"Mechanisms of wave‐driven water level variability on reef‐fringed coastlines","docAbstract":"Wave‐driven water level variability (and runup at the shoreline) is a significant cause of coastal flooding induced by storms. Wave runup is challenging to predict, particularly along tropical coral reef‐fringed coastlines due to the steep bathymetric profiles and large bottom roughness generated by reef organisms, which can violate assumptions in conventional models applied to open sandy coastlines. To investigate the mechanisms of wave‐driven water level variability on a reef‐fringed coastline, we performed a set of laboratory flume experiments on an along‐shore uniform bathymetric profile with and without bottom roughness. Wave setup and waves at frequencies lower than the incident sea‐swell forcing (infragravity waves) were found to be the dominant components of runup. These infragravity waves were positively correlated with offshore wave groups, signifying they were generated in the surf zone by the oscillation of the breakpoint. On the reef flat and at the shoreline, the low‐frequency waves formed a standing wave pattern with energy concentrated at the natural frequencies of the reef flat, indicating resonant amplification. Roughness elements used in the flume to mimic large reef bottom roughness reduced low frequency motions on the reef flat and reduced wave run up by 30% on average, compared to the runs over a smooth bed. These results provide insight into sea‐swell and infragravity wave transformation and wave setup dynamics on steep‐sloped coastlines, and the effect that future losses of reef bottom roughness may have on coastal flooding along reef‐fringed coasts.
","language":"English","publisher":"Wiley","doi":"10.1029/2018JC013933","usgsCitation":"Buckley, M.L., Lowe, R.J., Hansen, J.E., van Dongeren, A.R., and Storlazzi, C.D., 2018, Mechanisms of wave‐driven water level variability on reef‐fringed coastlines: Journal of Geophysical Research C: Oceans, v. 123, no. 5, p. 3811-3831, https://doi.org/10.1029/2018JC013933.","productDescription":"21 p.","startPage":"3811","endPage":"3831","ipdsId":"IP-092740","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468807,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://admin.research-repository.uwa.edu.au/en/publications/db5339a2-0de9-4c15-9798-f5eaddf31687","text":"Publisher Index Page"},{"id":437931,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F71V5D7J","text":"USGS data release","linkHelpText":"Water level and velocity measurements from the 2012 University of Western Australia Fringing Reef Experiment (UWAFRE)"},{"id":353758,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"123","issue":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-26","publicationStatus":"PW","scienceBaseUri":"5afee6cee4b0da30c1bfbe3e","contributors":{"authors":[{"text":"Buckley, Mark L. 0000-0002-1909-4831","orcid":"https://orcid.org/0000-0002-1909-4831","contributorId":203481,"corporation":false,"usgs":true,"family":"Buckley","given":"Mark","email":"","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":734068,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lowe, Ryan J.","contributorId":152265,"corporation":false,"usgs":false,"family":"Lowe","given":"Ryan","email":"","middleInitial":"J.","affiliations":[{"id":6986,"text":"Stanford University","active":true,"usgs":false}],"preferred":false,"id":734069,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hansen, Jeff E.","contributorId":204340,"corporation":false,"usgs":false,"family":"Hansen","given":"Jeff","email":"","middleInitial":"E.","affiliations":[{"id":24588,"text":"The University of Western Australia","active":true,"usgs":false}],"preferred":true,"id":734070,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"van Dongeren, Ap R.","contributorId":203482,"corporation":false,"usgs":false,"family":"van Dongeren","given":"Ap","email":"","middleInitial":"R.","affiliations":[{"id":36257,"text":"Deltares","active":true,"usgs":false}],"preferred":false,"id":734071,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Storlazzi, Curt D. 0000-0001-8057-4490 cstorlazzi@usgs.gov","orcid":"https://orcid.org/0000-0001-8057-4490","contributorId":140584,"corporation":false,"usgs":true,"family":"Storlazzi","given":"Curt","email":"cstorlazzi@usgs.gov","middleInitial":"D.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":734072,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70196719,"text":"70196719 - 2018 - Profiles of digestive enzymes of two competing planktivores, silver carp and gizzard shad, differ","interactions":[],"lastModifiedDate":"2018-04-26T16:23:33","indexId":"70196719","displayToPublicDate":"2018-04-26T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5680,"text":"Ichthyological Research","active":true,"publicationSubtype":{"id":10}},"title":"Profiles of digestive enzymes of two competing planktivores, silver carp and gizzard shad, differ","docAbstract":"Typically, studies in digestive physiology in fish focus on a few enzymes and provide insight into the specific processes of the enzyme in a targeted species. Comparative studies assessing a wide number of digestive enzymes on fishes that compete for food resources are lacking, especially in the context of an introduced species. It is generally thought that the invasive silver carp (SVC; Hypophthalmichthys molitrix) directly compete for food resources with the native gizzard shad (GZS; Dorosoma cepedianum) in waters where they coexist. We compared 19 digestive enzymes between SVC and GZS throughout a year and in two rivers in the Midwestern United States: Illinois River and Wabash River. All digestive enzymes analyzed were detected in both SVC and GZS in both rivers. However, the profiles of the digestive enzymes varied by species. Alkaline phosphatase, valine arylamidase, acid phosphatase, naphthol-AS-BI-phosphohydrolase and N-acetyl-β-glucosaminidase were all much higher in SVC than in GZS. Differences between digestive enzyme profiles were also observed between rivers and months. This study demonstrates the utility of using an ecological approach to compare physiological features in fishes.
","language":"English","publisher":"Springer","doi":"10.1007/s10228-018-0615-x","usgsCitation":"Amberg, J., Jensen, N., Erickson, R.A., Sauey, B.W., and Jackson, C., 2018, Profiles of digestive enzymes of two competing planktivores, silver carp and gizzard shad, differ: Ichthyological Research, v. 65, no. 2, p. 245-251, https://doi.org/10.1007/s10228-018-0615-x.","productDescription":"7 p.","startPage":"245","endPage":"251","ipdsId":"IP-076712","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":353749,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"65","issue":"2","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-02-01","publicationStatus":"PW","scienceBaseUri":"5afee6cde4b0da30c1bfbe32","contributors":{"authors":[{"text":"Amberg, Jon 0000-0002-8351-4861 jamberg@usgs.gov","orcid":"https://orcid.org/0000-0002-8351-4861","contributorId":149785,"corporation":false,"usgs":true,"family":"Amberg","given":"Jon","email":"jamberg@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":734091,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jensen, Nathan R.","contributorId":201065,"corporation":false,"usgs":false,"family":"Jensen","given":"Nathan R.","affiliations":[],"preferred":false,"id":734092,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Erickson, Richard A. 0000-0003-4649-482X rerickson@usgs.gov","orcid":"https://orcid.org/0000-0003-4649-482X","contributorId":5455,"corporation":false,"usgs":true,"family":"Erickson","given":"Richard","email":"rerickson@usgs.gov","middleInitial":"A.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":734093,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sauey, Blake W. 0000-0003-2819-0814 bsauey@usgs.gov","orcid":"https://orcid.org/0000-0003-2819-0814","contributorId":202175,"corporation":false,"usgs":true,"family":"Sauey","given":"Blake","email":"bsauey@usgs.gov","middleInitial":"W.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":734094,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jackson, Craig 0000-0003-4023-0276 cjackson@usgs.gov","orcid":"https://orcid.org/0000-0003-4023-0276","contributorId":192276,"corporation":false,"usgs":true,"family":"Jackson","given":"Craig","email":"cjackson@usgs.gov","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":734095,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70196708,"text":"70196708 - 2018 - Pharmaceutical manufacturing facility discharges can substantially increase the pharmaceutical load to U.S. wastewaters","interactions":[],"lastModifiedDate":"2021-05-28T14:06:57.742111","indexId":"70196708","displayToPublicDate":"2018-04-26T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Pharmaceutical manufacturing facility discharges can substantially increase the pharmaceutical load to U.S. wastewaters","docAbstract":"Discharges from pharmaceutical manufacturing facilities (PMFs) previously have been identified as important sources of pharmaceuticals to the environment. Yet few studies are available to establish the influence of PMFs on the pharmaceutical source contribution to wastewater treatment plants (WWTPs) and waterways at the national scale. Consequently, a national network of 13 WWTPs receiving PMF discharges, six WWTPs with no PMF input, and one WWTP that transitioned through a PMF closure were selected from across the United States to assess the influence of PMF inputs on pharmaceutical loading to WWTPs. Effluent samples were analyzed for 120 pharmaceuticals and pharmaceutical degradates. Of these, 33 pharmaceuticals had concentrations substantially higher in PMF-influenced effluent (maximum 555,000 ng/L) compared to effluent from control sites (maximum 175 ng/L). Concentrations in WWTP receiving PMF input are variable, as discharges from PMFs are episodic, indicating that production activities can vary substantially over relatively short (several months) periods and have the potential to rapidly transition to other pharmaceutical products. Results show that PMFs are an important, national-scale source of pharmaceuticals to the environment.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2018.04.160","usgsCitation":"Scott, T., Phillips, P.J., Kolpin, D., Finkelstein, K.M., Furlong, E., Foreman, W.T., and Gray, J., 2018, Pharmaceutical manufacturing facility discharges can substantially increase the pharmaceutical load to U.S. wastewaters: Science of the Total Environment, v. 636, p. 69-79, https://doi.org/10.1016/j.scitotenv.2018.04.160.","productDescription":"11 p.","startPage":"69","endPage":"79","ipdsId":"IP-095342","costCenters":[{"id":452,"text":"National Water Quality Laboratory","active":true,"usgs":true},{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":468809,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2018.04.160","text":"Publisher Index Page"},{"id":353759,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"636","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6cee4b0da30c1bfbe40","contributors":{"authors":[{"text":"Scott, Tia-Marie 0000-0002-5677-0544 tia-mariescott@usgs.gov","orcid":"https://orcid.org/0000-0002-5677-0544","contributorId":5122,"corporation":false,"usgs":true,"family":"Scott","given":"Tia-Marie","email":"tia-mariescott@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":734061,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Phillips, Patrick J. 0000-0001-5915-2015 pjphilli@usgs.gov","orcid":"https://orcid.org/0000-0001-5915-2015","contributorId":172757,"corporation":false,"usgs":true,"family":"Phillips","given":"Patrick","email":"pjphilli@usgs.gov","middleInitial":"J.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":734062,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kolpin, Dana W. 0000-0002-3529-6505","orcid":"https://orcid.org/0000-0002-3529-6505","contributorId":204154,"corporation":false,"usgs":true,"family":"Kolpin","given":"Dana W.","affiliations":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":35680,"text":"Illinois-Iowa-Missouri Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"preferred":true,"id":734063,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Finkelstein, Kaitlyn M. 0000-0003-1588-3312","orcid":"https://orcid.org/0000-0003-1588-3312","contributorId":202727,"corporation":false,"usgs":true,"family":"Finkelstein","given":"Kaitlyn","email":"","middleInitial":"M.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":734067,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Furlong, Edward T. 0000-0002-7305-4603","orcid":"https://orcid.org/0000-0002-7305-4603","contributorId":204151,"corporation":false,"usgs":true,"family":"Furlong","given":"Edward T.","affiliations":[{"id":38175,"text":"Toxics Substances Hydrology Program","active":true,"usgs":true},{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true}],"preferred":true,"id":734064,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Foreman, William T. 0000-0002-2530-3310 wforeman@usgs.gov","orcid":"https://orcid.org/0000-0002-2530-3310","contributorId":190786,"corporation":false,"usgs":true,"family":"Foreman","given":"William","email":"wforeman@usgs.gov","middleInitial":"T.","affiliations":[{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":734065,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gray, James L. 0000-0002-0807-5635","orcid":"https://orcid.org/0000-0002-0807-5635","contributorId":202726,"corporation":false,"usgs":true,"family":"Gray","given":"James L.","affiliations":[{"id":5046,"text":"Branch of Analytical Serv (NWQL)","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true}],"preferred":true,"id":734066,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70195642,"text":"sir20185010 - 2018 - Characterization of water quality in Bushy Park Reservoir, South Carolina, 2013–15","interactions":[],"lastModifiedDate":"2018-04-25T16:19:05","indexId":"sir20185010","displayToPublicDate":"2018-04-25T15:15:00","publicationYear":"2018","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":"2018-5010","title":"Characterization of water quality in Bushy Park Reservoir, South Carolina, 2013–15","docAbstract":"The Bushy Park Reservoir is the principal water supply for 400,000 people in the greater Charleston, South Carolina, area, which includes homes as well as businesses and industries in the Bushy Park Industrial Complex. Charleston Water System and the U.S. Geological Survey conducted a cooperative study during 2013–15 to assess the circulation of Bushy Park Reservoir and its effects on water-quality conditions, specifically, recurring taste-and-odor episodes. This report describes the water-quality data collected for the study that included a combination of discrete water-column sampling at seven locations in the reservoir and longitudinal water-quality profiling surveys of the reservoir and tributaries to characterize the temporal and spatial water-quality dynamics of Bushy Park Reservoir. Water-quality profiling surveys were conducted with an autonomous underwater vehicle equipped with a multiparameter water-quality-sonde bulkhead. Data collected by the autonomous underwater vehicle included water temperature, dissolved oxygen, pH, specific conductance, turbidity, total chlorophyll as fluorescence (estimate of algal biomass), and phycocyanin as fluorescence (estimate of cyanobacteria biomass) data.
Characterization of the water-quality conditions in the reservoir included comparison to established State nutrient guidelines, identification of any spatial and seasonal variation in water-quality conditions and phytoplankton community structures, and assessment of the degree of influence of water-quality conditions related to Foster Creek and Durham Canal inflows, especially during periods of elevated taste-and-odor concentrations. Depth-profile and autonomous underwater vehicle survey data were used to identify areas within the reservoir where greater phytoplankton and cyanobacteria densities were most likely occurring.
Water-quality survey results indicated that Bushy Park Reservoir tended to stratify thermally at a depth of about 20 feet from June to early October. The stratification was limited to the deeper portions of the reservoir near the dam and often dissipated within the reservoir near the CWS intake less than a mile upstream from the dam. Where thermally stratified, a corresponding depletion of dissolved oxygen also occurred at about the same depth and resulted in an anoxic hypolimnion below the 25-foot depth and an increase in specific conductance, likely due to re-mobilized metals and phosphorus under reducing conditions. In general, chlorophyll estimated from fluorescence exhibited some spatial variation, but no strong consistent pattern or “hot spot” was observed. Phycocyanin, estimated from relative fluorescence unit output as blue-green algae cell density, periodically seemed to be greater in the upper portion of the reservoir, but those differences may be attributed to increased turbidity and the potential change in phytoplankton community structure that affects fluorescence. Increased phycocyanin was observed at about the 10-foot depth during the summer months.
A constant production of 2-methylisoborneol (MIB) near the dam and geosmin in the middle and upper portions of the reservoir appears to be occurring during the summer and early fall in the reservoir, but concentrations of these compounds tend to be between 10 and 15 nanograms per liter, which is at the Charleston Water System treatment threshold. At the Bushy Park Reservoir intake, the dominant taste-and-odor compound tended to be MIB, measured at a 2- or 3-to-1 ratio with geosmin during the summer and fall. During springtime episodes, however, when taste-and-odor compound concentrations typically are elevated above the Charleston Water System treatment threshold, the spatial distribution of geosmin concentrations greater than 15 nanograms per liter (28 to 38 nanograms per liter) was best explained by in situ production in the lower portion of the Bushy Park Reservoir near the dam rather than transport from Foster Creek. This pattern seems to indicate a possible shift in phytoplankton communities (or, at least, cyanobacteria communities) from MIB producers to geosmin producers.
The spatial and seasonal assessment of water-quality conditions in Bushy Park Reservoir identified seasonal differences in water chemistry and spatial differences between the upper and lower portions of the reservoir that correspond to the location of elevated geosmin concentrations. On the basis of the spatial and seasonal assessment of actinomycetes concentrations compared to taste-and-odor compound concentrations, cyanobacteria production likely was the dominant source of the taste-and-odor episodes rather than actinomycetes. The lack of spatial and seasonal patterns in actinomycetes concentrations did not correspond to the springtime geosmin concentrations that were elevated above the Charleston Water System treatment threshold in the lower portion of the reservoir. Additionally, actinomycetes concentrations, although ubiquitous, had a median of about 9 and maximum of about 20 colonies per milliliter, which can be considered low for elevated taste-and-odor compound production. Nonetheless, the potential exists for actinomycetes to be a secondary source of taste-and-odor production and could explain some of the ubiquitous occurrence of low-level taste-and-odor production, such as MIB concentrations, observed throughout the summer and early fall months.
When evaluated by biovolume, cyanobacteria were not the dominant phytoplankton group in Bushy Park Reservoir during the study period. Dolichospermum planctonicum (previously Anabaena planktonica ) was the dominant genera of the cyanobacteria group during spring periods. The geosmin-producing genera that were identified in the 2014 and 2015 spring communities in Bushy Park Reservoir were not observed in the 1999 and 2000 algal taxonomic data.
A more robust examination of phytoplankton species was conducted by using a multivariate analysis that identified seasonal changes in phytoplankton community structure. These seasonal phytoplankton communities appeared to be explained by seasonal changes in water chemistry and may be responsible for episodes of taste-and-odor occurrence, especially geosmin. The most probable source of geosmin identified during the study was D. planctonicum.
In a synoptic sampling event during a taste-and-odor episode in April 2015, cyanobacteria, not acinomycetes, also was indicated to be the more prevalent source of the geosmin. Although the Edisto River intake and its associated supply tunnel to the treatment facility had relatively high actinomycetes concentrations (130 and 140 colonies per milliliter, respectively) compared to the Bushy Park intake and tunnel (2 colonies per milliliter), corresponding geosmin concentrations were below 5 nanograms per liter for source water from the Edisto River intake and tunnel. Elevated geosmin concentrations above the Charleston Water System treatment threshold were identified in source waters from the Bushy Park Reservoir. The cyanobacteria community at the sampled sites in April 2015 was statistically similar to the community in the Bushy Park Reservoir in April 2014, when geosmin concentrations also were elevated. The only geosmin-producing genus identified at the Bushy Park intake, however, was D. planctonicum.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185010","collaboration":"Prepared in cooperation with Charleston Water System","usgsCitation":"Conrads, P.A., Journey, C.A., Petkewich, M.D., Lanier, T.H., and Clark, J.M., 2018, Characterization of water quality in Bushy Park Reservoir, South Carolina, 2013–15: U.S. Geological Survey Scientific Investigations Report 2018–5010, 175 p., https://doi.org/10.3133/sir20185010. ","productDescription":"xi, 175 p.","numberOfPages":"192","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-087952","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":437934,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Z7YOXC","text":"USGS data release","linkHelpText":"Phycocyanin, Velocity, AUV, and Profile Data for William Station Shutdown in Bushy Park Reservoir, South Carolina, 2017"},{"id":353632,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5010/sir20185010.pdf","text":"Report","size":"27.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5010"},{"id":353631,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5010/coverthb.jpg"},{"id":353639,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7NG4NVX","text":"USGS data release","description":"USGS data release","linkHelpText":"Water Quality Data for Bushy Park Reservoir, South Carolina 2013–2015"}],"country":"United States","state":"South Carolina","otherGeospatial":"Bushy Park Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.364990234375,\n 32.816132537537115\n ],\n [\n -79.43939208984375,\n 32.816132537537115\n ],\n [\n -79.43939208984375,\n 33.51162942617925\n ],\n [\n -80.364990234375,\n 33.51162942617925\n ],\n [\n -80.364990234375,\n 32.816132537537115\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, South Altantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Stephenson Center, Suite 129
Columbia, SC 29210
Hurricane Sandy was a large and intense storm with high winds that caused total water levels from combined tides and storm surge to reach 4.0 m in the Atlantic Ocean and 2.5 m in Great South Bay (GSB), a back-barrier bay between Fire Island and Long Island, New York. In this study the impact of the hurricane winds and waves are examined in order to understand the flow of ocean water into the back-barrier bay and water level variations within the bay. To accomplish this goal, a high resolution hurricane wind field is used to drive the coupled Delft3D-SWAN hydrodynamic and wave models over a series of grids with the finest resolution in GSB. The processes that control water levels in the back-barrier bay are investigated by comparing the results of four cases that include: (i) tides only; (ii) tides, winds and waves with no overwash over Fire Island allowed; (iii) tides, winds, waves and limited overwash at the east end of the island; (iv) tides, winds, waves and extensive overwash along the island. The results indicate that strong local wind-driven storm surge along the bay axis had the largest influence on the total water level fluctuations during the hurricane. However, the simulations allowing for overwash have higher correlation with water level observations in GSB and suggest that island overwash provided a significant contribution of ocean water to eastern GSB during the storm. The computations indicate that overwash of 7500–10,000 m3s−1 was approximately the same as the inflow from the ocean through the major existing inlet. Overall, the model results indicate the complex variability in total water levels driven by tides, ocean storm surge, surge from local winds, and overwash that had a significant impact on the circulation in Great South Bay during Hurricane Sandy.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.csr.2018.04.003","usgsCitation":"Bennett, V.C., Mulligan, R.P., and Hapke, C.J., 2018, A numerical model investigation of the impacts of Hurricane Sandy on water level variability in Great South Bay, New York: Continental Shelf Research, v. 161, p. 1-11, https://doi.org/10.1016/j.csr.2018.04.003.","productDescription":"11 p.","startPage":"1","endPage":"11","ipdsId":"IP-082328","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":468811,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.csr.2018.04.003","text":"Publisher Index Page"},{"id":353706,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Great South Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.7,\n 40.55\n ],\n [\n -72.7,\n 40.55\n ],\n [\n -72.7,\n 40.8\n ],\n [\n -73.7,\n 40.8\n ],\n [\n -73.7,\n 40.55\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"161","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee6d0e4b0da30c1bfbe52","contributors":{"authors":[{"text":"Bennett, Vanessa C. C.","contributorId":204457,"corporation":false,"usgs":false,"family":"Bennett","given":"Vanessa","email":"","middleInitial":"C. C.","affiliations":[{"id":36943,"text":"Queens University","active":true,"usgs":false}],"preferred":false,"id":734015,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mulligan, Ryan P.","contributorId":194423,"corporation":false,"usgs":false,"family":"Mulligan","given":"Ryan","email":"","middleInitial":"P.","affiliations":[{"id":35723,"text":"Queen's University - Kingston, Ontario","active":true,"usgs":false}],"preferred":false,"id":734016,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hapke, Cheryl J. 0000-0002-2753-4075 chapke@usgs.gov","orcid":"https://orcid.org/0000-0002-2753-4075","contributorId":2981,"corporation":false,"usgs":true,"family":"Hapke","given":"Cheryl","email":"chapke@usgs.gov","middleInitial":"J.","affiliations":[{"id":6676,"text":"USGS (retired)","active":true,"usgs":false}],"preferred":true,"id":734014,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70196693,"text":"70196693 - 2018 - Remote measurement of canopy water content in giant sequoias (Sequoiadendron giganteum) during drought","interactions":[],"lastModifiedDate":"2018-04-25T10:42:11","indexId":"70196693","displayToPublicDate":"2018-04-25T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Remote measurement of canopy water content in giant sequoias (Sequoiadendron giganteum) during drought","title":"Remote measurement of canopy water content in giant sequoias (Sequoiadendron giganteum) during drought","docAbstract":"California experienced severe drought from 2012 to 2016, and there were visible changes in the forest canopy throughout the State. In 2014, unprecedented foliage dieback was recorded in giant sequoia (Sequoiadendron giganteum) trees in Sequoia National Park, in the southern California Sierra Nevada mountains. Although visible changes in sequoia canopies can be recorded, biochemical and physiological responses to drought stress in giant sequoia canopies are not well understood. Ground-based measurements provide insight into the mechanisms of drought responses in trees, but are often limited to few individuals, especially in trees of tall stature such as giant sequoia. Recent studies demonstrate that remotely measured forest canopy water content (CWC) is a general indicator of canopy response to drought, but the underpinning leaf- to canopy-level causes of observed variation in CWC remain poorly understood. We combined field and airborne remote sensing measurements taken in 2015 and 2016 to assess the biophysical responses of giant sequoias to drought. In 49 study trees, CWC was related to leaf water potential, but not to the other foliar traits, suggesting that changes in CWC were made at whole-canopy rather than leaf scales. We found a non-random, spatially varying pattern in mapped CWC, with lower CWC values at lower elevation and along the outer edges of the groves. This pattern was also observed in empirical measurements of foliage dieback from the ground, and in mapped CWC across multiple sequoia groves in this region, supporting the hypothesis that drought stress is expressed in canopy-level changes in giant sequoias. The fact that we can clearly detect a relationship between CWC and foliage dieback, even without taking into account prior variability or new leaf growth, strongly suggests that remotely sensed CWC, and changes in CWC, are a useful measure of water stress in giant sequoia, and valuable for assessing and managing these iconic forests in drought.
The Oregon Department of Transportation (ODOT) and other state departments of transportation need quantitative information about the percentages of different land cover categories above any given stream crossing in the state to assess and address roadway contributions to water-quality impairments and resulting total maximum daily loads. The U.S. Geological Survey, in cooperation with ODOT and the FHWA, added roadway and land cover information to the online StreamStats application to facilitate analysis of stormwater runoff contributions from different land covers. Analysis of 25 delineated basins with drainage areas of about 100 mi2 indicates the diversity of land covers in the Willamette Valley, Oregon. On average, agricultural, developed, and undeveloped land covers comprise 15%, 2.3%, and 82% of these basin areas. On average, these basins contained about 10 mi of state highways and 222 mi of non-state roads. The Stochastic Empirical Loading and Dilution Model was used with available water-quality data to simulate long-term yields of total phosphorus from highways, non-highway roadways, and agricultural, developed, and undeveloped areas. These yields were applied to land cover areas obtained from StreamStats for the Willamette River above Wilsonville, Oregon. This analysis indicated that highway yields were larger than yields from other land covers because highway runoff concentrations were higher than other land covers and the highway is fully impervious. However, the total highway area was a fraction of the other land covers. Accordingly, highway runoff mitigation measures can be effective for managing water quality locally, they may have limited effect on achieving basin-wide stormwater reduction goals.
The Gunnison Basin Selenium Management Program implemented a water-quality monitoring network in 2011 in the lower Gunnison River Basin in Colorado. Selenium is a trace element that bioaccumulates in aquatic food chains and can cause reproductive failure, deformities, and other harmful effects. This report presents the percentile values of selenium because regulatory agencies in Colorado make decisions based on the U.S. Environmental Protection Agency (EPA) Clean Water Act Section 303(d) that uses percentile values of concentration. Also presented are dissolved-selenium loads at 18 sites in the lower Gunnison River Basin for water years (WYs) 2011–2016 (October 1, 2010, through September 30, 2016). Annual dissolved-selenium loads were calculated for five sites with continuous U.S. Geological Survey (USGS) streamflow-gaging stations. Annual dissolved-selenium loads for WY 2011 through WY 2016 ranged from 179 and 391 pounds (lb) at Uncompahgre River at Colona to 11,100 and 17,300 lb at Gunnison River near Grand Junction (herein called Whitewater), respectively.
Instantaneous loads were calculated for five sites with continuous U.S. Geological Survey (USGS) streamflow-gaging stations and 13 ancillary sites where discrete water-quality sampling also took place, using discrete water-quality samples and the associated discharge measurements collected during the period. Median instantaneous loads ranged from 0.01 pound per day (lb/d) at Smith Fork near Lazear to 33.0 lb/d at Whitewater. Mean instantaneous loads ranged from 0.06 lb/d at Smith Fork near Lazear to 36.2 lb/d at Whitewater. Most tributary sites in the basin had a median instantaneous dissolved-selenium load of less than 20.0 lb/day. In general, dissolved-selenium loads at Gunnison River main-stem sites showed an increase from upstream to downstream.
The State of Colorado water-quality standard for dissolved selenium of 4.6 micrograms per liter (µg/L) was compared to the 85th percentiles for dissolved selenium at selected sites. Annual 85th percentiles for dissolved selenium were calculated for the five core sites having USGS streamflow-gaging stations using estimated dissolved-selenium concentrations from linear regression models. The 85th-percentile concentrations for WYs 2011–2016 based on this method ranged from 0.62 µg/L and 1.1µg/L at Uncompahgre River at Colona to 12.1 µg/L and 18.7 µg/L at Uncompahgre River at Delta.
The 85th percentiles for dissolved selenium also were calculated for sites with sufficient data using water-quality samples collected during WYs 2011–2016. The annual 85th-percentile concentrations based on the discrete samples ranged from 0.16 µg/L and 0.17 µg/L at Gunnison River below Gunnison Tunnel to 62.2 µg/L and 170 µg/L at Loutzenhizer Arroyo at North River Road.
A trend analysis was completed for Whitewater to determine if dissolved-selenium loads are increasing or decreasing. The trend analysis indicates a decrease of 9,100 lb from WY 1986 to WY 2016, a 40.8 percent reduction during the time period. The trend analysis for the annual dissolved-selenium load for WY 1994 to WY 2016 indicates a decrease of 6,300 lb per year, or 33.3 percent.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185001","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Henneberg, M.F., 2018, Assessment of dissolved-selenium concentrations and loads in the lower Gunnison River Basin, Colorado, as part of the Selenium Management Program, from 2011 to 2016: U.S. Geological Survey Scientific Investigations Report 2018–5001, 23 p., https://doi.org/10.3133/ofr20185001.","productDescription":"v, 23 p.","numberOfPages":"33","onlineOnly":"Y","ipdsId":"IP-090932","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":353466,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5001/coverthb.jpg"},{"id":353467,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5001/sir20185001.pdf","text":"Report","size":"2.95 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5001"}],"country":"United States","state":"Colorado","otherGeospatial":"Lower Gunnison River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.5,\n 38\n ],\n [\n -107.25,\n 38\n ],\n [\n -107.25,\n 39.25\n ],\n [\n -108.5,\n 39.25\n ],\n [\n -108.5,\n 38\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Colorado Water Science Center
U.S. Geological Survey
Box 25046, MS 415
Denver, CO 80225
The city of Goma and its surrounding villages (Democratic Republic of the Congo, DRC) are among the world’s most densely populated regions strongly affected by volcanic hazards. In 2002, Nyiragongo volcano erupted destroying 10–15% of Goma and forced a mass evacuation of the population. Hence, the ~ 1.5 million inhabitants of Goma and Gisenyi (Rwanda) continue to live with the threat of new lava flows and other eruptive hazards from this volcano. The current network of fractures extends from Nyiragongo summit to Goma and continues beneath Lake Kivu, which gives rise to the fear that an eruption could even produce an active vent within the center of Goma or within the lake. A sub-lacustrine volcanic eruption with vents in the floor of the main basin and/or Kabuno Bay of Lake Kivu could potentially release about 300 km3 of carbon dioxide (CO2) and 60 km3 of methane (CH4) dissolved in its deep waters that would be catastrophic to populations (~ 2.5 million people) along the lake shores. For the time being, ongoing hazards related to Nyiragongo and Nyamulagira volcanoes silently kill people and animals, slowly destroy the environment, and seriously harm the health of the population. They include mazuku (CO2-rich locations where people often die of asphyxiation), the highly fluoridated surface and ground waters, and other locally neglected hazards. The volcanic gas plume causes poor air quality and acid rain, which is commonly used for drinking water. Given the large number of people at risk and the continued movement of people to Goma and the surrounding villages, there is an urgent need for a thorough natural hazards assessment in the region. This paper presents a general view of natural hazards in the region around Goma based on field investigations, CO2 measurements in mazuku, and chemistry data for Lake Kivu, rivers and rainwater. The field investigations and the datasets are used in conjunction with extremely rich-historical (1897–2000) and recently published information about Nyiragongo and Nyamulagira volcanoes and Lake Kivu. We also present maps of mazuku and fractures in Goma, describe the volcanic eruption history with hazard assessment and mitigation implications, and consider social realities useful for an integrated risk management strategy.
","language":"English","publisher":"Springer","doi":"10.1007/s11069-018-3288-x","usgsCitation":"Balagizi, C.M., Kies, A., Kasereka, M.M., Tedesco, D., Yalire, M.M., and McCausland, W.A., 2018, Natural hazards in Goma and the surrounding villages, East African Rift System: Natural Hazards, v. 93, no. 1, p. 31-66, https://doi.org/10.1007/s11069-018-3288-x.","productDescription":"36 p.","startPage":"31","endPage":"66","ipdsId":"IP-061455","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":353654,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Democratic Republic of the Congo","city":"Goma","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 20.1708984375,\n -5.353521355337321\n ],\n [\n 31.3330078125,\n -5.353521355337321\n ],\n [\n 31.3330078125,\n 6.18424616128059\n ],\n [\n 20.1708984375,\n 6.18424616128059\n ],\n [\n 20.1708984375,\n -5.353521355337321\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"93","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-03-31","publicationStatus":"PW","scienceBaseUri":"5afee6d3e4b0da30c1bfbe74","contributors":{"authors":[{"text":"Balagizi, Charles M.","contributorId":204381,"corporation":false,"usgs":false,"family":"Balagizi","given":"Charles","email":"","middleInitial":"M.","affiliations":[{"id":36925,"text":"Goma Volcano Observatory","active":true,"usgs":false}],"preferred":false,"id":733837,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kies, Antoine","contributorId":204383,"corporation":false,"usgs":false,"family":"Kies","given":"Antoine","email":"","affiliations":[{"id":36926,"text":"University of Luxembourg","active":true,"usgs":false}],"preferred":false,"id":733839,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kasereka, Marcellin M.","contributorId":204382,"corporation":false,"usgs":false,"family":"Kasereka","given":"Marcellin","email":"","middleInitial":"M.","affiliations":[{"id":36925,"text":"Goma Volcano Observatory","active":true,"usgs":false}],"preferred":false,"id":733838,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tedesco, Dario","contributorId":204384,"corporation":false,"usgs":false,"family":"Tedesco","given":"Dario","email":"","affiliations":[{"id":36927,"text":"Second University of Naples","active":true,"usgs":false}],"preferred":false,"id":733840,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Yalire, Mathieu M.","contributorId":204385,"corporation":false,"usgs":false,"family":"Yalire","given":"Mathieu","email":"","middleInitial":"M.","affiliations":[{"id":36925,"text":"Goma Volcano Observatory","active":true,"usgs":false}],"preferred":false,"id":733841,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McCausland, Wendy A. 0000-0002-8683-1440","orcid":"https://orcid.org/0000-0002-8683-1440","contributorId":204380,"corporation":false,"usgs":true,"family":"McCausland","given":"Wendy","email":"","middleInitial":"A.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":733836,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70196410,"text":"ofr20181023 - 2018 - California State Waters Map Series — Offshore of Gaviota, California","interactions":[],"lastModifiedDate":"2022-04-19T19:28:07.118361","indexId":"ofr20181023","displayToPublicDate":"2018-04-20T16:00:00","publicationYear":"2018","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":"2018-1023","title":"California State Waters Map Series — Offshore of Gaviota, California","docAbstract":"In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within the 3-nautical-mile limit of California’s State Waters. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data, acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow subsurface geology.
The map area is in the southern part of the Western Transverse Ranges geologic province, which is north of the California Continental Borderland. Significant clockwise rotation—at least 90°—since the early Miocene has been proposed for the Western Transverse Ranges province, and the region is presently undergoing north-south shortening. The offshore part of the map area lies south of the steep south flank of the Santa Ynez Mountains. The crest of the range, which has a maximum elevation of about 760 m in the map area, lies about 4 km north of the shoreline.
Gaviota is an unincorporated community that has a sparse population (less than 100), and the coastal zone is largely open space that is locally used for cattle grazing. The Union Pacific railroad tracks extend westward along the coast through the entire map area, within a few hundred meters of the shoreline. Highway 101 crosses the eastern part of the map area, also along the coast, then turns north (inland) and travels through Cañada de la Gaviota and Gaviota Pass en route to Buellton. Gaviota State Park lies at the mouth of Cañada de la Gaviota. West of Gaviota, the onland coastal zone is occupied by the Hollister Ranch, a privately owned, gated community that has no public access.
The map area has a long history of petroleum exploration and development. Several offshore gas fields were discovered and were developed by onshore directional drilling in the 1950s and 1960s. Three offshore petroleum platforms were installed in adjacent federal waters in 1976 (platform “Honda”) and 1989 (platforms “Heritage” and “Harmony”). Local offshore and onshore operations were serviced for more than a century by the Gaviota marine terminal, which is currently being decommissioned and will be abandoned in an intended transition to public open space.
The Offshore of Gaviota map area lies within the western Santa Barbara Channel region of the Southern California Bight, and it is somewhat protected from large Pacific swells from the north and northwest by Point Conception and from south and southwest swells by offshore islands and banks. Much of the shoreline in the map area is characterized by narrow beaches that have thin sediment cover, backed by low (10- to 20-m-high) cliffs that are capped by a narrow coastal terrace. Beaches are subject to wave erosion during winter storms, followed by gradual sediment recovery or accretion in the late spring, summer, and fall months during the gentler wave climate.
The map area lies in the western-central part of the Santa Barbara littoral cell, which is characterized by west-to-east transport of sediment from Point Arguello on the northwest to Hueneme and Mugu Canyons on the southeast. Sediment supply to the western and central part of the littoral cell is mainly from relatively small coastal watersheds. In the map area, sediment sources include Cañada de la Gaviota (52 km2), as well as Cañada de la Llegua, Arroyo el Bulito, Cañada de Santa Anita, Cañada de Alegria, Cañada del Agua Caliente, Cañada del Barro, Cañada del Leon, Cañada San Onofre, and many others. Coastal-watershed discharge and sediment load are highly variable, characterized by brief large events during major winter storms and long periods of low (or no) flow and minimal sediment load between storms. In recent (recorded) history, the majority of high-discharge, high-sediment-flux events have been associated with El Niño phases of the El Niño–Southern Oscillation climatic pattern.
Shelf width in the Offshore of Gaviota map area ranges from about 4.3 to 4.7 km, and shelf slopes average about 1.0° to 1.2° but are highly variable because of the presence of the large Gaviota sediment bar. This bar extends southwestward for about 9 km from the mouth of Cañada de la Gaviota to the shelf break, is as wide as 2 km, and is by far the largest shore-attached sediment bar in the Santa Barbara Channel. The shelf is underlain by bedrock and variable amounts (0 to as much as 36 m in the Gaviota bar) of upper Quaternary sediments deposited as sea level fluctuated in the late Pleistocene. The trend of the shelf break changes from about 276° to 236° azimuth over a distance of about 12 km, and it ranges in depth from about 91 m to as shallow as 62 to 73 m where significant shelf-break and upper-slope failure and landsliding has apparently occurred. The shelf break in the western part of the map area is notably embayed by the heads of three large (150- to 300-m-wide) channels that have been referred to as “the Gaviota Canyons” or as “Drake Canyon,” “Sacate Canyon,” and “Alegria Canyon.”
Seafloor habitats in the broad Santa Barbara Channel region consist of significant amounts of soft, unconsolidated sediment interspersed with isolated areas of rocky habitat that support kelp-forest communities in the nearshore and rocky-reef communities in deeper water. The potential marine benthic habitat types mapped in the Offshore of Gaviota map area are directly related to its Quaternary geologic history, geomorphology, and active sedimentary processes. These potential habitats lie primarily within the Shelf (continental shelf) but also partly within the Flank (basin flank or continental slope) megahabitats. The fairly homogeneous seafloor of sediment and low-relief bedrock provides characteristic habitat for rockfish, groundfish, crabs, shrimp, and other marine benthic organisms. Several areas of smooth sediment form nearshore terraces that have relatively steep, smooth fronts, which may be attractive to groundfish. Below the steep shelf break, soft, unconsolidated sediment is interrupted by the heads of several submarine canyons and rills, some bedrock exposures, and small carbonate mounds associated with asphalt mounds and pockmarks, also good potential habitat for rockfish. The map area includes the relatively small (5.2 km2) Kashtayit State Marine Conservation Area, which largely occupies the inner part of the Gaviota sediment bar.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181023","usgsCitation":"Johnson, S.Y., Dartnell, P., Cochrane, G.R., Hartwell, S.R., Golden, N.E., Kvitek, R.G., and Davenport, C.W. (S.Y. Johnson and S.A. 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Johnson"},{"id":353506,"rank":10,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1023/coverthb.jpg"}],"scale":"24000","country":"United States","state":"California","city":"Gaviota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.3753,\n 34.4056\n ],\n [\n -120.1833,\n 34.4056\n ],\n [\n -120.1833,\n 34.5425\n ],\n [\n -120.3753,\n 34.5425\n ],\n [\n -120.3753,\n 34.4056\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information
Pacific Coastal & Marine Science Center
U.S. Geological Survey
Pacific Science Center
2885 Mission St.
Santa Cruz, CA 95060
http://walrus.wr.usgs.gov/
In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within the 3-nautical-mile limit of California’s State Waters. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data, acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow subsurface geology.
The Offshore of Point Conception map area is in the westernmost part of the Western Transverse Ranges geologic province, which is north of the California Continental Borderland. Significant clockwise rotation—at least 90°—since the early Miocene has been proposed for the Western Transverse Ranges province, and this region is presently undergoing north-south shortening. The offshore part of the map area lies south of the steep south and west flanks of the Santa Ynez Mountains. The crest of the range, which has a maximum elevation of about 340 m in the map area, lies about 5 km north and east of the arcuate shoreline.
The onland part of the coastal zone is remote and sparsely populated. The road to Jalama Beach County Park provides the only public coastal access in the entire map area. North of this county park, the coastal zone is part of Vandenberg Air Force Base. South of Jalama Beach County Park, most of the coastal zone is part of the Cojo-Jalama Ranch, purchased by the Nature Conservancy in December 2017. A relatively small part of the coastal zone in the eastern part of the map area lies within the privately owned Hollister Ranch. The nearest significant commercial centers are Lompoc (population, about 42,000), about 10 km north of the map area, and Goleta (population, about 30,000), about 50 km east of the map area. The Union Pacific railroad tracks run west and northwest along the coast through the entire map area, within a few hundred meters of the shoreline. The map area has a long history of petroleum exploration, and the seafloor notably includes large asphalt mounds and pockmarks that result from petroleum seepage. Several offshore gas and oil fields were discovered, and some were developed, in and on the margin of California’s State Waters.
Much of the shoreline in the Offshore of Point Conception map area is characterized by narrow beaches that have thin sediment cover above bedrock platforms, backed by low (10- to 20-m-high) cliffs that are capped by a coastal terrace. Beaches are subject to wave erosion during winter storms, followed by gradual sediment recovery or accretion in the late spring, summer, and fall months during the gentler wave climate. The map area lies in the west-central part of the Santa Barbara littoral cell, which is characterized by west-to-east transport of sediment from Point Arguello on the northwest to Hueneme and Mugu Canyons on the southeast. Sediment supply to the map area is mainly from relatively small coastal watersheds, including the Jalama Creek–Espada Creek drainage basin (about 63 km2), as well as Cañada del Jolloru, Black Canyon, Wood Canyon, Cañada del Cojo, and Barranca Honda. Coastal-watershed discharge and sediment load are highly variable, characterized by brief large events during major winter storms and long periods of low (or no) flow and minimal sediment load between storms. In recent (recorded) history, the majority of high-discharge, high-sediment-flux events have been associated with El Niño phases of the El Niño–Southern Oscillation climatic pattern.
Following the coastline, the shelf bends to the north and northwest around Point Conception, and the trend of the shelf break changes from about 298° to 241° azimuth. Shelf width ranges from about 5 km south of Point Conception to about 11 km northwest of it; the slope ranges from about 1.0° to 1.2° to about 0.7° south and northwest of Point Conception, respectively. Southwest of Point Conception, the shelf break and upper slope are incised by a 600-m-wide, 20- to 30-m-deep, south-facing trough, one of five heads of the informally named Arguello submarine canyon.
The map area is located at a major biogeographic transition zone between the east-west-trending Santa Barbara Channel region of the Southern California Bight and the northwest-trending central California coast. North of Point Conception, the coast is subjected to high wave exposure from the north, west, and south, as well as consistently strong upwelling that brings cold, nutrient-rich waters to the surface. Southeast of Point Conception, the Santa Barbara Channel is largely protected from strong north swells by Point Conception and from south swells by the Channel Islands; surface waters are warmer, and upwelling is weak and seasonal.
Seafloor habitats in the broad Santa Barbara Channel region consist of significant amounts of soft, unconsolidated sediment interspersed with isolated areas of rocky habitat that support kelp-forest communities in the nearshore and rocky-reef communities in deeper water. The potential marine benthic habitat types mapped in the Offshore of Point Conception map area are directly related to its Quaternary geologic history, geomorphology, and active sedimentary processes. These potential habitats lie primarily within the Shelf (continental shelf) but also partly within the Flank (basin flank or continental slope) megahabitats. The fairly homogeneous seafloor of sediment and low-relief bedrock provides characteristic habitat for rockfish, groundfish, crabs, shrimp, and other marine benthic organisms. Several areas of smooth sediment form nearshore terraces that have relatively steep, smooth fronts, which are attractive to groundfish. Below the steep shelf break, soft, unconsolidated sediment is interrupted by the heads of several submarine canyons, gullies, and rills, also good potential habitat for rockfish. The map area includes the large (58.3 km2) Point Conception State Marine Reserve.
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Pacific Coastal & Marine Science Center
U.S. Geological Survey
Pacific Science Center
2885 Mission St.
Santa Cruz, CA 95060
http://walrus.wr.usgs.gov/
The collection of high-frequency (in other words, “continuous”) water data has been made easier over the years because of advances in technologies to measure, transmit, store, and query large, temporally dense datasets. Commercially available, in-situ sensors and data-collection platforms—together with new techniques for data analysis—provide an opportunity to monitor water quantity and quality at time scales during which meaningful changes occur. The U.S. Geological Survey (USGS) Continuous Monitoring Workshop was held to build stronger collaboration within the Water Mission Area on the collection, interpretation, and application of continuous monitoring data; share technical approaches for the collection and management of continuous data that improves consistency and efficiency across the USGS; and explore techniques and tools for the interpretation of continuous monitoring data, which increases the value to cooperators and the public. The workshop was organized into three major themes: Collecting Continuous Data, Understanding and Using Continuous Data, and Observing and Delivering Continuous Data in the Future. Presentations each day covered a variety of related topics, with a special session at the end of each day designed to bring discussion and problem solving to the forefront.
The workshop brought together more than 70 USGS scientists and managers from across the Water Mission Area and Water Science Centers. Tools to manage, assure, control quality, and explore large streams of continuous water data are being developed by the USGS and other organizations and will be critical to making full use of these high-frequency data for research and monitoring. Disseminating continuous monitoring data and findings relevant to critical cooperator and societal issues is central to advancing the USGS networks and mission. Several important outcomes emerged from the presentations and breakout sessions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181059","usgsCitation":"Sullivan, D.J., Joiner, J.K., Caslow, K.A., Landers, M.N., Pellerin, B.A., Rasmussen, P.P., and Sheets, R.A., 2018, U.S. Geological Survey continuous monitoring workshop—Workshop summary report: U.S. Geological Survey Open-File Report 2018–1059, 29 p., https://doi.org/10.3133/ofr20181059.","productDescription":"iv, 29 p.","numberOfPages":"33","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-092143","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":353586,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1059/coverthb.jpg"},{"id":353587,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1059/ofr20181059.pdf","text":"Report","size":"1.01 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1059"}],"contact":"Director, Upper Midwest Water Science Center
U.S. Geological Survey
8505 Research Way
Middleton, WI 53562
The largest populations of federally endangered Lost River (Deltistes luxatus) and shortnose suckers (Chasmistes brevirostris) exist in Upper Klamath Lake, Oregon, and Clear Lake Reservoir, California. Upper Klamath Lake populations are decreasing because adult mortality, which is relatively low, is not being balanced by recruitment of young adult suckers into known spawning aggregations. Most Upper Klamath Lake juvenile sucker mortality appears to occur within the first year of life. Annual production of juvenile suckers in Clear Lake Reservoir appears to be highly variable and may not occur at all in very dry years. However, juvenile sucker survival is much higher in Clear Lake, with non-trivial numbers of suckers surviving to join spawning aggregations. Long-term monitoring of juvenile sucker populations is needed to (1) determine if there are annual and species-specific differences in production, survival, and growth, (2) to identify the season (summer or winter) in which most mortality occurs, and (3) to help identify potential causes of high juvenile sucker mortality, particularly in Upper Klamath Lake.
We initiated an annual juvenile sucker monitoring program in 2015 to track cohorts in 3 months (June, August, and September) annually in Upper Klamath Lake and Clear Lake Reservoir. We tracked annual variability in age-0 sucker apparent production, juvenile sucker apparent survival, and apparent growth. Using genetic markers, we were able to classify suckers as one of three taxa: shortnose or Klamath largescale suckers, Lost River, or suckers with genetic markers of both species (Intermediate Prob[LRS]). Using catch data, we generated taxa-specific indices of year class strength, August–September apparent survival, and overwinter apparent survival. We also examined prevalence and severity of afflictions such as parasites, wounds, and deformities.
Indices of year class strength in Upper Klamath Lake were similar for shortnose suckers in 2015 and 2016, but about twice as high for Lost River suckers and suckers having intermediate Prob[LRS] in 2016 than in 2015. Indices of apparent August–September survival were lower in 2016 (0.41) than in 2015 (1.07) for shortnose suckers and suckers identified as having intermediate Prob [LRS] (0.14 in 2016 and 1.69 in 2015). Indices of apparent August—September survival were similar in 2016 (0.16) and 2015 (0.07) for Lost River suckers. Indices of apparent survival were lower for age-0 Lost River suckers than age-0 shortnose suckers in both years. Although samples sizes are small, a declining trend in the ratio of Lost River to shortnose suckers from 28/23 (1.22) as age-0 fish in September of 2015 to 1/9 (0.11) as age-1 fish in June of 2016 is consistent with higher over winter apparent mortality for Lost River suckers than shortnose suckers in Upper Klamath Lake.
Shortnose sucker year class strength was greater in years with high Willow Creek inflows and Clear Lake surface elevation during the spawning season, indicating that access to spawning habitat was an important contributing factor. In previous sampling, age-0 sucker catch per unit effort (CPUE) was relatively high in 2011 and 2012, moderately high in 2013, and zero in 2014 and 2015. The 2011 and 2012 year classes continued to be detected, but the 2013 year class went undetected for the first time in 2016. The 2014 year class continued to be undetected in 2016. Three suckers with one annulus each on fin rays were captured in Clear Lake in 2016. Although these fish are potential representatives of the 2015 year class, they were small for their age, indicating they may have hatched in 2016. Age-0 shortnose and Lost River suckers were captured in Clear Lake in 2016, indicating new cohorts of both taxa were produced. Moderate to abundant year classes were produced in 2011, 2012, and 2016 when lake surface elevation greater than 1,378.9 m (4,524 ft) during the February–June spawning season. Also in 2011 and 2016, rapid increases in lake-surface elevation indicated potentially high Willow Creek inflows. A somewhat less abundant year class produced in 2012 than in 2011 and 2016 was associated with lower spawning season inflows. The apparently smaller 2013 year class was formed when Willow Creek inflows were apparently low and lake surface never exceeded 1,379.2 m (4,524.9 ft). In 2014 and 2015, when year-classes were small or not detected, the Clear Lake surface elevations were at or below 1,378.2 m (4,522 ft), and there was very little spring time Willow Creek inflow.
Age-0 shortnose sucker CPUE in Clear Lake was correlated with seasonal decreases in water volumes in 2016 and could not be used to create indices of August–September survival. Age-0 shortnose sucker catch rates in Clear Lake Reservoir were about seven times less in August than in September. Meanwhile, the water volume in Clear Lake Reservoir declined by about 36 percent between these two sampling periods. Higher September catch rates may have resulted from additional age-0 suckers entering the lake from the river, a concentrating effect of declining water volumes, or both.
Differences in August standard length, apparent growth rates, and the prevalence of abnormalities were consistent with healthier age-0 suckers in Clear Lake Reservoir than in Upper Klamath Lake. Age-0 suckers were larger in August in Clear Lake Reservoir than in Upper Klamath Lake, which may be due to an earlier hatch date, faster growth, or both in Clear Lake Reservoir. Sample sizes were only large enough to compare growth rates of age-0 shortnose suckers from Upper Klamath Lake in 2015 to Clear Lake Reservoir in 2016. Age-0 shortnose suckers grew more between August and September in Clear Lake Reservoir in 2016 than in Upper Klamath Lake in 2015. Petechial hemorrhages of the skin on age-0 suckers were more prevalent in Upper Klamath Lake than in Clear Lake Reservoir in 2016. Deformed opercula, black-spot forming parasites, and infections presumed to be Columnaris sp. were observed on less than 12 percent of suckers from Upper Klamath Lake but were not observed on suckers from Clear Lake Reservoir in 2016.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181066","usgsCitation":"Burdick, S.M., Ostberg, C.O., and Hoy, M.S., 2018, Juvenile Lost River and shortnose sucker year class strength, survival, and growth in Upper Klamath Lake, Oregon, and Clear Lake Reservoir, California—2016 Monitoring Report: U.S. Geological Survey Open-File Report 2018–1066, 43 p., https://doi.org/10.3133/ofr20181066.","productDescription":"vi, 43 p.","numberOfPages":"54","onlineOnly":"Y","ipdsId":"IP-094193","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":353625,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1066/coverthb.jpg"},{"id":353626,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1066/ofr20181066.pdf","text":"Report","size":"1.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1066"}],"country":"United States","state":"California, Oregon","county":"Klamath County, Modoc County","otherGeospatial":"Clear Lake Reservoir, Upper Klamath Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.11509704589845,\n 42.222924262739824\n ],\n [\n -121.75186157226561,\n 42.222924262739824\n ],\n [\n -121.75186157226561,\n 42.61829672418602\n ],\n [\n -122.11509704589845,\n 42.61829672418602\n ],\n [\n -122.11509704589845,\n 42.222924262739824\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.23687744140624,\n 41.781552998900345\n ],\n [\n -121.04736328125,\n 41.781552998900345\n ],\n [\n -121.04736328125,\n 41.94365947797709\n ],\n [\n -121.23687744140624,\n 41.94365947797709\n ],\n [\n -121.23687744140624,\n 41.781552998900345\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115
The first U.S. Department of the Interior Economics Workshop was held April 5–7, 2017 in Washington, D.C., to identify, highlight, and better understand needs and opportunities for economic analysis to support the Department of the Interior’s mission. The Economics Workshop, jointly convened by the Department of the Interior Office of Policy Analysis and the U.S. Geological Survey Science and Decisions Center, provided an opportunity for Department of the Interior’s economists to share expertise and experiences and to build collaboration and communication channels across the Department of the Interior.
Natural and cultural resource managers face complex questions and often have to balance competing stakeholder interests. Per the mission statement, the Department of the Interior “protects and manages the Nation’s natural resources and cultural heritage; provides scientific and other information about those resources; and honors its trust responsibilities or special commitments to American Indians, Alaska Natives, and affiliated island communities.” Economic analysis is relevant to issues integral to nearly all the land and water management decisions made by the Department of the Interior. More than 80 Department of the Interior economists gathered at the Economics Workshop to share their work, discuss common challenges, and identify approaches to advance the use and contribution of economics at the Department of the Interior.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181054","collaboration":"Prepared in cooperation with the Office of Policy Analysis, U.S. Department of the Interior","usgsCitation":"Pindilli, E.J., Crowley, C.S.L., Cline, S.A., Good, A.J., Shapiro, C.D., and Simon, B.M., 2018, Supporting natural resource management—The role of economics at the Department of the Interior—A workshop report: U.S. Geological Survey Open-File Report 2018–1054, 32 p., https://doi.org/10.3133/ofr20181054.","productDescription":"iv, 32 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-093562","costCenters":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"links":[{"id":353564,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1054/coverthb.jpg"},{"id":353565,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1054/ofr20181054.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1054"}],"contact":"Director, Science and Decisions Center
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
Coastal communities are increasingly concerned about the dynamic balance between freshwater and saltwater because of its implications for societal, economic, and ecological resources. While the mixing of freshwater and saltwater sources defines coastal estuaries and lagoons, sudden changes in this balance can have a large effect on critical ecosystems and infrastructure. Any change to the delivery of water from either source has the potential to affect the health of both humans and natural biota and also to damage coastal infrastructure. This fact sheet discusses the potential of major shifts in the dynamic freshwater-saltwater balance to alter the environment and coastal stability.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20183022","usgsCitation":"Conrads, P.A., Rodgers, K.D., Passeri, D.L., Prinos, S.T., Smith, C., Swarzenski, C.M., and Middleton, B.A., 2018, Coastal estuaries and lagoons: The delicate balance at the edge of the sea: U.S. Geological Survey Fact Sheet 2018–3022, 4 p., https://doi.org/10.3133/fs20183022. ","productDescription":"4 p.","onlineOnly":"N","ipdsId":"IP-094263","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":353584,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2018/3022/coverthb2.jpg"},{"id":353585,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2018/3022/fs20183022.pdf","text":"Report","size":"1.11 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2018–3022"}],"contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern
Columbia, SC 29210