In cooperation with the New Mexico County of Bernalillo, the U.S. Geological Survey characterized potential polychlorinated biphenyl (PCB) concentration and estimated loading into the Rio Grande from watersheds that are under the county’s jurisdiction. Water and sediment samples were collected in 2017–18 from six sites within four stormwater drainage basins in the Albuquerque, New Mexico, urbanized area for the analysis of PCB congeners and other water-quality constituents during dry and wet seasons. Also, the rainfall-runoff model Arid Lands Hydrologic Model (AHYMO) was used to estimate stormwater discharge at the two sample collection sites not affected by pump station operation. Along with the PCB analysis, the discharge data were used to estimate total PCB stormflow event loads for eight events in these urban Rio Grande tributaries. PCBs were detected in 34 of 36 water samples at concentrations as high as 65.8 nanograms per liter and in 12 of 13 sediment samples at concentrations as high as 163,000 nanograms per kilogram dry weight. Six of the 36 water samples exceeded the New Mexico surface-water quality standard for protection of wildlife habitat and aquatic life of 14 nanograms per liter for PCBs. None of the water samples exceeded the U.S. Environmental Protection Agency’s National Pollutant Discharge Elimination System permit level limit of 200 nanograms per liter for PCBs in stormwater systems discharging into the Rio Grande. PCB concentrations in water samples in this study were not linearly related to antecedent precipitation or measured water-quality parameters, but PCB concentrations had a statistically significant positive Kendall’s tau correlation with total suspended solids for water samples and with total organic carbon for sediment samples. The PCB congener profiles indicate that sources to stormwater drainage basins in Bernalillo County originate both from legacy sources, such as Aroclors (for example, in landfills and old building materials), and from current-use sources, such as yellow pigments (for example, in printed materials and packaging in urban litter or refuse). Total PCB stormflow event loads were calculated with average potential minimum and maximum event loads of 0.73 and 4.32 milligrams per storm event, respectively, at the Adobe Acres pump station site and 56.78 and 315.13 milligrams per storm event at the Sanchez Farms inflow at Albuquerque, N. Mex., site.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191106","collaboration":"Prepared in cooperation with Bernalillo County","usgsCitation":"Shephard, Z.M., Conn, K.E., Beisner, K.R., Jornigan, A.D., and Bryant, C.F., 2019, Characterization and load estimation of polychlorinated biphenyls (PCBs) from selected Rio Grande tributary stormwater channels in the Albuquerque urbanized area, New Mexico, 2017–18: U.S. Geological Survey Open-File Report 2019–1106, 48 p., https://doi.org/10.3133/of20191106.","productDescription":"x, 48 p.","numberOfPages":"61","onlineOnly":"Y","ipdsId":"IP-109136","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":367784,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1106/coverthb.jpg"},{"id":367785,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1106/ofr20191106.pdf","size":"4.96 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019–1106"}],"country":"United States","state":"New Mexico","city":"Albuquerque","otherGeospatial":"Rio Grande","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.8255615234375,\n 34.9371707067839\n ],\n [\n -106.48223876953125,\n 34.9371707067839\n ],\n [\n -106.48223876953125,\n 35.20579439829525\n ],\n [\n -106.8255615234375,\n 35.20579439829525\n ],\n [\n -106.8255615234375,\n 34.9371707067839\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Mexico Water Science Center
6700 Edith Blvd.
Albuquerque, NM 87113
A generalized potentiometric-surface map of the Madison aquifer near Jewel Cave National Monument was constructed using water levels measured from calendar years 1988 to 2019 in 24 groundwater wells and 4 subterranean cave lakes interpreted to be in hydraulic connection with the aquifer. The map indicated that groundwater near Jewel Cave National Monument originates from recharge sources to the Madison aquifer in the higher elevations in the north-central area of the map, flows west to south-southwest through the Jewel Cave network, then southeast.
Hydrographs were constructed using water levels from four observation wells and one subterranean lake (Hourglass Lake) in the Jewel Cave network to evaluate historical and current groundwater recharge to the Madison aquifer in the study area. Hydrographs from 1992 through 2018 indicated water levels were lowest from the early to mid-1990s, increased through the late 1990s, peaked in the early 2000s, decreased until 2010, and then increased to the highest levels during 2016–18. A visual comparison of the Hourglass Lake hydrograph with cumulative precipitation, and quantitative (statistical) comparison of lake-water levels with cumulative precipitation, indicated that lake-water levels increased as cumulative precipitation increased, most likely due to some degree of precipitation recharge to hydraulically connected Madison Limestone outcrops.
Comparing the potentiometric-surface map constructed for this study, with a map by Strobel and others (2000) of the same region and aquifer, indicated similarity and, therefore, provided some validation of map construction. The potentiometric-surface map constructed for this study could be used by park managers and others as a tool to evaluate the hydrogeologic characteristics of the Madison aquifer in the study area.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195098","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Anderson, T.M., Eldridge, W.G., Valder, J.F., and Wiles, M., 2019, Generalized potentiometric-surface map and groundwater flow directions in the Madison aquifer near Jewel Cave National Monument, South Dakota: U.S. Geological Survey Scientific Investigations Report 2019–5098, 16 p., https://doi.org/10.3133/sir20195098.","productDescription":"vi, 16 p.","numberOfPages":"26","onlineOnly":"Y","ipdsId":"IP-109769","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":367748,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5098/sir20195098.pdf","text":"Report","size":"5.33 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5098"},{"id":367747,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5098/coverthb.jpg"},{"id":369716,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/fs20193072","text":"FS 2019–3072","size":"3.51 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2019–3072","linkHelpText":"– Groundwater Characterization of the Madison Aquifer near Jewel Cave National Monument, South Dakota"}],"country":"United States","state":"South Dakota","otherGeospatial":"Jewel Cave, Madison Aquifer","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.05426025390625,\n 43.60823944964323\n ],\n [\n -103.4417724609375,\n 43.60823944964323\n ],\n [\n -103.4417724609375,\n 44.11716972942086\n ],\n [\n -104.05426025390625,\n 44.11716972942086\n ],\n [\n -104.05426025390625,\n 43.60823944964323\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Dakota Water Science Center
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The introduction of snakeheads from their origins in Asia is relatively recent to the conterminous United States with the first of many collections beginning in the late 1990s. For decades they have been commercially fished and aquacultured around the world for human food and, to a lesser degree, for the aquarium trade. Over a dozen snakehead species known to be of economic importance outside the US, five have been introduced into the United States. Three of the four species collected in open waters have successfully established reproducing populations. The most widespread is a temperate species, Northern Snakehead Channa argus, primarily found in the Mid-Atlantic region of the United States. The other two snakehead species that established populations are the Bullseye Snakehead Channa marulius in the state of Florida and Blotched Snakehead Channa maculata in the state of Hawai’i. A fifth species, Chevron Snakehead Channa striata, is also present in Hawai’i, but only in aquaculture, not in open waters. Introductions of snakehead fishes into the United States were most likely the result of the popularity of this group of fishes in Asia.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":" Proceedings of the First International Snakehead Symposium, American Fisheries Society Symposium 89","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"First International Snakehead Symposium","conferenceDate":"July 17-18, 2018","conferenceLocation":"Alexandria, VA","language":"English","usgsCitation":"Benson, A., 2019, Snakehead fishes (Channa spp.) in the USA, in Proceedings of the First International Snakehead Symposium, American Fisheries Society Symposium 89, Alexandria, VA, July 17-18, 2018, p. 3-21.","productDescription":"19 p.","startPage":"3","endPage":"21","ipdsId":"IP-102874","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":367732,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":360942,"type":{"id":15,"text":"Index 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Challenges and Opportunities from North to South was held April 10-11, 2018 in Denver, Colorado. The geographical focus for the summit was the entire Great Plains. The summit was designed to provide syntheses of information about key grassland topics of interest in the Great Plains; networking and learning channels for managers, researchers and stakeholders; and working sessions for sharing input and ideas about challenges and future research and management opportunities. The summit was convened to better understand Great Plains stressors and resource demands and how to manage them, and to discuss methods for improved collaboration among natural resource managers, scientists, and stakeholders. Over 200 stakeholders, who collectively were affiliated with all of the Great Plains states, attended the summit. Attendees included university researchers, government scientists, and individuals affiliated with federal and state agencies, tribes, the private sector, and non-governmental organizations (NGOs). Plenary speakers provided syntheses of current knowledge on key topics to help stage working sessions on working lands, native plants and pollinators, native wildlife and biological diversity, invasive species, wildland and prescribed fire, energy development, and weather, water, and climate. The summit steering committee designed one suite of questions that were asked of participants in each working session. This report is a digest of the input from those who attended the seven working sessions and responded to the structured questions.","language":"English","publisher":"USDA Forest Service","usgsCitation":"Finch, D., Baldwin, C., Brown, D.P., Driscoll, K.P., Fleishman, E., Ford, P.L., Hanberry, B., Symstad, A., Van Pelt, B., and Zabel, R., 2019, Management opportunities and research priorities for Great Plains grasslands: General Technical Report 398, vi, 56 p.","productDescription":"vi, 56 p.","ipdsId":"IP-105426","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":367778,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":367750,"type":{"id":11,"text":"Document"},"url":"https://www.fs.fed.us/rm/pubs_series/rmrs/gtr/rmrs_gtr398.pdf"}],"country":"United States","state":"Colorado, Illinois, Iowa, Kansas, Minnesota, Missouri, Montana, Nebraska, New Mexico, North Dakota, Ohio, Oklahoma, South Dakota, Texas, Wyoming","otherGeospatial":"Great Plains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.294921875,\n 27.72243591897343\n ],\n [\n -95.00976562499999,\n 29.22889003019423\n ],\n [\n -95.2734375,\n 34.08906131584994\n ],\n [\n -95.00976562499999,\n 36.59788913307022\n ],\n [\n -93.07617187499999,\n 39.36827914916014\n ],\n [\n -92.10937499999999,\n 38.92522904714054\n ],\n [\n -85.869140625,\n 39.9434364619742\n ],\n [\n -85.6494140625,\n 41.376808565702355\n ],\n [\n -85.869140625,\n 41.705728515237524\n ],\n [\n -87.5830078125,\n 41.244772343082076\n ],\n [\n -92.0654296875,\n 42.09822241118974\n ],\n [\n -96.328125,\n 48.777912755501845\n ],\n [\n -113.51074218749999,\n 48.951366470947725\n ],\n [\n -107.9736328125,\n 42.74701217318067\n ],\n [\n -106.171875,\n 32.65787573695528\n ],\n [\n 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P","contributorId":219276,"corporation":false,"usgs":false,"family":"Brown","given":"David","email":"","middleInitial":"P","affiliations":[{"id":39984,"text":"USDA Agricultural Research Service, El Reno, OK","active":true,"usgs":false}],"preferred":false,"id":771857,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Driscoll, Katelyn P.","contributorId":195582,"corporation":false,"usgs":false,"family":"Driscoll","given":"Katelyn","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":771858,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fleishman, Erica 0000-0003-4435-3134","orcid":"https://orcid.org/0000-0003-4435-3134","contributorId":215096,"corporation":false,"usgs":false,"family":"Fleishman","given":"Erica","email":"","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":771859,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ford, Paulette L.","contributorId":219277,"corporation":false,"usgs":false,"family":"Ford","given":"Paulette","email":"","middleInitial":"L.","affiliations":[{"id":39982,"text":"USDA Forest Service, Albuquerque, NM","active":true,"usgs":false}],"preferred":false,"id":771860,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hanberry, Brice","contributorId":219278,"corporation":false,"usgs":false,"family":"Hanberry","given":"Brice","affiliations":[{"id":39985,"text":"USDA Forest Service, Rapid City, SD","active":true,"usgs":false}],"preferred":false,"id":771861,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Symstad, Amy 0000-0003-4231-2873 asymstad@usgs.gov","orcid":"https://orcid.org/0000-0003-4231-2873","contributorId":201095,"corporation":false,"usgs":true,"family":"Symstad","given":"Amy","email":"asymstad@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":771854,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Van Pelt, Bill","contributorId":219279,"corporation":false,"usgs":false,"family":"Van Pelt","given":"Bill","affiliations":[{"id":39986,"text":"Western Association of Fish and Wildlife Agencies, Phoenix, AZ","active":true,"usgs":false}],"preferred":false,"id":771862,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Zabel, Richard","contributorId":219280,"corporation":false,"usgs":false,"family":"Zabel","given":"Richard","affiliations":[{"id":39987,"text":"Western Forestry and Conservation Association, Portland, OR","active":true,"usgs":false}],"preferred":false,"id":771863,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70204046,"text":"sir20195045 - 2019 - The hydrologic system of the south Florida peninsula—Development and application of the Biscayne and Southern Everglades Coastal Transport (BISECT) model","interactions":[],"lastModifiedDate":"2019-10-03T10:19:21","indexId":"sir20195045","displayToPublicDate":"2019-09-26T15:40:18","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":"2019-5045","displayTitle":"The Hydrologic System of the South Florida Peninsula: Development and Application of the Biscayne and Southern Everglades Coastal Transport (BISECT) Model","title":"The hydrologic system of the south Florida peninsula—Development and application of the Biscayne and Southern Everglades Coastal Transport (BISECT) model","docAbstract":"The Biscayne and Southern Everglades Coastal Transport (BISECT) model was developed by the U.S. Geological Survey under the Greater Everglades Priority Ecosystem Studies Initiative to evaluate, both separately and in conjunction, the likely effects on surface-water stages and flows, hydroperiod, and groundwater levels and salinity in south Florida of (1) a vertical Biscayne aquifer barrier to maintain higher wetland levels, (2) possible future changes to current water-management practices, and (3) sea-level rise. The BISECT model is a combination of the Tides and Inflows to the Mangrove Everglades (TIME) and Biscayne models of the western and eastern parts of south Florida including Everglades National Park, the southern Miami-Dade urban area, and the Biscayne Bay coast and simulates hydrodynamic surface-water flow and three-dimensional groundwater conditions dynamically for the period 1996–2004 by using the Flow and Transport in a Linked Overland/Aquifer Density-Dependent System (FTLOADDS) simulator. BISECT includes a number of parameter and algorithmic refinements that improve simulation results relative to the TIME and Biscayne models and represents the hydrologic system more explicitly, including (1) improved topographic representations, (2) refined Manning’s friction coefficients, (3) improved evapotranspiration computation through spatially variable albedo, (4) increased vertical aquifer discretization, and (5) extension of the western boundary farther offshore.
Sensitivity analyses demonstrate that simulated flows into Long Sound have a different pattern of response to tidal amplitude, wind, and frictional resistance changes than do other coastal streams in the model; flows at Broad River and Lostmans River are most sensitive to tidal amplitude, wind, and frictional resistance changes; and flow to the Everglades coastal streams is substantially affected by surface-water/groundwater interactions in the eastern urban areas. Insight into the hydrologic system came from scenario simulations that represent proposed management actions, such as grouting of the aquifer to prevent seepage from the wetlands and changes to water deliveries proposed by the Comprehensive Everglades Restoration Plan (CERP), and projected sea-level rise. These scenario management changes are considered separately to isolate their specific effects and also in conjunction with sea-level rise. Scenario simulations show that (1) attempts to prevent seepage from the wetlands by grouting the aquifer along the L 31N levee produce minimal effects on surface-water levels; (2) the increased water deliveries proposed in the CERP redistribute flow to the northwestern coastal part of the study area with a minimal reduction to the southeast and a more substantial reduction in flows in the intervening coastal zones, mitigating some sea-level rise effects; (3) sea-level rise has a larger effect on the hydrology (water levels, flow, and salinity) than does CERP restoration; and (4) support for ecological models and hydrologic studies can be provided by applying BISECT to scenarios influenced by climatic and anthropogenic changes or by meteorological variability, such as extreme wet or dry periods.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195045","collaboration":"USGS Greater Everglades Priority Ecosystem Studies Initiative","usgsCitation":"Swain, E.D., Lohmann, M.A., and Goodwin, C.R., 2019, The hydrologic system of the south Florida peninsula—Development and application of the Biscayne and Southern Everglades Coastal Transport (BISECT) model: U.S. Geological Survey Scientific Investigations Report 2019–5045, 114 p., https://doi.org/10.3133/sir20195045.","productDescription":"Report: viii, 114 p.; Data Release","numberOfPages":"126","onlineOnly":"Y","ipdsId":"IP-062750","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":367710,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/P9MDUQPK","text":"USGS data release ","description":"USGS Data Release","linkHelpText":"FTLOADDS (combined SWIFT2D surface-water model and SEAWAT groundwater model) simulator used to assess proposed sea-level rise response and water-resource management plans for the hydrologic system of the south Florida peninsula for the Biscayne and Southern Everglades Coastal Transport (BISECT) model"},{"id":367709,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5045/sir20195045.pdf","text":"Report","size":"24.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5045"},{"id":367708,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5045/coverthb2.jpg"}],"country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.49795532226562,\n 25.11544539706194\n ],\n [\n -80.15213012695312,\n 25.11544539706194\n ],\n [\n -80.15213012695312,\n 25.856751966503136\n ],\n [\n -81.49795532226562,\n 25.856751966503136\n ],\n [\n -81.49795532226562,\n 25.11544539706194\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
Assessing landscape patterns in climate vulnerability, as well as resilience and resistance to drought, disturbance, and invasive species, requires appropriate metrics of relevant environmental conditions. In dryland systems of western North America, soil temperature and moisture regimes have been widely utilized as an indicator of resilience to disturbance and resistance to invasive plant species by providing integrative indicators of long-term site aridity, which relates to ecosystem recovery potential and climatic suitability to invaders. However, the impact of climate change on these regimes, and the suitability of the indicator for estimating resistance and resilience in the context of climate change have not been assessed. Here we utilized a daily time-step, process-based, ecosystem water balance model to characterize current and future patterns in soil temperature and moisture conditions in dryland areas of western North America, and evaluate the impact of these changes on estimation of resilience and resistance. Soil temperature increases in the twenty-first century are substantial, relatively uniform geographically, and robust across climate models. Higher temperatures will expand the areas of mesic and thermic soil temperature regimes while decreasing the area of cryic and frigid temperature conditions. Projections for future precipitation are more variable both geographically and among climate models. Nevertheless, future soil moisture conditions are relatively consistent across climate models for much of the region. Projections of drier soils are expected in most of Arizona and New Mexico, as well as the central and southern U.S. Great Plains. By contrast, areas with projections of increasing soil moisture include northeastern Montana, southern Alberta and Saskatchewan, and many areas dominated by big sagebrush, particularly the Central and Northern Basin and Range and the Wyoming Basin ecoregions. In addition, many areas dominated by big sagebrush are expected to experience pronounced shifts toward cool season moisture, which will create more area with xeric moisture conditions and less area with ustic conditions. In addition to indicating widespread geographic shifts in the distribution of soil temperature and moisture regimes, our results suggest opportunities for enhancing the integration of these conditions into a quantitative framework for assessing climate change impacts on dryland ecosystem resilience and resistance that is responsive to long-term projections.
","language":"English","publisher":"Frontiers Media, Inc.","doi":"10.3389/fevo.2019.00358","usgsCitation":"Bradford, J., Schlaepfer, D., Lauenroth, W.K., Palmquist, K.A., Chambers, J.C., Maestas, J.D., and Campbell, S.B., 2019, Climate-driven shifts in soil temperature and moisture regimes suggest opportunities to enhance assessments of dryland resilience and resistance: Frontiers in Ecology and Evolution, v. 7, 358, 16 p., https://doi.org/10.3389/fevo.2019.00358.","productDescription":"358, 16 p.","ipdsId":"IP-107352","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":459723,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fevo.2019.00358","text":"Publisher Index Page"},{"id":437323,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9PJFE82","text":"USGS data release","linkHelpText":"Historical and 21st century soil temperature and moisture data for drylands of western U.S. and Canada"},{"id":367777,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Alberta, Arizona, British Columbia, California, Colorado, Idaho, Kansas, Montana, Nebraska, Nevada, New Mexico, North Dakota, Oklahoma, Oregon, Saskatchewan, South Dakota, Texas, Utah, Washington, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -129.462890625,\n 28.497660832963472\n ],\n [\n -94.74609375,\n 28.497660832963472\n ],\n [\n -94.74609375,\n 53.98193516209167\n ],\n [\n -129.462890625,\n 53.98193516209167\n ],\n [\n -129.462890625,\n 28.497660832963472\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2019-09-26","publicationStatus":"PW","contributors":{"authors":[{"text":"Bradford, John B. 0000-0001-9257-6303","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":219257,"corporation":false,"usgs":true,"family":"Bradford","given":"John B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":771811,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schlaepfer, Daniel R.","contributorId":105189,"corporation":false,"usgs":false,"family":"Schlaepfer","given":"Daniel R.","affiliations":[{"id":7098,"text":"University of Wyoming, Department of Botany, 1000 E. University Avenue, Laramie, WY 82071, USA","active":true,"usgs":false}],"preferred":false,"id":771812,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lauenroth, William K.","contributorId":80982,"corporation":false,"usgs":false,"family":"Lauenroth","given":"William","email":"","middleInitial":"K.","affiliations":[{"id":7098,"text":"University of Wyoming, Department of Botany, 1000 E. University Avenue, Laramie, WY 82071, USA","active":true,"usgs":false}],"preferred":false,"id":771813,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Palmquist, Kyle A.","contributorId":169517,"corporation":false,"usgs":false,"family":"Palmquist","given":"Kyle","email":"","middleInitial":"A.","affiliations":[{"id":7098,"text":"University of Wyoming, Department of Botany, 1000 E. University Avenue, Laramie, WY 82071, USA","active":true,"usgs":false}],"preferred":false,"id":771814,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Chambers, Jeanne C.","contributorId":178256,"corporation":false,"usgs":false,"family":"Chambers","given":"Jeanne","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":771815,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Maestas, Jeremy D.","contributorId":219258,"corporation":false,"usgs":false,"family":"Maestas","given":"Jeremy","email":"","middleInitial":"D.","affiliations":[{"id":39978,"text":"USDA Natural Resources Conservation Service, Redmond, OR","active":true,"usgs":false}],"preferred":false,"id":771816,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Campbell, Steven B.","contributorId":219259,"corporation":false,"usgs":false,"family":"Campbell","given":"Steven","email":"","middleInitial":"B.","affiliations":[{"id":39979,"text":"USDA Natural Resources Conservation Service, Portland, OR","active":true,"usgs":false}],"preferred":false,"id":771817,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70205574,"text":"70205574 - 2019 - Stormwater-quality performance of line permeable pavement systems","interactions":[],"lastModifiedDate":"2019-12-05T09:49:15","indexId":"70205574","displayToPublicDate":"2019-09-26T08:24:12","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Stormwater-quality performance of line permeable pavement systems","docAbstract":"Three permeable pavements were evaluated for their ability to improve the quality of stormwater runoff over a 22-month period in Madison, Wisconsin. Using a lined system with no internal water storage, permeable interlocking concrete pavers (PICP), pervious concrete (PC), and porous asphalt (PA) were able to significantly remove sediment and sediment-bound pollutant loads from runoff originating from an asphalt parking lot five times larger than the receiving permeable pavement area. Reductions in total suspended solids were similar for all three surfaces at approximately 60 percent. Clogging occurred after approximately one year, primarily due to winter sand application that led to high sediment load in spring runoff. Winter road salt application resulted in high chloride load that was initially attenuated in all three permeable pavements but later released during subsequent spring runoff events. Total phosphorus load was reduced by nearly 20 percent for PICP and PA, and 43 percent for PC. These values were likely tempered by the export of dissolved phosphorus observed in PICP and PA, but not PC. Average removal efficiencies for metals were 40, 42, and 49 percent in PA, PICP, and PC, respectively. A median pH of 10.2 in PC effluent could explain elevated removal efficiency of phosphorus and select metals in PC over PICP and PA (median = 7.5 and 7.8, respectfully) through enhanced precipitation. Elevated pH values in PC may also have led to higher removal efficiencies for select metals than PICP or PA. The environmental benefits as well as potential unintended consequences of stormwater practices like permeable pavement that utilize infiltration as a form of treatment warrant consideration in management of urban runoff.","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2019.109510","usgsCitation":"Selbig, W.R., Buer, N., and Danz, M., 2019, Stormwater-quality performance of line permeable pavement systems: Journal of Environmental Management, v. 251, 109510, 13 p. , https://doi.org/10.1016/j.jenvman.2019.109510.","productDescription":"109510, 13 p. ","ipdsId":"IP-108288","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":437326,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9IQHJ06","text":"USGS data release","linkHelpText":"Stormwater-quality data for lined permeable pavement systems in Madison, WI, from September 2016 through July 2018"},{"id":367716,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","county":"Dane County","city":"Madison","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-89.0094,43.286],[-89.0084,43.2555],[-89.0094,43.2],[-89.01,43.1131],[-89.0109,43.0849],[-89.0107,43.0271],[-89.0132,42.9353],[-89.013,42.8762],[-89.0119,42.8471],[-89.132,42.8479],[-89.2488,42.8478],[-89.3689,42.8484],[-89.3688,42.8575],[-89.4832,42.858],[-89.6026,42.8575],[-89.7196,42.8587],[-89.8377,42.8598],[-89.8375,42.9471],[-89.8386,43.0317],[-89.8384,43.1181],[-89.8394,43.205],[-89.8325,43.2123],[-89.825,43.2187],[-89.8175,43.226],[-89.8125,43.2342],[-89.8088,43.2369],[-89.8012,43.2365],[-89.7874,43.2356],[-89.771,43.237],[-89.7579,43.2379],[-89.7529,43.2443],[-89.7485,43.2507],[-89.7391,43.2548],[-89.7259,43.2644],[-89.7171,43.2739],[-89.714,43.2821],[-89.7165,43.2867],[-89.7235,43.2935],[-89.7209,43.2935],[-89.6008,43.2932],[-89.4819,43.2942],[-89.3617,43.2954],[-89.3624,43.2832],[-89.246,43.2834],[-89.1271,43.2827],[-89.0094,43.286]]]},\"properties\":{\"name\":\"Dane\",\"state\":\"WI\"}}]}","volume":"251","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Selbig, William R. 0000-0003-1403-8280 wrselbig@usgs.gov","orcid":"https://orcid.org/0000-0003-1403-8280","contributorId":877,"corporation":false,"usgs":true,"family":"Selbig","given":"William","email":"wrselbig@usgs.gov","middleInitial":"R.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":771703,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Buer, Nicolas 0000-0002-4369-8715","orcid":"https://orcid.org/0000-0002-4369-8715","contributorId":204808,"corporation":false,"usgs":true,"family":"Buer","given":"Nicolas","email":"","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":771705,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Danz, Mari 0000-0002-4716-0170 medanz@usgs.gov","orcid":"https://orcid.org/0000-0002-4716-0170","contributorId":219227,"corporation":false,"usgs":true,"family":"Danz","given":"Mari","email":"medanz@usgs.gov","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":771704,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70205500,"text":"sim3438 - 2019 - Map of the approximate inland extent of saltwater at the base of the Biscayne aquifer in Miami-Dade County, Florida, 2018","interactions":[],"lastModifiedDate":"2019-09-26T08:02:35","indexId":"sim3438","displayToPublicDate":"2019-09-25T14:58:55","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3438","displayTitle":"Map of the Approximate Inland Extent of Saltwater at the Base of the Biscayne Aquifer in Miami-Dade County, Florida, 2018","title":"Map of the approximate inland extent of saltwater at the base of the Biscayne aquifer in Miami-Dade County, Florida, 2018","docAbstract":"The inland extent of saltwater at the base of the Biscayne aquifer in eastern Miami-Dade County, Florida, was mapped in 2011, and it was mapped in the Model Land Area in 2016. The saltwater interface has continued to move inland in some areas and is now near several active well fields. An updated approximation of the inland extent of saltwater has been created by using data collected during March 8–December 13, 2018, from 111 monitoring wells open to the Biscayne aquifer near its base. Chloride concentrations in water samples from the monitoring wells and bulk conductivity from geophysical logs and measurements of the specific conductance of groundwater were used to approximate the position of the isochlor representing a chloride concentration of 1,000 milligrams per liter (mg/L) at the base of the Biscayne aquifer.
An average rate of saltwater interface movement of about 102 meters per year in the Model Land Area along SW 360 Street was estimated from the approximated dates of arrival of the 250-, 500-, and 1,000-mg/L isochlors at wells TPGW-7L (2013–2014) and ACI-MW-05-FS (2017–2018). This estimate assumes that the interface is traveling in a path parallel to an imaginary line connecting the two monitoring wells.
Of the 111 wells from which data were used, 80 wells have open intervals of ≤ 4 meters, 20 of the wells have open intervals that range from 4.3 to 39.6 meters, and the lengths of the open intervals could not be determined in 11 wells. Studies have shown that long open intervals might allow water from various depths to mix under ambient or pumped conditions, which in turn could alter the maximum chloride concentration sampled in the well, or it might change the depth at which the maximum specific conductance is measured within a well, relative to its depth in the aquifer. The approximation of the inland extent of the saltwater interface and the estimated rate of movement of the interface are dependent on the quality of existing data. Improved estimates could be obtained by installing uniformly designed monitoring wells in systematic transects extending landward of the advancing saltwater interface. To achieve this goal, Miami-Dade County and some other organizations are routinely adding new monitoring wells with short open intervals and replacing poorly designed or positioned monitoring wells to improve spatial coverage of the network.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3438","collaboration":"Prepared in cooperation with Miami-Dade County","usgsCitation":"Prinos, S.T., 2019, Map of the approximate inland extent of saltwater at the base of the Biscayne aquifer in Miami-Dade County, Florida, 2018: U.S. Geological Survey Scientific Investigations Map 3438, 10-p. pamphlet, 1 sheet, https://doi.org/10.3133/sim3438.","productDescription":"Pamphlet: vii, 10 p.; 1 Plate: 35.8 x 46.0 inches; Data Release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-107371","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":367675,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3438/sim3438.pdf","text":"Sheet","size":"898 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3438"},{"id":367674,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3438/coverthb3.jpg"},{"id":367676,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3438/sim3438_pamphlet.pdf","text":"Pamphlet","size":"857 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3438 Pamphlet"},{"id":367677,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9ZIC1O4","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Data Pertaining to Mapping the Approximate Inland Extent of Saltwater at the Base of the Biscayne Aquifer in Miami-Dade County, Florida, 2018"}],"country":"United States","state":"Florida","county":"Miami-Dade County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.8538818359375,\n 25.095548539604252\n ],\n [\n -79.9969482421875,\n 25.095548539604252\n ],\n [\n -79.9969482421875,\n 26.892679095908164\n ],\n [\n -80.8538818359375,\n 26.892679095908164\n ],\n [\n -80.8538818359375,\n 25.095548539604252\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
The U.S. Geological Survey publishes information on the mass, or load, of water-quality constituents transported through rivers and streams sampled as part of the operation of the National Water Quality Network (NWQN). This study evaluates methods for computing annual water-quality loads, specifically with respect to procedures currently (2019) used at sites in the NWQN. Near-daily datasets of chloride, total nitrogen, nitrate plus nitrite, total phosphorus, and suspended sediment were subset to determine the accuracy of various load-estimation methods, including linear interpolation, ratio estimators, and linear and weighted-regression methods. Water-quality loads are computed under different sampling strategies and at multiple sampling sites to provide a more complete evaluation of load-estimation methods.
Estimation methods were less accurate when computing loads at annual rather than decadal time steps. Depending on the water-quality constituent, annual loads were within comparable accuracy thresholds 21 to 64 percent of the time relative to decadal loads. The accuracy of annual load estimates varied among water-quality constituents, sampling strategies, sampling sites, and estimation methods. Methods were most accurate when estimating chloride and decreased in accuracy when estimating total nitrogen, nitrate plus nitrite, total phosphorus, and suspended-sediment loads. Estimation methods were most likely to compute accurate annual loads when samples were collected frequently (26 samples per year) and when sampling strategies targeted high-flow conditions. For a given water-quality constituent, estimation accuracy differed substantially among sampling sites; estimates were more likely to be accurate at large rivers with less variability in concentration and (or) discharge conditions and were less likely to be accurate at smaller stream sites with more variable streamflow and (or) water-quality concentrations.
The Weighted Regressions on Time, Discharge, and Season method with Kalman filtering (WRTDS_K) generally produced the most accurate annual load estimates among sampling sites and water-quality constituents. Although WRTDS_K was the most accurate generally, every estimation method evaluated had the potential to produce accurate (and inaccurate) load estimates depending on the site, constituent, and water year. Linear interpolation and ratio estimators that used samples exclusively from the year being estimated were among the best performing methods for total nitrogen and nitrate plus nitrite loads but were among the least accurate when estimating annual total phosphorus and suspended-sediment loads. Ratio estimation that considered samples from previous years and stratified based on streamflow conditions produced among the most accurate total phosphorus estimates but was among the least accurate for other constituents. Regression-based methods that assumed linear or quadratic relations among the logarithm of water-quality concentrations and streamflow conditions were among the least accurate methods generally, whereas regression-based methods that considered cubic relations among the logarithm of concentration and streamflow and the Weighted Regressions on Time, Discharge, and Season (WRTDS) method were typically more accurate. Methods that adjusted daily estimates computed from regression or weighted-regression methods based on departures from sampled values, such as WRTDS_K and the composite method, improved estimate accuracy for most sites and constituents, but especially for chloride, total nitrogen, nitrate plus nitrite, and suspended-sediment estimates.
Investigation of the underlying causes of estimation method bias indicated that sites and years with more variability in concentration and loading conditions, higher slopes in the relation of the logarithm of concentration and discharge, and sampling plans that underrepresented high-flow conditions generally led to less accurate load estimates. Finally, because all methods indicated the capacity to produce biased load estimates, additional work is needed to identify the capacity of new technologies, such as continuous water-quality sensors, to improve the accuracy of annual or shorter term load estimates. Based on findings in this report, the NWQN will continue to publish water-quality loads using LOADEST-based methods that consider multiple transformations of streamflow, as well as season, time, and variables indicative of historical streamflow conditions to maintain consistent methods for stakeholders. However, the NWQN also plans to begin publishing annual load estimates using the WRTDS_K method in 2020 because this method was determined to be the most accurate for a given site, constituent, and water year.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195084","usgsCitation":"Lee, C.J., Hirsch, R.M., and Crawford, C.G., 2019, An evaluation of methods for computing annual water-quality loads: U.S. Geological Survey Scientific Investigations Report 2019–5084, 59 p., https://doi.org/10.3133/sir20195084.","productDescription":"Report: x, 59 p.; Appendix Figures 3–7; Data Release","startPage":"1-84","numberOfPages":"74","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-103673","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":367653,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9BK91LN","text":"USGS data release","linkHelpText":"Supplementary data used to evaluate methods for computing annual water-quality loads, 1948–2016"},{"id":367650,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5084/coverthb.jpg"},{"id":367651,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5084/sir20195084.pdf","text":"Report","size":"3.93 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019–5084"},{"id":367652,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2019/5084/downloads","text":"Appendix figures 3–7","description":"SIR 2019–5084 Appendix Figures 3–7"}],"contact":"Chief, National Water-Quality Assessment Program
U.S. Geological Survey
413 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
The U.S. Army Corps of Engineers (USACE), Nashville District, is conducting ongoing water-supply analyses of USACE reservoirs in the Cumberland River watershed to identify areas where potential water-resources issues may arise in the future. To assist the USACE in their efforts, the U.S. Geological Survey, in cooperation with the USACE, collected and analyzed water-use data to estimate public-supply, self-supplied industrial, irrigation, and thermoelectric water use for 2010 and to project water demand to 2040 for the Cumberland River watershed area.
Estimates of water use for public supply were projected in 10-year increments through 2040 and were based on 2010 public water-supply data and population projections for 2020 to 2040. Additionally, estimates of consumptive use, wastewater releases, and thermoelectric power and industrial return flows were calculated. All estimates are presented for the entire watershed and for the 10 reservoir catchment areas (RCAs) within the watershed.
Estimated water withdrawals in the Cumberland River watershed during 2010 averaged 3,456.23 million gallons per day (Mgal/d) of freshwater for offstream use. Return flow was estimated to be 3,370.08 Mgal/d, or 98 percent of the water withdrawn during 2010. Total consumptive use accounts for the remaining 2 percent, or 86.2 Mgal/d. Estimates of water withdrawals by source indicate that withdrawals from surface water during 2010 accounted for more than 99 percent of the total withdrawals, or 3,437.90 Mgal/d. Total groundwater withdrawals during 2010 were 18.33 Mgal/d, or less than 1 percent of the total withdrawals.
During 2010, withdrawals by category were estimated as follows: thermoelectric power, 3,051.12 Mgal/d; public supply, 360.00 Mgal/d; industrial, 31.5 Mgal/d; and irrigation, 13.6 Mgal/d. Return flows were estimated as thermoelectric power, 3,051.06 Mgal/d, and industrial and public supply, 319.02 Mgal/d. Consumptive use was estimated as thermoelectric power, 0.06 Mgal/d; industrial and public supply, 72.5 Mgal/d; and irrigation, 13.6 Mgal/d.
By 2040, the public supply of raw and (or) finished water to meet demand for the 10 RCAs is projected to increase 48 percent to 532.51 Mgal/d. This projected increase includes an increase from 51.5 to 72.5 Mgal/d, or 41 percent, in the Barkley RCA. The combined total water demand for the Cheatham, J. Percy Priest, and Old Hickory RCAs is projected to increase from 224.08 to 359.58 Mgal/d, or 61 percent. The combined total water demand for the Center Hill, Cordell Hull, and Dale Hollow RCAs is projected to increase from 31.7 to 43.0 Mgal/d, or 36 percent. The combined total water demand for the Martins Fork, Laurel, and Wolf Creek RCAs is projected to increase from 52.8 to 57.4 Mgal/d, or 9 percent. The only RCA in the watershed with a projected decrease in water demand is Martins Fork.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185130","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Nashville District","usgsCitation":"Robinson, J.A., 2019, Estimated use of water in the Cumberland River watershed in 2010 and projections of public-supply water use to 2040: U.S. Geological Survey Scientific Investigations Report 2018–5130, 62 p., https://doi.org/10.3133/sir20185130.","productDescription":"Report: viii, 62 p.; Data Release","numberOfPages":"74","onlineOnly":"Y","ipdsId":"IP-044987","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":367657,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7M043KK","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Public Supply Water Use in the Cumberland River Watershed in 2010 and Projections of Public-supply Water Use to 2040"},{"id":367656,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5130/sir20185130.pdf","text":"Report","size":"10.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018–5131"},{"id":367655,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5130/coverthb.jpg"}],"country":"United States","state":"Kentucky, Tennessee, Virginia","otherGeospatial":"Cumberland River Watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.472900390625,\n 37.23907530202184\n ],\n [\n -87.725830078125,\n 36.36822190085111\n ],\n [\n -86.50634765625,\n 35.737595151747826\n ],\n [\n -82.55126953124999,\n 36.74768773190056\n ],\n [\n -82.562255859375,\n 36.99377838872517\n ],\n [\n -83.60595703125,\n 36.83566824724438\n ],\n [\n -84.462890625,\n 37.57070524233116\n ],\n [\n -85.166015625,\n 37.54457732085582\n ],\n [\n -85.572509765625,\n 36.677230602346214\n ],\n [\n -88.472900390625,\n 37.23907530202184\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
640 Grassmere Park, Suite 100
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Although streamflow is widely recognized as a controlling factor in stream health, empirical relations between indicators of anthropogenic modification of streamflow and ecological indicators have been elusive. The objective of this report is to build upon specific findings reported in recent publications by providing a library of empirical models that describe the relations between streamflow modification and indicators of biological integrity. Biological monitoring data from 812 streams and rivers across the United States were matched with sites where daily streamflow was also monitored by the U.S. Geological Survey. Of these sites, 118 were sampled by the U.S. Geological Survey along gradients of streamflow modification within 3 regional focus studies. The integrity of invertebrate and fish communities was expressed as a binary variable, “impaired” or “unimpaired,” signifying whether or not the composition and structure of the biological community was statistically reduced relative to regional reference sites. Streamflow modification at each gaged site was quantified with 509 streamflow statistics scaled to express the ratio of observed streamflow conditions to site-specific expected conditions in the absence of human influences on watershed hydrology. For each region, generalized additive modeling was used to examine relations between each indicator of streamflow modification and indicators of biological integrity (response variable). In every region examined, statistically defensible and ecologically realistic relations were found between indicators of streamflow modification and indicators of biological integrity. These findings can aid practitioners and managers seeking to (1) propose empirically based hypotheses about the specific components of streamflow regimes that are critical to aquatic communities, which can subsequently be explored in detail in a region or river basin of interest; and (2) predict biological responses to anthropogenic modification of specific components of the streamflow regime.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191088","usgsCitation":"Carlisle, D.M., Grantham, T.E., Eng, K., Wolock, D.M., 2019, Regional-scale associations between indicators of biological integrity and indicators of streamflow modification: U.S. Geological Survey Open-File Report 2019–1088, 10 p., https://doi.org/10.3133/ofr20191088.\n","productDescription":"iv, 10 p.","numberOfPages":"18","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-097828","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":367467,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9O2ZV0M","linkHelpText":"Regional-scale Model Predictions of the Relation Between Biological Integrity and Streamflow Modification"},{"id":367452,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1088/ofr20191088.pdf","text":"Report","size":"12.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1088"},{"id":367451,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1088/coverthb.jpg"}],"contact":"Director, USGS Kansas Water Science Center
1217 Biltmore Drive
Lawrence, KS 66049
785-842-9909
Phosphorus (P) fertilizer has contributed to the eutrophication of freshwater ecosystems. Watershed-based conservation programs aiming to reduce external P loading to surface waters have not resulted in significant water-quality improvements. One factor that can help explain the lack of water-quality response is remobilization of accumulated legacy (historical) P within the terrestrial-aquatic continuum, which can obscure the beneficial impacts of current conservation efforts. We examined how contemporary river P trends (between 1992 and 2012) responded to estimated changes in contemporary agricultural P balances [(fertilizer + manure inputs)—crop uptake and harvest removal] for 143 watersheds in the conterminous United States, while also developing a proxy estimate of legacy P contribution, which refers to anthropogenic P inputs before 1992. We concluded that legacy sources contributed to river export in 49 watersheds because mean contemporary river P export exceeded mean contemporary agricultural P balances. For the other 94 watersheds, agricultural P balances exceeded river P export, and our proxy estimate of legacy P was inconclusive. If legacy contributions occurred in these locations, they were likely small and dwarfed by contemporary P sources. Our continental-scale P mass balance results indicated that improved incentives and strategies are needed to promote the adoption of nutrient-conserving practices and reduce widespread contemporary P surpluses. However, a P surplus reduction is only 1 component of an effective nutrient plan as we found agricultural balances decreased in 91 watersheds with no consistent water-quality improvements, and balances increased in 52 watersheds with no consistent water-quality degradation.
","language":"English","publisher":"National Academy of Sciences","doi":"10.1073/pnas.1903226116","usgsCitation":"Stackpoole, S.M., Stets, E.G., and Sprague, L.A., 2019, Variable impacts of contemporary versus legacy agricultural phosphorus on US river water quality: PNAS, v. 116, no. 41, p. 20562-20567, https://doi.org/10.1073/pnas.1903226116.","productDescription":"6 p.","startPage":"20562","endPage":"20567","ipdsId":"IP-110112","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":459747,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1073/pnas.1903226116","text":"Publisher Index Page"},{"id":437329,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P972DHYF","text":"USGS data release","linkHelpText":"Watershed-scale agricultural phosphorus balances and river export trends for the conterminous United States, 1992-2012"},{"id":371731,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"geometry\": {\n \"type\": \"MultiPolygon\",\n \"coordinates\": [\n [\n [\n [\n -94.81758,\n 49.38905\n ],\n [\n -94.64,\n 48.84\n ],\n [\n -94.32914,\n 48.67074\n ],\n [\n -93.63087,\n 48.60926\n ],\n [\n -92.61,\n 48.45\n ],\n [\n -91.64,\n 48.14\n ],\n [\n -90.83,\n 48.27\n ],\n [\n -89.6,\n 48.01\n ],\n [\n -89.27292,\n 48.01981\n ],\n [\n -88.37811,\n 48.30292\n ],\n [\n -87.43979,\n 47.94\n ],\n [\n -86.46199,\n 47.55334\n ],\n [\n -85.65236,\n 47.22022\n ],\n [\n -84.87608,\n 46.90008\n ],\n [\n -84.77924,\n 46.6371\n ],\n [\n -84.54375,\n 46.53868\n ],\n [\n -84.6049,\n 46.4396\n ],\n [\n -84.3367,\n 46.40877\n ],\n [\n -84.14212,\n 46.51223\n ],\n [\n -84.09185,\n 46.27542\n ],\n [\n -83.89077,\n 46.11693\n ],\n [\n 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Encompassing investigations of conventional and renewable energy development across the United States, from the Arctic Coastal Plain of Alaska to the balmy waters of Florida, the report features progress made by USGS scientists and partners in developing methods to minimize the impacts of energy infrastructure on wildlife. The report is available at https://doi.org/10.3133/cir1458.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/gip193","usgsCitation":"Khalil, M., 2019, U.S. Geological Survey energy and wildlife research annual report for 2019 postcard: U.S. Geological Survey General Information Product 193, 2 p., https://doi.org/10.3133/gip193.","productDescription":"Postcard: 5.8 x 4.1 inches","onlineOnly":"N","ipdsId":"IP-111521","costCenters":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"links":[{"id":367592,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/gip/0193/coverthb.jpg"},{"id":367593,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/gip/0193/gip193.pdf","text":"Report ","size":"266 KB","linkFileType":{"id":1,"text":"pdf"},"description":"GIP 193"},{"id":367594,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/publication/cir1458","text":"Circular 1458","linkHelpText":"- U.S. Geological Survey Energy and Wildlife Research Annual Report for 2019"}],"contact":"Energy and Wildlife Program
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
The challenges of providing safe and sustainable water supplies for human and ecological uses and protecting lives and property during water emergencies are well recognized. The U.S. Geological Survey (USGS) plays an essential role in meeting these challenges through its observational networks and renowned water science and research activities (National Academies of Science, Engineering, and Medicine, 2018). Substantial advances in water science, together with emerging breakthroughs in technical and computational capabilities, have led the USGS to develop a Next Generation Water Observing System (NGWOS). The NGWOS will provide real-time data on water quantity and quality in more affordable and rapid ways than previously possible, and in more locations. The data will be served through a modernized USGS National Water Information System that will be coupled to advanced modeling tools to inform daily water operations, decision-making during water emergencies (like floods, droughts, and contaminant spills), assessments of past trends in water quantity and quality, and forecasts of future water availability.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20193046","usgsCitation":"Eberts, S.M., Wagner, C.R., and Woodside, M.D., 2019, Water priorities for the Nation—The U.S. Geological Survey Next Generation Water Observing System: U.S. Geological Survey Fact Sheet 2019–3046, 2 p., https://doi.org/10.3133/fs20193046.","productDescription":"2 p.","onlineOnly":"Y","ipdsId":"IP-109916","costCenters":[{"id":38131,"text":"WMA - Office of Planning and Programming","active":true,"usgs":true}],"links":[{"id":366749,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2019/3046/coverthb.jpg"},{"id":367487,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2019/3046/fs20193046.pdf","text":"Report","size":"2.01 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Fact Sheet 2019-3046"}],"contact":"U.S. Geological Survey
Water Resources Mission Area
Groundwater and Streamflow Information Program
3916 Sunset Ridge Road
Raleigh, North Carolina 26707
Information concerning the availability, use, and quality of water in Lincoln Parish, Louisiana, is critical for proper water-supply management. The purpose of this fact sheet is to present information that can be used by water managers, parish residents, and others for stewardship of this vital resource. In 2014, about 7.76 million gallons per day (Mgal/d) of water were withdrawn in Lincoln Parish: 7.69 Mgal/d from groundwater sources and 0.07 Mgal/d from surface-water sources. Withdrawals for public-supply use accounted for about 89 percent (6.88 Mgal/d) of the total water withdrawn. Other categories of use included industrial, general irrigation, livestock, and rural domestic. Water-use data collected at 5-year intervals from 1960 to 2010 and again in 2014 indicate that water withdrawals peaked in 2000 at 11.01 Mgal/d.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20193019","collaboration":"Prepared in cooperation with the Louisiana Department of Transportation and Development","usgsCitation":"White, V.E., 2019, Water resources of Lincoln Parish, Louisiana: U.S. Geological Survey Fact Sheet 2019–3019, 6 p., https://doi.org/10.3133/fs20193019.","productDescription":"Report: 6 p; Data Release","onlineOnly":"N","ipdsId":"IP-081706","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":367462,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2019/3019/coverthb.jpg"},{"id":367464,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F78051VM","text":"USGS data release ","description":"USGS Data Release","linkHelpText":"Water withdrawals by source and category in Louisiana Parishes, 2014–2015"},{"id":367463,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2019/3019/fs20193019.pdf","text":"Report","size":"871 kB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2019–3019"}],"country":"United States","state":"Louisiana","county":"Lincoln Parish","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-92.8807,32.5853],[-92.8808,32.5898],[-92.8809,32.5953],[-92.881,32.6003],[-92.875,32.6026],[-92.8723,32.6022],[-92.8669,32.6068],[-92.8655,32.6178],[-92.8645,32.626],[-92.8609,32.6374],[-92.8638,32.6497],[-92.8667,32.6592],[-92.8647,32.6661],[-92.8686,32.6729],[-92.866,32.6788],[-92.8623,32.6871],[-92.8548,32.6926],[-92.8484,32.7009],[-92.8409,32.7106],[-92.835,32.7134],[-92.8284,32.7125],[-92.8287,32.7603],[-92.8014,32.7602],[-92.7757,32.76],[-92.7256,32.7597],[-92.6361,32.7597],[-92.6312,32.7593],[-92.6279,32.7575],[-92.6191,32.7548],[-92.6147,32.7526],[-92.6099,32.7549],[-92.6044,32.7555],[-92.5968,32.7551],[-92.5913,32.7528],[-92.5852,32.7488],[-92.5787,32.748],[-92.5722,32.7489],[-92.5672,32.7453],[-92.5572,32.7331],[-92.5517,32.7268],[-92.5472,32.7205],[-92.5418,32.7187],[-92.5374,32.7206],[-92.5342,32.7224],[-92.5271,32.7202],[-92.5233,32.723],[-92.5195,32.7239],[-92.5188,32.6725],[-92.4736,32.6715],[-92.4153,32.672],[-92.4132,32.5845],[-92.4155,32.4952],[-92.6231,32.497],[-92.6228,32.4747],[-92.6231,32.4537],[-92.7768,32.4548],[-92.8078,32.4545],[-92.8795,32.4541],[-92.8779,32.5202],[-92.8807,32.5853]]]},\"properties\":{\"name\":\"Lincoln\",\"state\":\"LA\"}}]}","contact":"Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
3535 S. Sherwood Forest Blvd., Suite 120
Baton Rouge, LA 70816
Information concerning the availability, use, and quality of water in Winn Parish, Louisiana, is critical for proper water-supply management. The purpose of this fact sheet is to present information that can be used by water managers, parish residents, and others for stewardship of this vital resource. In 2014, about 2.74 million gallons per day (Mgal/d) of water were withdrawn in Winn Parish: 2.69 Mgal/d from groundwater sources and 0.05 Mgal/d from surface-water sources. Withdrawals for public supply accounted for about 71 percent (1.95 Mgal/d) of the total water withdrawn, and industrial use accounted for about 19 percent (0.51 Mgal/d). Other categories of use included rural domestic, livestock, and general irrigation. Water-use data collected at 5-year intervals from 1960 to 2010 and again in 2014 indicated that water withdrawals peaked in 2000 at about 3.81 Mgal/d.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20193022","collaboration":"Prepared in cooperation with the Louisiana Department of Transportation and Development","usgsCitation":"White, V.E., 2019, Water resources of Winn Parish, Louisiana: U.S. Geological Survey Fact Sheet 2019–3022, 6 p., https://doi.org/10.3133/fs20193022.","productDescription":"Report: 6 p; Data Release","onlineOnly":"N","ipdsId":"IP-081708","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":367459,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2019/3022/coverthb.jpg"},{"id":367460,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2019/3022/fs20193022.pdf","text":"Report","size":"857 kB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2019–3022"},{"id":367461,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F78051VM","text":"USGS data release ","linkHelpText":"Water withdrawals by source and category in Louisiana Parishes, 2014–2015"}],"country":"United States","state":"Louisiana ","otherGeospatial":"Winn Parish ","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-92.3114,32.1483],[-92.3129,31.9276],[-92.3126,31.8966],[-92.3136,31.8934],[-92.3201,31.8893],[-92.3216,31.8847],[-92.3194,31.8792],[-92.3221,31.8719],[-92.3241,31.8605],[-92.3295,31.8577],[-92.3354,31.8563],[-92.3375,31.854],[-92.3348,31.8499],[-92.3315,31.8463],[-92.3352,31.8394],[-92.34,31.8307],[-92.3383,31.8239],[-92.3404,31.8207],[-92.3409,31.8157],[-92.3489,31.8092],[-92.3532,31.8083],[-92.3586,31.8073],[-92.359,31.8014],[-92.3628,31.7968],[-92.4043,31.797],[-92.4156,31.7969],[-92.428,31.7972],[-92.4662,31.7969],[-92.6193,31.7978],[-92.6196,31.7836],[-92.6194,31.7686],[-92.6202,31.7101],[-92.6541,31.7098],[-92.6708,31.7096],[-92.8248,31.7102],[-92.9647,31.7098],[-92.9734,31.7147],[-92.9657,31.7354],[-92.9693,31.7473],[-92.973,31.7512],[-92.9733,31.7523],[-92.9742,31.7562],[-92.9742,31.7582],[-92.9735,31.7606],[-92.9723,31.7637],[-92.967,31.7759],[-92.9633,31.7796],[-92.9547,31.7816],[-92.9538,31.7884],[-92.9528,31.7939],[-92.9518,31.7967],[-92.9464,31.8004],[-92.9465,31.8045],[-92.9476,31.8081],[-92.9418,31.8151],[-92.9489,31.8186],[-92.9517,31.8231],[-92.9512,31.8254],[-92.9491,31.8273],[-92.9469,31.8268],[-92.9409,31.8224],[-92.9382,31.8238],[-92.9389,31.8288],[-92.9465,31.8351],[-92.9498,31.8387],[-92.9494,31.8441],[-92.9468,31.8492],[-92.9506,31.8523],[-92.9528,31.8569],[-92.9464,31.8574],[-92.9415,31.8543],[-92.9366,31.8534],[-92.9263,31.8548],[-92.9178,31.8528],[-92.9101,31.851],[-92.9068,31.8553],[-92.904,31.8547],[-92.8992,31.8598],[-92.9067,31.8698],[-92.9025,31.8757],[-92.9033,31.8926],[-92.8943,31.9014],[-92.8971,31.91],[-92.8951,31.9174],[-92.893,31.9197],[-92.8871,31.9243],[-92.8836,31.9378],[-92.8745,31.9427],[-92.8735,31.9459],[-92.8833,31.9535],[-92.8888,31.9562],[-92.8894,31.9612],[-92.8878,31.964],[-92.8852,31.9667],[-92.8836,31.9672],[-92.883,31.9682],[-92.8837,31.9727],[-92.8832,31.9804],[-92.8924,31.9812],[-92.8962,31.9816],[-92.9011,31.9825],[-92.9083,31.9902],[-92.9045,31.9929],[-92.8965,31.9967],[-92.8906,32.0018],[-92.8892,32.0118],[-92.8893,32.0191],[-92.8873,32.0269],[-92.8934,32.0364],[-92.8931,32.0478],[-92.8998,32.0628],[-92.9084,32.0722],[-92.9131,32.0781],[-92.9078,32.0868],[-92.9079,32.0914],[-92.9129,32.0982],[-92.9143,32.1008],[-92.9162,32.104],[-92.9218,32.1117],[-92.9262,32.118],[-92.935,32.1257],[-92.9363,32.138],[-92.938,32.1425],[-92.9402,32.1457],[-92.9407,32.148],[-92.9376,32.148],[-92.8207,32.149],[-92.812,32.1491],[-92.3114,32.1483]]]},\"properties\":{\"name\":\"Winn\",\"state\":\"LA\"}}]}","contact":"Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
3535 S. Sherwood Forest Blvd., Suite 120
Baton Rouge, LA 70816
Information concerning the availability, use, and quality of water in Franklin Parish, Louisiana, is critical for proper water-supply management. The purpose of this fact sheet is to present information that can be used by water managers, parish residents, and others for stewardship of this vital resource. In 2014, about 41.79 million gallons per day (Mgal/d) of water were withdrawn in Franklin Parish: 37.73 Mgal/d from groundwater sources and 4.06 Mgal/d from surface-water sources. Withdrawals for agricultural use—composed of general irrigation, rice irrigation, aquaculture, and livestock—accounted for about 89 percent (37.16 Mgal/d) of the total water withdrawn. Public-supply use accounted for about 3 percent (1.07 Mgal/d); industry accounted for about 7 percent (2.92 Mgal/d); and rural domestic use accounted for about 2 percent (0.64 Mgal/d). Water-use data collected at 5-year intervals from 1960 to 2010 and again in 2014 indicated that water withdrawals peaked in 2005 at more than 50 Mgal/d.
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Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
3535 S. Sherwood Forest Blvd., Suite 120
Baton Rouge, LA 70816
Information concerning the availability, use, and quality of water in Madison Parish, Louisiana, is critical for proper water-supply management. The purpose of this fact sheet is to present information that can be used by water managers, parish residents, and others for stewardship of this vital resource. In 2014, 50.66 million gallons per day (Mgal/d) of water were withdrawn in Madison Parish: 44.37 Mgal/d from groundwater sources and 6.30 Mgal/d from surface-water sources. Withdrawals for agricultural use—composed of general irrigation, rice irrigation, livestock, and aquaculture—accounted for about 96 percent (48.86 Mgal/d) of the total water withdrawn. Other categories of use included public supply and rural domestic. Water-use data collected at 5-year intervals from 1960 to 2010 and again in 2014 indicated that water withdrawals peaked in 2014. The relatively large increase in water use from 2005 to 2010 is largely attributable to a change in the methods used for estimation of general irrigation land usage. General irrigation withdrawals from groundwater increased from 11.13 Mgal/d in 2005 to 28.28 Mgal/d in 2010.
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The System-Wide Assessment and Monitoring Program (SWAMP) has been envisioned as a long-term monitoring program to ensure a comprehensive network of coastal data collection activities is in place to support the development, implementation, and adaptive management of the coastal protection and restoration program within coastal Louisiana. The Coastwide Reference Monitoring System (CRMS) and Barrier Island Comprehensive Monitoring (BICM) programs have been implemented under SWAMP, while other aspects of system dynamics, including offshore and inland water-body boundary conditions, nontidal freshwater habitats, riverine conditions, risk status, and protection performance, are not presently the subject of CPRA-coordinated (Coastal Protection and Restoration Authority) monitoring. In order to implement these additional aspects of SWAMP, CPRA partnered with The Water Institute of the Gulf and others to develop 1) a programmatic monitoring plan for evaluating the effectiveness of the coastal protection and restoration program on a coastwide scale, and 2) basinwide monitoring plans that will incorporate the elements of the programmatic plan with specific data collection activities designed to capture effects within the basin. Monitoring plans were developed for Barataria Basin, Pontchartrain Region (includes Breton Sound, Pontchartrain and Mississippi River Delta Basins), and the western basins (Calcasieu-Sabine, Mermentau, Teche-Vermilion, Atchafalaya, and Terrebonne) for both the natural and human systems using a process to identify the monitoring variables, objectives, and sampling design. The monitoring variables and objectives identified fall under the general categories of weather and climate, biotic integrity, water quality, hydrology, physical terrain, population and demographics, housing and community characteristics, economy and employment, ecosystem dependency, residential properties protection, and critical infrastructure and essential services protection. A rigorous statistical analysis, examination of modeling needs, and thorough reviews of previous planning and monitoring efforts were conducted to develop the sampling designs for the natural and human system monitoring plans. The plan relies heavily on the use of existing data, thus, coordination with other agencies (e.g., LDEQ , LDWF) and CPRA’s existing monitoring programs (e.g., BICM, CRMS) is critical to the plan’s success. Implementation of the plans will require development of quality control and quality assurance protocols, specific standardized operating procedures for each of the data collection efforts, a data management plan, and a reporting framework to contribute to decision making and reducing uncertainty in management actions.
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