Groundwater withdrawals since the 1940s have lowered water levels, altered groundwater-flow directions, and caused saltwater to intrude within some freshwater-containing sands of the fluvial-deltaic Southern Hills regional aquifer system beneath Baton Rouge, Louisiana. New interpretations of stratigraphic correlations amongst geophysical well logs were utilized to revise a hydrogeologic framework that delineates the depth and thickness variations of aquifers and confining units in the Southern Hills regional aquifer system. A groundwater-flow and chloride-transport model incorporating the revised framework was constructed to assess the effects of groundwater withdrawals on the rate and pathways of saltwater migration in the “1,500-foot” sand, “2,400-foot” sand, and the “2,800-foot” sand. Groundwater withdrawals reported since 1940 were compiled to specify annual average withdrawal rates through 2016 for 722 wells. Regional groundwater flow throughout the Southern Hills regional aquifer system was first simulated with MODFLOW, and flow-model parameters were calibrated to 8,810 water levels observed through 2016 by using the parameter-estimation code PEST++. Saltwater transport was subsequently simulated for the “1,500-foot” sand, “2,400-foot” sand, and the “2,800-foot” sand by using the variable-density code, SEAWAT. Chloride-concentration measurements were used as a proxy for saltwater to formulate the concentration initial conditions and calibrate the transport-model parameters.
Three groundwater-management scenarios were simulated to evaluate the effects of different groundwater withdrawals on future groundwater levels and saltwater concentrations in the “1,500-foot” sand, “2,400-foot” sand, and “2,800-foot” sand. All three scenarios simulated the period from 2017 through 2112 (96 years), and the water levels and concentrations simulated for 2047 and 2112 were compared among the scenarios. The first scenario simulated a continuation of groundwater withdrawals at 2016 rates and represents the “status quo” of groundwater withdrawals. The second scenario simulated the effects of discontinuing 10,620 gallons per minute (gal/min) of withdrawals from the “2,800-foot” sand, and the third scenario simulated reallocating 2,000 gal/min of withdrawals from the “1,500-foot” sand to the “2,800-foot” sand. Continuation of the “status quo” withdrawals results in lower water levels by 2047 around groundwater-withdrawal locations in the “1,500-foot” sand, “2,400-foot” sand, and “2,800-foot” sand. By 2112, water levels recover to higher levels as flow in the aquifer approaches equilibrium. Saltwater within the “1,500-foot” sand would continue migrating toward public-supply wells located 2.4 miles (mi) north of the Baton Rouge Fault, but a “scavenger well” that removes relatively concentrated water from the base of the “1,500-foot” sand attenuates chloride concentrations at the public-supply wells. Saltwater within the “2,400-foot” sand would continue to encroach on a well with large withdrawals and farther east within an area about 1 mi north of the Baton Rouge Fault. Saltwater within the “2,800-foot” sand would migrate northward toward withdrawal wells located about 3 mi north of the industrial district. Cessation of 10,620 gal/min of industrial withdrawals from the “2,800-foot” sand about 12 mi northwest of the industrial district (scenario 2) would cause a substantial water-level recovery in the “2,800-foot” sand in the area of discontinued withdrawals. Groundwater levels 3 mi north of the industrial district would be 25–30 feet higher in 2047 than predicted for the “status quo” withdrawals. Saltwater encroachment toward wells north of the industrial district would be slowed because of the decreased hydraulic gradient. Reallocating 2,000 gal/min of withdrawals from the “1,500-foot” sand to the “2,800-foot” sand 12 mi northwest of the industrial district (scenario 3) would have a negligible effect on water levels and chloride concentrations in the “1,500-foot” sand 15 mi to the south-southeast where saltwater is encroaching toward wells in the “1,500-foot” sand. Within the “2,800-foot” sand, the area of saltwater encroachment is only 3 mi from increased withdrawals in the “2,800-foot” sand, and water levels would be about 5 feet lower in 2047 than for the “status quo” scenario. A larger hydraulic gradient would cause slightly faster saltwater transport and higher chloride concentrations within this area of the “2,800-foot” sand.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195102","collaboration":"Prepared in cooperation with the Capital Area Groundwater Conservation Commission; the Louisiana Department of Transportation and Development, Public Works and Water Resources Division; and the City of Baton Rouge and Parish of East Baton Rouge","usgsCitation":"Heywood, C.E., Lindaman, M., and Lovelace, J.K., 2019, Simulation of groundwater flow and chloride transport in the “1,500-foot” sand, “2,400-foot” sand, and “2,800-foot” sand of the Baton Rouge area, Louisiana: U.S. Geological Survey Scientific Investigations Report 2019–5102, 49 p., https://doi.org/10.3133/sir20195102.","productDescription":"Report: ix, 49 p.; Data Release","numberOfPages":"63","onlineOnly":"N","ipdsId":"IP-099059","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":399545,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109561.htm"},{"id":370615,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5102/sir20195102.pdf","text":"Report","size":"22.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5102"},{"id":370616,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9URJ38Q","text":"USGS data release","description":"USGS Data Release","linkHelpText":"SEAWAT model archive of chloride transport in the “1,500-foot”, “2,400-foot”, and “2,800-foot” sands of the Baton Rouge Area, Louisiana"},{"id":370614,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5102/coverthb.jpg"}],"country":"United States","state":"Louisiana","city":"Baton Rouge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.75,\n 31.25\n ],\n [\n -90.5,\n 31.25\n ],\n [\n -90.5,\n 30.25\n ],\n [\n -91.75,\n 30.25\n ],\n [\n -91.75,\n 31.25\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
640 Grassmere Park Drive, Suite 100
Nashville, TN 37211
Quantifying temperature and moisture at the soil surface is essential for understanding how soil surface biota respond to changes in the environment. However, at the soil surface these variables are highly dynamic and standard sensors do not explicitly measure temperature or moisture in the upper few millimeters of the soil profile. This paper describes methods for manufacturing simple, inexpensive sensors that simultaneously measure the temperature and moisture of the upper 5 mm of the soil surface. In addition to sensor construction, steps for quality control, as well as for calibration for various substrates, are explained. The sensors incorporate a Type E thermocouple to measure temperature and assess soil moisture by measuring the resistance between two gold-plated metal probes at the end of the sensor at a depth of 5 mm. The methods presented here can be altered to customize probes for different depths or substrates. These sensors have been effective in a variety of environments and have endured months of heavy rains in tropical forests as well as intense solar radiation in deserts of the southwestern U.S. Results demonstrate the effectiveness of these sensors for evaluating warming, drying, and freezing of the soil surface in a global change experiment.
","language":"English","publisher":"JOVE","doi":"10.3791/60308","usgsCitation":"Howell, A.J., Tucker, C., Grote, E.E., Veste, M., Belnap, J., Kast, G., Weber, B., and Reed, S.C., 2019, Manufacturing simple and inexpensive soil surface temperature and gravimetric water content sensors: Journal of Visualized Experiments, v. 154, e60308, 13 p., https://doi.org/10.3791/60308.","productDescription":"e60308, 13 p.","ipdsId":"IP-108933","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":458912,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://resolver.obvsg.at/urn:nbn:at:at-ubg:3-13924","text":"Publisher Index Page"},{"id":377455,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"154","noUsgsAuthors":false,"publicationDate":"2019-12-21","publicationStatus":"PW","contributors":{"authors":[{"text":"Howell, Armin J. 0000-0003-1243-0238 ahowell@usgs.gov","orcid":"https://orcid.org/0000-0003-1243-0238","contributorId":196798,"corporation":false,"usgs":true,"family":"Howell","given":"Armin","email":"ahowell@usgs.gov","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":796052,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tucker, Colin 0000-0002-4539-7780 ctucker@usgs.gov","orcid":"https://orcid.org/0000-0002-4539-7780","contributorId":167487,"corporation":false,"usgs":true,"family":"Tucker","given":"Colin","email":"ctucker@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":796053,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grote, Edmund E. 0000-0002-9103-9482 ed_grote@usgs.gov","orcid":"https://orcid.org/0000-0002-9103-9482","contributorId":4271,"corporation":false,"usgs":true,"family":"Grote","given":"Edmund","email":"ed_grote@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":796054,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Veste, Maik","contributorId":238105,"corporation":false,"usgs":false,"family":"Veste","given":"Maik","email":"","affiliations":[],"preferred":false,"id":796055,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Belnap, Jayne 0000-0001-7471-2279 jayne_belnap@usgs.gov","orcid":"https://orcid.org/0000-0001-7471-2279","contributorId":1332,"corporation":false,"usgs":true,"family":"Belnap","given":"Jayne","email":"jayne_belnap@usgs.gov","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":796056,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kast, Gerhard","contributorId":238106,"corporation":false,"usgs":false,"family":"Kast","given":"Gerhard","email":"","affiliations":[],"preferred":false,"id":796057,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Weber, Bettina","contributorId":21447,"corporation":false,"usgs":true,"family":"Weber","given":"Bettina","affiliations":[],"preferred":false,"id":796058,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Reed, Sasha C. 0000-0002-8597-8619 screed@usgs.gov","orcid":"https://orcid.org/0000-0002-8597-8619","contributorId":462,"corporation":false,"usgs":true,"family":"Reed","given":"Sasha","email":"screed@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":796059,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70203334,"text":"sir20195038 - 2019 - Estimation of groundwater flow through Yucca Flat based on a multiple-well aquifer test at well ER-6–1–2 main, Nevada National Security Site, southern Nevada","interactions":[],"lastModifiedDate":"2019-12-19T16:54:16","indexId":"sir20195038","displayToPublicDate":"2019-12-19T14:24:46","publicationYear":"2019","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":"2019-5038","displayTitle":"Estimation of Groundwater Flow Through Yucca Flat Based on a Multiple-Well Aquifer Test at Well ER-6-1-2 Main, Nevada National Security Site, Southern Nevada","title":"Estimation of groundwater flow through Yucca Flat based on a multiple-well aquifer test at well ER-6–1–2 main, Nevada National Security Site, southern Nevada","docAbstract":"The rate of groundwater flow past underground nuclear testing areas in Yucca Flat at the Nevada National Security Site, southern Nevada, was estimated using results from the ER-6-1-2 main multiple-well aquifer test (MWAT), done during February 5–July 23, 2004. Drawdowns in 13 observation wells were evaluated from pumping in well ER-6-1-2 main and used as observations in a regional groundwater-flow model to estimate the groundwater-flow rate. Flow from southern Yucca Flat regionally was constrained by detecting drawdown in Tracer Well 3, which is 33 miles south-southwest of pumping well ER-6-1-2 main. Predevelopment flow, the ER-6-1-2 main MWAT, and regional groundwater pumping were simulated in separate models that jointly informed estimates of transmissivity and specific-yield distributions. Predevelopment flow constrained groundwater-flow estimates from southern Yucca Flat because the steady-state model correctly simulated regional groundwater discharges in the Ash Meadows groundwater basin and the surrounding basins. Less than 600 acre-feet per year of groundwater moves from underground nuclear testing areas and flows south of well ER-6-1-2 main in southern Yucca Flat.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195038","collaboration":"Prepared in cooperation with the U.S. Department of Energy Office of Environmental Management, National Nuclear Security Administration, Nevada Site Office, under Interagency Agreement DE-EM0004969","usgsCitation":"Jackson, T.R., and Halford, K.J., 2019, Estimation of groundwater flow through Yucca Flat based on a multiple-well aquifer test at well ER-6–1–2 main, Nevada National Security Site, southern Nevada: U.S. Geological Survey Scientific Investigations Report 2019–5038, 27 p., https://doi.org/10.3133/sir20195038.\n","productDescription":"Report: vi, 27 p.; Data Release","numberOfPages":"38","onlineOnly":"Y","ipdsId":"IP-098808","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":370390,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5038/coverthb.jpg"},{"id":370391,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5038/sir20195038.pdf","text":"Report","size":"3.99 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5038"},{"id":370392,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9U2WG04","text":"USGS data release","linkHelpText":"Supplemental data for estimation of groundwater flow through Yucca Flat based on a multiple-well aquifer test at well ER-6–1–2 main, Nevada National Security Site, southern Nevada"}],"country":"United States","state":"Nevada","otherGeospatial":"Nevada National Security Site","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.633333,\n 37.283333\n ],\n [\n -116.633333,\n 36.966667\n ],\n [\n -116.45,\n 36.966667\n ],\n [\n -116.45,\n 37.283333\n ],\n [\n -116.633333,\n 37.283333\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Nevada Water Science Center
U.S. Geological Survey
2730 N. Deer Run Road
Carson City, Nevada 95819
The U.S. Geological Survey, in cooperation with the Puerto Rico Electric Power Authority, conducted a sedimentation survey of Lago Guayabal in 2017 to determine reservoir infill sedimentation rates, generate a bathymetric map of the bottom elevations of the reservoir, and create a stage-volume relation. The original (1913) capacity of Lago Guayabal was 11.82 million cubic meters, and efforts to increase the storage capacity were made in 1950 by the installation of flashboards. The 2017 survey indicated that storage capacity of Lago Guayabal is 4.98 million cubic meters. The estimated full sediment infill of Lago Guayabal is expected in 77 years, based on the long-term sedimentation rate of 0.065 million cubic meters per year determined for the 1972–2017 period.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3442","collaboration":"Prepared in cooperation with the Puerto Rico Electric Power Authority","usgsCitation":"Gómez-Fragoso, J.M., and Rosario, M., 2019, Sedimentation survey of Lago Guayabal, Villalba, Puerto Rico, December 2017: U.S. Geological Survey Scientific Investigations Map 3442, 1 sheet, https://doi.org/10.3133/sim3442.","productDescription":"1 Plate: 29.00 x 32.00 inches; Data Release","onlineOnly":"Y","ipdsId":"IP-099137","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":370191,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3442/sim3442.pdf","text":"Report","size":"7.55 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3442"},{"id":370190,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3442/coverthb.jpg"},{"id":370192,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/P9FD12Y5","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Sedimentation survey data for Lago Guayabal, December 2017"}],"otherGeospatial":"Puerto Rico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -66.51569366455078,\n 18.082058622333665\n ],\n [\n -66.49080276489258,\n 18.082058622333665\n ],\n [\n -66.49080276489258,\n 18.104331760155084\n ],\n [\n -66.51569366455078,\n 18.104331760155084\n ],\n [\n -66.51569366455078,\n 18.082058622333665\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
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Lutz, FL 33559
The glacial kettle ponds in the Hyannis Ponds Wildlife Management Area in Barnstable, Massachusetts, support a community of rare and endangered plants. The ponds are hydraulically connected to the unconfined aquifer that underlies Cape Cod. The plants are adapted to the rise and fall of water levels in the ponds as the water table fluctuates in response to seasonal and year-to-year natural changes in recharge. Pumping from wells for public water supply and recharge of wastewater at water pollution control facilities and septic systems also affect groundwater levels. The Hyannis Water System has proposed to install two additional wells in the Hyannis Ponds Wildlife Management Area and adjust rates of withdrawals and recharge of wastewater return flows for the municipal system that serves the village of Hyannis in the town of Barnstable. The proposal has raised concerns that pumping from the proposed wells could cause long-term average changes in pond levels that could adversely affect the critical pond-shore plant habitat.
An available three-dimensional steady-state groundwater-flow model was used to simulate the hydrologic effects of nine pumping and wastewater return-flow scenarios prepared by the Hyannis Water System. These effects were quantified by comparison of water levels simulated for the scenarios to water levels simulated for a reference condition based on 2015 withdrawal and wastewater return-flow rates. Maps of water-level responses were prepared to show the effects of pumping from a single well at different locations in the Hyannis Ponds Wildlife Management Area on the water levels of six ponds. Steady-state simulations of the nine scenarios indicated that the shapes of the simulated water-table contours near the wildlife management area changed only slightly at the regional scale, with the largest shifts near the wildlife management area and the Barnstable Water Pollution Control Facility. The simulated changes in pond levels at 10 ponds of interest for the nine scenarios relative to the simulated pond levels for the 2015 reference condition ranged from small increases (less than 0.1 foot) in one pond each in two scenarios to declines (drawdowns) of 1.03–1.11 feet at three ponds in one scenario. Water levels at the Barnstable Water Pollution Control Facility increased because part of the increase in total withdrawals from the Hyannis Water System wells was recharged as wastewater at the water pollution control facility.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195121","collaboration":"Prepared in cooperation with the Town of Barnstable","usgsCitation":"LeBlanc, D.R., McCobb, T.D., and Barbaro, J.R., 2019, Simulated water-table and pond-level responses to proposed public water-supply withdrawals in the Hyannis Ponds Wildlife Management Area, Barnstable, Massachusetts: U.S. Geological Survey Scientific Investigations Report 2019–5121, 32 p., https://doi.org/10.3133/sir20195121.","productDescription":"Report: vii, 32 p.; Data Release","numberOfPages":"44","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-109032","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":370347,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5121/sir20195121.pdf","text":"Report","size":"3.89 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5121"},{"id":370346,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5121/coverthb.jpg"},{"id":370348,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9U5AKLC","text":"USGS data release","linkHelpText":"MODFLOW2005 groundwater-flow model used to simulate water-supply pumping scenarios near the Hyannis Ponds Wildlife Management Area, Barnstable, Massachusetts"}],"country":"United States","state":"Massachusetts","city":"Barnstable","otherGeospatial":"Hyannis Ponds Wildlife Management Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.28074264526367,\n 41.67297593102651\n ],\n [\n -70.26091575622559,\n 41.67297593102651\n ],\n [\n -70.26091575622559,\n 41.68771986229327\n ],\n [\n -70.28074264526367,\n 41.68771986229327\n ],\n [\n -70.28074264526367,\n 41.67297593102651\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
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The study of eukaryotic extremophiles is relatively novel, and, therefore, documentation of the structure and function of micro-organisms in continental hydrothermal systems globally is limited. In this study, we investigate fossil diatoms in siliceous hydrothermal deposits of the Upper Geyser and Yellowstone Lake hydrothermal basins in Yellowstone National Park, and utilize preserved diatom assemblages to infer local environmental conditions. Siliceous sinter from both the Upper Geyser Basin and Yellowstone Lake contains evidence of in-situ diatom growth within these environments. At Upper Geyser Basin, the assemblage consisted of species that could grow on moist siliceous sinter and was dominated by Rhopalodia gibberula. Diatom valves were found in various preservation states, ranging from nearly pristine to highly diagenetically altered. Diatoms collected from siliceous spires in Yellowstone Lake consisted largely of tychoplanktonic and benthic species that were almost certainly growing on the outside of the structure, with an assemblage indicative of relatively shallow, alkaline waters. What remains unclear without access to material for high-resolution dating is whether diatoms colonized the spires during hydrothermal activity or after activity ceased. Our results indicate that diatom frustules can, to some extent, survive alteration in low-temperature (<76°C) hydrothermal environments.
The National Hydrography Dataset Plus High Resolution (NHDPlus HR) is a scalable geospatial hydrography framework built from the High Resolution (1:24,000-scale or better) National Hydrography Dataset (NHD), nationally complete Watershed Boundary Dataset (WBD), and ⅓-arc-second (10-meter ground spacing) 3D Elevation Program (3DEP) digital elevation model (DEM) data. The NHDPlus HR brings modeling and assessment to a local neighborhood level while nesting seamlessly into the national context.
NHDPlus HR is modeled after the highly successful NHDPlus version 2 (NHDPlus V2). Like the NHDPlus V2, the NHDPlus HR includes data for a nationally seamless network of stream reaches, elevation-based catchment areas, flow surfaces, and value-added attributes that enhance stream-network navigation, analysis, and data display. Users will find that the NHDPlus HR, however, provides much greater detail. This User’s Guide is intended to provide necessary information and guidance in the use of NHDPlus HR data.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191096","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Moore, R.B., McKay, L.D., Rea, A.H., Bondelid, T.R., Price, C.V., Dewald, T.G., and Johnston, C.M., 2019, User's guide for the national hydrography dataset plus (NHDPlus) high resolution: U.S. Geological Survey Open-File Report 2019–1096, 66 p., https://doi.org/10.3133/ofr20191096.","productDescription":"Report: x, 66 p.; Dataset","numberOfPages":"80","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-091493","costCenters":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"links":[{"id":399414,"rank":4,"type":{"id":36,"text":"NGMDB Index 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U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
The California Groundwater Ambient Monitoring and Assessment Program Priority Basin Project (GAMA-PBP) is a long-term cooperative project designed to assess the quality of groundwater resources used for public and domestic drinking water supplies in the State of California, to monitor and evaluate changes to that quality, to investigate the human and natural factors controlling water quality, and to improve the availability of comprehensive groundwater quality data and information. Between May 18, 2004, and May 3, 2018, the GAMA-PBP collected 3001 groundwater samples for analysis of pesticide constituents by the U.S. Geological Survey (USGS) National Water Quality Laboratory (NWQL)(note that ‘pesticide constituents’ includes parent compounds and degradates). Of these samples, 2994 were analyzed for pesticide constituents on schedules 2003, 2032, or 2033 (65 to 84 constituents), and 840 were analyzed for pesticide constituents on schedule 2060 (58 constituents). The original dataset reported by the NWQL to the USGS National Water Information System (NWIS) database contained a total of 2,688 detections of 78 pesticide constituents and 253,825 non-detections. In this original dataset, 33 percent of the 3,001 samples analyzed had reported detections of one or more pesticide constituents.
This report describes the GAMA-PBP data-quality objectives for pesticide data, the procedures used to establish study reporting limits, and use of those reporting limits to censor the data from the NWQL so that the final data published by the GAMA-PBP meet these data-quality objectives. The final GAMA-PBP dataset for samples collected from May 2004 to May 2018, after censoring, had a total of 1,632 detections of 37 pesticide constituents. In the final GAMA-PBP dataset, 25 percent of the 3,001 samples analyzed had detections of one or more pesticide constituents.
The presence of pesticides in groundwater is commonly evaluated by calculating detection frequencies. Detection frequencies for pesticides are sensitive to detection limits and method performance for concentrations near those limits; therefore, the two primary data quality issues addressed in the GAMA-PBP data-quality objectives for pesticides are (1) establishing criteria for classifying data from the laboratory as detections or non-detections for the purpose of data reporting by the project and (2) accounting for changes in analytical methods or method performance over time. The GAMA-PBP addresses these issues by developing study reporting limits that are used as the boundary between detections and non-detections for the reporting of GAMA-PBP results. These reporting limits are defined from method detection limits (MDLs) provided by the NWQL, unless examination of results from laboratory set blanks (LSBs) and GAMA-PBP field blanks indicates that a higher concentration censoring limit is warranted. The GAMA-PBP selected the MDL as the primary choice for defining study reporting limits for consistency with U.S. Environmental Protection Agency (EPA) guidelines for reporting detections of pesticides and other organic constituents.
A five-step procedure is used to develop study reporting limits and censor the GAMA-PBP dataset accordingly. The effect of the censoring at each step is described to provide information about the relative effect of each step on the overall censoring of the dataset. Steps 1 and 2 can be implemented at the time the data are received, whereas steps 3−5 require information accumulated over an extended period.
As of 2019, the USGS NWIS database does not have the capability to store both the original value reported by the NWQL and the final value published by the GAMA-PBP that reflects application of the quality-control censoring described in this report. In the interim, while this capability is developed, the 1,031 results censored in steps 2−5 are blocked from public release in NWIS, and the GAMA-PBP has published the original and final values in a USGS data release accompanying this report. The entire GAMA-PBP final dataset for pesticide constituents on schedules 2003, 2032, or 2033, or on schedule 2060 is publicly available in that USGS data release, through the USGS GAMA-PBP public web portal, and through the California State Water Resources Control Board GAMA public groundwater information system.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195107","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Fram, M.S., and Stork, S.V., 2019, Determination of study reporting limits for pesticide constituent data for the California Groundwater Ambient Monitoring and Assessment Program Priority Basin Project, 2004–2018—Part 1: National Water Quality Schedules 2003, 2032, or 2033, and 2060: U.S. Geological Survey Scientific Investigations Report 2019–5107, 129 p., https://doi.org/10.3133/sir20195107.","productDescription":"Report: viii, 129 p.; Dataset","numberOfPages":"129","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-101851","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":370195,"rank":3,"type":{"id":30,"text":"Data 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\"}}]}","contact":"Director,
California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
Constraining the magnitude of past hydrological change may improve understanding and predictions of future shifts in water availability. Here we demonstrate that water-table depth, a sensitive indicator of hydroclimate, can be quantitatively reconstructed using Kr and Xe isotopes in groundwater. We present the first-ever measurements of these dissolved noble gas isotopes in groundwater at high precision (≤0.005‰ amu−1; 1σ), which reveal depth-proportional signals set by gravitational settling in soil air at the time of recharge. Analyses of California groundwater successfully reproduce modern groundwater levels and indicate a 17.9 ± 1.3 m (±1 SE) decline in water-table depth in Southern California during the last deglaciation. This hydroclimatic transition from the wetter glacial period to more arid Holocene accompanies a surface warming of 6.2 ± 0.6 °C (±1 SE). This new hydroclimate proxy builds upon an existing paleo-temperature application of noble gases and may identify regions prone to future hydrological change.
","language":"English","publisher":"Nature","doi":"10.1038/s41467-019-13693-2","usgsCitation":"Seltzer, A.M., Ng, J., Danskin, W.R., Kulongoski, J.T., Gannon, R., Stute, M., and Severinghaus, J.P., 2019, Deglacial water-table decline in Southern California recorded by noble gas isotopes: Nature Communications, v. 10, 5739, 6 p., https://doi.org/10.1038/s41467-019-13693-2.","productDescription":"5739, 6 p.","ipdsId":"IP-108743","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":458949,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41467-019-13693-2","text":"Publisher Index Page"},{"id":391384,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"San Diego","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.44384765625,\n 32.56996256044998\n ],\n [\n -116.663818359375,\n 32.56996256044998\n ],\n [\n -116.663818359375,\n 32.99484290420988\n ],\n [\n -117.44384765625,\n 32.99484290420988\n ],\n [\n -117.44384765625,\n 32.56996256044998\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","noUsgsAuthors":false,"publicationDate":"2019-12-16","publicationStatus":"PW","contributors":{"authors":[{"text":"Seltzer, Alan M.","contributorId":192321,"corporation":false,"usgs":false,"family":"Seltzer","given":"Alan","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":826385,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ng, Jessica","contributorId":268304,"corporation":false,"usgs":false,"family":"Ng","given":"Jessica","email":"","affiliations":[{"id":38264,"text":"Scripps Institution of Oceanography","active":true,"usgs":false}],"preferred":false,"id":826386,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Danskin, Wesley R. 0000-0001-8672-5501 wdanskin@usgs.gov","orcid":"https://orcid.org/0000-0001-8672-5501","contributorId":1034,"corporation":false,"usgs":true,"family":"Danskin","given":"Wesley","email":"wdanskin@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":826387,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kulongoski, Justin T. 0000-0002-3498-4154 kulongos@usgs.gov","orcid":"https://orcid.org/0000-0002-3498-4154","contributorId":173457,"corporation":false,"usgs":true,"family":"Kulongoski","given":"Justin","email":"kulongos@usgs.gov","middleInitial":"T.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":826388,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gannon, Riley 0000-0002-1239-1083","orcid":"https://orcid.org/0000-0002-1239-1083","contributorId":205967,"corporation":false,"usgs":true,"family":"Gannon","given":"Riley","email":"","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":826389,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Stute, Martin","contributorId":131127,"corporation":false,"usgs":false,"family":"Stute","given":"Martin","email":"","affiliations":[{"id":7254,"text":"Columbia University - Lamont Doherty Earth Observatory","active":true,"usgs":false}],"preferred":false,"id":826390,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Severinghaus, Jeffery P. 0000-0001-8883-3119","orcid":"https://orcid.org/0000-0001-8883-3119","contributorId":268306,"corporation":false,"usgs":false,"family":"Severinghaus","given":"Jeffery","email":"","middleInitial":"P.","affiliations":[{"id":38264,"text":"Scripps Institution of Oceanography","active":true,"usgs":false}],"preferred":false,"id":826391,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70207565,"text":"70207565 - 2019 - Isolation of methylmercury using distillation and anion-exchange chromatography for isotopic analyses in natural matrices","interactions":[],"lastModifiedDate":"2020-02-06T11:27:15","indexId":"70207565","displayToPublicDate":"2019-12-13T13:16:06","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":764,"text":"Analytical and Bioanalytical Chemistry","active":true,"publicationSubtype":{"id":10}},"title":"Isolation of methylmercury using distillation and anion-exchange chromatography for isotopic analyses in natural matrices","docAbstract":"The development of mercury (Hg) stable isotope measurements has enhanced the study of Hg sources and transformations in the environment. As a result of the mixing of inorganic Hg (iHg) and methylmercury (MeHg) species within organisms of the aquatic food web, understanding species-specific Hg stable isotopic compositions is of significant importance. The lack of MeHg isotope measurements is due to the analytical difficulty in the separation of the MeHg from the total Hg pool, with only a few methods having been tested over the past decade with varying degrees of success, and only a handful of environmentally relevant measurements. Here, we present a novel anion-exchange resin separation method using AG 1-X4 that further isolates MeHg from the sample matrix, following a distillation pretreatment, in order to obtain ambient MeHg stable isotopic compositions. This method avoids the use of organic reagents, does not require complex instrumentation, and is applicable across matrices. Separation tests across sediment, water, and biotic matrices showed acceptable recoveries (98 ± 5%, n = 54) and reproducible δ202Hg isotope results (2 SDs ≤ 0.15‰) down to 5 ng of MeHg. The measured MeHg pools in natural matrices, such as plankton and sediments, showed large deviations from the non-speciated total Hg measurement, indicating that there is an important isotopic shift during methylation that is not recorded by typical measurements, but is vital in order to assess sources of Hg during bioaccumulation.
Worldwide, human activities have modified hydrology and nutrient loading regimes in coastal wetlands. Understanding the interplay between these drivers and subsequent response of wetland plant communities is essential to informing wetland management and restoration efforts. Recent restoration strategies in Louisiana proposes to use sediment diversions from the Mississippi River to build land in adjacent wetlands and reduce the rate of land to open water conversion. In conjunction with sediment delivery, diversions can increase nutrient loads and water levels in the receiving basins. We conducted a greenhouse mesocosm experiment in which we exposed three common tidal freshwater and brackish marsh plants (Panicum hemitomon, Sagittaria lancifolia, and Spartina patens) to two nitrate loading rates [high (35 g N m2 year−1) and low (0.25 g N m2 year−1)], and two flooding treatments (with and without diversion pulsing). Experimental units were set at two different elevations within the treatment tanks to simulate both a healthy and degraded marsh. Plant growth metrics and soil physicochemical properties were measured monthly. Final total biomass was determined at the study’s conclusion. Growth responses differed between species but were not significantly influenced by the treatments. Soil redox potential decreased significantly following the increase in flooding associated with the diversion pulse, but recovered to pre-diversion levels after a 3-month recovery period. Our study suggests short flooding pulses with a recovery period may be key for maintaining healthy marshes, however there remains a need for longer-term empirical studies to understand marsh response to pressures associated with river sediment diversions over time.
","language":"English","publisher":"Springer","doi":"10.1007/s11273-019-09699-8","usgsCitation":"McCoy, M.M., Sloey, T.M., Howard, R.J., and Hester, M.W., 2019, Response of tidal marsh vegetation to pulsed increases in flooding and nitrogen: Wetlands Ecology and Management, v. 28, p. 119-135, https://doi.org/10.1007/s11273-019-09699-8.","productDescription":"17 p.","startPage":"119","endPage":"135","ipdsId":"IP-106945","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":370302,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","otherGeospatial":"Jean Lafitte National Historical Park and Preserve, Lake Salvador Wildlife Management Area ","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 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M","contributorId":149516,"corporation":false,"usgs":false,"family":"Sloey","given":"Taylor","email":"","middleInitial":"M","affiliations":[{"id":17763,"text":"University of Louisiana, Lafayette","active":true,"usgs":false}],"preferred":false,"id":777557,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Howard, Rebecca J. 0000-0001-7264-4364 howardr@usgs.gov","orcid":"https://orcid.org/0000-0001-7264-4364","contributorId":2429,"corporation":false,"usgs":true,"family":"Howard","given":"Rebecca","email":"howardr@usgs.gov","middleInitial":"J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":777555,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hester, Mark W.","contributorId":195572,"corporation":false,"usgs":false,"family":"Hester","given":"Mark","email":"","middleInitial":"W.","affiliations":[{"id":34316,"text":"University of Louisiana at Lafayette, Lafayette, LA, USA","active":true,"usgs":false}],"preferred":false,"id":777558,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70207510,"text":"70207510 - 2019 - Developing and optimizing shrub parameters representing sagebrush (Artemisia spp.) ecosystems in the Northern Great Basin using the Ecosystem Demography (EDv2.2) model","interactions":[],"lastModifiedDate":"2019-12-22T14:03:15","indexId":"70207510","displayToPublicDate":"2019-12-12T14:00:55","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1818,"text":"Geoscientific Model Development","active":true,"publicationSubtype":{"id":10}},"title":"Developing and optimizing shrub parameters representing sagebrush (Artemisia spp.) ecosystems in the Northern Great Basin using the Ecosystem Demography (EDv2.2) model","docAbstract":"Ecosystem dynamic models are useful for understanding ecosystem characteristics over time and space because of their efficiency over direct field measurements and applicability to broad spatial extents. Their application, however, is challenging due to internal model uncertainties and complexities arising from distinct qualities of the ecosystems being analyzed. The sagebrush-steppe in western North America, for example, has substantial spatial and temporal heterogeneity as well as variability due to anthropogenic disturbance, invasive species, climate change, and altered fire regimes, which collectively make modelling dynamic ecosystem processes difficult. Ecosystem Demography (EDv2.2) is a robust ecosystem dynamic model, initially developed for tropical forests, that simulates energy, water, and carbon fluxes at fine scales. Although EDv2.2 has since been tested on different ecosystems via development of different Plant Function Types (PFT), it still lacks a shrub PFT. In this study, we developed and parameterized a shrub PFT representative of sagebrush (Artemisia spp.) ecosystems in order to initialize and test it within EDv2.2, and to promote future broad-scale analysis of restoration activities, climate change, and fire regimes in the sagebrush-steppe. Specifically, we parameterized the sagebrush PFT within EDv2.2 to estimate gross primary production (GPP), using data from two sagebrush study sites in the northern Great Basin. To accomplish this, we employed a three-tier approach: 1) To initially parameterize the sagebrush PFT, we fitted allometric relationships for sagebrush using field-collected data, information from existing sagebrush literature, and parameters from other land models. 2) To determine influential parameters in GPP prediction, we used a sensitivity analysis to identify the five most sensitive parameters. 3) To improve model performance and validate results, we optimized these five parameters using an exhaustive search method to estimate GPP, and compared results with observations from two Eddy Covariance (EC) sites in the study area. Our modeled results were encouraging, with reasonable fidelity to observed values, although some negative biases (i.e., seasonal underestimates of GPP) were apparent.","language":"English","publisher":"European Geosciences Union","doi":"10.5194/gmd-12-4585-2019","usgsCitation":"Pandit, K., Dasthi, H., Glenn, N., Flores, A., Maguire, K.C., Shinneman, D.J., Flerchinger, G., and Fellow, A., 2019, Developing and optimizing shrub parameters representing sagebrush (Artemisia spp.) ecosystems in the Northern Great Basin using the Ecosystem Demography (EDv2.2) model: Geoscientific Model Development, v. 12, p. 4585-4601, https://doi.org/10.5194/gmd-12-4585-2019.","productDescription":"17 p.","startPage":"4585","endPage":"4601","ipdsId":"IP-102648","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":458969,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/gmd-12-4585-2019","text":"Publisher Index Page"},{"id":370607,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Great Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.56347656249999,\n 42.032974332441405\n ],\n [\n -118.16894531249999,\n 35.35321610123823\n ],\n [\n -112.2802734375,\n 34.59704151614417\n ],\n [\n -109.248046875,\n 38.37611542403604\n ],\n [\n -110.0830078125,\n 43.13306116240612\n ],\n [\n -112.8955078125,\n 44.02442151965934\n ],\n [\n -115.6201171875,\n 43.58039085560784\n ],\n [\n -119.35546875000001,\n 44.15068115978094\n ],\n [\n -121.025390625,\n 44.08758502824516\n ],\n [\n -122.56347656249999,\n 42.032974332441405\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2019-11-05","publicationStatus":"PW","contributors":{"authors":[{"text":"Pandit, Karun","contributorId":221464,"corporation":false,"usgs":false,"family":"Pandit","given":"Karun","email":"","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":778308,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dasthi, Hamid","contributorId":221465,"corporation":false,"usgs":false,"family":"Dasthi","given":"Hamid","email":"","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":778309,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Glenn, Nancy","contributorId":181558,"corporation":false,"usgs":false,"family":"Glenn","given":"Nancy","affiliations":[],"preferred":false,"id":778310,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Flores, Alejandro","contributorId":221466,"corporation":false,"usgs":false,"family":"Flores","given":"Alejandro","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":778311,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Maguire, Kaitlin C. 0000-0001-8193-2384","orcid":"https://orcid.org/0000-0001-8193-2384","contributorId":203419,"corporation":false,"usgs":true,"family":"Maguire","given":"Kaitlin","email":"","middleInitial":"C.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":778312,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shinneman, Douglas J. 0000-0002-4909-5181 dshinneman@usgs.gov","orcid":"https://orcid.org/0000-0002-4909-5181","contributorId":147745,"corporation":false,"usgs":true,"family":"Shinneman","given":"Douglas","email":"dshinneman@usgs.gov","middleInitial":"J.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true}],"preferred":true,"id":778307,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Flerchinger, Gerald","contributorId":221467,"corporation":false,"usgs":false,"family":"Flerchinger","given":"Gerald","affiliations":[{"id":37009,"text":"USDA Agricultural Research Service","active":true,"usgs":false}],"preferred":false,"id":778313,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Fellow, Aaron","contributorId":221468,"corporation":false,"usgs":false,"family":"Fellow","given":"Aaron","email":"","affiliations":[{"id":37009,"text":"USDA Agricultural Research Service","active":true,"usgs":false}],"preferred":false,"id":778314,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70207581,"text":"70207581 - 2019 - Multiorder hydrologic position in the conterminous United States: A set of metrics in support of groundwater mapping at regional and national scales","interactions":[],"lastModifiedDate":"2020-02-06T11:28:53","indexId":"70207581","displayToPublicDate":"2019-12-11T07:33:26","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Multiorder hydrologic position in the conterminous United States: A set of metrics in support of groundwater mapping at regional and national scales","docAbstract":"The location of a point on the landscape within a stream network (hydrologic position) can be an important predictive measure in hydrology. Hydrologic position is defined here by two metrics: lateral position and distance from stream to divide, both measured horizontally. Lateral position (dimensionless) is the relative position of a point between the stream and its watershed divide. Distance from stream to divide (units of length) is an indicator of position within a watershed: generally small near a confluence and generally large in headwater areas. Watersheds and watershed divides are defined here by Thiessen polygons rather than topographic divides. Lateral position and distance from stream to divide are also defined in the context of hydrologic order. Hydrologic order “n” is defined as the network of streams, and associated divides, of order n and higher. And given that a point can have different positions in different hydrologic orders the term multiorder hydrologic position (MOHP) is used to describe the ensemble of hydrologic positions. MOHP was mapped across the conterminous United States for nine hydrologic orders at a spatial resolution of 30 m (about 8.7 billion pixels). There are 18 metrics for each pixel. Four case studies are presented that use MOHP metrics as explanatory factors in random forest machine learning models. The case studies show that lower order MOHP metrics can serve as indicators of hydrologic process while higher‐order metrics serve as indicators of location. MOHP is shown to have utility as a predictor variable across a large range of scales (50,000 to 8,000,000 km2).
Recovering species are often limited to much smaller areas than they historically occupied. Conservation planning for the recovering species is often based on this limited range, which may simply be an artifact of where the surviving population persisted. Southern sea otters (Enhydra lutris nereis) were hunted nearly to extinction but recovered from a small remnant population on a remote stretch of the California outer coast, where most of their recovery has occurred. However, studies of recently-recolonized estuaries have revealed that estuaries can provide southern sea otters with high quality habitats featuring shallow waters, high production and ample food, limited predators, and protected haul-out opportunities. Moreover, sea otters can have strong effects on estuarine ecosystems, fostering seagrass resilience through their consumption of invertebrate prey. Using a combination of literature reviews, population modeling, and prey surveys we explored the former estuarine habitats outside the current southern sea otter range to determine if these estuarine habitats can support healthy sea otter populations. We found the majority of studies and conservation efforts have focused on populations in exposed, rocky coastal habitats. Yet historical evidence indicates that sea otters were also formerly ubiquitous in estuaries. Our habitat-specific population growth model for California’s largest estuary—San Francisco Bay—determined that it alone can support about 6,600 sea otters, more than double the 2018 California population. Prey surveys in estuaries currently with (Elkhorn Slough and Morro Bay) and without (San Francisco Bay and Drakes Estero) sea otters indicated that the availability of prey, especially crabs, is sufficient to support healthy sea otter populations. Combining historical evidence with our results, we show that conservation practitioners could consider former estuarine habitats as targets for sea otter and ecosystem restoration. This study reveals the importance of understanding how recovering species interact with all the ecosystems they historically occupied, both for improved conservation of the recovering species and for successful restoration of ecosystem functions and processes.
","language":"English","publisher":"PeerJ","doi":"10.7717/peerj.8100","usgsCitation":"Hughes, B.B., Wasson, K., Tinker, M., Williams, S.L., Carswell, L., Boyer, K.E., Beck, M.W., Eby, R., Scoles, R., Staedler, M.M., Espinosa, S., Hessing-Lewis, M., Foster, E.U., Beheshti, K., Grimes, T.M., Becker, B.H., Needles, L., Tomoleoni, J.A., Rudebusch, J., Hines, E.M., and Silliman, B.R., 2019, Species recovery and recolonization of past habitats: Lessons for science and conservation from sea otters in estuaries: PeerJ, v. 7, e8100, 30 p., https://doi.org/10.7717/peerj.8100.","productDescription":"e8100, 30 p.","ipdsId":"IP-098446","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":458985,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.7717/peerj.8100","text":"Publisher Index Page"},{"id":371544,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Elkhorn Slough, Morro Bay, San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.62390136718749,\n 37.38325280195101\n ],\n [\n -121.8878173828125,\n 37.38325280195101\n ],\n [\n -121.8878173828125,\n 38.229550455326134\n ],\n [\n -122.62390136718749,\n 38.229550455326134\n ],\n [\n -122.62390136718749,\n 37.38325280195101\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.8170928955078,\n 36.79993834872292\n ],\n [\n -121.73057556152344,\n 36.79993834872292\n ],\n [\n -121.73057556152344,\n 36.87110680999585\n ],\n [\n -121.8170928955078,\n 36.87110680999585\n ],\n [\n -121.8170928955078,\n 36.79993834872292\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.97869873046875,\n 35.25907654252574\n ],\n [\n -120.76171875,\n 35.25907654252574\n ],\n [\n -120.76171875,\n 35.458432791026304\n ],\n [\n -120.97869873046875,\n 35.458432791026304\n ],\n [\n -120.97869873046875,\n 35.25907654252574\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2019-12-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Hughes, Brent B.","contributorId":201240,"corporation":false,"usgs":false,"family":"Hughes","given":"Brent","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":780221,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wasson, Kerstin","contributorId":221786,"corporation":false,"usgs":false,"family":"Wasson","given":"Kerstin","email":"","affiliations":[{"id":6949,"text":"University of California, Santa Cruz","active":true,"usgs":false}],"preferred":false,"id":780222,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tinker, M. 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2019 - Trends in streamflow and concentrations and flux of nutrients and total suspended solids in the Upper White River at Muncie, near Nora, and near Centerton, Indiana","interactions":[],"lastModifiedDate":"2022-04-25T18:47:12.543093","indexId":"sir20195119","displayToPublicDate":"2019-12-10T16:08:12","publicationYear":"2019","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":"2019-5119","displayTitle":"Trends in Streamflow and Concentrations and Flux of Nutrients and Total Suspended Solids in the Upper White River at Muncie, near Nora, and near Centerton, Indiana","title":"Trends in streamflow and concentrations and flux of nutrients and total suspended solids in the Upper White River at Muncie, near Nora, and near Centerton, Indiana","docAbstract":"The U.S. Geological Survey (USGS), in cooperation with The Nature Conservancy, completed a study to estimate and assess trends in streamflow and annual mean concentrations and flux of nutrients (nitrate plus nitrite, total Kjeldahl nitrogen, and total phosphorus) and total suspended solids at three USGS streamgages (hereafter referred to as “study gages”) on the Upper White River at Muncie (USGS station 03347000), near Nora (USGS station 03351000), and near Centerton (USGS station 03354000), Indiana. Water-quality data used in the analyses were collected by several agencies between calendar years 1991 and 2017, and streamflow (discharge) data were collected by the USGS. For most of the water-quality constituents, there were suitable data to facilitate an analysis of the 26-year period extending from calendar years 1991 to 2017 (water years 1992 to 2017); however, shorter analytical periods were necessary for total Kjeldahl nitrogen for the study gages at Muncie and near Centerton and for total suspended solids for the study gage near Centerton.
Temporal trends in streamflows at the study gages for the period extending from water years 1978 to 2017 were assessed using Exploration and Graphics for RivEr Trends (EGRET) and Mann-Kendall and Pettitt tests. With just one exception, the annual maximum and mean daily streamflows and the annual minimum 7-day mean streamflows at the study gages demonstrated upward trends (increasing streamflows) in the EGRET analyses. The exception was the annual 7-day minimum streamflow at the study gage near Nora, which indicated no trend. Mann-Kendall tests also indicated that the average trend for the annual maximum daily, annual mean daily, and annual 7-day minimum streamflow statistics between water years 1978 and 2017 was upward at each of the study gages; however, only the trends in the annual mean daily streamflows at the study gage at Muncie and the annual maximum daily streamflows at the study gages near Nora and near Centerton were statistically significant at a 0.05 probability level. The Pettitt tests indicated that a statistically significant step trend (abrupt change) in annual mean daily streamflows occurred at each of the study gages around water year 2001.
The seasonal distributions of total suspended solids, total phosphorus, nitrate plus nitrite, and total Kjeldahl nitrogen concentrations at the study gages were evaluated to identify patterns and other distinguishing characteristics by examining boxplots of concentrations as a function of month of the year. Seasonal distributions of nitrate plus nitrite concentrations and total suspended solids concentrations differed from each other but were generally similar among the three study gages for a given constituent. Median concentrations of nitrate plus nitrite were highest during the January–June months, whereas median concentrations of total suspended solids were highest during June and July. Seasonal distributions of total phosphorus concentrations were similar at the study gages near Nora and near Centerton, but the seasonal distribution was noticeably different at the study gage at Muncie, which had monthly median concentrations that were substantially lower than at the two downstream study gages (near Nora and near Centerton). The seasonal distribution of total Kjeldahl nitrogen concentrations differed in pattern among the three study gages; however, in general, some of the higher monthly median total Kjeldahl nitrogen concentrations at each study gage were associated with the late spring and summer periods.
The Weighted Regressions on Time, Discharge, and Season (WRTDS) method implemented in EGRET was used to estimate water-year annual mean daily concentrations and flux of nutrients and total suspended solids, as well as estimates of concentrations and flux that were “normalized” to remove the effect of year-to-year variation in streamflow. The approximate coefficients of determination for the WRTDS regression models ranged from a high of 0.82 for total phosphorus for the study gage near Centerton to a low of 0.19 for nitrate plus nitrite for the study gage near Nora.
Loads and yields of total suspended solids, total phosphorus, nitrate plus nitrite, and total Kjeldahl nitrogen were estimated for analytical periods consisting of the longest periods of concurrent record at the three study gages. Loads of each of the constituents increased sequentially from the most upstream study gage to the most downstream study gage; however, the same was not true for yields. The highest yields of total suspended solids, total phosphorus, and total Kjeldahl nitrogen occurred at the most upstream study gage (at Muncie); however, the highest yield of nitrate plus nitrite occurred at the most downstream study gage (near Centerton).
WRTDS bootstrap tests were used to assess the magnitude, direction, and likelihood of changes in annual flow-normalized mean daily concentrations and flux of total suspended solids, total phosphorus, nitrate plus nitrite, and total Kjeldahl nitrogen at the study gages between water years 1997 and 2017. Changes in flow-normalized concentrations and flux of the constituents between water years 1997 and 2017 were mostly downward (decreasing). The exceptions were likely to highly likely upward (increasing) changes in (1) flow-normalized annual mean daily concentration and annual flux for total suspended solids and total phosphorus at the study gage at Muncie, (2) flow-normalized annual mean daily total phosphorus concentration at the study gage near Centerton, (3) flow-normalized annual flux of total phosphorus at the study gage near Centerton, and (4) flow-normalized annual mean daily nitrate plus nitrite concentration at the study gage near Centerton. Although an upward change in flow-normalized nitrate plus nitrite concentrations was likely at the study gage near Centerton, flow-normalized annual flux of nitrate plus nitrite at that study gage was determined to have a highly likely downward change.
EGRET and Exploration and Graphics for RivEr Trends Confidence Intervals (EGRETci) analyses can be used to improve our understanding of how concentrations and flux change as functions of time and streamflow, as well as provide information on how the relations between streamflow and constituent concentrations have changed within the calendar year between any 2 years included in the analyses. Examples of those uses, illustrating changes between calendar years 1992 and 2017, were given for total suspended solids concentrations at the study gage near Nora and for nitrate plus nitrite concentrations at the study gage near Centerton.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195119","collaboration":"Prepared in cooperation with The Nature Conservancy","usgsCitation":"Koltun, G.F., 2019, Trends in streamflow and concentrations and flux of nutrients and total suspended solids in the Upper White River at Muncie, near Nora, and near Centerton, Indiana: U.S. Geological Survey Scientific Investigations Report 2019–5119, 34 p., https://doi.org/10.3133/sir20195119.","productDescription":"Report: viii, 34 p.; Data Release","numberOfPages":"46","onlineOnly":"Y","ipdsId":"IP-109722","costCenters":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":399602,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109513.htm"},{"id":370134,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9VN5RKV","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Total suspended solids, total phosphorus, nitrate plus nitrite, and total Kjeldahl nitrogen concentration data for the White River at Muncie, near Nora, and near Centerton, Indiana, 1991–2017"},{"id":370133,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5119/sir20195119.pdf","text":"Report","size":"3.99 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5119"},{"id":370132,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5119/coverthb.jpg"}],"country":"United States","state":"Indiana","county":"Morgan County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -86.8311,\n 39.2633\n ],\n [\n -84.9667,\n 39.2633\n ],\n [\n -84.9667,\n 40.3608\n ],\n [\n -86.8311,\n 40.3608\n ],\n [\n -86.8311,\n 39.2633\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Ohio-Kentucky-Indiana Water Science Center
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The U.S. Geological Survey (USGS) is developing a multi-resource analysis (MRA) line of products to inform land-use decision makers. Specifically, MRA products will integrate scientific information, include considerations for natural resource interrelations, and quantify the effects of resource management decisions in biophysical, economic, and societal terms. As part of the establishment of the MRA, the USGS, in collaboration with the University of New Mexico, has developed the Net Resources Assessment (NetRA) decision support tool. As a proof of concept analysis, the NetRA was applied to the Piceance basin in Colorado in a hypothetical example to illustrate how resource managers could use the NetRA to consider tradeoffs of natural resources among alternative development plans and land cover patterns within a geographic region.
The NetRA is a policy-relevant approach to assess the availability of multiple natural resources. It is an analytical toolset that may be used to examine the spatiotemporal relations between development of energy and mineral resources and delivery of biological natural resources. The NetRA operates at multiple map scales and contains a set of integrated, compatible submodels with specific data requirements for natural resource stocks, engineering economics, biophysical, and ecological data for ecosystem services stocks, market prices, regulations, and nonmarket values.
The NetRA includes an explicit process to consider the interdependence between development and conservation, which is a crucial consideration in land-management and land-use decisions. The NetRA is used to estimate an expected net resource value (NRV). The NRV is the expected, present value, economic benefit from the extraction of a resource (for example, natural gas) minus the total cost of production, which is the aggregation of the development, production, and social costs. Social costs include private costs plus any external costs. There can be external social benefits associated with natural gas production, such as increased demand for locally produced goods and increased employment in the local area through backward and forward linkages of natural gas production. The NRV is used to compare development outcomes (scenarios) from a range of exploration and development plans for cumulative energy production.
The Piceance basin application of the NetRA uses the NRV to assess the tradeoff between continuous natural gas extraction and the effects to the local populations of Odocoileus hemionus (mule deer) and aquatic species and to consumptive water uses for an area the size and resolution of a USGS energy resource assessment unit. In the proof of concept simulation, the 2.9-square-mile-area of USGS oil and gas assessment unit 50200263 (Piceance basin continuous gas unit of the Mesaverde Total Petroleum System) was gridded into 588 cells. From this area, seven clusters with potential for development and three that cannot be developed were identified; the three clusters that cannot be developed were identified as wilderness study areas, areas of critical environmental concern, and national forests. On the basis of these criteria, there are 118 cells unsuitable for development in the oil and gas assessment unit: 84 are in national forests, 23 are areas of critical environmental concern, and 11 are wilderness study areas. The remaining cells in the oil and gas assessment unit can be developed on both private and public lands.
Two scenarios were considered that are distinguished as plan 1 and plan 2. Plan 1 keeps the amount of land disturbance unchanged and limits the number of development locations to 140 grid cells for the production period, which constrains the amount of the energy resources available for development; the plan requires the usage of the Bureau of Land Management (BLM) unsuitability criteria. Plan 2 also limits the number of development locations to 140 grid cells for the production period but provides a constant volume of energy production by increasing the density of well pads within the cells. The effects of plan 2 to the NRV when there are five wells per pad and five pads per square mile happen mostly in the first 5 years of development, even though the effects on the population of mule deer continue in later years. This outcome is the result of the upfront development and investment costs and the initial effect to the ecosystem services.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195086","collaboration":"Prepared in cooperation with the University of New Mexico","usgsCitation":"Bernknopf, R., Broadbent, C., Adhikari, D., Mamun, S., Tidwell, V., Babis, C., and Pindilli, E., 2019, Multi-resource analysis—A proof of concept study of natural resource tradeoffs in the Piceance Basin, Colorado, using the net resources assessment (NetRA) decision support tool: U.S. Geological Survey Scientific Investigations Report 2019–5086, 40 p., https://doi.org/10.3133/sir20195086.","productDescription":"viii, 40 p.","numberOfPages":"52","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-088615","costCenters":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"links":[{"id":370122,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/cir1442","text":"Circular 1442","linkHelpText":"- Multi-Resource Analysis—Methodology and synthesis"},{"id":399539,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109512.htm"},{"id":370092,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5086/coverthb.jpg"},{"id":370099,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5086/sir20195086.pdf","text":"Report","size":"8.39 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5086"}],"country":"United States","state":"Colorado","otherGeospatial":"Piceance Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.22607421875,\n 40.463666324587685\n ],\n [\n -109.09423828125,\n 38.03078569382294\n ],\n [\n -108.12744140625,\n 37.43997405227057\n ],\n [\n -107.07275390625,\n 36.94989178681327\n ],\n [\n -106.2158203125,\n 36.84446074079564\n ],\n [\n -105.8203125,\n 37.142803443716836\n ],\n [\n -105.6884765625,\n 37.49229399862877\n ],\n [\n -105.0732421875,\n 37.125286284966805\n ],\n [\n -104.4580078125,\n 37.666429212090605\n ],\n [\n -104.4140625,\n 37.90953361677018\n ],\n [\n -104.8974609375,\n 38.77121637244273\n ],\n [\n -105.75439453125,\n 39.740986355883564\n ],\n [\n -105.18310546875,\n 40.17887331434696\n ],\n [\n -109.22607421875,\n 40.463666324587685\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Science and Decisions Center
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