The U.S. Geological Survey (USGS), in partnership with the Idaho Department of Water Resources (IDWR) and Idaho Water Resource Board (IWRB), will construct a numerical groundwater-flow model of the Treasure Valley and surrounding area. Resource managers will use the model to simulate potential anthropogenic and climatic effects on groundwater for water-supply planning and management. As part of model construction, the hydrogeologic understanding of the aquifer system will be updated with information collected during the last two decades, as well as new data collected for the study.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20173027","collaboration":"Prepared in cooperation with the Idaho Department of Water Resources","usgsCitation":"Bartolino, J.R., and Vincent, Sean, 2017, A groundwater-flow model for the Treasure Valley and surrounding area, southwestern Idaho: U.S. Geological Survey Fact Sheet 2017-3027, 4 p., https://doi.org/10.3133/fs20173027.","productDescription":"4 p.","ipdsId":"IP-080721","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":339801,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2017/3027/fs20173027.pdf","text":"Report","size":"4.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2017-3027"},{"id":339800,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2017/3027/coverthb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Treasure Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117,\n 43\n ],\n [\n -115.5,\n 43\n ],\n [\n -115.5,\n 44\n ],\n [\n -117,\n 44\n ],\n [\n -117,\n 43\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Idaho Water Science Center
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F.H. Newell Federal building
230 Collins Road
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http://id.water.usgs.gov
Digital flood-inundation maps were created for a 12.9‑mile reach of Johnson Creek by the U.S. Geological Survey (USGS). The flood-inundation maps depict estimates of water depth and areal extent of flooding from the mouth of Johnson Creek to just upstream of Southeast 174th Avenue in Portland, Oregon. Each flood-inundation map is based on a specific water level and associated streamflow at the USGS streamgage, Johnson Creek at Sycamore, Oregon (14211500), which is located near the upstream boundary of the maps. The maps produced by the USGS, and the forecasted flood hydrographs produced by National Weather Service River Forecast Center can be accessed through the USGS Flood Inundation Mapper Web site (http://wimcloud.usgs.gov/apps/FIM/FloodInundationMapper.html).
Water-surface elevations were computed for Johnson Creek using a combined one-dimensional and two‑dimensional unsteady hydraulic flow model. The model was calibrated using data collected from the flood of December 2015 (including the calculated streamflows at two USGS streamgages on Johnson Creek) and validated with data from the flood of January 2009. Results were typically within 0.6 foot (ft) of recorded or measured water-surface elevations from the December 2015 flood, and within 0.8 ft from the January 2009 flood. Output from the hydraulic model was used to create eight flood inundation maps ranging in stage from 9 to 16 ft. Boundary condition hydrographs were identical in shape to those from the December 2015 flood event, but were scaled up or down to produce the amount of streamflow corresponding to a specific water-surface elevation at the Sycamore streamgage (14211500). Sensitivity analyses using other hydrograph shapes, and a version of the model in which the peak flow is maintained for an extended period of time, showed minimal variation, except for overbank areas near the Foster Floodplain Natural Area.
Simulated water-surface profiles were combined with light detection and ranging (lidar) data collected in 2014 to delineate water-surface extents for each of the eight modeled stages. The availability of flood-inundation maps in conjunction with real-time data from the USGS streamgages along Johnson Creek and forecasted hydrographs from the National Weather Service Northwest River Forecast Center will provide residents of the watershed and emergency management personnel with valuable information that may aid in flood response, including potential evacuations, road closures, and mitigation efforts. In addition, these maps may be used for post-flood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175024","collaboration":"Prepared in cooperation with the City of Portland Bureau of Environmental Services","usgsCitation":"Stonewall, A.J., and Beal, B.A., 2017, Developing flood-Inundation maps for Johnson Creek, Portland, Oregon: U.S. Geological Survey Scientific Investigations Report 2017–5024, 26 p., https://doi.org/10.3133/sir20175024.","productDescription":"v, 26 p.","onlineOnly":"Y","ipdsId":"IP-080503","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":339976,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F75X273G","text":"USGS data release","description":"USGS data release","linkHelpText":"Flood inundation mapping data for Johnson Creek near Sycamore, Oregon"},{"id":339738,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5024/coverthb.jpg"},{"id":339739,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5024/sir20175024.pdf","text":"Report","size":"9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5024"}],"country":"United States","state":"Oregon","city":"Portland","otherGeospatial":"Johnson Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.655556,\n 45.506944\n ],\n [\n -122.472222,\n 45.506944\n ],\n [\n -122.472222,\n 45.408333\n ],\n [\n -122.655556,\n 45.408333\n ],\n [\n -122.655556,\n 45.506944\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
http://or.water.usgs.gov
The Little Plover River is a groundwater-fed stream in the sand plains region of central Wisconsin. In this region, sandy sediment deposited during or soon after the last glaciation forms an important unconfined sand and gravel aquifer. This aquifer supplies water for numerous high-capacity irrigation, municipal, and industrial wells that support a thriving agricultural industry. In recent years the addition of many new wells, combined with observed diminished flows in the Little Plover and other nearby rivers, has raised concerns about the impacts of the wells on groundwater levels and on water levels and flows in nearby lakes, streams, and wetlands. Diverse stakeholder groups, including well operators, Growers, environmentalists, local land owners, and regulatory and government officials have sought a better understanding of the local groundwater-surface water system and have a shared desire to balance the water needs of the he liagricultural, industrial, and urban users with the maintenance and protection of groundwater-dependent natural resources. To help address these issues, the Wisconsin Department of Natural Resources requested that the Wisconsin Geological and Natural History Survey and U.S. Geological Survey cooperatively develop a groundwater flow model that could be used to demonstrate the relationships among groundwater, surface water, and well withdrawals and also be a tool for testing and evaluating alternative water management strategies for the central sands region. Because of an abundance of previous studies, data availability, local interest, and existing regulatory constraints the model focuses on the Little Plover River watershed, but the modeling methodology developed during this study can apply to much of the larger central sands of Wisconsin. The
Little Plover River groundwater flow model simulates three-dimensional groundwater movement in and around the Little Plover River basin under steady-state and transient conditions. This model explicitly includes all high-capacity wells in the model domain and simulates seasonal variations in recharge and well pumping. The model represents the Little Plover River, and other significant streams and drainage ditches in the model domain, as fully connected to the groundwater system, computes stream base flow resulting from groundwater discharge, and routes the flow along the stream channel. A separate soil-water-balance (SWB) model was used to develop groundwater recharge arrays as input for the groundwater flow model. The SWB model uses topography, soils, land use, and climatic data to estimate recharge as deep drainage from the soil zone. The SWB model explicitly includes recharge originating as irrigation water, and computes irrigation using techniques similar to those used by local irrigation operators.
The groundwater flow model uses the U.S. Geological Survey’s MODFLOW modeling code which is freely available, widely accepted, and commonly used by the groundwater community. The groundwater flow model and the SWB model use identical high-resolution numerical grids having model cells 100 feet on a side, with physical properties assigned to each grid cell. This grid allows accurate geographic placement of wells, streams, and other model features. The 3-dimensional grid has three layers; layers 1 and 2 represent the sand and gravel aquifer and layer 3 represents the underlying sandstone. The distribution of material properties in the model (hydraulic conductivity, aquifer thickness, etc.) comes from previous published geologic studies of the region, updated by calibration to recent streamflow and groundwater level data. The SWB model operates on a daily time step. The groundwater flow model was calibrated to monthly stress periods with time steps ranging from 1 to 16 days. More detailed time discretization is possible.
The groundwater model was calibrated to water-level and streamflow data collected during 2013 and 2014 by adjusting model parameters (primarily hydraulic conductivity, storage, and recharge) until the model produced a conditionally optimal fit between field observations and model output, subject to consistency with previously published geologic studies. Calibration was performed under both steady and transient conditions, and used a sophisticated parameter-estimation procedure (PEST) for the calibration process and to identify important model parameters. For the Little Plover River, the two most important parameters are the global recharge multiplier and the hydraulic conductivity of the stream bed. The calibrated model produces water-level and mass-balance results that are consistent with field observations and previous studies of the area.
The completed model is a powerful tool for testing and demonstrating alternative water-management scenarios. Example model applications described in this report include simulating how the cumulative impacts of pumping and land-use change have affected average baseflow in the Little Plover River. Depletion-potential mapping represents a method for predicting which wells and well locations have the greatest impact on nearby surface-water resources.
The completed model is publicly available, along with a companion user’s guide to assist with its operation, at http://wgnhs.org/littleplover- river-groundwater-model.
","language":"English","publisher":"Wisconsin Geological and Natural History Survey","publisherLocation":"Madison, WI","usgsCitation":"Bradbury, K., Fienen, M., Kniffin, M., Jacob Krause, Westenbroek, S.M., Leaf, A.T., and Barlow, P.M., 2017, Groundwater flow model for the Little Plover River basin in Wisconsin’s Central Sands: Bulletin 111, Zip file: Report: x, 82 p., Appendixes 1-8.","productDescription":"Zip file: Report: x, 82 p., Appendixes 1-8","ipdsId":"IP-080836","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":339550,"type":{"id":15,"text":"Index Page"},"url":"https://wgnhs.org/little-plover-river-groundwater-model/"},{"id":339556,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wisconsin","otherGeospatial":"Little Plover River watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.74731445312499,\n 43.61221676817573\n ],\n [\n -89.5880126953125,\n 43.60823944964323\n ],\n [\n -89.37377929687499,\n 43.67979094030124\n ],\n [\n -89.307861328125,\n 43.72744458647464\n ],\n [\n -89.20349121093749,\n 43.79885402720351\n ],\n [\n -89.044189453125,\n 43.92559366355069\n ],\n [\n -88.97827148437499,\n 44.01652134387752\n ],\n [\n -88.956298828125,\n 44.13097085672744\n ],\n [\n -88.93432617187499,\n 44.24913396886892\n ],\n [\n -89.02770996093749,\n 44.69989765840318\n ],\n [\n -89.0167236328125,\n 44.84029065139799\n ],\n [\n -89.0936279296875,\n 45.04635929200553\n ],\n [\n -89.51110839843749,\n 45.04247805089152\n ],\n [\n -89.50561523437499,\n 44.86365630540608\n ],\n [\n -89.59350585937499,\n 44.55133484083592\n ],\n [\n -89.67315673828125,\n 44.4729911726025\n ],\n [\n -89.85992431640624,\n 44.34938634389527\n ],\n [\n -89.93408203124999,\n 44.17826452922573\n ],\n [\n -90.02471923828125,\n 44.081666311450526\n ],\n [\n -89.99450683593749,\n 43.92361542884112\n ],\n [\n -89.97528076171874,\n 43.84839376489152\n ],\n [\n -89.74731445312499,\n 43.61221676817573\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58edb944e4b0eed1ab8c6f05","contributors":{"authors":[{"text":"Bradbury, Ken","contributorId":190742,"corporation":false,"usgs":false,"family":"Bradbury","given":"Ken","email":"","affiliations":[],"preferred":false,"id":690592,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fienen, Michael N. 0000-0002-7756-4651 mnfienen@usgs.gov","orcid":"https://orcid.org/0000-0002-7756-4651","contributorId":177065,"corporation":false,"usgs":true,"family":"Fienen","given":"Michael N.","email":"mnfienen@usgs.gov","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":690591,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kniffin, Maribeth","contributorId":190743,"corporation":false,"usgs":false,"family":"Kniffin","given":"Maribeth","email":"","affiliations":[{"id":13562,"text":"University of Wisconsin, Madison","active":true,"usgs":false}],"preferred":false,"id":690593,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jacob Krause","contributorId":190744,"corporation":false,"usgs":false,"family":"Jacob Krause","affiliations":[],"preferred":false,"id":690594,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Westenbroek, Stephen M. 0000-0002-6284-8643 smwesten@usgs.gov","orcid":"https://orcid.org/0000-0002-6284-8643","contributorId":2210,"corporation":false,"usgs":true,"family":"Westenbroek","given":"Stephen","email":"smwesten@usgs.gov","middleInitial":"M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":690595,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Leaf, Andrew T. 0000-0001-8784-4924 aleaf@usgs.gov","orcid":"https://orcid.org/0000-0001-8784-4924","contributorId":5156,"corporation":false,"usgs":true,"family":"Leaf","given":"Andrew","email":"aleaf@usgs.gov","middleInitial":"T.","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":690596,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Barlow, Paul M. 0000-0003-4247-6456 pbarlow@usgs.gov","orcid":"https://orcid.org/0000-0003-4247-6456","contributorId":1200,"corporation":false,"usgs":true,"family":"Barlow","given":"Paul","email":"pbarlow@usgs.gov","middleInitial":"M.","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":true,"id":690597,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70182153,"text":"ds1033 - 2017 - Post-Hurricane Katrina coastal oblique aerial photographs collected from Panama City, Florida, to Lakeshore, Mississippi, and the Chandeleur Islands, Louisiana, August 31, 2005","interactions":[],"lastModifiedDate":"2017-04-03T16:43:37","indexId":"ds1033","displayToPublicDate":"2017-04-03T16:45:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1033","title":"Post-Hurricane Katrina coastal oblique aerial photographs collected from Panama City, Florida, to Lakeshore, Mississippi, and the Chandeleur Islands, Louisiana, August 31, 2005","docAbstract":"The U.S. Geological Survey (USGS), as part of the National Assessment of Storm-Induced Coastal Change Hazards project, conducts baseline and storm-response photography missions to document and understand the changes in vulnerability of the Nation's coasts to extreme storms. On August 31, 2005, the USGS conducted an oblique aerial photographic survey from Panama City, Florida, to Lakeshore, Mississippi, and the Chandeleur Islands, Louisiana, aboard a Piper Navajo Chieftain aircraft at an altitude of 500 feet and approximately 1,000 feet offshore. This mission was flown to collect post-Hurricane Katrina data, which can be used to assess incremental changes in the beach and nearshore area and can be used to assess future coastal change.
The photographs in this report are Joint Photographic Experts Group (JPEG) images. These photographs document the state of the barrier islands and other coastal features at the time of the survey.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1033","usgsCitation":"Morgan, K.L.M., and DeWitt, N.T., 2017, Post-Hurricane Katrina coastal oblique aerial photographs collected from Panama City, Florida, to Lakeshore, Mississippi, and the Chandeleur Islands, Louisiana, August 31, 2005: U.S. Geological Survey Data Series 1033, https://doi.org/10.3133/ds1033.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-079893","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":338244,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1033/coverthb.jpg"},{"id":338245,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1033/index.html","text":"Report HTML"}],"country":"United States","state":"Florida","city":"Panama City","otherGeospatial":"Pensacola Beach","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.20672607421875,\n 30.337324394179017\n ],\n [\n -87.19024658203124,\n 30.30176068632071\n ],\n [\n -86.87713623046875,\n 30.36102635890718\n ],\n [\n -86.59423828125,\n 30.372875188118016\n ],\n [\n -86.3140869140625,\n 30.351546261929034\n ],\n [\n -86.143798828125,\n 30.29701788337205\n ],\n [\n -85.94879150390625,\n 30.225848323247707\n ],\n [\n -85.7537841796875,\n 30.107117887092357\n ],\n [\n -85.6988525390625,\n 30.1380015549519\n ],\n [\n -85.98724365234375,\n 30.28990324883237\n ],\n [\n -86.2591552734375,\n 30.372875188118016\n ],\n [\n -86.46514892578124,\n 30.401306519203583\n ],\n [\n -86.77276611328125,\n 30.413150465068853\n ],\n [\n -86.96502685546875,\n 30.391830328088137\n ],\n [\n -87.20672607421875,\n 30.337324394179017\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
https://coastal.er.usgs.gov/
The U.S. Geological Survey (USGS), in cooperation with the Colorado River Basin Salinity Control Forum, studied trends in dissolved-solids loads at selected sites in and near the Uinta Basin, Utah. The Uinta Basin study area includes the Duchesne River Basin and the Middle Green River Basin in Utah from below Flaming Gorge Reservoir to the town of Green River.
Annual dissolved-solids loads for water years (WY) 1989 through 2013 were estimated for 16 gaging stations in the study area using streamflow and water-quality data from the USGS National Water Information System database. Eight gaging stations that monitored catchments with limited or no agricultural land use (natural subbasins) were used to assess loads from natural sources. Four gaging stations that monitored catchments with agricultural land in the Duchesne River Basin were used to assess loads from agricultural sources. Four other gaging stations were included in the dissolved-solids load and trend analysis to help assess the effects of agricultural areas that drain to the Green River in the Uinta Basin, but outside of the Duchesne River Basin.
Estimated mean annual dissolved-solids loads for WY 1989–2013 ranged from 1,520 tons at Lake Fork River above Moon Lake, near Mountain Home, Utah (UT), to 1,760,000 tons at Green River near Green River, UT. The flow-normalized loads at gaging stations upstream of agricultural activities showed no trend or a relatively small change. The largest net change in modeled flow-normalized load was -352,000 tons (a 17.8-percent decrease) at Green River near Green River, UT.
Annual streamflow and modeled dissolved-solids loads at the gaging stations were balanced between upstream and downstream sites to determine how much water and dissolved solids were transported to the Duchesne River and a section of the Green River, and how much was picked up in each drainage area. Mass-balance calculations of WY 1989–2013 mean annual dissolved-solids loads at the studied sites show that Green River near Jensen, UT, accounts for 64 percent of the load in the river at Green River, UT, while the Duchesne River and White River contribute 10 and 13 percent, respectively.
Annual streamflow and modeled dissolved-solids loads at the gaging stations were balanced between upstream and downstream sites to determine how much water and dissolved solids were transported to the Duchesne River and a section of the Green River, and how much was picked up in each drainage area. Mass-balance calculations of WY 1989–2013 mean annual dissolved-solids loads at the studied sites show that Green River near Jensen, UT, accounts for 64 percent of the load in the river at Green River, UT, while the Duchesne River and White River contribute 10 and 13 percent, respectively.
The flow-normalized dissolved-solids loads estimated at Duchesne River near Randlett, UT, and White River near Watson, UT, decreased by 68,000 and 55,300 tons, or 27.8 and 20.8 percent respectively, when comparing 1989 to 2013. The drainage basins for both rivers have undergone salinity-control projects since the early 1980s to reduce the dissolved-solids load entering the Colorado River. Approximately 19 percent of the net change in flow-normalized load at Green River at Green River, UT, is from changes in load modeled at Duchesne River near Randlett, UT, and 16 percent from changes in load modeled at White River near Watson, UT. The net change in flow-normalized load estimated at Green River near Greendale, UT, for WY 1989–2013 accounts for about 45 percent of the net change estimated at Green River at Green River, UT.
Mass-balance calculations of WY 1989–2013 mean annual dissolved-solids loads at the studied sites in the Duchesne River Basin show that 75,400 tons or 44 percent of the load at the Duchesne River near Randlett, UT, gaging station was not accounted for at any of the upstream gages. Most of this unmonitored load is derived from tributary inflow, groundwater discharge, unconsumed irrigation water, and irrigation tail water.
A mass balance of WY 1989–2013 flow-normalized loads estimated at sites in the Duchesne River Basin indicates that the flow-normalized load of unmonitored inflow to the Duchesne River between the Myton and Randlett gaging stations decreased by 38 percent. The total net decrease in flow-normalized load calculated for unmonitored inflow in the drainage basin accounts for 94 percent of the decrease in WY 1989–2013 flow-normalized load modeled at the Duchesne River near Randlett, UT, gaging station. Irrigation improvements in the drainage basin have likely contributed to the decrease in flow-normalized load.
Reductions in dissolved-solids load estimated by the Natural Resources Conservation Service (NRCS) and the Bureau of Reclamation (Reclamation) from on- and off-farm improvements in the Uinta Basin totaled about 135,000 tons in 2013 (81,900 tons from on-farm improvements and 53,300 tons from off-farm improvements). The reduction in dissolved-solids load resulting from on- and off-farm improvements facilitated by the NRCS and Reclamation in the Price River Basin from 1989 to 2013 was estimated to be 64,800 tons.
The amount of sprinkler-irrigated land mapped in the drainage area or subbasin area for a gaging station was used to estimate the reduction in load resulting from the conversion from flood to sprinkler irrigation. Sprinkler-irrigated land mapped in the Uinta Basin totaled 109,630 acres in 2012. Assuming conversion to wheel-line sprinklers, a reduction in dissolved-solids load in the Uinta Basin of 95,800 tons in 2012 was calculated using the sprinkler-irrigation acreage and a pre-salinity-control project dissolved-solids yield of 1.04 tons per acre.
A reduction of 72,800 tons in dissolved-solids load from irrigation improvements was determined from sprinkler-irrigated lands in the Ashley Valley and Jensen, Pelican Lake, and Pleasant Valley areas (mapped in 2012); and in the Price River Basin (mapped in 2011). This decrease in dissolved-solids load is 8,800 tons more than the decrease in unmonitored flow-normalized dissolved-solids load (-64,000 tons) determined for the Green River between the Jensen and Green River gaging stations.
The net WY 1989–2013 change in flow-normalized dissolved-solids load at the Duchesne River near Randlett, UT, and the Green River between the Jensen and Green River, UT, gaging stations determined from mass-balance calculations was compared to reported reductions in dissolved-solids load from on- and off-farm improvements and estimated reductions in load determined from mapped sprinkler-irrigated areas in the Duchesne River Basin and the area draining to the Green River between the Jensen and Green River gaging stations. The combined NRCS and Reclamation estimates of reduction in dissolved-solids load from on- and off-farm improvements in the study area (200,000 tons) is more than the reduction in load estimated using the acreage with sprinkler improvements (136,000 tons) or the mass-balance of flow-normalized load (132,000 tons).
Director, Utah Water Science Center
U.S. Geological Survey
2329 West Orton Circle
Salt Lake City, UT 84119-2047
(801) 908-5000
http://ut.water.usgs.gov/
Trait-based approaches to vegetation analyses are becoming more prevalent in studies of riparian vegetation dynamics, including responses to flow regulation, groundwater pumping, and climate change. These analyses require species trait data compiled from the literature and floras or original field measurements. Gathering such data makes trait-based research time intensive at best and impracticable in some cases. To support trait-based analysis of vegetation along the Colorado River through Grand Canyon, a data set of 20 biological traits and ecological affinities for 179 species occurring in that study area was compiled. This diverse flora shares species with many riparian areas in the western USA and includes species that occur across a wide moisture gradient. Data were compiled from published scientific papers, unpublished reports, plant fact sheets, existing trait databases, regional floras, and plant guides. Data for ordinal environmental tolerances were more readily available than were quantitative traits. More publicly available data are needed for traits of both common and rare southwestern U.S. plant species to facilitate comprehensive, trait-based research. The trait data set is free to use and can be downloaded from ScienceBase: https://www.sciencebase.gov/catalog/item/58af41dee4b01ccd54f9f2ff and https://dx.doi.org/10.5066/F7QV3JN1
","language":"English","publisher":"Monte L. Bean Life Science Museum, Brigham Young University","doi":"10.3398/064.077.0104","usgsCitation":"Palmquist, E.C., Ralston, B.E., Daniel, S., Merritt, D., Shafroth, P.B., and Scott, J., 2017, Functional traits and ecological affinities of riparian plants along the Colorado River in Grand Canyon: Western North American Naturalist, v. 77, no. 1, p. 22-30, https://doi.org/10.3398/064.077.0104.","productDescription":"9 p.","startPage":"22","endPage":"30","ipdsId":"IP-070768","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":488970,"rank":1,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://scholarsarchive.byu.edu/wnan/vol77/iss1/3","text":"External Repository"},{"id":438415,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7QV3JN1","text":"USGS data release","linkHelpText":"Southwestern Riparian Plant Trait Matrix, Colorado River, Grand Canyon, 2014 - 2016Data"},{"id":337615,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Colorado River, Grand Canyon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.0545654296875,\n 35.576916524038616\n ],\n [\n -111.2200927734375,\n 35.576916524038616\n ],\n [\n -111.2200927734375,\n 37.00693943418586\n ],\n [\n -114.0545654296875,\n 37.00693943418586\n ],\n [\n -114.0545654296875,\n 35.576916524038616\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"77","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58ca52c7e4b0849ce97c8680","contributors":{"authors":[{"text":"Palmquist, Emily C. 0000-0003-1069-2154 epalmquist@usgs.gov","orcid":"https://orcid.org/0000-0003-1069-2154","contributorId":5669,"corporation":false,"usgs":true,"family":"Palmquist","given":"Emily","email":"epalmquist@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":684464,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ralston, Barbara E. 0000-0001-9991-8994 bralston@usgs.gov","orcid":"https://orcid.org/0000-0001-9991-8994","contributorId":606,"corporation":false,"usgs":true,"family":"Ralston","given":"Barbara","email":"bralston@usgs.gov","middleInitial":"E.","affiliations":[{"id":501,"text":"Office of Science Quality and Integrity","active":true,"usgs":true}],"preferred":false,"id":684465,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Daniel, Sarr.","contributorId":189307,"corporation":false,"usgs":false,"family":"Daniel","given":"Sarr.","email":"","affiliations":[],"preferred":false,"id":684466,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Merritt, David","contributorId":189308,"corporation":false,"usgs":false,"family":"Merritt","given":"David","affiliations":[],"preferred":false,"id":684467,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shafroth, Patrick B","contributorId":189309,"corporation":false,"usgs":false,"family":"Shafroth","given":"Patrick","email":"","middleInitial":"B","affiliations":[],"preferred":false,"id":684468,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Scott, Julian","contributorId":61764,"corporation":false,"usgs":false,"family":"Scott","given":"Julian","affiliations":[{"id":12742,"text":"University of Nevada Reno","active":true,"usgs":false}],"preferred":false,"id":684469,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70179144,"text":"sir20165142 - 2017 - The effects of forest cover on base flow of streams in the mountainous interior of Puerto Rico, 2010","interactions":[],"lastModifiedDate":"2017-03-14T09:22:51","indexId":"sir20165142","displayToPublicDate":"2017-03-07T15:45:00","publicationYear":"2017","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":"2016-5142","title":"The effects of forest cover on base flow of streams in the mountainous interior of Puerto Rico, 2010","docAbstract":"The U.S. Geological Survey, in cooperation with the Puerto Rico Department of Natural and Environmental Resources, completed a study to determine whether a relation exists between the extent of forest cover and the magnitude of base flow at two sets of paired drainage basins in the highlands of the municipalities of Adjuntas and Utuado within the mountainous interior of Puerto Rico. One set of paired basins includes the Río Guaónica and Río Tanamá, both tributaries of the Río Grande de Arecibo. The other set includes two smaller basins in the drainage basin of the Río Coabey, which is a tributary of the Río Tanamá. The paired basins in each set have similar rainfall patterns, geologic substrate, and aspect; the principal difference identified in the study is the extent of forest cover and related land uses such as the cultivation of shade and sun coffee. Data describing the hydrology, hydrogeology, and streamflow were used in the analysis. The principal objective of the study was to compare base flow per unit area among basins having different areal extents of forest cover and land uses such as shade coffee and sun coffee cultivation.
Within the mountainous interior of Puerto Rico, a substantial amount of the annual rainfall (45 to 39 percent in the Rio Guaónica and Rio Tanamá, respectively) can migrate to the subsurface and later emerge as base flow in streams. The magnitude of base flow within the two sets of paired basins varies seasonally. Minimum base flows occur during the annual dry season (generally from January to March), and maximum base flows occur during the wet season (generally from August to October). During the dry season or periods of below-normal rainfall, base flow is either the primary or the sole component of streamflow. Daily mean base flow ranged from 3.2 to 20.5 cubic feet per second (ft3 /s) at the Rio Guaónica Basin, and from 4.2 to 23.0 ft3 /s at the Rio Tanamá Basin. The daily mean base flows during 2010 ranged from 0.28 to 0.98 ft3 /s at Tributary 1 and from 0.22 to 0.58 ft3 /s at Tributary 2 of the Rio Coabey. The normalized daily base flow at the Río Guaónica and Río Tanamá Basin during 2010 ranged from 1.3 to 8.1 cubic feet per second per square mile (ft3 /s)/mi2 and from 1.1 to 6.1 (ft3 /s)/mi2 , respectively. The normalized daily base flow for the basins of Tributary 1 and Tributary 2 of Río Coabey during 2010 ranged from 1.0 to 3.6 (ft3 /s)/mi2 and from 1.5 to 3.9 (ft3 /s)/mi2 , respectively.
The normalized mean annual base flow is similar within the larger paired basins of Río Tanamá (2.74 [ft3 /s]/mi2 ) and Río Guaónica (3.15 [ft3 /s]/mi2 ). The mean annual base flow per unit area for both of these basins is about 79 percent of the mean annual streamflow. In the large paired basins, the proportion of Type I land use (forest patches, shade and mixed shade/sun coffee with associated cash crops) is substantially higher in Rio Guaónica Basin (81 percent) than in the Rio Tanamá Basin (59 percent), and the base flow per unit area is also higher. In the small paired basins of Rio Coabey, the proportion of Type I land use is much higher at Tributary 1 (52 percent) than at Tributary 2 (15 percent), but, in contrast to the large basins, the mean annual base flow per unit area is lower (2.22 and 2.62 [ft3 /s]/mi2 , respectively). There is no consistent relation between land use and normalized base flow between the two sets of paired basins in the study.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165142","collaboration":"Prepared in cooperation with the Puerto Rico Department of Natural and Environmental Resources","usgsCitation":"Rodríguez-Martínez, Jesús, and Santiago, Marilyn, 2017, The effects of forest cover on base flow of streams in the mountainous interior of Puerto Rico, 2010: U.S. Geological Survey Scientific Investigations Report 2016–5142, 19 p., https://doi.org/10.3133/sir20165142.","productDescription":"Report: vii, 19 p.; Data Release","numberOfPages":"32","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-061550","costCenters":[{"id":156,"text":"Caribbean Water Science Center","active":true,"usgs":true}],"links":[{"id":438424,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7N58JG5","text":"USGS data release","linkHelpText":"Hydrologic data for the effects of forest cover on base flow of streams in the mountainous interior of Puerto Rico"},{"id":336264,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7N58JG5","text":"USGS data release ","description":"USGS data release","linkHelpText":"Hydrologic data for the effects of forest cover on base flow of streams in the mountainous interior of Puerto Rico"},{"id":336240,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5142/coverthb.jpg"},{"id":336241,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5142/sir20165142.pdf","text":"Report","size":"15.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5142"}],"otherGeospatial":"Puerto Rico","contact":"Director, Caribbean-Florida Water Science Center
4446 Pet Lane
Suite 108
Lutz, FL 33559
https://pr.water.usgs.gov
Understanding nitrate dynamics in groundwater systems as a function of climatic conditions, especially during contrasting patterns of drought and wet cycles, is limited by a lack of temporal and spatial data. Nitrate sensors have the capability for making accurate, high-frequency measurements of nitrate in situ, but have not yet been evaluated for long-term use in groundwater wells. We measured in situ nitrate continuously in two groundwater monitoring wells —one rural and one urban—located in the recharge zone of a productive karst aquifer in central Texas in order to resolve changes that occur over both short-term (hourly to daily) and long-term (monthly to yearly) periods. Nitrate concentrations, measured as nitrate-nitrogen in milligrams per liter (mg/L), during drought conditions showed little or no temporal change as groundwater levels declined. During aquifer recharge, extremely rapid changes in concentration occurred at both wells as documented by hourly data. At both sites, nitrate concentrations were affected by recharging surface water as evidenced by nitrate concentrations in groundwater recharge (0.8–1.3 mg/L) that were similar to previously reported values for regional recharging streams. Groundwater nitrate concentrations responded differently at urban and rural sites during groundwater recharge. Concentrations at the rural well (approximately 1.0 mg/L) increased as a result of higher nitrate concentrations in groundwater recharge relative to ambient nitrate concentrations in groundwater, whereas concentrations at the urban well (approximately 2.7 mg/L) decreased as a result of the dilution of higher ambient nitrate concentrations relative to those in groundwater recharge. Notably, nitrate concentrations decreased to as low as 0.8 mg/L at the urban site during recharge but postrecharge concentrations exceeded 3.0 mg/L. A return to higher nitrate concentrations postrecharge indicates mobilization of a localized source of elevated nitrate within the urbanized area of the aquifer. Changes in specific conductance were observed at both sites during groundwater recharge, and a significant correlation between specific conductance and nitrate (correlation coefficient [R] = 0.455) was evident at the urban site where large (3-fold) changes in nitrate occurred. Nitrate concentrations and specific conductance measured during a depth profile indicated that the water column was generally homogeneous as expected for this karst environment, but changes were observed in the most productive zone of the aquifer that might indicate some heterogeneity within the complex network of flow paths. Resolving the timing and magnitude of changes and characterizing fine-scale vertical differences would not be possible using conventional sampling techniques. The patterns observed in situ provided new insight into the dynamic nature of nitrate in a karst groundwater system.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2016.12.038","usgsCitation":"Opsahl, S.P., Musgrove, M., and Slattery, R.N., 2017, New insights into nitrate dynamics in a karst groundwater system gained from in situ high-frequency optical sensor measurements: Journal of Hydrology, v. 546, p. 179-188, https://doi.org/10.1016/j.jhydrol.2016.12.038.","productDescription":"10 p.","startPage":"179","endPage":"188","ipdsId":"IP-067710","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":347247,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","otherGeospatial":"Edwards Aquifer","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -100.469970703125,\n 29.11857441491087\n ],\n [\n -97.55584716796875,\n 29.11857441491087\n ],\n [\n -97.55584716796875,\n 30.458144351018078\n ],\n [\n -100.469970703125,\n 30.458144351018078\n ],\n [\n -100.469970703125,\n 29.11857441491087\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"546","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59f05123e4b0220bbd9a1d9f","contributors":{"authors":[{"text":"Opsahl, Stephen P. 0000-0002-4774-0415 sopsahl@usgs.gov","orcid":"https://orcid.org/0000-0002-4774-0415","contributorId":4713,"corporation":false,"usgs":true,"family":"Opsahl","given":"Stephen","email":"sopsahl@usgs.gov","middleInitial":"P.","affiliations":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":713011,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Musgrove, MaryLynn 0000-0003-1607-3864 mmusgrov@usgs.gov","orcid":"https://orcid.org/0000-0003-1607-3864","contributorId":197013,"corporation":false,"usgs":true,"family":"Musgrove","given":"MaryLynn","email":"mmusgrov@usgs.gov","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"preferred":false,"id":713012,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Slattery, Richard N. 0000-0002-9141-9776 rnslatte@usgs.gov","orcid":"https://orcid.org/0000-0002-9141-9776","contributorId":2471,"corporation":false,"usgs":true,"family":"Slattery","given":"Richard","email":"rnslatte@usgs.gov","middleInitial":"N.","affiliations":[{"id":48595,"text":"Oklahoma-Texas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":713013,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70179834,"text":"ds1029 - 2017 - Winter 2016, Part A—Coastal oblique aerial photographs collected from the South Carolina/North Carolina border to Assateague Island, Virginia, February 18–19, 2016","interactions":[],"lastModifiedDate":"2017-03-28T10:44:02","indexId":"ds1029","displayToPublicDate":"2017-02-28T14:15:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1029","title":"Winter 2016, Part A—Coastal oblique aerial photographs collected from the South Carolina/North Carolina border to Assateague Island, Virginia, February 18–19, 2016","docAbstract":"The U.S. Geological Survey (USGS), as part of the National Assessment of Coastal Change Hazards project, conducts baseline and storm-response photography missions to document and understand the changes in the vulnerability of the Nation's coasts to extreme storms. On February 18–19, 2016, the USGS conducted an oblique aerial photographic survey from the South Carolina/North Carolina border to Assateague Island, Virginia, aboard a Cessna 182 (aircraft) at an altitude of 500 feet (ft) and approximately 1,200 ft offshore. This mission was flown to collect baseline data for assessing incremental changes in the beach and nearshore area and can be used to assess future coastal change.
The photographs in this report document the state of the barrier islands and other coastal features at the time of the survey.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1029","usgsCitation":"Morgan, K.L.M., 2017, Winter 2016, part A—Coastal oblique aerial photographs collected from the South Carolina/North Carolina border to Assateague Island, Virginia, February 18–19, 2016: U.S. Geological Survey Data Series 1029, https://doi.org/10.3133/ds1029.\n\n","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-076239","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":334924,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/publication/ds1030","text":"Data Series 1030 - ","description":"DS 1030 HTML","linkHelpText":"Winter 2016, Part B—Coastal Oblique Aerial Photographs Collected from Assateague Island, Virginia, to Montauk Point, New York, March 8–9, 2016"},{"id":334923,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1029/index.html","text":"Report HTML","linkFileType":{"id":5,"text":"html"},"description":"DS 1029 HTML"},{"id":334922,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1029/coverthb1.jpg"}],"country":"United States","state":"North Carolina, Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78.695068359375,\n 33.916013113401696\n ],\n [\n -78.5247802734375,\n 33.81110228864701\n ],\n [\n -78.34899902343749,\n 33.83848275599514\n ],\n [\n -78.15673828125,\n 33.83848275599514\n ],\n [\n -78.0084228515625,\n 33.792843773631844\n ],\n [\n -77.8985595703125,\n 33.78827853625996\n ],\n [\n -77.8765869140625,\n 33.884097379274905\n ],\n [\n -77.8106689453125,\n 34.07086232376631\n ],\n [\n -77.6458740234375,\n 34.266296360583546\n ],\n [\n -77.508544921875,\n 34.4069096565206\n ],\n [\n -77.27783203125,\n 34.48392002731987\n ],\n [\n -77.0745849609375,\n 34.56990638085636\n ],\n [\n -76.761474609375,\n 34.619647359797185\n ],\n [\n -76.5966796875,\n 34.58347505599177\n ],\n [\n -76.5087890625,\n 34.5020297944346\n ],\n [\n -76.475830078125,\n 34.58799745550482\n ],\n [\n -76.3604736328125,\n 34.710009159224946\n ],\n [\n -76.2396240234375,\n 34.827332061981586\n ],\n [\n -76.04736328125,\n 34.94448806230625\n ],\n [\n -75.8880615234375,\n 35.007502842952896\n ],\n [\n -75.552978515625,\n 35.146862906756304\n ],\n [\n -75.333251953125,\n 35.22318504970181\n ],\n [\n -75.2838134765625,\n 35.652832827451654\n ],\n [\n -75.41015624999999,\n 35.91129848822746\n ],\n [\n -75.5804443359375,\n 36.28413532741724\n ],\n [\n -75.7672119140625,\n 36.52288052805137\n ],\n [\n -75.82763671875,\n 36.6992553955527\n ],\n [\n -75.83862304687499,\n 36.87962060502676\n ],\n [\n -75.816650390625,\n 37.02448395075965\n ],\n [\n -75.706787109375,\n 37.304644804751106\n ],\n [\n -75.4705810546875,\n 37.64903402157866\n ],\n [\n -75.44860839843749,\n 37.74900069437069\n ],\n [\n -75.3277587890625,\n 37.83148014503288\n ],\n [\n -75.2178955078125,\n 38.013476231041935\n ],\n [\n -75.4046630859375,\n 38.017803980061124\n ],\n [\n -75.849609375,\n 37.94419750075404\n ],\n [\n -76.17919921875,\n 37.37015718405753\n ],\n [\n -76.168212890625,\n 37.046408899699564\n ],\n [\n -76.0308837890625,\n 36.575835338491764\n ],\n [\n -75.9649658203125,\n 36.23984280222428\n ],\n [\n -75.7012939453125,\n 35.84008157153468\n ],\n [\n -75.69580078125,\n 35.51881428123057\n ],\n [\n -75.98693847656249,\n 35.191766965947394\n ],\n [\n -76.3604736328125,\n 34.96699890670367\n ],\n [\n -76.5802001953125,\n 34.827332061981586\n ],\n [\n -76.8109130859375,\n 34.89043681762452\n ],\n [\n -77.0086669921875,\n 34.863397850419524\n ],\n [\n -77.3602294921875,\n 34.69194468425019\n ],\n [\n -77.6348876953125,\n 34.52466147177172\n ],\n [\n -77.816162109375,\n 34.29353023058858\n ],\n [\n -77.98095703125,\n 34.125447565116126\n ],\n [\n -78.145751953125,\n 34.066311964721045\n ],\n [\n -78.3544921875,\n 34.03900467904445\n ],\n [\n -78.6016845703125,\n 34.020794936018724\n ],\n [\n -78.73901367187499,\n 33.99802726234877\n ],\n [\n -78.695068359375,\n 33.916013113401696\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
(727) 502–8000
https://coastal.er.usgs.gov/
In a study conducted by the U.S. Geological Survey in cooperation with the New Jersey Department of Environmental Protection and the Delaware River Basin Commission, trend tests were conducted on selected water-quality characteristics measured at stations on streams in New Jersey during selected periods over water years 1971‒2011. Tests were conducted on 3 nutrients (total nitrogen, filtered nitrate plus nitrite, and total phosphorus) at 28 water-quality stations. At 4 of these stations, tests were also conducted on 3 measures of major ions (specific conductance, filtered chloride, and total dissolved solids).
Two methods were used to identify trends—Weighted Regressions on Time, Discharge, and Season (WRTDS) models and seasonal rank-sum tests. For this report, the use of WRTDS models included the use of the WRTDS Bootstrap Test (WBT). WRTDS models identified trends in flow-normalized annual concentrations and flow-normalized annual fluxes over water years 1980‒2011 and 2000‒11 for each nutrient, filtered chloride, and total dissolved solids. WRTDS models were developed for each nutrient at the 20 or 21 stations at which streamflow was measured or estimated. Trends in nutrient concentration were reported for these stations; trends in nutrient fluxes were reported only for 15–17 of these stations.
The results of WRTDS models for water years 1980‒2011 identified more stations with downward trends in concentrations of either total nitrogen or total phosphorus than upward trends. For total nitrogen, there were downward trends at 9 stations and an upward trend at 1 station. For total phosphorus, there were downward trends at 8 stations and an upward trend at 1 station. For filtered nitrate plus nitrite, there were downward trends at 6 stations and upward trends at 6 stations. The result of the trend test in flux for a selected nutrient at a selected station (downward trend, no trend, or upward trend) usually matched the trend result in concentration.
Seasonal rank-sum tests, the second method used, identified step trends in water-quality measured in different decades—1970s, 1980s, 1990s, and 2000s. Tests were conducted on all nutrients at 28 stations and on all measures of major ions at the 4 selected stations. Results of seasonal rank-sum tests between the 1980s and the 2000s identified more stations with downward trends in concentrations of total nitrogen (14) than stations with upward trends (2) and more stations with downward trends in concentrations of total phosphorus (18) than stations with upward trends (1).
A combined dataset of trend results for concentrations over water years 1980‒2011 was created from the results of the two tests for the period. Results of WRTDS models were included in this combined dataset, if available. Otherwise, the results of the seasonal rank-sum tests between water-quality characteristics measured in the 1980s and 2000s were included.
Trend results over water years 1980‒2011 in the combined dataset show that few of the 28 stations had upward trends in concentrations of either total nitrogen or total phosphorus. There were only 2 stations with upward trends in total nitrogen concentration and 1 station with an upward trend in total phosphorus concentration. Results for filtered nitrate plus nitrite show about the same number of stations with upward trends (9) as stations with downward trends (7). Results for all measures of major ions show upward trends at the four stations tested.
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Jersey\",\"nation\":\"USA \"}}]}","contact":"Director New Jersey Water Science Center
U.S. Geological Survey
3450 Princeton Pike, Suite 110
Lawrenceville, NJ 08648
http://nj.usgs.gov/
The U.S. Geological Survey (USGS), in cooperation with Gwinnett County Department of Water Resources, established a Long-Term Trend Monitoring (LTTM) program in 1996. The LTTM program is a comprehensive, long-term, water-quantity and water-quality monitoring program designed to document and analyze the hydrologic and water-quality conditions of selected watersheds in Gwinnett County, Georgia. Water-quality monitoring initially began in six watersheds and currently [2016] includes 13 watersheds.
As part of the LTTM program, streamflow, precipitation, water temperature, specific conductance, and turbidity were measured every 15 minutes for water years 2001–15 at 12 of the 13 watershed monitoring stations and for water years 2010–15 at the other watershed. In addition, discrete water-quality samples were collected seasonally from May through October (summer) and November through April (winter), including one base-flow and three stormflow event composite samples, during the study period. Samples were analyzed for nutrients (nitrogen and phosphorus), total organic carbon, trace elements (total lead and total zinc), total dissolved solids, and total suspended sediment (total suspended solids and suspended-sediment concentrations). The sampling scheme was designed to identify variations in water quality both hydrologically and seasonally.
The 13 watersheds were characterized for basin slope, population density, land use for 2012, and the percentage of impervious area from 2000 to 2014. Several droughts occurred during the study period—water years 2002, 2007–08, and 2011–12. Watersheds with the highest percentage of impervious areas had the highest runoff ratios, which is the portion of precipitation that occurs as runoff. Watershed base-flow indexes, the ratio of base-flow runoff to total runoff, were inversely correlated with watershed impervious area.
Flood-frequency estimates were computed for 13 streamgages in the study area that have 10 or more years of annual peak flow data through water year 2015, using the expected moments algorithm to fit a Pearson Type III distribution to logarithms of annual peak flows. Kendall’s tau nonparametric test was used to determine the statistical significance of trends in the annual peak flows, with none of the 13 streamgages exhibiting significant trends.
A comparison of base-flow and stormflow water-quality samples indicates that turbidity and concentrations of total ammonia plus organic nitrogen, total nitrogen, total phosphorus, total organic carbon, total lead, total zinc, total suspended solids, and suspended-sediment concentrations increased with increasing discharge at all watersheds. Specific conductance decreased during stormflow at all watersheds, and total dissolved solids concentrations decreased during stormflow at a few of the watersheds. Total suspended solids and suspended-sediment concentrations typically were two orders of magnitude higher in stormflow samples, turbidities were about 1.5 orders of magnitude higher, total phosphorus and total zinc were about one order of magnitude higher, and total ammonia plus organic nitrogen, total nitrogen, total organic carbon, and total lead were about twofold higher than in base-flow samples.
Seasonality and long-term trends were identified for the period water years 2001–15 for 10 constituents—total nitrogen, total nitrate plus nitrite, total phosphorus, dissolved phosphorus, total organic carbon, total suspended solids, suspended-sediment concentration, total lead, total zinc, and total dissolved solids. Seasonal patterns were present in most watersheds for all constituents except total dissolved solids, and the watersheds had fairly similar patterns of higher concentrations in the summer and lower concentrations in the winter. A linear long-term trend analysis of residual concentrations from the flow-only load estimation model (without time-trend terms) identified significant trends in 67 of the 130 constituent-watershed combinations. Seventy percent of the significant trends were negative. Total organic carbon and total dissolved solids had predominantly positive trends. Total phosphorus, total suspended solids, suspended-sediment concentration, total lead, and total zinc had only negative trends. The other three constituents exhibited fewer trends, both positive and negative.
Streamwater loads were estimated annually for the 13-year period water years 2003–15 for the same 10 constituents in the trend analysis. Loads were estimated using a regression-model-based approach developed by the USGS for the Gwinnett County LTTM program that accommodates the use of storm-event composited samples. Concentrations were modeled as a function of discharge, base flow, time, season, and turbidity to improve model predictions and reduce errors in load estimates. Total suspended solids annual loads have been identified in Gwinnett County’s Watershed Protection Plan for target performance criterion.
Although the amount of annual runoff was the primary factor in variations in annual loads, climatic conditions (classified as dry, average, or wet) affected annual loads beyond what was attributed to climatic-related variations in annual runoff. Significant negative trends in loads were estimated for the combined area of the watersheds for all constituents except dissolved phosphorus, total organic carbon, and total dissolved solids. The trend analysis indicated that total suspended solids and suspended-sediment concentration loads in the study area were decreasing by 57,000 and 87,000 pounds per day per year, respectively.
Variations in constituent yields between watersheds appeared to be related to various watershed characteristics. Suspended sediment (as either total suspended solids or suspended-sediment concentrations), along with constituents transported predominately in solid phase (total phosphorus, total organic carbon, total lead, and total zinc), and total dissolved solids typically had higher yields from watersheds that had high percentages of impervious areas or high basin slope. High total nitrogen yields were also associated with watersheds with high percentages of impervious areas. Low total nitrogen, total suspended solids, total lead, and total zinc yields appeared to be associated with watersheds that had a low percentage of high-density development.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175012","collaboration":"Prepared in cooperation with the Gwinnett County Department of Water Resources","usgsCitation":"Aulenbach, B.T., Joiner, J.K., and Painter, J.A., 2017, Hydrology and water quality in 13 watersheds in Gwinnett County, Georgia, 2001–15: U.S. Geological Survey Scientific Investigations Report 2017– 5012, 82 p., https://doi.org/10.3133/sir20175012. 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South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Stephenson Center, Suite 129
Columbia, SC 29210
Or visit the South Atlantic Water Science Center website at
http://www.usgs.gov/water/southatlantic/
The U.S. Geological Survey (USGS), in cooperation with the Texas Water Development Board and the Galveston Bay Estuary Program, collected streamflow and water-quality data at USGS streamflow-gaging stations in the lower Trinity River watershed from May 2014 to December 2015 to characterize and improve the current understanding of the quantity and quality of freshwater inflow entering Galveston Bay from the Trinity River. Continuous streamflow records at four USGS streamflow-gaging stations were compared to quantify differences in streamflow magnitude between upstream and downstream reaches of the lower Trinity River. Water-quality conditions were characterized from discrete nutrient and sediment samples collected over a range of hydrologic conditions at USGS streamflow-gaging station 08067252 Trinity River at Wallisville, Tex. (hereinafter referred to as the “Wallisville site”), approximately 4 river miles upstream from where the Trinity River enters Galveston Bay.
Based on streamflow records, annual mean outflow from Livingston Dam into the lower Trinity River was 2,240 cubic feet per second (ft3/s) in 2014 and 22,400 ft3/s in 2015, the second lowest and the highest, respectively, during the entire period of record (1966–2015). During this study, only about 54 percent of the total volume measured at upstream sites was accounted for at the Wallisville site as the Trinity River enters Galveston Bay. This difference in water volumes between upstream sites and the Wallisville site indicates that at high flows a large part of the volume released from Lake Livingston does not reach Galveston Bay through the main channel of the Trinity River. These findings indicate that water likely flows into wetlands and water bodies surrounding the main channel of the Trinity River before reaching the Wallisville site and is being stored or discharged through other channels that flow directly into Galveston Bay.
To characterize suspended-sediment concentrations and loads in Trinity River inflow to Galveston Bay, a regression model was developed to estimate suspended-sediment concentrations by using acoustic backscatter data as a surrogate. The model yielded an adjusted coefficient of determination value of 0.92 and a root mean square error of 1.65 milligrams per liter (mg/L). The mean absolute percentage error between measured and estimated suspended-sediment concentration was 35 percent. During this study, estimated suspended-sediment concentrations ranged from 2 to 701 mg/L, with a mean of 97 mg/L. Suspended-sediment concentrations varied in response to changes in discharge, with peak suspended-sediment concentrations occurring 1 to 2 days before the peak discharge for each event. The total suspended-sediment load at the Wallisville site during May 2014–December 2015 was approximately 2,200,000 tons, with a minimum monthly suspended-sediment load of 100 tons in October 2014 and a maximum monthly load of 441,000 tons in November 2015.
Results from nutrient samples collected at the Wallisville site indicate that total nitrogen and total phosphorus concentrations fluctuated at a similar rate, with the highest nutrient concentrations occurring during periods of high flow corresponding to releases from Lake Livingston. The mean concentrations of total nitrogen and total phosphorus were approximately 75 percent higher during high flow releases than during periods of low flow, overshadowing variations in nutrient concentrations caused by seasonality at the Wallisville site.
Results from the study indicate nutrient delivery to Galveston Bay from the main channel of the Trinity River is likely controlled primarily by high-flow releases from Lake Livingston. For most samples collected at the Wallisville site, organic nitrogen was the predominant form of nitrogen; however, when discharge increased because of releases from Lake Livingston, the percentage of organic nitrogen typically decreased and the percentage of nitrate increased. The concentrations of total phosphorus also increased during high-flow events, likely as a result of suspended sediment within Lake Livingston releases and mobilization of sediment particles in the river channel and flood plain during these periods of high flow. The predominant source of phosphorous to Galveston Bay from the Trinity River is in particulate form closely tied to suspended-sediment concentrations. The changes in nutrient concentration and composition caused by releases from Lake Livingston during this study indicate the reservoir may play an important role in the delivery of nutrients into Galveston Bay. Further study is required to better understand the processes in Lake Livingston influencing the characteristics of nutrient and sediment inflow to Galveston Bay. With phosphorous concentrations correlated to suspended-sediment concentrations (coefficient of determination value of 0.75) and with the concentrations of nutrients changing as the discharge changes, the diversion of water and suspended sediment into surrounding wetlands and channels outside of the main channel of the Trinity River may play a large role in regulating nutrient inputs into Galveston Bay.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165177","isbn":"978-1-4113-4107-4","collaboration":"Prepared in cooperation with the Texas Water Development Board and the Galveston Bay Estuary Program ","usgsCitation":"Lucena, Zulimar, and Lee, M.T., 2017, Characterization of streamflow, suspended sediment, and nutrients entering Galveston Bay from the Trinity River, Texas, May 2014–December 2015: U.S. Geological Survey Scientific Investigations Report 2016–5177, 38 p., https://doi.org/10.3133/sir20165177.\n","productDescription":"vii, 37 p.","numberOfPages":"49","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-077707","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":335588,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5177/sir20165177.pdf","text":"Report","size":"11.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5177"},{"id":335587,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5177/coverthb.jpg"}],"country":"United States","state":"Texas","otherGeospatial":"Galveston Bay, Trinity River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -95.15533447265625,\n 29.7596087873038\n ],\n [\n -94.58953857421875,\n 29.7596087873038\n ],\n [\n -94.58953857421875,\n 30.982318643027536\n ],\n [\n -95.15533447265625,\n 30.982318643027536\n ],\n [\n -95.15533447265625,\n 29.7596087873038\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, X 78754
https://tx.usgs.gov/
Trends in long-term water-quality and streamflow data from six water-quality-monitoring stations within three major river basins in Massachusetts and Rhode Island that flow into Narragansett Bay and Little Narragansett Bay were evaluated for water years 1979–2015. In this study, conducted by the U.S. Geological Survey in cooperation with the Rhode Island Department of Environmental Management, the Rhode Island Water Resources Board, and the U.S. Environmental Protection Agency, water-quality and streamflow data were evaluated with a Weighted Regressions on Time, Discharge, and Season smoothing method, which removes the effects of year-to-year variation in water-quality conditions due to variations in streamflow (discharge). Trends in annual mean, annual median, annual maximum, and annual 7-day minimum flows at four continuous streamgages were evaluated by using a time-series smoothing method for water years 1979–2015.
Water quality at all monitoring stations changed over the study period. Decreasing trends in flow-normalized nutrient concentrations and loads were observed during the period at most monitoring stations for total nitrogen, nitrite plus nitrate, and total phosphorus. Average flow-normalized loads for water years 1979–2015 decreased in the Blackstone River by up to 46 percent in total nitrogen, 17 percent in nitrite plus nitrate, and 69 percent in total phosphorus. The other rivers also had decreasing flow-normalized trends in nutrient concentrations and loads, except for the Pawtuxet River, which had an increasing trend in nitrite plus nitrate. Increasing trends in flow-normalized chloride concentrations and loads were observed during the study period at all of the rivers, with increases of more than 200 percent in the Blackstone River.
Small increasing trends in annual mean daily streamflow were observed in 3 of the 4 rivers, with increases of 1.2 to 11 percent; however, the trends were not significant. All 4 rivers had decreases in streamflow for the annual 7-day minimums, but only 3 of the 4 rivers had decreases that were significant (34 to 54 percent). The Branch River had decreasing annual mean daily streamflow (7.5 percent) and the largest decrease in the annual 7-day minimum streamflow. The Blackstone and Pawtuxet Rivers had the largest increases in annual maximum daily flows but had decreases in the annual 7-day minimum flows.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165178","isbn":"978-1-4113-4102-9","collaboration":"Prepared in cooperation with the Rhode Island Department of Environmental Management, the Rhode Island Water Resources Board, and the U.S. Environmental Protection Agency ","usgsCitation":"Savoie, J.G., Mullaney, J.R., and Bent, G.C., 2017, Analysis of trends of water quality and streamflow in the Blackstone, Branch, Pawtuxet, and Pawcatuck Rivers, Massachusetts and Rhode Island, 1979 to 2015: U.S. Geological Survey Scientific Investigations Report 2016–5178, 43 p., https://doi.org/10.3133/sir20165178.","productDescription":"v, 43 p.","numberOfPages":"54","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-075513","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":335759,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5178/coverthb.jpg"},{"id":335760,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5178/sir20165178.pdf","text":"Report","size":"2.60 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5178"}],"country":"United States","state":"Massachusetts, Rhode Island","otherGeospatial":"Blackstone River, Branch River, Pawcatuck River. Pawtuxet River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72.04833984375,\n 41.269549502842565\n ],\n [\n -71.35345458984375,\n 41.269549502842565\n ],\n [\n -71.35345458984375,\n 42.10433598038485\n ],\n [\n -72.04833984375,\n 42.10433598038485\n ],\n [\n -72.04833984375,\n 41.269549502842565\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Or visit our Web site at:
http://newengland.water.usgs.gov
This report describes a study of the hydrogeology and simulation of groundwater flow for the Canadian River alluvial aquifer in western and central Oklahoma conducted by the U.S. Geological Survey in cooperation with the Oklahoma Water Resources Board. The report (1) quantifies the groundwater resources of the Canadian River alluvial aquifer by developing a conceptual model, (2) summarizes the general water quality of the Canadian River alluvial aquifer groundwater by using data collected during August and September 2013, (3) evaluates the effects of estimated equal proportionate share (EPS) on aquifer storage and streamflow for time periods of 20, 40, and 50 years into the future by using numerical groundwater-flow models, and (4) evaluates the effects of present-day groundwater pumping over a 50-year period and sustained hypothetical drought conditions over a 10-year period on stream base flow and groundwater in storage by using numerical flow models. The Canadian River alluvial aquifer is a Quaternary-age alluvial and terrace unit consisting of beds of clay, silt, sand, and fine gravel sediments unconformably overlying Tertiary-, Permian-, and Pennsylvanian-age sedimentary rocks. For groundwater-flow modeling purposes, the Canadian River was divided into Reach I, extending from the Texas border to the Canadian River at the Bridgeport, Okla., streamgage (07228500), and Reach II, extending downstream from the Canadian River at the Bridgeport, Okla., streamgage (07228500), to the confluence of the river with Eufaula Lake. The Canadian River alluvial aquifer spans multiple climate divisions, ranging from semiarid in the west to humid subtropical in the east. The average annual precipitation in the study area from 1896 to 2014 was 34.4 inches per year (in/yr).
A hydrogeologic framework of the Canadian River alluvial aquifer was developed that includes the areal and vertical extent of the aquifer and the distribution, texture variability, and hydraulic properties of aquifer materials. The aquifer areal extent ranged from less than 0.2 to
8.5 miles wide. The maximum aquifer thickness was 120 feet (ft), and the average aquifer thickness was 50 ft. Average horizontal hydraulic conductivity for the Canadian River alluvial aquifer was calculated to be 39 feet per day, and the maximum horizontal hydraulic conductivity was calculated to be 100 feet per day.
Recharge rates to the Canadian River alluvial aquifer were estimated by using a soil-water-balance code to estimate the spatial distribution of groundwater recharge and a water-table fluctuation method to estimate localized recharge rates. By using daily precipitation and temperature data from 39 climate stations, recharge was estimated to average 3.4 in/yr, which corresponds to 8.7 percent of precipitation as recharge for the Canadian River alluvial aquifer from 1981 to 2013. The water-table fluctuation method was used at one site where continuous water-level observation data were available to estimate the percentage of precipitation that becomes groundwater recharge. Estimated annual recharge at that site was 9.7 in/yr during 2014.
Groundwater flow in the Canadian River alluvial aquifer was identified and quantified by a conceptual flow model for the period 1981–2013. Inflows to the Canadian River alluvial aquifer include recharge to the water table from precipitation, lateral flow from the surrounding bedrock, and flow from the Canadian River, whereas outflows include flow to the Canadian River (base-flow gain), evapotranspiration, and groundwater use. Total annual recharge inflows estimated by the soil-water-balance code were multiplied by the area of each reach and then averaged over the simulated period to produce an annual average of 28,919 acre-feet per year (acre-ft/yr) for Reach I and 82,006 acre-ft/yr for Reach II. Stream base flow to the Canadian River was estimated to be the largest outflow of groundwater from the aquifer, measured at four streamgages, along with evapotranspiration and groundwater use, which were relatively minor discharge components.
Objectives for the numerical groundwater-flow models included simulating groundwater flow in the Canadian River alluvial aquifer from 1981 to 2013 to address groundwater use and drought scenarios, including calculation of the EPS pumping rates. The EPS for the alluvial and terrace aquifers is defined by the Oklahoma Water Resources Board as the amount of fresh water that each landowner is allowed per year per acre of owned land to maintain a saturated thickness of at least 5 ft in at least 50 percent of the overlying land of the groundwater basin for a minimum of 20 years.
The groundwater-flow models were calibrated to water-table altitude observations, streamgage base flows, and base-flow gain to the Canadian River. The Reach I water-table altitude observation root-mean-square error was 6.1 ft, and 75 percent of residuals were within ±6.7 ft of observed measurements. The average simulated stream base-flow residual at the Bridgeport streamgage (07228500) was 8.8 cubic feet per second (ft3/s), and 75 percent of residuals were within ±30 ft3/s of observed measurements. Simulated base-flow gain in Reach I was 8.8 ft3/s lower than estimated base-flow gain. The Reach II water-table altitude observation root-mean-square error was 4 ft, and 75 percent of residuals were within ±4.3 ft of the observations. The average simulated stream base-flow residual in Reach II was between 35 and 132 ft3/s. The average simulated base-flow gain residual in Reach II was between 11.3 and 61.1 ft3/s.
Several future predictive scenarios were run, including estimating the EPS pumping rate for 20-, 40-, and 50-year life of basin scenarios, determining the effects of current groundwater use over a 50-year period into the future, and evaluating the effects of a sustained drought on water availability for both reaches. The EPS pumping rate was determined to be 1.35 acre-feet per acre per year ([acre-ft/acre]/yr) in Reach I and 3.08 (acre-ft/acre)/yr in Reach II for a 20-year period. For the 40- and 50-year periods, the EPS rate was determined to be
1.34 (acre-ft/acre)/yr in Reach I and 3.08 (acre-ft/acre)/yr in Reach II. Storage changes decreased in tandem with simulated groundwater pumping and were minimal after the first 15 simulated years for Reach I and the first 8 simulated years for Reach II.
Groundwater pumping at year 2013 rates for a period of 50 years resulted in a 0.2-percent decrease in groundwater-storage volumes in Reach I and a 0.6-percent decrease in the groundwater-storage volumes in Reach II. The small changes in storage are due to groundwater use by pumping, which composes a small percentage of the total groundwater-flow model budgets for Reaches I and II.
A sustained drought scenario was used to evaluate the effects of a hypothetical 10-year drought on water availability. A 10-year period was chosen where the effects of drought conditions would be simulated by decreasing recharge by 75 percent. In Reach I, average simulated stream base flow at the Bridgeport streamgage (07228500) decreased by 58 percent during the hypothetical 10-year drought compared to average simulated stream base flow during the nondrought period. In Reach II, average simulated stream base flows at the Purcell streamgage (07229200) and Calvin streamgage (07231500) decreased by 64 percent and 54 percent, respectively. In Reach I, the groundwater-storage drought scenario resulted in a storage decline of 30 thousand acre-feet, or an average decline in the water table of
1.2 ft. In Reach II, the groundwater-storage drought scenario resulted in a storage decline of 71 thousand acre-feet, or an average decline in the water table of 2.0 ft.
Director, Oklahoma Water Science Center
U.S. Geological Survey
202 NW 66th, Bldg 7
Oklahoma City, OK 73116
Director, California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
https://ca.water.usgs.gov
Digital flood-inundation maps for a 6.6-mile reach of the St. Joseph River at Elkhart, Indiana, were created by the U.S. Geological Survey (USGS) in cooperation with the Indiana Office of Community and Rural Affairs. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at https://water.usgs.gov/osw/flood_inundation/, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage 04101000, St. Joseph River at Elkhart, Ind. Real-time stages at this streamgage may be obtained on the Internet from the USGS National Water Information System at https://waterdata.usgs.gov/nwis or the National Weather Service (NWS) Advanced Hydrologic Prediction Service at http:/water.weather.gov/ahps/, which also forecasts flood hydrographs at this site (NWS site EKMI3).
Flood profiles were computed for the stream reach by means of a one-dimensional, step-backwater hydraulic modeling software developed by the U.S. Army Corps of Engineers. The hydraulic model was calibrated using the current stage-discharge rating at the USGS streamgage 04101000, St. Joseph River at Elkhart, Ind., and the documented high-water marks from the flood of March 1982. The hydraulic model was then used to compute six water-surface profiles for flood stages at 1-foot (ft) intervals referenced to the streamgage datum ranging from 23.0 ft (the NWS “action stage”) to 28.0 ft, which is the highest stage interval of the current USGS stage-discharge rating curve and 1 ft higher than the NWS “major flood stage.” The simulated water-surface profiles were then combined with a Geographic Information System digital elevation model (derived from light detection and ranging [lidar] data having a 0.49-ft root mean squared error and 4.9-ft horizontal resolution, resampled to a 10-ft grid) to delineate the area flooded at each stage.
The availability of these maps, along with Internet information regarding current stage from the USGS streamgage and forecasted high-flow stages from the NWS, will provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, as well as for post-flood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165179","collaboration":"Prepared in cooperation with the Indiana Office of Community and Rural Affairs","usgsCitation":"Martin, Z.W., 2017, Flood-inundation maps for the St. Joseph River at Elkhart, Indiana: U.S. Geological Survey Scientific Investigations Report 2016–5179, 10 p., https://doi.org/10.3133/sir20165179.","productDescription":"Report: vi, 10 p.; Data Release","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-079008","costCenters":[{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true}],"links":[{"id":333769,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7QZ2836","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"St. Joseph River at Elkhart, Indiana, Flood-Inundation HEC-RAS Model"},{"id":333734,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5179/coverthb.jpg"},{"id":333735,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5179/sir20165179.pdf","text":"Report","size":"1.35 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5179"}],"country":"United States","state":"Indiana","otherGeospatial":"St. Joseph River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -86.04475021362305,\n 41.67355293097283\n ],\n [\n -86.04475021362305,\n 41.69380876113261\n ],\n [\n -85.97402572631836,\n 41.69380876113261\n ],\n [\n -85.97402572631836,\n 41.67355293097283\n ],\n [\n -86.04475021362305,\n 41.67355293097283\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Indiana Water Science Center
U.S. Geological Survey
5957 Lakeside Boulevard,
Indianapolis, IN 46278–1996
The U.S. Geological Survey completed hydrologic and hydraulic analyses of Cromwell Brook and the Sieur de Monts tributary in Acadia National Park, Maine, to better understand causes of flooding in complex hydrologic and hydraulic environments, like those in the Great Meadow wetland and Sieur de Monts Spring area. Regional regression equations were used to compute peak flows with from 2 to 100-year recurrence intervals at seven locations. Light detection and ranging data were adjusted for bias caused by dense vegetation in the Great Meadow wetland; and then combined with local ground surveys used to define the underwater topography and hydraulic structures in the study area. Hydraulic modeling was used to evaluate flood response in the study area to a variety of hydrologic and hydraulic scenarios.
Hydraulic modeling indicates that enlarging the culvert at Park Loop Road could help mitigate flooding near the Sieur de Monts Nature Center that is caused by streamflows with large recurrence intervals; however, hydraulic modeling also indicates that the Park Loop Road culvert does not aggravate flooding near the Nature Center caused by the more frequent high intensity rainstorms. That flooding is likely associated with overland flow resulting from (1) quick runoff from the steep Dorr Mountain hitting the lower gradient Great Meadow wetland area and (2) poor drainage aggravated by beaver dams holding water in the wetland.
Rapid geomorphic assessment data collected in June 2015 and again in April 2016 indicate that Cromwell Brook has evidence of aggradation, degradation, and channel widening throughout the drainage basin. Two of five reference cross sections developed for this report also indicate channel aggradation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165159","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Lombard, P.J., 2017, Hydrologic and hydraulic analyses of Great Meadow wetland, Acadia National Park, Maine: U.S. Geological Survey Scientific Investigations Report 2016–5159, 39 p., https://doi.org/10.3133/sir20165159.","productDescription":"viii, 39 p.","numberOfPages":"52","onlineOnly":"Y","ipdsId":"IP-077064","costCenters":[{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true}],"links":[{"id":333754,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5159/sir20165159.pdf","text":"Report","size":"7.66 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5159"},{"id":333753,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5159/coverthb.jpg"}],"country":"United States","state":"Maine","otherGeospatial":"Acadia National Park, Mount Desert Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -68.43795776367188,\n 44.22158376545796\n ],\n [\n -68.43795776367188,\n 44.44554600843547\n ],\n [\n -68.16329956054688,\n 44.44554600843547\n ],\n [\n -68.16329956054688,\n 44.22158376545796\n ],\n [\n -68.43795776367188,\n 44.22158376545796\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
196 Whitten Road
Augusta, ME 04330
Or visit our Web site at:
http://newengland.water.usgs.gov
Climate change is presenting new challenges for natural resource managers charged with maintaining sustainable ecosystems and landscapes. Phenology, a branch of science dealing with seasonal natural phenomena (bird migration or plant flowering in response to weather changes, for example), bridges the gap between the biosphere and the climate system. Phenological processes operate across scales that span orders of magnitude—from leaf to globe and from days to seasons—making phenology ideally suited to multiscale, multiplatform data integration and delivery of information at spatial and temporal scales suitable to inform resource management decisions.
A workshop report: Workshop held June 2016 to investigate opportunities and challenges facing multi-scale, multi-platform integration of phenological data to support natural resource management decision-making.
Topock Marsh is a 1,637-hectare (4,045-acre) wetland adjacent to the Colorado River near Needles, California, and a main feature of Havasu National Wildlife Refuge (NWR). The U.S. Fish and Wildlife Service, in cooperation with the Bureau of Reclamation, began construction of an infrastructure improvement project in 2010 to increase the efficiency of water use and to help protect the habitats and species found within the Havasu NWR. During construction, normal water delivery from the Colorado River into Topock Marsh through the Inlet Canal was restricted, which resulted in unusually low water elevations in 2011. The U.S. Geological Survey, commissioned by the U.S. Fish and Wildlife Service, undertook the investigation of the water quality and aquatic flora and fauna during the low water conditions. Subsequently, water elevations in the marsh returned to more normal elevations after the new concrete-lined Fire Break Canal became fully operational in January 2012.
The U.S. Geological Survey made 11 field trips to the Havasu NWR between July 2011 and October 2014 to assess the effects of the temporary low water conditions and the change of inflow location (from the Inlet Canal to the Fire Break Canal) on water quality and aquatic habitat. The following conditions were monitored: water quality, sediment and plant chemistry, phytoplankton, zooplankton, aquatic macro-invertebrates, and emergent and submerged aquatic vegetation (SAV). Water-quality and biota data collected during 2013–14 were then compared with data collected during the 2011–12 low water period.
Once the new Fire Break Canal became operational and Colorado River water flowed regularly into the marsh, concentrations of several water quality parameters decreased (for example, specific conductance, total dissolved solids, turbidity, chlorophyll a, and total and organic nitrogen), and phytoplankton abundance was reduced at the upstream sampling stations (TP-3, TP-2, and TP-6); the water flow pushed water with higher concentrations of these components downstream (measured at TP-8). The upstream sampling locations in 2013–14 had decreased turbidity, therefore more SAV biomass accumulated, especially in shallow areas with water depths of ≤1.0 meter (≤3.3 feet). However, the furthest downstream station had higher turbidity caused by both the suspension of autochthonous sediment and high phytoplankton density and biovolume. This higher turbidity resulted in minimal SAV growth, especially in the deeper water (>1.0 meter [>3.3 feet]). Emergent vegetation not only survived the low water conditions of 2011, but expanded its areal coverage and subsequently thrived in the higher water elevations.
Overall, no immediate critically negative consequences were detected for aquatic fauna or flora that could be attributd unequivocally to the effect of low water levels. Concentrations of nutrient and trace elements in all water samples were below wildlife toxicity thresholds as established by Arizona Department of Environmental Quality. Three nonnative species were discovered shortly after the Fire Break Canal went into operation. Of the three, gizzard shad (Dorosoma cepedianum) and Eurasian watermilfoil (Myriophyllum spicatum) increased substantially in numbers from 2011–14, but quagga mussels (Dreissena bugensis) did not increase. Future monitoring will determine the long-term impact of the new flow regime
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161195","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service–Region 2–National Wildlife Refuge System, the Havasu National Wildlife Refuge, and the Desert Landscape Conservation Cooperative","usgsCitation":"Daniels, J.S., and Haegele, J.C., 2017, Assessment of ecosystem response to a temporary water level drawdown and subsequent refilling at Topock Marsh, Arizona—July 2011–October 2014: U.S. Geological Survey Open-File Report 2016–1195, 93 p., https://doi.org/10.3133/ofr20161195.","productDescription":"Report: vi, 92 p.; Appendixes 1-2","onlineOnly":"Y","ipdsId":"IP-051540","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":333180,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1195/ofr20161195_Appendix2_2014_Topock_Marsh_Fish_Survey_AGFD.pdf","text":"Appendix 2-2014 Topock Marsh Fish Survey AGFD","size":"116 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1195 Appendix 2 2014"},{"id":333171,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1195/coverthb2.jpg"},{"id":333179,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1195/ofr20161195_Appendix2_2013_Topock_Marsh_Fish_Survey_AGFD.pdf","text":"Appendix 2-2013 Topock Marsh Fish Survey AGFD","size":"28.0 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1195 Appendix 2 2013"},{"id":333175,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1195/ofr20161195_Appendix 1-Reclamation_longterm_WQ_data_1983-2015.xlsx","text":"Appendix 1-Reclamation longterm WQ data 1983-2015","size":"120 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2016-1195 Appendix 1"},{"id":333172,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1195/ofr20161195.pdf","text":"Report","size":"4.48 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1195"},{"id":333181,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1195/ofr20161195_Appendix2_2015_Topock_Marsh_Fish_Survey_AGFD.pdf","text":"Appendix 2-2015 Topock Marsh Fish Survey AGFD","size":"120 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1195 Appendix 2 2015"},{"id":333176,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1195/ofr20161195_Appendix2_2010-2011-Topock_Marsh_Fish_Surveys_AGFD.pdf","text":"Appendix 2-2010-2011 Topock Marsh Fish Surveys AGFD","size":"20.0 kb","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1195 Appendix 2 2010-2011"},{"id":333178,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1195/ofr20161195_Appendix2_2012_Topock_Marsh_Fish_Survey_AGFD.pdf","text":"Appendix 2-2012 Topock Marsh Fish Survey AGFD","size":"24.0 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1195 Appendix 2 2012"}],"country":"United States","state":"Arizona","otherGeospatial":"Topock Marsh","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.5625,\n 34.844444\n ],\n [\n -114.5625,\n 34.733333\n ],\n [\n -114.466667,\n 34.733333\n ],\n [\n -114.466667,\n 34.844444\n ],\n [\n -114.5625,\n 34.844444\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Center Director, USGS Fort Collins Science Center
2150 Centre Ave., Bldg. C
Fort Collins, CO 80526-8118
Since the original publication of the Death Valley regional groundwater flow system (DVRFS) numerical model in 2004, more information on the regional groundwater flow system in the form of new data and interpretations has been compiled. Cooperators such as the Bureau of Land Management, National Park Service, U.S. Fish and Wildlife Service, the Department of Energy, and Nye County, Nevada, recognized a need to update the existing regional numerical model to maintain its viability as a groundwater management tool for regional stakeholders. The existing DVRFS numerical flow model was converted to MODFLOW-2005, updated with the latest available data, and recalibrated. Five main data sets were revised: (1) recharge from precipitation varying in time and space, (2) pumping data, (3) water-level observations, (4) an updated regional potentiometric map, and (5) a revision to the digital hydrogeologic framework model.
The resulting DVRFS version 2.0 (v. 2.0) numerical flow model simulates groundwater flow conditions for the Death Valley region from 1913 to 2003 to correspond to the time frame for the most recently published (2008) water-use data. The DVRFS v 2.0 model was calibrated by using the Tikhonov regularization functionality in the parameter estimation and predictive uncertainty software PEST. In order to assess the accuracy of the numerical flow model in simulating regional flow, the fit of simulated to target values (consisting of hydraulic heads and flows, including evapotranspiration and spring discharge, flow across the model boundary, and interbasin flow; the regional water budget; values of parameter estimates; and sensitivities) was evaluated. This evaluation showed that DVRFS v. 2.0 simulates conditions similar to DVRFS v. 1.0. Comparisons of the target values with simulated values also indicate that they match reasonably well and in some cases (boundary flows and discharge) significantly better than in DVRFS v. 1.0.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165150","collaboration":"Prepared in cooperation with the Bureau of Land Management, National Park Service, U.S. Department of Energy National Nuclear Security Administration (Interagency Agreement DE–AI52–01NV13944), and Office of Civilian Radioactive Waste Management (Interagency Agreement DE–AI28–02RW12167), U.S. Fish and Wildlife Service, and Nye County, Nevada","usgsCitation":"Belcher, W.R., Sweetkind, D.S., Faunt, C.C., Pavelko, M.T., and Hill, M.C., 2017, An update of the Death Valley regional groundwater flow system transient model, Nevada and California: U.S. Geological Survey Scientific Investigations Report 2016-5150, 74 p., 1 pl. https://doi.org/10.3133/sir20165150","productDescription":"Report: x, 74 p.; Plate: 18 x 26 inches","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-045053","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":333413,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5150/coverthb.jpg"},{"id":333414,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5150/sir20165150.pdf","text":"Report","size":"4.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5150 Report PDF"},{"id":333415,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2016/5150/sir20165150_plate.pdf","text":"Plate 1","size":"5.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5150 Plate 1"}],"country":"United States","state":"California, Nevada","otherGeospatial":"Death Valley regional groundwater flow system","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118,\n 35\n ],\n [\n -118,\n 38.25\n ],\n [\n -115,\n 38.25\n ],\n [\n -115,\n 35\n ],\n [\n -118,\n 35\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Nevada Water Science Center
U.S. Geological Survey
2730 N. Deer Run Rd.
Carson City, NV 89701
http://nevada.usgs.gov/
As part of the National Water Availability and Use Program established by the U.S. Geological Survey (USGS) in 2005, this study took advantage of about 14 million records from State-managed collections of water-well drillers’ records and created a database of hydrogeologic properties for the glaciated United States. The water-well drillers’ records were standardized to be relatively complete and error-free and to provide consistent variables and naming conventions that span all State boundaries.
Maps and geospatial grids were developed for (1) total thickness of glacial deposits, (2) total thickness of coarse-grained deposits, (3) specific-capacity based transmissivity and hydraulic conductivity, and (4) texture-based estimated equivalent horizontal and vertical hydraulic conductivity and transmissivity. The information included in these maps and grids is required for most assessments of groundwater availability, in addition to having applications to studies of groundwater flow and transport. The texture-based estimated equivalent horizontal and vertical hydraulic conductivity and transmissivity were based on an assumed range of hydraulic conductivity values for coarse- and fine-grained deposits and should only be used with complete awareness of the methods used to create them. However, the maps and grids of texture-based estimated equivalent hydraulic conductivity and transmissivity may be useful for application to areas where a range of measured values is available for re-scaling.
Maps of hydrogeologic information for some States are presented as examples in this report but maps and grids for all States are available electronically at the project Web site (USGS Glacial Aquifer System Groundwater Availability Study, http://mi.water.usgs.gov/projects/WaterSmart/Map-SIR2015-5105.html) and the Science Base Web site, https://www.sciencebase.gov/catalog/item/58756c7ee4b0a829a3276352.
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5957 Lakeside Blvd
Indianapolis, IN 46278
Phone: (317) 290-3333
https://in.water.usgs.gov/
The U.S. Geological Survey, in cooperation with the Georgia Department of Natural Resources, Environmental Protection Division, developed regional regression equations for estimating selected low-flow frequency and mean annual flow statistics for ungaged streams in north Georgia that are not substantially affected by regulation, diversions, or urbanization. Selected low-flow frequency statistics and basin characteristics for 56 streamgage locations within north Georgia and 75 miles beyond the State’s borders in Alabama, Tennessee, North Carolina, and South Carolina were combined to form the final dataset used in the regional regression analysis. Because some of the streamgages in the study recorded zero flow, the final regression equations were developed using weighted left-censored regression analysis to analyze the flow data in an unbiased manner, with weights based on the number of years of record. The set of equations includes the annual minimum 1- and 7-day average streamflow with the 10-year recurrence interval (referred to as 1Q10 and 7Q10), monthly 7Q10, and mean annual flow. The final regional regression equations are functions of drainage area, mean annual precipitation, and relief ratio for the selected low-flow frequency statistics and drainage area and mean annual precipitation for mean annual flow. The average standard error of estimate was 13.7 percent for the mean annual flow regression equation and ranged from 26.1 to 91.6 percent for the selected low-flow frequency equations.
The equations, which are based on data from streams with little to no flow alterations, can be used to provide estimates of the natural flows for selected ungaged stream locations in the area of Georgia north of the Fall Line. The regression equations are not to be used to estimate flows for streams that have been altered by the effects of major dams, surface-water withdrawals, groundwater withdrawals (pumping wells), diversions, or wastewater discharges. The regression equations should be used only for ungaged sites with drainage areas between 1.67 and 576 square miles, mean annual precipitation between 47.6 and 81.6 inches, and relief ratios between 0.146 and 0.607; these are the ranges of the explanatory variables used to develop the equations. An attempt was made to develop regional regression equations for the area of Georgia south of the Fall Line by using the same approach used during this study for north Georgia; however, the equations resulted with high average standard errors of estimates and poorly predicted flows below 0.5 cubic foot per second, which may be attributed to the karst topography common in that area.
The final regression equations developed from this study are planned to be incorporated into the U.S. Geological Survey StreamStats program. StreamStats is a Web-based geographic information system that provides users with access to an assortment of analytical tools useful for water-resources planning and management, and for engineering design applications, such as the design of bridges. The StreamStats program provides streamflow statistics and basin characteristics for U.S. Geological Survey streamgage locations and ungaged sites of interest. StreamStats also can compute basin characteristics and provide estimates of streamflow statistics for ungaged sites when users select the location of a site along any stream in Georgia.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175001","collaboration":"Prepared in cooperation with the Georgia Department of Natural Resources, Environmental Protection Division","usgsCitation":"Gotvald, A.J., 2017, Methods for estimating selected low-flow frequency statistics and mean annual flow for ungaged locations on streams in North Georgia: U.S. Geological Survey Scientific Investigations Report 2017–5001, 25 p., https://doi.org/10.3133/sir20175001. ","productDescription":"Report: vi, 25 p.; 3 Tables","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-077003","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":333138,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5001/sir20175001.pdf","text":"Report","size":"1.35 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5001"},{"id":333139,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2017/5001/sir20175001_tables1-2-5.xlsx","text":"Tables 1, 2, and 5 - ","size":"74.8 KB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"Table 1. Description of streamgages evaluated for use in the regional regression analysis for north GeorgiaDirector, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Stephenson Center, Suite 129
Columbia, SC 29210
http://www.usgs.gov/water/southatlantic/
A comprehensive survey of geologic structures formed in the Earth’s brittle regime in the eastern Española Basin and flank of the Rio Grande rift, New Mexico, reveals a complex and protracted record of multiple tectonic events. Data and analyses from this representative rift flank-basin pair include measurements from 53 individual fault zones and 22 other brittle structures, such as breccia zones, joints, and veins, investigated at a total of just over 100 sites. Structures were examined and compared in poorly lithified Tertiary sediments, as well as in Paleozoic sedimentary and Proterozoic crystalline rocks. Data and analyses include geologic maps; field observations and measurements; orientation, kinematic, and paleostress analyses; statistical examination of fault trace lengths derived from aeromagnetic data; mineralogy and chemistry of host and fault rocks; and investigation of fault versus bolide-impact hypotheses for the origin of enigmatic breccias found in the Proterozoic basement rocks. Fault kinematic and paleostress analyses suggest a record of transitional, and perhaps partitioned, strains from the Laramide orogeny through Rio Grande rifting. Normal faults within Tertiary basin-fill sediments are consistent with more typical WNW-ESE Rio Grande rift extension, perhaps decoupled from bedrock structures due to strength contrasts favoring the formation of new faults in the relatively weak sediments. Analyses of the fault-length data indicate power-law length distributions similar to those reported from many geologic settings globally. Mineralogy and chemistry in Proterozoic fault-related rocks reveal geochemical changes tied to hydrothermal alteration and nearly isochemical transformation of feldspars to clay minerals. In sediments, faulted minerals are characterized by mechanical entrainment with minor secondary chemical changes. Enigmatic breccias in rift-flanking Proterozoic rocks are autoclastic and isochemical with respect to their protoliths and exist near shatter cones believed to be related to a previously reported pre-Pennsylvanian impact event. A weak iridium anomaly is associated with the breccias as well as adjacent protoliths, thus an impact shock wave cannot be ruled out for their origin. Major fault zones along the eastern rift-flank mountain front are discontinuous and unlikely to impede regional groundwater flow into Española Basin aquifers. The breccia bodies are not large enough to constitute aquifers, and no fault- or breccia-related geochemical anomalies were identified as potential contamination sources for ground or surface waters. The results of this work provide a broad picture of structural diversity and tectonic evolution along the eastern flank of the central Rio Grande rift and the adjacent Española Basin representative of the rift as a whole and many rifts worldwide.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES01348.1","usgsCitation":"Caine, J.S., Minor, S.A., Grauch, V.J., Budahn, J.R., and Keren, T.T., 2017, A comprehensive survey of faults, breccias, and fractures in and flanking the eastern Española Basin, Rio Grande rift, New Mexico: Geosphere, v. 13, p. 1566-1609, https://doi.org/10.1130/GES01348.1.","productDescription":"43 p.","startPage":"1566","endPage":"1609","ipdsId":"IP-072811","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":470199,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges01348.1","text":"Publisher Index Page"},{"id":343179,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":346150,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7222RXW","text":"Data for a comprehensive survey of fault zones, breccias, and fractures in and flanking the eastern Española Basin, Rio Grande Rift, New Mexico"}],"country":"United States","state":"New Mexico","otherGeospatial":"Española Basin, Rio Grande Rift","volume":"13","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-08-09","publicationStatus":"PW","scienceBaseUri":"595611b6e4b0d1f9f0506760","contributors":{"authors":[{"text":"Caine, Jonathan S. 0000-0002-7269-6989 jscaine@usgs.gov","orcid":"https://orcid.org/0000-0002-7269-6989","contributorId":1272,"corporation":false,"usgs":true,"family":"Caine","given":"Jonathan","email":"jscaine@usgs.gov","middleInitial":"S.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":false,"id":702908,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Minor, Scott A. 0000-0002-6976-9235 sminor@usgs.gov","orcid":"https://orcid.org/0000-0002-6976-9235","contributorId":765,"corporation":false,"usgs":true,"family":"Minor","given":"Scott","email":"sminor@usgs.gov","middleInitial":"A.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":702909,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grauch, V. J. S. 0000-0002-0761-3489 tien@usgs.gov","orcid":"https://orcid.org/0000-0002-0761-3489","contributorId":886,"corporation":false,"usgs":true,"family":"Grauch","given":"V.","email":"tien@usgs.gov","middleInitial":"J. S.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":702910,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Budahn, James R. 0000-0001-9794-8882","orcid":"https://orcid.org/0000-0001-9794-8882","contributorId":177797,"corporation":false,"usgs":false,"family":"Budahn","given":"James","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":702911,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Keren, Tucker T. 0000-0003-0208-0086","orcid":"https://orcid.org/0000-0003-0208-0086","contributorId":177798,"corporation":false,"usgs":false,"family":"Keren","given":"Tucker","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":702912,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70170461,"text":"sir20165047 - 2017 - Response of selenium concentrations in groundwater to seasonal canal leakage, lower Gunnison River Basin, Colorado, 2013","interactions":[],"lastModifiedDate":"2017-01-17T13:32:56","indexId":"sir20165047","displayToPublicDate":"2016-05-23T14:45:00","publicationYear":"2017","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":"2016-5047","title":"Response of selenium concentrations in groundwater to seasonal canal leakage, lower Gunnison River Basin, Colorado, 2013","docAbstract":"Selenium is a water-quality concern in the lower Gunnison River Basin because irrigation water interacting with seleniferous soils derived from the Mancos Shale Formation has mobilized selenium and increased its concentrations in surface water. Understanding the occurrence of elevated selenium concentrations in groundwater is necessary because groundwater discharge is an important source of selenium in surface water in the basin. In 2013, the U.S. Geological Survey, in cooperation with the Bureau of Reclamation and the Colorado Water Conservation Board, began a study to understand how changes in groundwater levels attributed to canal leakage affected the concentrations and speciation of dissolved selenium in groundwater. The purpose of this report is to characterize the groundwater adjacent to an unlined leaky canal. Two locations, near the East Canal (W-N1 and W-N2) and farther from the East Canal (W-M1 and W-M2), were selected for nested monitoring well installations. The pressure exerted by changes in canal stage was more readily transferred to the deep groundwater measured in the W-N1 near the canal than the shallow groundwater at the W-N2 well. No definitive relation could be made between canal water-level elevation and water-level elevations in monitoring wells farther from the canal (W-M1 and W-M2).
\nWater flowing through the East Canal before the irrigation season had much higher selenium concentrations (140 micrograms per liter) than water in the canal during the irrigation season (3.02 micrograms per liter). Total selenium concentrations in the monitoring wells near the canal initially increased to 51.8 micrograms per liter in W-N1 and 1.66 micrograms per liter in W-N2. The initial increase in groundwater selenium concentrations presumably resulted from the dissolution of salts in the unsaturated zone by rising groundwater levels associated with canal leakage. The subsequent decrease in total selenium concentrations resulted from a combination of dilution by canal leakage and selenium reduction processes. Total selenium concentrations in monitoring wells located farther from the canal were not directly affected by canal leakage.
\nSelenite/total selenium mass ratios in the East Canal samples ranged from about 0.02 to 0.13, indicating that about 2 to 13 percent of the total selenium in canal samples was composed of selenite. The increase in total selenium at W-N1 from before the irrigation season to the early irrigation season was accompanied by a decrease in the percentage of selenite from about 10 to 1 percent, indicating that selenate was added to the groundwater. A nitrate pulse occurred with the selenate pulse in W-N1 at the beginning of the irrigation season but apparently dissipated to a low enough concentration during the irrigation season to allow for selenate reduction to occur, as indicated by the relatively high percentages of selenite in W-N1 during the late irrigation season. W-N2 generally contained higher percentages of selenite than W-N1.
\nPercentages of selenite in W-M1 did not change in response to filling the canal and generally composed less than 1 percent of the total selenium in that well. The predominance of selenate in W-M1, and apparent lack of selenate reduction, cannot be explained by a lack of anoxic conditions in the groundwater because all the available dissolved-oxygen data indicate that concentrations were less than 0.5 milligrams per liter. The most likely explanation for the lack of selenate reduction in W-M1 is that the exceptionally high concentrations of nitrate in the groundwater (about 340 to 390 milligrams per liter as nitrogen) inhibited selenate reduction. These high nitrate concentrations presumably come from the Mancos Shale and its weathering products because there was no evidence for a human source of nitrate at the lower Gunnison River Basin wetland. The high concentrations of selenate in W-M1 may persist and eventually discharge to surface water unless nitrate concentrations are reduced to low enough levels to permit substantial selenate reduction to occur. Well W-M2 contained relatively low concentrations of total selenium and high percentages of selenite before and at the onset of the irrigation season. An increase in total selenium concentration associated with a drying and wetting period later in the summer was accompanied by a decrease in the percentage of selenite to near 0 percent, indicating that selenate was added to the groundwater. This pattern is consistent with the examples of increasing concentrations of total selenium in the other wells and presumably resulted from the dissolution of selenate-bearing salts in the unsaturated zone by rising water levels in W-M2.
\n","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165047","collaboration":"Prepared in cooperation with the Bureau of Reclamation and Colorado Water Conservation Board","usgsCitation":"Linard, J.I., McMahon, P.B., Arnold, L.R., and Thomas, J.C., 2017, Response of selenium concentrations in groundwater to seasonal canal leakage, lower Gunnison River Basin, Colorado, 2013 (ver. 1.1, January 2017): U.S. Geological Survey Scientific Investigations Report 2016–5047, 30 p., https://dx.doi.org/10.3133/sir20165047.","productDescription":"v, 30 p.","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2013-01-01","ipdsId":"IP-067265","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":333218,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2016/5047/versionHist.txt","text":"Version History","size":"4.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"SIR 2016-5047 Version History"},{"id":321476,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5047/sir20165047.pdf","text":"Report","size":"28.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5047"},{"id":321475,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5047/coverthb2.jpg"}],"country":"United States","state":"Colorado","county":"Montrose County","otherGeospatial":"Gunnison River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107.9583,\n 38.65\n ],\n [\n -107.9583,\n 38.6542\n ],\n [\n -107.9514,\n 38.6542\n ],\n [\n -107.9514,\n 38.65\n ],\n [\n -107.9583,\n 38.65\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: Originally posted May 23, 2016; Version 1.1: January 13, 2017","contact":"
Director, USGS Colorado Water Science Center
Box 25046, Mail Stop 415
Denver, CO 80225