In January 2001, the U.S. Geological Survey—in cooperation with the Edwards Aquifer Authority—began a study to refine and, if possible, extend previously derived (1995–96) relations between the stage in Medina Lake and recharge to the Edwards aquifer to include the effects of reservoir stages below 1,018 feet and greater than 1,046 feet above National Geodetic Vertical Datum of 1929. The principal objective of this present (2001–02) study was to estimate ground-water outflow (seepage) from Medina Lake, Diversion Lake, and from the Medina/Diversion Lake system through the calculation of water budgets representing steady-state conditions over as wide a range as possible in the stages of Medina and Diversion Lakes. The water budgets were compiled for selected periods during which time the water-budget components were inferred to be relatively stable and the influence of precipitation, stormwater runoff, and changes in storage were presumably minimal.
Water budgets for the Medina/Diversion Lake system were compiled for 127 water-budget periods ranging from 8 to 78 days from daily hydrologic data collected during March 1955–September 1964, October 1995–September 1996, and February 2001–June 2002. Budgets for Medina and Diversion Lakes were compiled for 14 periods ranging from 8 to 23 days from daily hydrologic data collected only during October 1995–September 1996 and April 2001–June 2002.
Linear equations were developed to relate the stage in Medina Lake to ground-water outflow from Medina Lake, Diversion Lake, and the Medina/Diversion Lake system. The computed mean rates of outflow from Medina Lake ranged from about 18 to 182 acre-feet per day between stages of 1,019 and 1,064 feet above National Geodetic Vertical Datum of 1929. The computed rates of outflow from Diversion Lake ranged from about -85 to 52 acre-feet per day. The rates of outflow from the entire lake system ranged from about 5 to 178 acre-feet per day between Medina Lake stages of 963 to 1,064 feet. It is assumed that all outflow from the lake system enters the ground-water system as recharge to the Edwards aquifer.
During the time that the stage in Medina Lake was greater than about 1,040 feet, Diversion Lake gained more water than it lost to the ground-water system and the rate of ground-water outflow from Medina Lake increased sharply while its stage was between about 1,043 and 1,045 feet. The observed outflow from Diversion Lake during this time decreased sharply to the extent that a net gain resulted—indicating that a substantial amount of the additional outflow from Medina Lake returned to Diversion Lake. When the stage in Medina Lake is at the spillway elevation of 1,064 feet, Diversion Lake appears to gain as much as 40 percent of the concurrent ground-water outflow from Medina Lake.
An indication of water moving from the lake system into the ground-water system and back to the surface-water system was observed in the most downstream reach of the Medina River, between Diversion Lake and the Medina River near Riomedina. During conditions of no flow over Diversion Dam, this reach of the Medina River gained from about 32 to 94 acre-feet per day, with the gain increasing with increasing stage in Diversion Lake.
The average of the monthly recharge to the Edwards aquifer from the Medina/Diversion Lake system—as estimated by the present study for the October 1995–September 2002 period—is 3,083 acre-feet, or about 56 percent of recharge computed for this period with a previously used (Lowry) method. The present study’s estimates of recharge for months with rising-lake stage conditions are about 44 percent of those computed with the previously used method, compared to about 60 percent for months with steady or falling-stage conditions. For stages greater than 1,045 feet, the present study estimated recharge to be about 52 percent of that computed with the previously used method, compared to about 64 percent at stages below 1,045 feet.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20045209","collaboration":"In cooperation with the Edwards Aquifer Authority","usgsCitation":"Slattery, R.N., and Miller, L.D., 2017, A water-budget analysis of Medina and Diversion Lakes and the Medina/Diversion Lake system, with estimated recharge to Edwards aquifer, San Antonio area, Texas (ver. 1.1, February 2017): U.S. Geological Survey Scientific Investigations Report 2004–5209, 41 p., https://doi.org/10.3133/sir20045209. ","productDescription":"Report: iv, 41 p.; Appendix; Data Release; Version History","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":181763,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":335301,"rank":7,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2004/5209/versionHist.txt","text":"Version History","size":"1.45 KB","linkFileType":{"id":2,"text":"txt"},"description":"Version History"},{"id":335300,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7ZS2TNF","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"Reanalysis of the Medina/Diversion Lake System Water-Budget, with Estimated Recharge to Edwards Aquifer, San Antonio Area, Texas"},{"id":335297,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2004/5209/coverthb.jpg"},{"id":335298,"rank":4,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2004/5209/sir20045209.pdf","text":"Report","size":"4.22 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2004–5209"},{"id":335299,"rank":5,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/publication/fs20173008","text":"Fact Sheet 2017–3008","size":"332 KB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2017–3008"},{"id":335302,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2004/5209/sir20045209_appendix1.pdf","text":"Appendix 1","size":"363 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2004–5209 Appendix 1"}],"country":"United States","state":"Texas","otherGeospatial":"Upper Medina Basin","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-98.7869,29.7168],[-98.8056,29.6968],[-98.8042,29.2513],[-98.8039,29.0884],[-99.4107,29.087],[-99.4132,29.6253],[-99.6033,29.6257],[-99.6031,29.9068],[-99.6908,29.9079],[-99.6915,29.9575],[-99.6923,30.0775],[-99.7577,30.0772],[-99.7576,30.2882],[-99.3032,30.289],[-99.3034,30.1398],[-98.9217,30.139],[-98.5896,30.1375],[-98.4138,29.9442],[-98.6478,29.7477],[-98.6493,29.7495],[-98.6508,29.7509],[-98.6514,29.7523],[-98.6529,29.7532],[-98.6534,29.7532],[-98.6555,29.7528],[-98.6561,29.7514],[-98.6561,29.7491],[-98.6567,29.7478],[-98.6583,29.7478],[-98.6593,29.7492],[-98.6609,29.7492],[-98.6624,29.7492],[-98.663,29.7483],[-98.6646,29.7465],[-98.6646,29.7447],[-98.6646,29.7433],[-98.6657,29.7415],[-98.6683,29.7415],[-98.6725,29.7429],[-98.6741,29.742],[-98.6762,29.7407],[-98.681,29.7389],[-98.6926,29.7381],[-98.6984,29.7364],[-98.7016,29.7341],[-98.7042,29.7332],[-98.7084,29.7337],[-98.711,29.7342],[-98.7132,29.7315],[-98.7153,29.7283],[-98.719,29.7274],[-98.7222,29.728],[-98.7279,29.7294],[-98.7316,29.7294],[-98.7342,29.7285],[-98.7343,29.7267],[-98.7338,29.7235],[-98.7333,29.7208],[-98.7407,29.7185],[-98.747,29.7186],[-98.7527,29.721],[-98.7595,29.7224],[-98.768,29.7216],[-98.7801,29.7204],[-98.7843,29.7195],[-98.7869,29.7168]]]},\"properties\":{\"name\":\"Bandera\",\"state\":\"TX\"}}]}","edition":"Originally posted December 22, 2004; Version 1.1: February 15, 2017","contact":"Director, Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754
This report presents results of the evaluation and interpretation of hydrologic and water-quality data collected as part of a cooperative program between the U.S. Geological Survey and the U.S. Environmental Protection Agency. Streamflow, phosphorus, and solids dissolved and suspended in stream water were the focus of monitoring by the U.S. Geological Survey at 10 sites on 9 selected tributaries to Lake Ontario during the period from October 2011 through September 2014. Streamflow yields (flow per unit area) were the highest from the Salmon River Basin due to sustained yields from the Tug Hill aquifer. The Eighteenmile Creek streamflow yields also were high as a result of sustained base flow contributions from a dam just upstream of the U.S. Geological Survey monitoring station at Burt. The lowest streamflow yields were measured in the Honeoye Creek Basin, which reflects a decrease in flow because of withdrawals from Canadice and Hemlock Lakes for the water supply of the City of Rochester. The Eighteenmile Creek and Oak Orchard Creek Basins had relatively high yields due in part to groundwater contributions from the Niagara Escarpment and seasonal releases from the New York State Barge Canal.
Annual constituent yields (load per unit area) of suspended solids, phosphorus, orthophosphate, and dissolved solids were computed to assess the relative contributions and allow direct comparison of loads among the monitored basins. High yields of total suspended solids were attributed to agricultural land use in highly erodible soils at all sites. The Genesee River, Irondequoit Creek, and Honeoye Creek had the highest concentrations and largest mean yields of total suspended solids (165 short tons per square mile [t/mi2], 184 t/mi2, and 89.7 t/mi2, respectively) of the study sites.
Samples from Eighteenmile Creek, Oak Orchard Creek at Kenyonville, and Irondequoit Creek had the highest concentrations and largest mean yields of phosphorus (0.27 t/mi2, 0.26 t/mi2, and 0.20 t/mi2, respectively) and orthophosphate (0.17 t/mi2, 0.13 t/mi2, and 0.04 t/mi2, respectively) of the study sites. These results were attributed to a combination of sources, including discharges from wastewater treatment plants, diversions from the New York State Barge Canal, and manure and fertilizers applied to agricultural land. Yields of phosphorus also were high in the Genesee River Basin (0.17 t/mi2) and were presumably associated with nutrient and sediment transport from agricultural land and from streambank erosion. The Salmon and Black Rivers, which drain a substantial amount of forested land and are influenced by large groundwater discharges, had the lowest concentrations and yields of phosphorus and orthophosphate of the study sites.
Mean annual yields of dissolved solids were the highest in Irondequoit Creek due to a high percentage of urbanized area in the basin and in Oak Orchard Creek at Kenyonville and in Eighteenmile Creek due to groundwater contributions from the Niagara Escarpment. High yields of dissolved solids of 840 t/mi2, 829 t/mi2, and 715 t/mi2, respectively, from these basins can be attributed to seasonal chloride yields associated with use of road deicing salts. The Niagara Escarpment can produce large amounts of dissolved solids from the dissolution of minerals (a continual process reflected in base flow samples). Groundwater inflows in the Salmon River have very low concentrations of dissolved solids due to minimal bedrock interaction along the Tug Hill Plateau and discharge from the Tug Hill sand and gravel aquifer, which has minimal mineralization.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165084","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency as part of the Great Lakes Restoration Initiative","usgsCitation":"Hayhurst, B.A., Fisher, B.N., and Reddy, J.E., 2016, Streamflow and estimated loads of phosphorus and dissolved and suspended solids from selected tributaries to Lake Ontario, New York, water years 2012–14: U.S. Geological Survey Scientific Investigations Report 2016–5084, 34 p., https://dx.doi.org/10.3133/sir20165084.","productDescription":"Report: viii, 46 p. Appendixes: 1-2","startPage":"1","endPage":"33","numberOfPages":"46","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-065269","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":325295,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5084/attachments/sir20165084_appendix2.xlsx","text":"Appendix 2 - Water-quality data - MS Excel","size":"80.7 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016-5084"},{"id":325296,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5084/attachments/sir20165084_appendix2.csv","text":"Appendix 2 - Water-quality data- CSV","size":"45.4 KB cvs","description":"SIR 2016-5084"},{"id":325384,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5084/attachments/sir20165084_appendix1.csv","text":"Appendix 1 -Streamflow and streamflow yields - CSV","size":"127 KB cvs","description":"SIR 2016-5084"},{"id":325291,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5084/coverthb.jpg"},{"id":325292,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5084/sir20165084.pdf","text":"Report","size":"6.55 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5084"},{"id":325293,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5084/attachments/sir20165084_appendix1.xlsx","text":"Appendix 1 - Streamflow and streamflow yields - MS Excel","size":"328 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016-5084"}],"country":"United States","state":"New York","otherGeospatial":"Lake Ontario","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78.88732910156249,\n 42.92827401776912\n ],\n [\n -78.9971923828125,\n 42.976520698105546\n ],\n [\n -78.9862060546875,\n 43.02071359427862\n ],\n [\n -78.9532470703125,\n 43.072900581493215\n ],\n [\n -79.03564453124999,\n 43.092960677116295\n ],\n [\n -79.024658203125,\n 43.16111586765961\n ],\n [\n -79.03564453124999,\n 43.28520334369384\n ],\n [\n -79.2059326171875,\n 43.432977075795606\n ],\n [\n -78.6785888671875,\n 43.61619382369188\n ],\n [\n -76.783447265625,\n 43.620170616189924\n ],\n [\n -76.4208984375,\n 44.10336537791152\n ],\n [\n -76.058349609375,\n 44.280604121518145\n ],\n [\n -75.9979248046875,\n 44.29240108529005\n ],\n [\n -76.0089111328125,\n 43.846412964702395\n ],\n [\n -76.1846923828125,\n 43.1090040242731\n ],\n [\n -76.2066650390625,\n 42.577354839557856\n ],\n [\n -77.1185302734375,\n 42.25291778330197\n ],\n [\n -78.88732910156249,\n 42.92827401776912\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
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30 Brown Road
Ithaca, NY 14850
Or visit our Web site at: http://ny.water.usgs.gov
","tableOfContents":"Trends in long-term water-quality and streamflow data from 14 water-quality monitoring sites in Connecticut were evaluated for water years 1974–2013 and 2001–13, coinciding with implementation of the Clean Water Act of 1972 and the Connecticut Nitrogen Credit Exchange program, as part of an assessment of nutrient and chloride concentrations and loads discharged to Long Island Sound. In this study, conducted by the U.S. Geological Survey in cooperation with the Connecticut Department of Energy and Environmental Protection, data were evaluated using a recently developed methodology of weighted regressions with time, streamflow, and season. Trends in streamflow were evaluated using a locally weighted scatterplot smoothing method. Annual mean streamflow increased at 12 of the 14 sites averaging 8 percent during the entire study period, primarily in the summer months, and increased by an average of 9 percent in water years 2001–13, primarily during summer and fall months. Downward trends in flow-normalized nutrient concentrations and loads were observed during both periods for most sites for total nitrogen, total Kjeldahl nitrogen, nitrite plus nitrate nitrogen, total phosphorus, and total organic carbon. Average flow-normalized loads of total nitrogen decreased by 23.9 percent for the entire period and 10.9 percent for the period of water years 2001‒13. Major factors contributing to decreases in flow-normalized loads and concentrations of these nutrients include improvements in wastewater treatment practices, declining atmospheric wet deposition of nitrogen, and changes in land management and land use.
\nLoads of dissolved silica (DSi; flow-normalized and non-flow-normalized) increased slightly at most stations during the study period and were positively correlated to urbanized land in the basin and negatively correlated to area of open water. Concentrations and loads of chloride increased at 12 of the 14 sites during both periods. Increases likely are the result of an increase in the use of salt for deicing, as well as other factors related to urbanization and population growth, such as increases in wastewater discharge and discharge from septic systems.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155189","collaboration":"Prepared in cooperation with the Connecticut Department of Energy and Environmental Protection","usgsCitation":"Mullaney, J.R., 2016, Nutrient, organic carbon, and chloride concentrations and loads in selected Long Island Sound tributaries—Four decades of change following the passage of the Federal Clean Water Act: U.S. Geological Survey Scientific Investigations Report 2015–5189, 47 p., https://dx.doi.org/10.3133/sir20155189.","productDescription":"Report: viii, 47 p.; Appendixes: 2.1-2.7","numberOfPages":"60","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-068448","costCenters":[{"id":196,"text":"Connecticut Water Science Center","active":true,"usgs":true}],"links":[{"id":318574,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5189/downloads/sir20155189_appendix2-7.xlsx","text":"Appendix 2.7","size":"43 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"Appendix 2.7 SIR 2015-5189","linkHelpText":"- Total chloride results"},{"id":318573,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5189/downloads/sir20155189_appendix2-6.xlsx","text":"Appendix 2.6","size":"43 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"Appendix 2.6 SIR 2015-5189","linkHelpText":"- Total dissolved silica results"},{"id":318566,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5189/coverthb2.jpg"},{"id":318568,"rank":2,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5189/downloads/sir20155189_appendix2-1.xlsx","text":"Appendix 2.1","size":"46 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"Appendix 2.1 SIR 2015-5189","linkHelpText":"- Total nitrogen results"},{"id":371144,"rank":9,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5189/sir20155189.pdf","text":"Report","size":"2.39 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5189"},{"id":318569,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5189/downloads/sir20155189_appendix2-2.xlsx","text":"Appendix 2.2","size":"44 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"Appendix 2.2 SIR 2015-5189","linkHelpText":"- Total Kjeldahl nitrogen results"},{"id":318570,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5189/downloads/sir20155189_appendix2-3.xlsx","text":"Appendix 2.3","size":"46 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"Appendix 2.3 SIR 2015-5189","linkHelpText":"- Nitrite plus nitrate nitrogen results"},{"id":318571,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5189/downloads/sir20155189_appendix2-4.xlsx","text":"Appendix 2.4","size":"45 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"Appendix 2.4 SIR 2015-5189","linkHelpText":"- Total phosphorus results"},{"id":318572,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5189/downloads/sir20155189_appendix2-5.xlsx","text":"Appendix 2.5","size":"43 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"Appendix 2.5 SIR 2015-5189","linkHelpText":"- Total organic carbon results"}],"country":"United States","state":"Connecticut","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.47381591796875,\n 41.0772807426254\n ],\n [\n -73.48480224609375,\n 41.31288691435732\n ],\n [\n -73.2183837890625,\n 41.7672146942102\n ],\n [\n -72.94647216796874,\n 41.97378534488489\n ],\n [\n -72.7459716796875,\n 42.002366213375524\n ],\n [\n -72.5372314453125,\n 42.01665183556825\n ],\n [\n -71.9549560546875,\n 42.02889410108475\n ],\n [\n -71.90277099609375,\n 41.781552998900345\n ],\n [\n -71.96319580078125,\n 41.32732632036622\n ],\n [\n -72.22137451171874,\n 41.292253642159466\n ],\n [\n -72.476806640625,\n 41.263356094059326\n ],\n [\n -72.63885498046875,\n 41.263356094059326\n ],\n [\n -72.75970458984375,\n 41.25716209782705\n ],\n [\n -72.88330078125,\n 41.24890252240322\n ],\n [\n -72.9766845703125,\n 41.24270715552139\n ],\n [\n -73.26507568359375,\n 41.11246878918086\n ],\n [\n -73.465576171875,\n 41.05035951931887\n ],\n [\n -73.47381591796875,\n 41.0772807426254\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
101 Pitkin Street
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Or visit our Web site at
http://newengland.water.usgs.gov/
Human activities can alter the environment to the point that it is unsuitable to the native species resulting in a loss of biodiversity. Ecologists understand the importance of biodiversity and the conservation of vulnerable species. Species that are narrowly endemic are considered to be particularly vulnerable because they often use specific habitats that are highly susceptible to human disturbance. The basic components of species conservation are 1) delineation of the spatial distribution of the species, 2) understanding how the species interacts with its environment, and 3) employing management strategies based on the ecology of the species. In this study, we investigated several crayfish species endemic to the Ouachita Mountains in Oklahoma and Arkansas. We established the spatial distributions (i.e., range) of the crayfish using Maximum Entropy species distribution modeling. We then investigated crayfish habitat use with quantitative sampling and a paired movement study. Finally, we evaluated the ability of crayfish to burrow under different environmental conditions in a controlled laboratory setting. Crayfish distribution at the landscape scale was largely driven by climate, geology and elevation. In general, the endemic crayfish in this study occurred above 300-m elevation where the geology was dominated by sandstone and shale, and rainfall totals were the highest compared to the rest of the study region. Our quantitative data indicated crayfish did not select for specific habitat types at the reach scale; however, crayfish appeared to continue to use shallow and dry habitat even as the streams dried. Movement by passive integrated transponder (PIT) tagged crayfish was highly variable but crayfish tended to burrow in response to drought rather than migrate to wet habitat. Controlled laboratory experiments revealed smaller substrate size (pebble) restricted crayfish burrowing more than larger substrates (cobble). We also found excess fine sediment restricted crayfish burrowing regardless of dominant substrate size. Our results suggest climate change and sedimentation resulting from land-use practices, combined with increased water withdrawals have the potential to alter crayfish distributions and affect persistence of some crayfish populations.
","language":"English","publisher":"U.S. Fish and Wildlife Service","publisherLocation":"OK","usgsCitation":"Brewer, S.K., and Dyer, J.J., 2016, The Impacts of flow alterations to crayfishes in Southeastern Oklahoma, with an emphasis on the mena crayfish (orconectes menae), ii, 103 p.","productDescription":"ii, 103 p.","ipdsId":"IP-054991","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":339982,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":339981,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://digitalmedia.fws.gov/cdm/ref/collection/document/id/2056"}],"country":"United States","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58f877b2e4b0b7ea54521c0b","contributors":{"authors":[{"text":"Brewer, Shannon K. 0000-0002-1537-3921 skbrewer@usgs.gov","orcid":"https://orcid.org/0000-0002-1537-3921","contributorId":2252,"corporation":false,"usgs":true,"family":"Brewer","given":"Shannon","email":"skbrewer@usgs.gov","middleInitial":"K.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":640997,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dyer, Joseph J.","contributorId":140681,"corporation":false,"usgs":false,"family":"Dyer","given":"Joseph","email":"","middleInitial":"J.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":692197,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70178429,"text":"70178429 - 2016 - Regional geophysics of western Utah and eastern Nevada, with emphasis on the Confusion Range","interactions":[],"lastModifiedDate":"2017-04-18T10:44:21","indexId":"70178429","displayToPublicDate":"2017-04-18T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":4,"text":"Book"},"title":"Regional geophysics of western Utah and eastern Nevada, with emphasis on the Confusion Range","docAbstract":"As part of a long term geologic and hydrologic study of several regional\ngroundwater flow systems in western Utah and eastern Nevada, the U.S. \nGeological Survey was contracted by the Southern Nevada Water Authority \nto provide geophysical data. The primary object of these data was to enable \nconstruction of the geological framework of the flow systems. The main \nnew geophysical data gathered during the study were gravity observations, \nand existing aeromagnetic data were also compiled. These data resulted in \nregional maps of the isostatic gravity and aeromagnetic fields of the area.\nThe isostatic gravity map shows a north-south grain to most of the area, \nwhich was imparted by post-20 Ma basin-range tectonism; whereas the \naeromagnetic map shows an east-west grain to the area, imparted by \nEocene to lower Miocene calc-alkaline calderas and source intrusions. \nTo de-emphasize surface and near-surface features and to gain greater \ninsight into contributions from deeper sources, the isostatic gravity \nanomalies were upward continued by 3 km and the aeromagnetic data \nwere transformed to their magnetic potential (\"pseudogravity\"). \nIdentification of maxima of the horizontal gradients in the gravity and \nmagnetic-potential data helped define deep-seated crustal blocks that are \ncharacterized by major changes in density and magnetization. Maps \nshowing these maxima were useful in defining large faults, especially \nrange-bounding faults, and margins of igneous bodies and calderas. A \ngravity inversion method was used to separate the isostatic residual anomaly \ninto pre-Cenozoic basement and young basin fill. Inasmuch as the primary \naquifer in the area is sedimentary basin fill, this method is especially valuable\nfor hydrogeologic analyses because it estimates the thickness of the fill.\nAs befits its name, the geology of the Confusion Range of Utah has been a \npoint of contention for many years, so we looked at it in greater detail in the \ncourse of our regional study. The northern part of the range is underlain by a \nlarge gravity high, which continues south through the Conger Range, Burbank \nHills, and northern Mountain Home Range. This is the \"structural trough\" \nreported in the literature that was mapped as the axial part of a Sevier \nsynclinorium and contains the maximum thickness (7 km) of high-density \ncarbonates in the area, thus the largest high gravity anomaly.","language":"English","publisher":"Utah Geological Association","usgsCitation":"Mankinen, E.A., Rowley, P.D., Dixon, G.L., and McKee, E.H., 2016, Regional geophysics of western Utah and eastern Nevada, with emphasis on the Confusion Range, v. 45, 13 p.","productDescription":"13 p.","startPage":"147","endPage":"166","ipdsId":"IP-073281","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":339850,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":339848,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.mapstore.utah.gov/uga45.html"}],"country":"United States","state":"Utah","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.0380859375,\n 42.00032514831621\n ],\n [\n -114.06005859375,\n 36.98500309285596\n ],\n [\n -109.05029296875,\n 36.98500309285596\n ],\n [\n -109.039306640625,\n 41.00477542222947\n ],\n [\n -111.03881835937499,\n 40.9964840143779\n ],\n [\n -111.0498046875,\n 42.00032514831621\n ],\n [\n -114.0380859375,\n 42.00032514831621\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"45","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58f725e5e4b0b7ea5451eec4","contributors":{"authors":[{"text":"Mankinen, Edward A. 0000-0001-7496-2681 emank@usgs.gov","orcid":"https://orcid.org/0000-0001-7496-2681","contributorId":1054,"corporation":false,"usgs":true,"family":"Mankinen","given":"Edward","email":"emank@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":691624,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rowley, Peter D.","contributorId":27435,"corporation":false,"usgs":true,"family":"Rowley","given":"Peter","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":691625,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Dixon, Gary L.","contributorId":23571,"corporation":false,"usgs":true,"family":"Dixon","given":"Gary","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":691626,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McKee, Edwin H. mckee@usgs.gov","contributorId":3728,"corporation":false,"usgs":true,"family":"McKee","given":"Edwin","email":"mckee@usgs.gov","middleInitial":"H.","affiliations":[],"preferred":true,"id":691627,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70187206,"text":"70187206 - 2016 - Establishing links between streamflow and ecological integrity in the Sudbury River (Northeastern U.S.)","interactions":[],"lastModifiedDate":"2017-04-27T09:59:13","indexId":"70187206","displayToPublicDate":"2016-12-31T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5373,"text":"Cooperator Science Series","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"122-2016","title":"Establishing links between streamflow and ecological integrity in the Sudbury River (Northeastern U.S.)","docAbstract":"With increased pressure from a growing human population, managers are challenged to understand how novel disturbances (e.g., climate change, increased water withdrawals, urbanization) may affect natural resources. The Sudbury River is a National Wild and Scenic River located in suburban Boston, Massachusetts (Northeastern US) with myriad impairments (e.g., mainstem impoundments, withdrawals, and urbanization) that is under increasing pressure from hydrologic alteration. We sampled fish, mussel, and macroinvertebrate assemblages in the Sudbury River and used species traits to investigate potential effects of past and future flow alteration on biota. Analysis of 33 years of stream gage data indicates continued hydrologic alteration of the Sudbury River, likely related to increased urbanization and water withdrawals over that time. These changes include a roughly 200% increase in rise rates of flows, an approximate 65% decrease in 1-day minimum flows, and a trend towards increasing high flow pulse counts. Biotic sampling in summer of 2014 demonstrated that the Sudbury River is now dominated by generalist species. Of five mussel species sampled, all are generalists in their habitat requirements. Though one mussel species of special concern was sampled, the most abundant species collected were the widespread Eastern elliptio (58%) and Eastern lampmussel (40%). We used the target fish community (TFC) model to assess the degree to which the fish assemblage deviated from that expected for a river with similar zoogeographic and physical features. Overall, the current community has a 22.7% similarity to the TFC. Of the four fluvial specialist species present in the TFC, only fallfish was sampled in our study. While the TFC showed that the historical assemblage was likely dominated by fluvial specialist and fluvial dependent species, the current assemblage is overwhelmingly dominated by macrohabitat generalists (90.6% of fishes sampled). These results are consistent with other studies that show shifts in assemblages from fluvial specialists to habitat generalists with hydrologic alteration. If the current trends continue, it is likely that biotic assemblages will experience increasing pressure from hydrologic alteration. While hydrologic alteration is likely impacting biotic assemblages in the Sudbury River, other factors such as high temperatures, low dissolved oxygen, high nutrients, low availability of high-quality habitat, and poor habitat connectivity may also be negatively impacting biotic assemblages. Comparisons to other rivers and a complete longitudinal habitat survey could help to identify availability of unique habitats and representativeness of this study. While this study suggests impacts of flow on biota, future studies with quantitative, habitat-specific sampling during different flow levels could help to directly identify links between hydrologic alteration and biotic impairment in the Sudbury River.
","language":"English","publisher":"U.S. Fish and Wildlife Service","usgsCitation":"Roy, A.H., Jane, S.F., Hazelton, P.D., Richards, T.A., Finn, J.T., and Randhir, T.O., 2016, Establishing links between streamflow and ecological integrity in the Sudbury River (Northeastern U.S.): Cooperator Science Series 122-2016, vi, 78 p.","productDescription":"vi, 78 p.","ipdsId":"IP-065793","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":340465,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":340464,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://digitalmedia.fws.gov/cdm/singleitem/collection/document/id/2152/rec/19"}],"country":"United States","state":"Massachussetts","otherGeospatial":"Sudbury River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.63497924804688,\n 42.13998671872691\n ],\n [\n -71.17767333984375,\n 42.13998671872691\n ],\n [\n -71.17767333984375,\n 42.5530802889558\n ],\n [\n -71.63497924804688,\n 42.5530802889558\n ],\n [\n -71.63497924804688,\n 42.13998671872691\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5901b1bae4b0c2e071a99b96","contributors":{"authors":[{"text":"Roy, Allison H. 0000-0002-8080-2729 aroy@usgs.gov","orcid":"https://orcid.org/0000-0002-8080-2729","contributorId":4240,"corporation":false,"usgs":true,"family":"Roy","given":"Allison","email":"aroy@usgs.gov","middleInitial":"H.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":693023,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jane, Stephen F.","contributorId":191442,"corporation":false,"usgs":false,"family":"Jane","given":"Stephen","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":693056,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hazelton, Peter D.","contributorId":171765,"corporation":false,"usgs":false,"family":"Hazelton","given":"Peter","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":693057,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Richards, Todd A.","contributorId":52266,"corporation":false,"usgs":true,"family":"Richards","given":"Todd","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":693058,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Finn, John T.","contributorId":43398,"corporation":false,"usgs":false,"family":"Finn","given":"John","email":"","middleInitial":"T.","affiliations":[{"id":16720,"text":"Department of Environmental Conservation, University of Massachusetts, Amherst, MA 01003-9485, USA","active":true,"usgs":false}],"preferred":false,"id":693059,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Randhir, Timothy O.","contributorId":191443,"corporation":false,"usgs":false,"family":"Randhir","given":"Timothy","email":"","middleInitial":"O.","affiliations":[],"preferred":false,"id":693060,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70178977,"text":"tm1D6 - 2016 - Continuous-flow centrifugation to collect suspended sediment for chemical analysis","interactions":[],"lastModifiedDate":"2017-01-04T14:42:01","indexId":"tm1D6","displayToPublicDate":"2016-12-22T19:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":335,"text":"Techniques and Methods","code":"TM","onlineIssn":"2328-7055","printIssn":"2328-7047","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1-D6","title":"Continuous-flow centrifugation to collect suspended sediment for chemical analysis","docAbstract":"Recent advances in suspended-sediment monitoring tools and surrogate technologies have greatly improved the ability to quantify suspended-sediment concentrations and to estimate daily, seasonal, and annual suspended-sediment fluxes from rivers to coastal waters. However, little is known about the chemical composition of suspended sediment, and how it may vary spatially between water bodies and temporally within a single system owing to climate, seasonality, land use, and other natural and anthropogenic drivers. Many water-quality contaminants, such as organic and inorganic chemicals, nutrients, and pathogens, preferentially partition in sediment rather than water. Suspended sediment-bound chemical concentrations may be undetected during analysis of unfiltered water samples, owing to small water sample volumes and analytical limitations. Quantification of suspended sediment‑bound chemical concentrations is needed to improve estimates of total chemical concentrations, chemical fluxes, and exposure levels of aquatic organisms and humans in receiving environments. Despite these needs, few studies or monitoring programs measure the chemical composition of suspended sediment, largely owing to the difficulty in consistently obtaining samples of sufficient quality and quantity for laboratory analysis.
A field protocol is described here utilizing continuous‑flow centrifugation for the collection of suspended sediment for chemical analysis. The centrifuge used for development of this method is small, lightweight, and portable for the field applications described in this protocol. Project scoping considerations, deployment of equipment and system layout options, and results from various field and laboratory quality control experiments are described. The testing confirmed the applicability of the protocol for the determination of many inorganic and organic chemicals sorbed on suspended sediment, including metals, pesticides, polycyclic aromatic hydrocarbons, and polychlorinated biphenyls. The particle-size distribution of the captured sediment changes to a more fine-grained sample during centrifugation, and the necessity to account for this change when extrapolating chemical concentrations on the centrifuged sediment sample to the environmental water system is discussed.
The data produced using this method will help eliminate a data gap of suspended sediment-bound chemical concentrations, and will support management decisions, such as chemical source-control efforts or in-stream restoration activities. When coupled with streamflow and sediment flux data, it will improve estimates of riverine chemical fluxes, and will aid in assessing the importance and impacts of suspended sediment-bound chemicals to downstream freshwater and coastal marine ecosystems.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section D: Water quality in Book 1: Collection of water data by direct measurement","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm1D6","collaboration":"Prepared in cooperation with the National Water Quality Monitoring Council and Washington State Department of Ecology","usgsCitation":"Conn, K.E., Dinicola, R.S., Black, R.W., Cox, S.E., Sheibley, R.W., Foreman, J.R., Senter, C.A., and Peterson, N.T., 2016, Continuous-flow centrifugation to collect suspended sediment for chemical analysis: U.S. Geological Survey Techniques and Methods, book 1, chap. D6, 31 p., plus appendixes, https://doi.org/10.3133/tm1D6.","productDescription":"Report: viii, 31 p.; Appendixes: A-E","numberOfPages":"44","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-079905","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":332505,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/tm/01/d6/tm1d6_appendixb.pdf","text":"Appendix B","size":"100 KB","linkFileType":{"id":1,"text":"pdf"},"description":"TM1-D6 Appendix B"},{"id":332503,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/01/d6/tm1d6.pdf","text":"Report","size":"2.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"TM1-D6 Report PDF"},{"id":332504,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/tm/01/d6/tm1d6_appendixa.xlsx","text":"Appendix A","size":"102 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"TM1-D6 Appendix A"},{"id":332506,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/tm/01/d6/tm1d6_appendixc.pdf","text":"Appendix C","size":"142 KB","linkFileType":{"id":1,"text":"pdf"},"description":"TM1-D6 Appendix C"},{"id":332507,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/tm/01/d6/tm1d6_appendixd.pdf","text":"Appendix D","size":"145 KB","linkFileType":{"id":1,"text":"pdf"},"description":"TM1-D6 Appendix D"},{"id":332508,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/tm/01/d6/tm1d6_appendixe.pdf","text":"Appendix E","size":"930 KB","linkFileType":{"id":1,"text":"pdf"},"description":"TM1-D6 Appendix E"},{"id":332502,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/tm/01/d6/coverthb.jpg"}],"publicComments":"This report is Chapter 6 of Section D: Water quality in Book 1: Collection of water data by direct measurement.","contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
http://wa.water.usgs.gov
Suspended-sediment and total phosphorus loads were computed for two sites in the Upper Klamath Basin on the Wood and Williamson Rivers, the two main tributaries to Upper Klamath Lake. High temporal resolution turbidity and acoustic backscatter data were used to develop surrogate regression models to compute instantaneous concentrations and loads on these rivers. Regression models for the Williamson River site showed strong correlations of turbidity with total phosphorus and suspended-sediment concentrations (adjusted coefficients of determination [Adj R2]=0.73 and 0.95, respectively). Regression models for the Wood River site had relatively poor, although statistically significant, relations of turbidity with total phosphorus, and turbidity and acoustic backscatter with suspended sediment concentration, with high prediction uncertainty. Total phosphorus loads for the partial 2014 water year (excluding October and November 2013) were 39 and 28 metric tons for the Williamson and Wood Rivers, respectively. These values are within the low range of phosphorus loads computed for these rivers from prior studies using water-quality data collected by the Klamath Tribes. The 2014 partial year total phosphorus loads on the Williamson and Wood Rivers are assumed to be biased low because of the absence of data from the first 2 months of water year 2014, and the drought conditions that were prevalent during that water year. Therefore, total phosphorus and suspended-sediment loads in this report should be considered as representative of a low-water year for the two study sites. Comparing loads from the Williamson and Wood River monitoring sites for November 2013–September 2014 shows that the Williamson and Sprague Rivers combined, as measured at the Williamson River site, contributed substantially more suspended sediment to Upper Klamath Lake than the Wood River, with 4,360 and 1,450 metric tons measured, respectively.
Surrogate techniques have proven useful at the two study sites, particularly in using turbidity to compute suspended-sediment concentrations in the Williamson River. This proof-of-concept effort for computing total phosphorus concentrations using turbidity at the Williamson and Wood River sites also has shown that with additional samples over a wide range of flow regimes, high-temporal-resolution total phosphorus loads can be estimated on a daily, monthly, and annual basis, along with uncertainties for total phosphorus and suspended-sediment concentrations computed using regression models. Sediment-corrected backscatter at the Wood River has potential for estimating suspended-sediment loads from the Wood River Valley as well, with additional analysis of the variable streamflow measured at that site. Suspended-sediment and total phosphorus loads with a high level of temporal resolution will be useful to water managers, restoration practitioners, and scientists in the Upper Klamath Basin working toward the common goal of decreasing nutrient and sediment loads in Upper Klamath Lake.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165167","collaboration":"Prepared in cooperation with the Bureau of Reclamation and the Klamath Tribes","usgsCitation":"Schenk, L.N., Anderson, C.W., Diaz, Paul, and Stewart, M.A., 2016, Evaluating external nutrient and suspended-sediment loads to Upper Klamath Lake, Oregon, using surrogate regressions with real-time turbidity and acoustic backscatter data: U.S. Geological Survey Scientific Investigations Report 2016–5167, 46 p., https://doi.org/10.3133/sir20165167.","productDescription":"vii, 46 p.","numberOfPages":"58","onlineOnly":"Y","ipdsId":"IP-075160","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":332500,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5167/sir20165167.pdf","text":"Report","size":"6.5","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5167 Report PDF"},{"id":332499,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5167/coverthb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Upper Klamath Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.3,\n 42.0\n ],\n [\n -122.3,\n 43.3\n ],\n [\n -120.4,\n 43.3\n ],\n [\n -120.4,\n 42.0\n ],\n [\n -122.3,\n 42.0\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
Estimates of juvenile salmon survival are important data for fishery managers in the Yakima River Basin. Radiotelemetry studies during 2012–14 showed that tagged juvenile Chinook salmon (Oncorhynchus tshawytscha) that passed through the fish bypass at Roza Dam had lower survival than fish that passed through other routes at the dam. That study also identified flow-survival relationships in the reaches between the Roza Dam tailrace and Sunnyside Dam. During 2012–14, survival also was estimated through reaches downstream of Sunnyside Dam, but generally, sample sizes were low and the estimates were imprecise. In 2016, we conducted an evaluation using acoustic cameras and acoustic telemetry to build on information collected during the previous study. The goal of the 2016 research was to identify areas where mortality occurs in the fish bypass at Roza Dam, and to estimate reach-specific survival in reaches downstream of the dam. The 2016 study included juvenile Chinook salmon and coho salmon (O. kisutch).
Three acoustic cameras were used to observe fish behavior (1) near the entrances to the fish bypass, (2) at a midway point in the fish bypass (convergence vault), and (3) at the bypass outfall. In total, 504 hours of acoustic camera footage was collected at these locations. We determined that smolt-sized fish (95–170 millimeters [mm]) were present in the highest proportions at each location, but predator-sized fish (greater than 250 mm) also were present at each site. Fish presence generally peaked during nighttime hours and crepuscular periods, and was low during daytime hours. In the convergence vault, smolt-sized fish exhibited holding behavior patterns, which may explain why some fish delayed while passing through the bypass.
Some of the acoustic-tagged fish were delayed in the fish bypass following release, but there was no evidence to suggest that they experienced higher mortality than fish that were released at the bypass outfall or downstream of the dam. Most of the tagged fish that were released in the fish bypass moved downstream and re-entered the river within 12 hours, but 9.8 percent of the Chinook salmon and 15.7 percent of the coho salmon remained in the bypass for 2.5–17.4 days. We developed a set of models for Chinook salmon and coho salmon and used model selection to determine if release site was an important predictor of survival of tagged fish. The models that provided the best fit to the Chinook salmon and coho salmon datasets did not include release site as a covariate. Furthermore, survival estimates for groups of fish from the various release sites were nearly identical for both species. Based on these observations, it appears that passage through the fish bypass did not result in increased mortality relative to groups of fish released downstream of the bypass.
Juvenile Chinook salmon migrated downstream faster than juvenile coho salmon and survival for each species varied with release timing. Median travel time from release at Roza Dam to arrival at a detection gate located at river kilometer (rkm) 527.8 on the Columbia River was 15.4 days for Chinook salmon and 37.4 days for coho salmon. Cumulative survival from Roza Dam to the Columbia River detection gate ranged from 0.299 to 0.678 for Chinook salmon, and from 0.321 to 0.627 for coho salmon. Survival was highest for both species when tagged fish were released in mid-April and lowest when tagged fish were released in early-May. Reach-specific survival estimates were standardized to create estimates that described survival per 100 rkm, which showed that survival was very low (less than 0.500) for some release groups, particularly in the Roza, Sunnyside, and Chandler diversion reaches. A more extensive analysis of reach-specific survival is planned for this dataset, which should provide insights into covariates that affected survival during 2016.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161210","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Kock, T.J., Perry, R.W., and Hansen, A.C., 2016, Survival of juvenile Chinook salmon and coho salmon in the Roza Dam fish bypass and in downstream reaches of the Yakima River, Washington, (ver. 1.1, April 2017): U.S. Geological Survey Open-File Report 2016–1210, 32 p., https://doi.org/10.3133/ofr20161210.","productDescription":"vi, 32 p.","numberOfPages":"42","onlineOnly":"Y","ipdsId":"IP-079554","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":332490,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1210/ofr20161210.pdf","text":"Report","size":"9.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1210 Report PDF"},{"id":339521,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2016/1210/versionHist.txt","text":"Version 1.1","size":"3 KB","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2016-1210 Version History"},{"id":339519,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1210/coverthb3.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Roza Dam, Yakima River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.53076171875,\n 46.14178273759234\n ],\n [\n -121.53076171875,\n 47.46523622438362\n ],\n [\n -119.04235839843749,\n 47.46523622438362\n ],\n [\n -119.04235839843749,\n 46.14178273759234\n ],\n [\n -121.53076171875,\n 46.14178273759234\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: Originally posted December 22, 2016; Version 1.1: April 10, 2017","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115
https://wfrc.usgs.gov/
Discharge from springs in Florida is sourced from aquifers, such as the Upper Floridan aquifer, which is overlain by an upper confining unit that locally can have properties of an aquifer. Water levels in aquifers are affected by several factors, such as precipitation, recharge, and groundwater withdrawals, which in turn can affect discharge from springs. Therefore, identifying groundwater sources and recharge characteristics can be important in assessing how these factors might affect flows and water levels in springs and can be informative in broader applications such as groundwater modeling. Recharge characteristics include the residence time of water at the surface, apparent age of recharge, and recharge water temperature.
The groundwater sources and recharge characteristics of three springs that discharge from the banks of the Suwannee River in northern Florida were assessed for this study: Bell Springs, White Springs, and Suwannee Springs. Sources of groundwater were also assessed for a 150-foot-deep well finished within the Upper Floridan aquifer, hereafter referred to as the UFA well. Water samples were collected for geochemical analyses in November 2012 and October 2013 from the three springs and the UFA well. Samples were analyzed for a suite of major ions, dissolved gases, and isotopes of sulfur, strontium, oxygen, and hydrogen. Daily means of water level and specific conductance at White Springs were continuously recorded from October 2012 through December 2013 by the Suwannee River Water Management District. Suwannee River stage at White Springs was computed on the basis of stage at a U.S. Geological Survey streamgage about 2.4 miles upstream. Water levels in two wells, located about 2.5 miles northwest and 13 miles southeast of White Springs, were also used in the analyses.
Major ion concentrations were used to differentiate water from the springs and Upper Floridan aquifer into three groups: Bell Springs, UFA well, and White and Suwannee Springs. When considered together, evidence from water-level, specific conductance, major-ion concentration, and isotope data indicated that groundwater at Bell Springs and the UFA well was a mixture of surface water and groundwater from the upper confining unit, and that groundwater at White and Suwannee Springs was a mixture of surface water, groundwater from the upper confining unit, and groundwater from the Upper Floridan aquifer. Higher concentrations of magnesium in groundwater samples at the UFA well than in samples at Bell Springs might indicate less mixing with surface water at the UFA well than at Bell Springs. Characteristics of surface-water recharge, such as residence time at the surface, apparent age, and recharge water temperature, were estimated on the basis of isotopic ratios, and dissolved concentrations of gases such as argon, tritium, and sulfur hexafluoride. Oxygen and deuterium isotopic ratios were consistent with rapid recharge by rainwater for samples collected in 2012, and longer residence time at the surface (ponding) for samples collected in 2013. Apparent ages of groundwater samples, computed on the basis of tritium activity and sulfur hexafluoride concentration, indicated groundwater recharge occurred after the late 1980s; however, the estimated apparent ages likely represent the average of ages of multiple sources. Recharge since the 1980s is consistent with groundwater from shallow sources, such as the upper confining unit and Upper Floridan aquifer. Recharge water temperature computed for the three springs and UFA well averaged 20.1 degrees Celsius, which is similar to the mean annual air temperature of 20.6 degrees Celsius at a nearby weather station for 1960–2014.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161190","collaboration":"Prepared in cooperation with the Suwannee River Water Management District","usgsCitation":"Stamm, J.F., and McBride, W.S., 2016, Sources of groundwater and characteristics of surface-water recharge at Bell, White, and Suwannee Springs, Florida: 2012–13: U.S. Geological Survey Open-File Report 2016–1190, 27 p., https://doi.org/10.3133/ofr20161190.","productDescription":"vii, 27 p.","numberOfPages":"40","onlineOnly":"Y","ipdsId":"IP-066218","costCenters":[{"id":270,"text":"FLWSC-Tampa","active":true,"usgs":true}],"links":[{"id":332418,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1190/coverthb.jpg"},{"id":332419,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1190/ofr20161190.pdf","text":"Report","size":"1.73 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1190"}],"country":"United States","state":"Florida","otherGeospatial":"Bell Spring, Suwannee Spring, White Spring","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.033333,\n 30.583333\n ],\n [\n -83.033333,\n 30.166667\n ],\n [\n -82.616667,\n 30.166667\n ],\n [\n -82.616667,\n 30.583333\n ],\n [\n -83.033333,\n 30.583333\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
The U.S. Geological Survey, in cooperation with the New England Interstate Water Pollution Control Commission and the Vermont Department of Environmental Conservation, estimated daily and 9-month concentrations and fluxes of total and dissolved phosphorus, total nitrogen, chloride, and total suspended solids from 1990 (or first available date) through 2014 for 18 tributaries of Lake Champlain. Estimates of concentration and flux, provided separately in Medalie (2016), were made by using the Weighted Regressions on Time, Discharge, and Season (WRTDS) regression model and update previously published WRTDS model results with recent data. Assessment of progress towards meeting phosphorus-reduction goals outlined in the Lake Champlain management plan relies on annual estimates of phosphorus flux. The percent change in annual concentration and flux is provided for two time periods. The R package EGRETci was used to estimate the uncertainty of the trend estimate. Differences in model specification and function between this study and previous studies that used WRTDS to estimate concentration and flux using data from Lake Champlain tributaries are described.
Winter data were too sparse and nonrepresentative to use for estimates of concentration and flux but were sufficient for estimating the percentage of total annual flux over the period of record. Median winter-to-annual fractions ranged between 21 percent for total suspended solids and 27 percent for dissolved phosphorus. The winter contribution was largest for all constituents from the Mettawee River and smallest from the Ausable River.
For the full record (1991 through 2014 for total and dissolved phosphorus and chloride and 1993 through 2014 for nitrogen and total suspended solids), 6 tributaries had decreasing trends in concentrations of total phosphorus, and 12 had increasing trends; concentrations of dissolved phosphorus decreased in 6 and increased in 8 tributaries; fluxes of total phosphorus decreased in 5 and increased in 10 tributaries; and fluxes of dissolved phosphorus decreased in 4 and increased in 10 tributaries (where the number of increasing and decreasing trends does not add up to 18, the remainder of tributaries had no trends). Concentrations and fluxes of nitrogen decreased in 10 and increased in 4 tributaries and of chloride decreased in 2 and increased in 15 tributaries. Concentrations of total suspended solids decreased in 4 and increased in 8 tributaries, and fluxes of total suspended solids decreased in 3 and increased in 11 tributaries.
Although time intervals for the percent changes from this report are not completely synchronous with those from previous studies, the numbers of and specific tributaries with overall negative percent changes in concentration and flux are similar. Concentration estimates of total phosphorus in the Winooski River were used to trace whether changes in trends between a previous study and the current study were due generally to differences in model specifications or differences from 4 years of additional data. The Winooski River analysis illustrates several things: that keeping all model specifications equal, concentration estimates increased from 2010 to 2014; the effects of a smoothing algorithm used in the current study that was not available previously; that narrowing model half-window widths increased year-to-year variations; and that the change from an annual to a 9-month basis by omitting winter estimates changed a few individual points but not the overall shape of the flow-normalized curve. Similar tests for other tributaries showed that the primary effect of differences in model specifications between the previous and current studies was perhaps to increase scatter over time but that changes in trends generally were the result of 4 years of additional data rather than artifacts of model differences.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161200","collaboration":"Prepared in cooperation with the New England Interstate Water Pollution Control Commission and the Vermont Department of Environmental Conservation","usgsCitation":"Medalie, Laura, 2016, Concentration, flux, and trend estimates with uncertainty for nutrients, chloride, and total suspended solids in tributaries of Lake Champlain, 1990–2014: U.S. Geological Survey Open-File Report 2016–1200, 22 p., https://doi.org/10.3133/ofr20161200.","productDescription":"Report: iv, 22 p.; Data Release","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-076110","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":438482,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7RN360M","text":"USGS data release","linkHelpText":"Estimates of annual and daily concentration and flux of nutrients, chloride, and suspended sediment in tributaries of Lake Champlain, 1990 through 2014"},{"id":332328,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7RN360M","text":"USGS data release - Estimates of annual and daily concentration and flux of nutrients, chloride, and total suspended solids in tributaries of Lake Champlain, 1990 through 2014","description":"Usgs Data Release"},{"id":332327,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1200/ofr20161200.pdf","text":"Report","size":"858 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1200"},{"id":332326,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1200/coverthb.jpg"}],"country":"United States","state":"New York, Vermont","otherGeospatial":"Lake Champlain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.597412109375,\n 44.01454613545038\n ],\n [\n -73.00140380859375,\n 44.01454613545038\n ],\n [\n -73.00140380859375,\n 45.00365115687186\n ],\n [\n -73.597412109375,\n 45.00365115687186\n ],\n [\n -73.597412109375,\n 44.01454613545038\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
331 Commerce Way
Pembroke, NH 03275
http://newengland.water.usgs.gov
","tableOfContents":"The High Plains aquifer is a nationally important water resource underlying about 175,000 square miles in parts of eight states: Colorado, Kansas, Oklahoma, Nebraska, New Mexico, South Dakota, Texas, and Wyoming. Droughts across much of the Northern High Plains from 2001 to 2007 have combined with recent (2004) legislative mandates to elevate concerns regarding future availability of groundwater and the need for additional information to support science-based water-resource management. To address these needs, the U.S. Geological Survey began the High Plains Groundwater Availability Study to provide a tool for water-resource managers and other stakeholders to assess the status and availability of groundwater resources.
A transient groundwater-flow model was constructed using the U.S. Geological Survey modular three-dimensional finite-difference groundwater-flow model with Newton-Rhapson solver (MODFLOW–NWT). The model uses an orthogonal grid of 565 rows and 795 columns, and each grid cell measures 3,281 feet per side, with one variably thick vertical layer, simulated as unconfined. Groundwater flow was simulated for two distinct periods: (1) the period before substantial groundwater withdrawals, or before about 1940, and (2) the period of increasing groundwater withdrawals from May 1940 through April 2009. A soil-water-balance model was used to estimate recharge from precipitation and groundwater withdrawals for irrigation. The soil-water-balance model uses spatially distributed soil and landscape properties with daily weather data and estimated historical land-cover maps to calculate spatial and temporal variations in potential recharge. Mean annual recharge estimated for 1940–49, early in the history of groundwater development, and 2000–2009, late in the history of groundwater development, was 3.3 and 3.5 inches per year, respectively.
Primary model calibration was completed using statistical techniques through parameter estimation using the parameter estimation suite of software with Tikhonov regularization. Calibration targets for the groundwater model included 343,067 groundwater levels measured in wells and 10,820 estimated monthly stream base flows at streamgages. A total of 1,312 parameters were adjusted during calibration to improve the match between calibration targets and simulated equivalents. Comparison of calibration targets to simulated equivalents indicated that, at the regional scale, the model correctly reproduced groundwater levels and stream base flows for 1940–2009. This comparison indicates that the model can be used to examine the likely response of the aquifer system to potential future stresses.
Mean calibrated recharge for 1940–49 and 2000–2009 was smaller than that estimated with the soil-water-balance model. This indicated that although the general spatial patterns of recharge estimated with the soil-water-balance model were approximately correct at the regional scale of the Northern High Plains aquifer, the soil-water-balance model had overestimated recharge, and adjustments were needed to decrease recharge to improve the match of the groundwater model to calibration targets. The largest components of the simulated groundwater budgets were recharge from precipitation, recharge from canal seepage, outflows to evapotranspiration, and outflows to stream base flow. Simulated outflows to irrigation wells increased from 7 percent of total outflows in 1940–49 to 38 percent of 1970–79 total outflows and 49 percent of 2000–2009 total outflows.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165153","usgsCitation":"Peterson, S.M., Flynn, A.T., and Traylor, J.P., 2016, Groundwater-flow model of the Northern High Plains aquifer in Colorado, Kansas, Nebraska, South Dakota, and Wyoming: U.S. Geological Survey Scientific Investigations Report 2016–5153, 88 p., https://doi.org/10.3133/sir20165153.","productDescription":"Report: x, 88 p.; 2 Figures: 11.00 x 8.50 inches; 2 Data Releases","numberOfPages":"102","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-070028","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":331684,"rank":4,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/sir/2016/5153/sir20165153_fig15.pdf","text":"Figure 15","size":"9.23 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5153 Figure 15"},{"id":331685,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7K072C9","text":"USGS data release - Base of aquifer contours for the Northern High Plains aquifer","description":"USGS Data Release"},{"id":331683,"rank":3,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/sir/2016/5153/sir20165153_fig14.pdf","text":"Figure 14","size":"988 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5153 Figure 14"},{"id":331686,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7JS9NKD","text":"USGS data release - MODFLOW-NWT groundwater flow model used to evaluate conditions in the Northern High Plains Aquifer in Colorado, Kansas, Nebraska, South Dakota, and Wyoming","description":"USGS Data Release"},{"id":331678,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5153/sir20165153.pdf","text":"Report","size":"36.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5153"},{"id":331677,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5153/coverthb.jpg"}],"country":"United States","state":"Colorado, Kansas, Nebraska, South Dakota, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106,\n 38\n ],\n [\n -106,\n 44\n ],\n [\n -96,\n 44\n ],\n [\n -96,\n 38\n ],\n [\n -106,\n 38\n ]\n ]\n ]\n }\n }\n ]\n}","publicComments":"Water Availability and Use Science Program","contact":"Director, Nebraska Water Science Center
U.S. Geological Survey
5231 South 19th Street
Lincoln, NE 68512
Time-series electromagnetic-induction log (TSEMIL) datasets are collected from polyvinyl-chloride cased or uncased monitoring wells to evaluate changes in water conductivity over time. TSEMIL datasets consist of a series of individual electromagnetic-induction logs, generally collected at a frequency of once per month or once per year that have been compiled into a dataset by eliminating small uniform offsets in bulk conductivity between logs probably caused by minor variations in calibration. These offsets are removed by selecting a depth at which no changes are apparent from year to year, and by adjusting individual logs to the median of all logs at the selected depth. Generally, the selected depths are within the freshwater saturated part of the aquifer, well below the water table. TSEMIL datasets can be used to monitor changes in water conductivity throughout the full thickness of an aquifer, without the need for long open-interval wells which have, in some instances, allowed vertical water flow within the well bore that has biased water conductivity profiles. The TSEMIL dataset compilation process enhances the ability to identify small differences between logs that were otherwise obscured by the offsets. As a result of TSEMIL dataset compilation, the root mean squared error of the linear regression between bulk conductivity of the electromagnetic-induction log measurements and the chloride concentration of water samples decreased from 17.4 to 1.7 millisiemens per meter in well G–3611 and from 3.7 to 2.2 millisiemens per meter in well G–3609. The primary use of the TSEMIL datasets in south Florida is to detect temporal changes in bulk conductivity associated with saltwater intrusion in the aquifer; however, other commonly observed changes include (1) variations in bulk conductivity near the water table where water saturation of pore spaces might vary and water temperature might be more variable, and (2) dissipation of conductive water in high-porosity rock layers, which might have entered these layers during drilling. Although TSEMIL dataset processing of even a few logs improves evaluations of the differences between the logs that are related to changes in the salinity, about 16 logs are needed to estimate the bulk conductivity within ±2 millisiemens per meter. Unlike many other types of data published by the U.S. Geological Survey, the median of TSEMIL datasets should not be considered final until 16 logs are collected and the median of the dataset is stable.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161194","usgsCitation":"Prinos, S.T., and Valderrama, Robert, 2016, Collection, processing, and quality assurance of time-series electromagnetic-induction log datasets, 1995–2016, south Florida: U.S. Geological Survey Open-File Report 2016–1194, 24 p., https://doi.org/10.3133/ofr20161194.","productDescription":"Report: vii, 24 p.; Data Release","numberOfPages":"36","onlineOnly":"Y","ipdsId":"IP-069121","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":438492,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P92Y62KV","text":"USGS data release","linkHelpText":"Time Series Electromagnetic Induction-Log Datasets, Including Logs Collected through the 2018 Water Year in South Florida"},{"id":438491,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F70R9NPF","text":"USGS data release","linkHelpText":"Time Series Electromagnetic Induction-Log Datasets, Including Logs Collected through the 2017 Water Year in South Florida"},{"id":438490,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7BG2MWD","text":"USGS data release","linkHelpText":"Time Series Electromagnetic Induction-Log Datasets, Including LogsCollected through the 2016 Water Year in South Florida"},{"id":332010,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F78W3BF5","text":"USGS data release - Time Series Electromagnetic Induction Log datasets","description":"USGS Data Release"},{"id":331983,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1194/coverthb.jpg"},{"id":331984,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1194/ofr20161194.pdf","text":"Report","size":"7.64 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1194"}],"country":"United States","state":"Florida","county":"Broward County, Glades County, Hendry County, Martin County, Miami-Dade County, Palm Beach County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.584716796875,\n 28.19792655722615\n ],\n [\n -80.2001953125,\n 27.430289738862594\n ],\n [\n -79.95849609375,\n 26.362342068998764\n ],\n [\n -80.04638671875,\n 25.97779895546436\n ],\n [\n -80.167236328125,\n 25.53252846853444\n ],\n [\n -80.474853515625,\n 25.11544539706194\n ],\n [\n -80.6396484375,\n 25.60190226111573\n ],\n [\n -80.96923828125,\n 26.49024045886963\n ],\n [\n -81.4306640625,\n 26.37218544169559\n ],\n [\n -81.661376953125,\n 27.059125784374068\n ],\n [\n -81.84814453125,\n 27.49852672279832\n ],\n [\n -80.584716796875,\n 28.19792655722615\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
Because natural patterns of streamflow are a fundamental property of the health of streams, there is a critical need to quantify the degree to which human activities have modified natural streamflows. A requirement for assessing streamflow modification in a given stream is a reliable estimate of flows expected in the absence of human influences. Although there are many techniques to predict streamflows in specific river basins, there is a lack of approaches for making predictions of natural conditions across large regions and over many decades. In this study conducted by the U.S. Geological Survey, in cooperation with The Nature Conservancy and Trout Unlimited, the primary objective was to develop empirical models that predict natural (that is, unaffected by land use or water management) monthly streamflows from 1950 to 2012 for all stream segments in California. Models were developed using measured streamflow data from the existing network of streams where daily flow monitoring occurs, but where the drainage basins have minimal human influences. Widely available data on monthly weather conditions and the physical attributes of river basins were used as predictor variables. Performance of regional-scale models was comparable to that of published mechanistic models for specific river basins, indicating the models can be reliably used to estimate natural monthly flows in most California streams. A second objective was to develop a model that predicts the likelihood that streams experience modified hydrology. New models were developed to predict modified streamflows at 558 streamflow monitoring sites in California where human activities affect the hydrology, using basin-scale geospatial indicators of land use and water management. Performance of these models was less reliable than that for the natural-flow models, but results indicate the models could be used to provide a simple screening tool for identifying, across the State of California, which streams may be experiencing anthropogenic flow modification.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161189","collaboration":"Prepared in cooperation with The Nature Conservancy and Trout Unlimited","usgsCitation":"Carlisle, D.M., Wolock, D.M., Howard, J.K., Grantham, T.E., Fesenmyer, Kurt, and Wieczorek, Michael, 2016, Estimating natural monthly streamflows in California and the likelihood of anthropogenic modification: U.S. Geological Survey Open-File Report 2016–1189, 27 p., https://doi.org/10.3133/ofr20161189.","productDescription":"vi, 27 p.","numberOfPages":"38","onlineOnly":"Y","ipdsId":"IP-068823","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"links":[{"id":438493,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7MP51DS","text":"USGS data release","linkHelpText":"Data Release for: Empirical Models for Estimating Baseline Streamflows in California and their Likelihood of 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\"}}]}","contact":"Chief, National Water-Quality Assessment Program
U.S. Geological Survey
413 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
Freshwater flow to the Ten Thousand Islands estuary has been altered by the construction of the Tamiami Trail and the Southern Golden Gate Estates. The Picayune Strand Restoration Project, which is associated with the Comprehensive Everglades Restoration Plan, has been implemented to improve freshwater delivery to the Ten Thousand Islands estuary by removing hundreds of miles of roads, emplacing hundreds of canal plugs, removing exotic vegetation, and constructing three pump stations. Quantifying the tributary flows and salinity patterns prior to, during, and after the restoration is essential to assessing the effectiveness of upstream restoration efforts.
Tributary flow and salinity patterns during preliminary restoration efforts and prior to the installation of pump stations were analyzed to provide baseline data and preliminary analysis of changes due to restoration efforts. The study assessed streamflow and salinity data for water years1 2007–2014 for the Faka Union River (canal flow included), East River, Little Wood River, Pumpkin River, and Blackwater River. Salinity data from the Palm River and Faka Union Boundary water-quality stations were also assessed.
Faka Union River was the dominant contributor of freshwater during water years 2007–14 to the Ten Thousand Islands estuary, followed by Little Wood and East Rivers. Pumpkin River and Blackwater River were the least substantial contributors of freshwater flow. The lowest annual flow volumes, the highest annual mean salinities, and the highest percentage of salinity values greater than 35 parts per thousand (ppt) occurred in water year 2011 at all sites with available data, corresponding with the lowest annual rainfall during the study. The highest annual flow volumes and the lowest percentage of salinities greater than 35 ppt occurred in water year 2013 for all sites with available data, corresponding with the highest rainfall during the study.
In water year 2014, the percentage of monitored annual flow contributed by East River increased and the percentage of flow contributed by Faka Union River decreased, compared to the earlier years. No changes in annual flow occurred at any sites west of Faka Union River. No changes in the relative flow contributions were observed during the wet season; however, the relative amounts of streamflow increased during the dry season at East River in 2014. East River had only 1 month of negative flow in 2014 compared to 6 months in 2011 and 7 months in 2008. Higher dry season flows in East River may be in response to restoration efforts. The sites to the west of Faka Union River had higher salinities on average than Faka Union River and East River. Faka Union River had the highest range in salinities, and Faka Union Boundary had the lowest range in salinities. Pumpkin River was the tributary with the lowest range in salinities.
1Water year is defined as the 12-month period from October 1, for any given year, through September 30 of the following year.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165158","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers as part of the U.S. Geological Survey Greater Everglades Priority Ecosystem Science","usgsCitation":"Booth, A.C., and Soderqvist, L.E., 2016, Flow characteristics and salinity patterns of tidal rivers within the northern Ten Thousand Islands, southwest Florida, water years 2007–14: U.S. Geological Survey Scientific\nInvestigations Report 2016–5158, 22 p., https://doi.org/10.3133/sir20165158.","productDescription":"vi, 22 p.","numberOfPages":"32","onlineOnly":"Y","ipdsId":"IP-072364","costCenters":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true}],"links":[{"id":331582,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5158/coverthb.jpg"},{"id":331583,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5158/sir20165158.pdf","text":"Report","size":"4.51 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5158"}],"country":"United States","state":"Florida","otherGeospatial":"Ten Thousand Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.73553466796875,\n 25.79370901679868\n ],\n [\n -81.73553466796875,\n 26.16776399795339\n ],\n [\n -81.34002685546875,\n 26.16776399795339\n ],\n [\n -81.34002685546875,\n 25.79370901679868\n ],\n [\n -81.73553466796875,\n 25.79370901679868\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
The U.S. Geological Survey, National Minerals Information Center, analyzes mineral and metal supply chains by identifying and describing major components of mineral and material flows from ore extraction, through intermediate forms, to a final product. This report focuses on an important component of the world’s supply chain: the amounts and global distribution of major consumer, producer, and exchange stocks of selected mineral commodities. In this report, the term “stock” is used instead of “inventory” and refers to accumulations of mined ore, intermediate products, and refined mineral-based commodities that are in a form that meets the agreed-upon specifications of a buyer or processor of intermediate products. These may include certain ores such as bauxite, concentrates, smelter products, and refined metals. Materials sometimes referred to as inventory for accounting purposes, such as ore contained in a deposit or in a leach pile, or materials that need to be further processed before they can be shipped to a consumer, are not considered. Stocks may be held (owned) by consumers, governments, investors, producers, and traders. They may serve as (1) a means to achieve economic, social, and strategic goals through government policies; (2) a secure source of supply to meet demand and to mitigate potential shortages in the supply chain; (3) a hedge to mitigate price volatility; and (4) vehicles for speculative investment.
The paucity and uneven reliability of data for stocks of ores and concentrates and for material held by producers, consumers, and merchants hinder the accurate estimating of the size and distribution of this portion of the supply chain for certain commodities. This paper reviews the more visible stocks held in commodity exchange warehouses distributed throughout the world.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165152","usgsCitation":"Wilburn, D.R., Bleiwas, D.I., and Karl, N.A., 2016, Global stocks of selected mineral-based commodities: U.S. Geological Survey Scientific Investigations Report 2016–5152, 13 p., https://doi.org/10.3133/sir20165152. ","productDescription":"Report: iv, 13 p.; Tables 2-10","numberOfPages":"22","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-074458","costCenters":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"links":[{"id":331397,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2016/5152/sir20165152_tables2-10.xlsx","text":"Tables 2 through 10","size":"94 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016-5152 - Tables 2-10","linkHelpText":"- Global Stocks of Selected Mineral-Based Commodities"},{"id":331396,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5152/sir20165152.pdf","text":"Report ","size":"1.79 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5152"},{"id":331395,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5152/coverthb.jpg"}],"contact":"Director, National Minerals Information Center
U.S. Geological Survey
988 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
Email: nmicrecordsmgt@usgs.gov
http://minerals.usgs.gov/minerals/
A new groundwater flow model for Dane County, Wisconsin, replaces an earlier model developed in the 1990s by the Wisconsin Geological and Natural History Survey (WGNHS) and the U.S. Geological Survey (USGS). This modeling study was conducted cooperatively by the WGNHS and the USGS with funding from the Capital Area Regional Planning Commission (CARPC). Although the overall conceptual model of the groundwater system remains largely unchanged, the incorporation of newly acquired high-quality datasets, recent research findings, and improved modeling and calibration techniques have led to the development of a more detailed and sophisticated model representation of the groundwater system. The new model is three-dimensional and transient, and conceptualizes the county’s hydrogeology as a 12-layer system including all major unlithified and bedrock hydrostratigraphic units and two high-conductivity horizontal fracture zones.
Beginning from the surface down, the model represents the unlithified deposits as two distinct model layers (1 and 2). A single layer (3) simulates the Ordovician sandstone and dolomite of the Sinnipee, Ancell, and Prairie du Chien Groups. Sandstone of the Jordan Formation (layer 4) and silty dolostone of the St. Lawrence Formation (layer 5) each comprise separate model layers. The underlying glauconitic sandstone of the Tunnel City Group makes up three distinct layers: an upper aquifer (layer 6), a fracture feature (layer 7), and a lower aquifer (layer 8). The fracture layer represents a network of horizontal bedding-plane fractures that serve as a preferential pathway for groundwater flow. The model simulates the sandstone of the Wonewoc Formation as an upper aquifer (layer 9) with a bedding-plane fracture feature (layer 10) at its base. The Eau Claire aquitard (layer 11) includes shale beds within the upper portion of the Eau Claire Formation. This layer, along with overlying bedrock units, is mostly absent in the preglacially eroded valleys along the Yahara River valley and in northeastern Dane County. Layer 12 represents the Mount Simon sandstone as the lowermost model layer. It directly overlies the Precambrian crystalline basement rock, whose top surface forms the lower boundary of the model.
The model uses the USGS MODFLOW-NWT finite-difference code, a standalone version of MODFLOW-2005 that incorporates the Newton (NWT) solver. MODFLOW-NWT improves the handling of unconfined conditions by smoothing the transition from wet to dry cells. The model explicitly simulates groundwater–surface-water interaction with streamflow routing and lake-level fluctuation. Model input included published and unpublished hydrogeologic data from recent estimates of aquifer hydraulic conductivities. A spatial groundwater recharge distribution was obtained from a recent GIS-based, soil-water-balance model for Dane County. Groundwater withdrawals from pumping were simulated for 572 wells across the entire model domain, which includes Dane County and portions of seven neighboring counties—Columbia, Dodge, Green, Iowa, Jefferson, Lafayette, and Rock. These wells withdrew an average of 60 million gallons per day (mgd) over the 5-year period from 2006 through 2010. Within Dane County, 385 wells were simulated with an average withdrawal rate of 52 mgd.
Model calibration used the parameter estimation code PEST, and calibration targets included heads, stream and spring flows, lake levels, and borehole flows. Steady-state calibration focused on the period 2006 through 2010; the transient calibration focused on the 7-week drought period from late May through July 2012.
This model represents a significant step forward from previous work because of its finer grid resolution, improved hydrostratigraphic discretization, transient capabilities, and more sophisticated representation of surface-water features and multi-aquifer wells.
Potential applications of the model include evaluation of potential sites for and impacts of new high-capacity wells, development of wellhead protection plans, evaluating the effects of changing land use and climate on groundwater, and quantifying the relationships between groundwater and surface water.
","language":"English","publisher":"Wisconsin Geological and Natural History Survey","isbn":"978-0-88169-992-0","usgsCitation":"Parsen, M.J., Bradbury, K.R., Hunt, R.J., and Feinstein, D.T., 2016, The 2016 groundwater flow model for Dane County, Wisconsin: Bulletin 110, 56 p.","productDescription":"56 p.","numberOfPages":"64","ipdsId":"IP-071783","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":332790,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":330992,"type":{"id":15,"text":"Index Page"},"url":"https://wgnhs.uwex.edu/dane-county-groundwater-model/"}],"country":"United States","state":"Wisconsin","county":"Dane County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-89.0094,43.286],[-89.0084,43.2555],[-89.0094,43.2],[-89.01,43.1131],[-89.0109,43.0849],[-89.0107,43.0271],[-89.0132,42.9353],[-89.013,42.8762],[-89.0119,42.8471],[-89.132,42.8479],[-89.2488,42.8478],[-89.3689,42.8484],[-89.3688,42.8575],[-89.4832,42.858],[-89.6026,42.8575],[-89.7196,42.8587],[-89.8377,42.8598],[-89.8375,42.9471],[-89.8386,43.0317],[-89.8384,43.1181],[-89.8394,43.205],[-89.8325,43.2123],[-89.825,43.2187],[-89.8175,43.226],[-89.8125,43.2342],[-89.8088,43.2369],[-89.8012,43.2365],[-89.7874,43.2356],[-89.771,43.237],[-89.7579,43.2379],[-89.7529,43.2443],[-89.7485,43.2507],[-89.7391,43.2548],[-89.7259,43.2644],[-89.7171,43.2739],[-89.714,43.2821],[-89.7165,43.2867],[-89.7235,43.2935],[-89.7209,43.2935],[-89.6008,43.2932],[-89.4819,43.2942],[-89.3617,43.2954],[-89.3624,43.2832],[-89.246,43.2834],[-89.1271,43.2827],[-89.0094,43.286]]]},\"properties\":{\"name\":\"Dane\",\"state\":\"WI\"}}]}","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"586cc695e4b0f5ce109fa953","contributors":{"authors":[{"text":"Parsen, Michael J.","contributorId":176845,"corporation":false,"usgs":false,"family":"Parsen","given":"Michael","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":657411,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bradbury, Kenneth R.","contributorId":49419,"corporation":false,"usgs":true,"family":"Bradbury","given":"Kenneth","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":657412,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hunt, Randall J. 0000-0001-6465-9304 rjhunt@usgs.gov","orcid":"https://orcid.org/0000-0001-6465-9304","contributorId":1129,"corporation":false,"usgs":true,"family":"Hunt","given":"Randall","email":"rjhunt@usgs.gov","middleInitial":"J.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":657413,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Feinstein, Daniel T. 0000-0003-1151-2530 dtfeinst@usgs.gov","orcid":"https://orcid.org/0000-0003-1151-2530","contributorId":1907,"corporation":false,"usgs":true,"family":"Feinstein","given":"Daniel","email":"dtfeinst@usgs.gov","middleInitial":"T.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":657414,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70178583,"text":"70178583 - 2016 - Geologic map and cross sections of the Embudo Fault Zone in the Southern Taos Valley, Taos County, New Mexico","interactions":[],"lastModifiedDate":"2017-04-18T09:47:08","indexId":"70178583","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":128,"text":"Open-File Report","active":false,"publicationSubtype":{"id":2}},"seriesNumber":"584","title":"Geologic map and cross sections of the Embudo Fault Zone in the Southern Taos Valley, Taos County, New Mexico","docAbstract":"The southern Taos Valley encompasses the physiographic and geologic transition zone between the Picuris Mountains and the San Luis Basin of the Rio Grande rift. The Embudo fault zone is the rift transfer structure that has accommodated the kinematic disparities between the San Luis Basin and the Española Basin during Neogene rift extension. The eastern terminus of the transfer zone coincides with the intersection of four major fault zones (Embudo, Sangre de Cristo, Los Cordovas, and Picuris-Pecos), resulting in an area of extreme geologic and hydrogeologic complexities in both the basin-fill deposits and the bedrock. \r\nAlthough sections of the Embudo fault zone are locally exposed in the bedrock of the Picuris Mountains and in the late Cenozoic sedimentary units along the top of the Picuris piedmont, the full proportions of the fault zone have remained elusive due to a pervasive cover of Quaternary surficial deposits. We combined insights derived from the latest geologic mapping of the area with deep borehole data and high-resolution aeromagnetic and gravity models to develop a detailed stratigraphic/structural model of the rift basin in the southern Taos Valley area.\r\nThe four fault systems in the study area overlap in various ways in time and space. Our geologic model states that the Picuris-Pecos fault system exists in the basement rocks (Picuris formation and older units) of the rift, where it is progressively down dropped and offset to the west by each Embudo fault strand between the Picuris Mountains and the Rio Pueblo de Taos. In this model, the Miranda graben exists in the subsurface as a series of offset basement blocks between the Ponce de Leon neighborhood and the Rio Pueblo de Taos. In the study area, the Embudo faults are pervasive structures between the Picuris Mountains and the Rio Pueblo de Taos, affecting all geologic units that are older than the Quaternary surficial deposits. The Los Cordovas faults are thought to represent the late Tertiary to Quaternary reactivation of the old and deeply buried Picuris-Pecos faults. If so, then the Los Cordovas structures may extend southward under the Picuris piedmont, where they form growth faults as they merge downward into the Picuris-Pecos bedrock faults.\r\nThe exceptionally high density of cross-cutting faults in the study area has severely disrupted the stratigraphy of the Picuris formation and the Santa Fe Group. The Picuris formation exists at the surface in the Miranda and Rio Grande del Rancho grabens, and locally along the top of the Picuris piedmont. In the subsurface, it deepens rapidly from the mountain front into the rift basin. In a similar manner, the Tesuque and Chamita Formations are shallowly exposed close to the mountain front, but are down dropped into the basin along the Embudo faults. The Ojo Caliente Sandstone Member of the Tesuque Formation appears to be thickest in the northwestern study area, and thins toward the south and the east. In the study area, the Lama formation thins westward and southward. The Servilleta Basalt is generally thickest to the north and northwest, thins under the Picuris piedmont, and terminates along a major, linear, buried strand of the Embudo fault zone, demonstrating that the Servilleta flows were spatially and temporally related to Embudo fault activity.","language":"English","publisher":"New Mexico Bureau of Geology and Mineral Resources","usgsCitation":"Bauer, P.W., Kelson, K., Grauch, V.J., Drenth, B.J., Johnson, P.S., Aby, S.B., and Felix, B., 2016, Geologic map and cross sections of the Embudo Fault Zone in the Southern Taos Valley, Taos County, New Mexico: Open-File Report 584, 46 p.","productDescription":"46 p.","ipdsId":"IP-078911","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":339840,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":331296,"type":{"id":15,"text":"Index Page"},"url":"https://geoinfo.nmt.edu/publications/openfile/details.cfml?Volume=584"}],"country":"United States","state":"New Mexico","otherGeospatial":"Taos Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.77980041503906,\n 36.42901741282473\n ],\n [\n -105.78117370605469,\n 36.26531407324164\n ],\n [\n -105.62942504882812,\n 36.26586770430287\n ],\n [\n -105.62805175781249,\n 36.21547120903648\n ],\n [\n -105.56007385253906,\n 36.2165791734887\n ],\n [\n -105.5621337890625,\n 36.43177971506432\n ],\n [\n -105.77980041503906,\n 36.42901741282473\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58f725e6e4b0b7ea5451eecc","contributors":{"authors":[{"text":"Bauer, Paul W.","contributorId":145562,"corporation":false,"usgs":false,"family":"Bauer","given":"Paul","email":"","middleInitial":"W.","affiliations":[{"id":16150,"text":"New Mexico Bureau of Geology and Mineral Resources","active":true,"usgs":false}],"preferred":false,"id":691307,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kelson, Keith I.","contributorId":75851,"corporation":false,"usgs":true,"family":"Kelson","given":"Keith I.","affiliations":[],"preferred":false,"id":691308,"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":691309,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Drenth, Benjamin J. 0000-0002-3954-8124 bdrenth@usgs.gov","orcid":"https://orcid.org/0000-0002-3954-8124","contributorId":1315,"corporation":false,"usgs":true,"family":"Drenth","given":"Benjamin","email":"bdrenth@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":691310,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, Peggy S.","contributorId":85689,"corporation":false,"usgs":true,"family":"Johnson","given":"Peggy","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":691311,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Aby, Scott B.","contributorId":172710,"corporation":false,"usgs":false,"family":"Aby","given":"Scott","email":"","middleInitial":"B.","affiliations":[{"id":27087,"text":"Muddy Spring Geology","active":true,"usgs":false}],"preferred":false,"id":691312,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Felix, Brigitte","contributorId":191017,"corporation":false,"usgs":false,"family":"Felix","given":"Brigitte","email":"","affiliations":[],"preferred":false,"id":691313,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70176666,"text":"sir20165134 - 2016 - Groundwater and surface-water interaction, water quality, and processes affecting loads of dissolved solids, selenium, and uranium in Fountain Creek, near Pueblo, Colorado, 2012–2014","interactions":[],"lastModifiedDate":"2026-02-23T18:19:23.800194","indexId":"sir20165134","displayToPublicDate":"2016-11-28T17:30:00","publicationYear":"2016","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":"2016-5134","displayTitle":"Groundwater and Surface-Water Interaction, Water Quality, and Processes Affecting Loads of Dissolved Solids, Selenium, and Uranium in Fountain Creek, near Pueblo, Colorado, 2012–2014","title":"Groundwater and surface-water interaction, water quality, and processes affecting loads of dissolved solids, selenium, and uranium in Fountain Creek, near Pueblo, Colorado, 2012–2014","docAbstract":"In 2012, the U.S. Geological Survey, in cooperation with the Arkansas River Basin Regional Resource Planning Group, initiated a study of groundwater and surface-water interaction, water quality, and loading of dissolved solids, selenium, and uranium to Fountain Creek near Pueblo, Colorado, to improve understanding of sources and processes affecting loading of these constituents to streams in the Arkansas River Basin. Fourteen monitoring wells were installed in a series of three transects across Fountain Creek near Pueblo, and temporary streamgages were established at each transect to facilitate data collection for the study. Groundwater and surface-water interaction was characterized by using hydrogeologic mapping, groundwater and stream-surface levels, groundwater and stream temperatures, vertical hydraulic-head gradients and ratios of oxygen and hydrogen isotopes in the hyporheic zone, and streamflow mass-balance measurements. Water quality was characterized by collecting periodic samples from groundwater, surface water, and the hyporheic zone for analysis of dissolved solids, selenium, uranium, and other selected constituents and by evaluating the oxidation-reduction condition for each groundwater sample under different hydrologic conditions throughout the study period. Groundwater loads to Fountain Creek and in-stream loads were computed for the study area, and processes affecting loads of dissolved solids, selenium, and uranium were evaluated on the basis of geology, geochemical conditions, land and water use, and evapoconcentration.
During the study period, the groundwater-flow system generally contributed flow to Fountain Creek and its hyporheic zone (as a single system) except for the reach between the north and middle transects. However, the direction of flow between the stream, the hyporheic zone, and the near-stream aquifer was variable in response to streamflow and stage. During periods of low streamflow, Fountain Creek generally gained flow from groundwater. However, during periods of high streamflow, the hydraulic gradient between groundwater and the stream temporarily reversed, causing the stream to lose flow to groundwater.
Concentrations of dissolved solids, selenium, and uranium in groundwater generally had greater spatial variability than surface water or hyporheic-zone samples, and constituent concentrations in groundwater generally were greater than in surface water. Constituent concentrations in the hyporheic zone typically were similar to or intermediate between concentrations in groundwater and surface water. Concentrations of dissolved solids, selenium, uranium, and other constituents in groundwater samples collected from wells located on the east side of the north monitoring well transect were substantially greater than for other groundwater, surface-water, and hyporheic-zone samples. With one exception, groundwater samples collected from wells on the east side of the north transect exhibited oxic to mixed (oxic-anoxic) conditions, whereas most other groundwater samples exhibited anoxic to suboxic conditions. Concentrations of dissolved solids, selenium, and uranium in surface water generally increased in a downstream direction along Fountain Creek from the north transect to the south transect and exhibited an inverse relation to streamflow with highest concentration occurring during periods of low streamflow and lowest concentrations occurring during periods of high streamflow.
Groundwater loads of dissolved solids, selenium, and uranium to Fountain Creek were small because of the small amount of groundwater flowing to the stream under typical low-streamflow conditions. In-stream loads of dissolved solids, selenium, and uranium in Fountain Creek varied by date, primarily in relation to streamflow at each transect and were much larger than computed constituent loads from groundwater. In-stream loads generally decreased with decreases in streamflow and increased as streamflow increased. In-stream loads of dissolved solids and selenium increased between the north and middle transects but generally decreased between the middle and south transects. By contrast, uranium loads generally decreased between the north and middle transects but increased between the middle and south transects. In-stream load differences between transects appear primarily to be related to differences in streamflow. However, because groundwater typically flows to Fountain Creek under low-flow conditions, and groundwater has greater concentrations of dissolved solids, selenium, and uranium than surface water in Fountain Creek, increases in loads between transects likely are affected by inflow of groundwater to the stream, which can account for a substantial proportion of the in-stream load difference between transects. When loads decreased between transects, the primary cause likely was decreased streamflow as a result of losses to groundwater and flow through the hyporheic zone. However, localized groundwater inflow likely attenuated the magnitude by which the in-stream loads decreased.
The combination of localized soluble geologic sources and oxic conditions likely is the primary reason for the occurrence of high concentrations of dissolved solids, selenium, and uranium in groundwater on the east side of the north monitoring well transect. To evaluate conditions potentially responsible for differences in water quality and redox conditions, physical characteristics such as depth to water, saturated thickness, screen depth below the water table, screen height above bedrock, and aquifer hydraulic conductivity were compared by using Wilcoxon rank-sum tests. Results indicated no significant difference between depth to water, screen height above bedrock, and hydraulic conductivity for groundwater samples collected from wells on the east side of the north transect and groundwater samples from all other wells. However, saturated thickness and screen depth below the water table both were significantly smaller for groundwater samples collected from wells on the east side of the north transect than for groundwater samples from other wells, indicating that these characteristics might be related to the elevated constituent concentrations found at that location. Similarly, saturated thickness and screen depth below the water table were significantly smaller for groundwater samples under oxic or mixed (oxic-anoxic) conditions than for those under anoxic to suboxic conditions.
The greater constituent concentrations at wells on the east side of the north transect also could, in part, be related to groundwater discharge from an unnamed alluvial drainage located directly upgradient from that location. Although the quantity and quality of water discharging from the drainage is not known, the drainage appears to collect water from a residential area located upgradient to the east of the wells, and groundwater could become concentrated in nitrate and other dissolved constituents before flowing through the drainage. High levels of nitrate, whether from anthropogenic or natural geologic sources, could promote more soluble forms of selenium and other constituents by affecting the redox condition of groundwater. Whether oxic conditions at wells on the east side of the north transect are the result of physical characteristics or of groundwater inflow from the alluvial drainage, the oxic conditions appear to cause increased dissolution of minerals from the shallow shale bedrock at that location. Because ratios of hydrogen and oxygen isotopes indicate evaporation likely has not had a substantial effect on groundwater, constituent concentrations at that location likely are not the result of evapoconcentration.
Director, USGS Colorado Water Science Center
Box 25046, Mail Stop 415
Denver, CO 80225
This study produced a geospatial database for use in a decision support system by the Bolivian authorities to investigate further development and investment potentials in sustainable hydropower in Bolivia. The study assessed theoretical hydropower of all 1-kilometer (km) stream segments in the country using multisource satellite data and a hydrologic modeling approach. With the assessment covering the 2 million square kilometer (km2) region influencing Bolivia’s drainage network, the potential hydropower figures are based on theoretical yield assuming that the systems generating the power are 100 percent efficient. There are several factors to consider when determining the real-world or technical power potential of a hydropower system, and these factors can vary depending on local conditions. Since this assessment covers a large area, it was necessary to reduce these variables to the two that can be modeled consistently throughout the region, streamflow or discharge, and elevation drop or head. First, the Shuttle Radar Topography Mission high-resolution 30-meter (m) digital elevation model was used to identify stream segments with greater than 10 km2 of upstream drainage. We applied several preconditioning processes to the 30-m digital elevation model to reduce errors and improve the accuracy of stream delineation and head height estimation. A total of 316,500 1-km stream segments were identified and used in this study to assess the total theoretical hydropower potential of Bolivia. Precipitation observations from a total of 463 stations obtained from the Bolivian Servicio Nacional de Meteorología e Hidrología (Bolivian National Meteorology and Hydrology Service) and the Brazilian Agência Nacional de Águas (Brazilian National Water Agency) were used to validate six different gridded precipitation estimates for Bolivia obtained from various sources. Validation results indicated that gridded precipitation estimates from the Tropical Rainfall Measuring Mission (TRMM) reanalysis product (3B43) had the highest accuracies. The coarse-resolution (25-km) TRMM data were disaggregated to 5-km pixels using climatology information obtained from the Climate Hazards Group Infrared Precipitation with Stations dataset. About a 17-percent bias was observed in the disaggregated TRMM estimates, which was corrected using the station observations. The bias-corrected, disaggregated TRMM precipitation estimate was used to compute stream discharge using a regionalization approach. In regionalization approach, required homogeneous regions for Bolivia were derived from precipitation patterns and topographic characteristics using a k-means clustering approach. Using the discharge and head height estimates for each 1-km stream segment, we computed hydropower potential for 316,490 stream segments within Bolivia and that share borders with Bolivia. The total theoretical hydropower potential (TTHP) of these stream segments was found to be 212 gigawatts (GW). Out of this total, 77.4 GW was within protected areas where hydropower projects cannot be developed; hence, the remaining total theoretical hydropower in Bolivia (outside the protected areas) was estimated as 135 GW. Nearly 1,000 1-km stream segments, however, were within the boundaries of existing hydropower projects. The TTHP of these stream segments was nearly 1.4 GW, so the residual TTHP of the streams in Bolivia was estimated as 133 GW. Care should be exercised to understand and interpret the TTHP identified in this study because all the stream segments identified and assessed in this study cannot be harnessed to their full capacity; furthermore, factors such as required environmental flows, efficiency, economics, and feasibility need to be considered to better identify a more real-world hydropower potential. If environmental flow requirements of 20–40 percent are considered, the total theoretical power available reduces by 60–80 percent. In addition, a 0.72 efficiency factor further reduces the estimation by another 28 percent. This study provides the base theoretical hydropower potential for Bolivia, the next step is to identify optimal hydropower plant locations and factor in the principles to appraise a real-world power potential in Bolivia.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161156","collaboration":"Prepared in cooperation with the CAF – Development Bank of Latin America","usgsCitation":"Velpuri, N.M., Pervez, M.S., and Cushing, W.M., 2016, Hydropower assessment of Bolivia—A multisource satellite data and hydrologic modeling approach: U.S. Geological Survey Open-File Report 2016–1156, 65 p., https://dx.doi.org/10.3133/ofr20161156.","productDescription":"Report: x, 65 p.; Appendixes: 2-4","numberOfPages":"79","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-075626","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":331175,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1156/ofr20161156.pdf","text":"Report","size":"23.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1156"},{"id":331174,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1156/coverthb.jpg"},{"id":331176,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1156/downloads","text":"Appendixes 2–4","description":"OFR 2016–1156 Appendixes 2–4"}],"country":"Bolivia","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-62.84647,-22.03499],[-63.98684,-21.99364],[-64.37702,-22.79809],[-64.96489,-22.07586],[-66.27334,-21.83231],[-67.10667,-22.73592],[-67.82818,-22.87292],[-68.21991,-21.49435],[-68.75717,-20.37266],[-68.44223,-19.40507],[-68.96682,-18.98168],[-69.10025,-18.26013],[-69.59042,-17.58001],[-68.95964,-16.5007],[-69.38976,-15.66013],[-69.16035,-15.32397],[-69.33953,-14.9532],[-68.94889,-14.45364],[-68.92922,-13.60268],[-68.88008,-12.89973],[-68.66508,-12.5613],[-69.52968,-10.95173],[-68.78616,-11.03638],[-68.27125,-11.01452],[-68.04819,-10.71206],[-67.1738,-10.30681],[-66.64691,-9.93133],[-65.33844,-9.76199],[-65.44484,-10.51145],[-65.3219,-10.89587],[-65.40228,-11.56627],[-64.31635,-12.46198],[-63.1965,-12.62703],[-62.80306,-13.00065],[-62.12708,-13.19878],[-61.7132,-13.4892],[-61.08412,-13.47938],[-60.5033,-13.77595],[-60.4592,-14.35401],[-60.26433,-14.64598],[-60.25115,-15.07722],[-60.54297,-15.09391],[-60.15839,-16.25828],[-58.24122,-16.29957],[-58.38806,-16.87711],[-58.2808,-17.27171],[-57.73456,-17.55247],[-57.49837,-18.17419],[-57.67601,-18.96184],[-57.95,-19.4],[-57.8538,-19.97],[-58.16639,-20.1767],[-58.18347,-19.8684],[-59.11504,-19.35691],[-60.04356,-19.34275],[-61.78633,-19.63374],[-62.26596,-20.51373],[-62.29118,-21.05163],[-62.68506,-22.24903],[-62.84647,-22.03499]]]},\"properties\":{\"name\":\"Bolivia\"}}]}","contact":"Director, Earth Resources Observation and Science (EROS) Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
The hydrogeology and hydrologic characteristics of the Ozark Plateaus aquifer system were characterized as part of ongoing U.S. Geological Survey efforts to assess groundwater availability across the Nation. The need for such a study in the Ozark Plateaus physiographic province (Ozark Plateaus) is highlighted by increasing demand on groundwater resources by the 5.3 million people of the Ozark Plateaus, water-level declines in some areas, and potential impacts of climate change on groundwater availability. The subject study integrates knowledge gained through local investigation within a regional perspective to develop a regional conceptual model of groundwater flow in the Ozark Plateaus aquifer system (Ozark system), a key phase of groundwater availability assessment. The Ozark system extends across much of southern Missouri and northwestern and north-central Arkansas and smaller areas of southeastern Kansas and northeastern Oklahoma. The region is one of the major karst landscapes in the United States, and karst aquifers are predominant in the Ozark system. Groundwater flow is ultimately controlled by aquifer and confining unit lithologies and stratigraphic relations, geologic structure, karst development, and the character of surficial lithologies and regolith mantle. The regolith mantle is a defining element of Ozark Plateaus karst, affecting recharge, karst development, and vulnerability to surface-derived contaminants. Karst development is more advanced—as evidenced by larger springs, hydraulic characteristics, and higher well yields—in the Salem Plateau and in the northern part of the Springfield Plateau (generally north of the Arkansas-Missouri border) as compared with the southern part of the Springfield Plateau in Arkansas, largely due to thinner, less extensive regolith and purer carbonate lithology.
Precipitation is the ultimate source of all water to the Ozark system, and the hydrologic budget for the Ozark system includes inputs from recharge, losing-stream sections, and groundwater inflows and losses of water to gaining-stream sections, groundwater withdrawals, and surface-water and groundwater outflows to neighboring systems. Groundwater recharge, estimated by a soil-water-balance model, represents about 24 percent, or 11 inches, of 43.9 inches annual precipitation. Recharge is spatially variable, being greater in the northern Springfield Plateau and Salem Plateau than in the southern Springfield Plateau (generally south of the Arkansas border) because of differences in regolith mantle extent and thickness and carbonate lithology and hydraulic properties. Increased precipitation and decreased agricultural land use during the period 1951 through 2011 increased recharge by approximately 5 percent. Although all Ozark streams have losing, neutral, and gaining sections, they are dominantly gaining and are a net sink for groundwater with nearly 90 percent of groundwater recharge returned to springs and streams. Groundwater pumping is a small but important loss of water in the Ozark system hydrologic budget; water-level declines and local cones of depression have been observed around pumping centers and strong concerns exist over potential effects on stream and spring flow.
Data indicate that societal needs for freshwater resources in the Ozark Plateaus will continue to increase and will do so in the context of changing climate and hydrology. Groundwater will continue to be an important part of supporting these societal needs and also local ecosystems. The unique character and hydrogeologic variability across the Ozark system will control how the system responds to future stress. Groundwater of the Ozark system in the northern study area is more dynamic, has greater storage and larger flux, and has greater potential for further development than in the part of the study area south of the Arkansas-Missouri border. Further south in Arkansas, a line exists, roughly defined as 5 miles south of the Springfield Plateau-Boston Mountains boundary, beyond which further extensive municipal or commercial development appears unlikely under current economic and resource-need conditions. A small part of the Ozark system groundwater budget is currently drafted for use, leaving an apparently large component available for further development and use—particularly in the northern Springfield Plateau and Salem Plateau; however, the effects of increased pumping on groundwater’s role in maintaining ecosystems and ecosystem services are not quantitatively well understood, and the close relation between groundwater and surface water highlights the importance of further quantitative assessment.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165137","collaboration":"Prepared in cooperation with the Groundwater Resources Program","usgsCitation":"Hays, P.D., Knierim, K.J., Breaker, Brian, Westerman, D.A., and Clark, B.R., 2016, Hydrogeology and hydrologic conditions of the Ozark Plateaus aquifer system: U.S. Geological Survey Scientific Investigations Report 2016–5137, 61 p., https://dx.doi.org/10.3133/sir20165137. \n\n","productDescription":"Report: vii, 61 p.; Appendixes: 1-2","numberOfPages":"73","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-071467","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":331147,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5137/coverthb.jpg"},{"id":331148,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5137/sir20165137.pdf","description":"SIR 2016–5137"},{"id":331149,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5137/downloads","text":"Appendix 1 & 2","description":"SIR 2016–5137 Appendix 1 & 2"}],"country":"United States","state":"Arkansas, Kansas, Missouri, Oklahoma","otherGeospatial":"Ozark Plateaus Aquifer System","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.1263427734375,\n 38.81831117374662\n ],\n [\n -90.3076171875,\n 38.89103282648846\n ],\n [\n -90.4559326171875,\n 38.8225909761771\n ],\n [\n -90.692138671875,\n 38.70694605159386\n ],\n [\n -90.8734130859375,\n 38.556757147352215\n ],\n [\n -91.0546875,\n 38.59970036588819\n ],\n [\n -91.2689208984375,\n 38.66835610151506\n ],\n [\n -91.3897705078125,\n 38.71551876930462\n ],\n [\n -91.571044921875,\n 38.68122173079789\n ],\n [\n -91.7083740234375,\n 38.70265930723801\n ],\n [\n -91.9171142578125,\n 38.65119833229951\n ],\n [\n -92.07092285156249,\n 38.57823196583313\n ],\n [\n -92.197265625,\n 38.586820096127674\n ],\n [\n -92.3345947265625,\n 38.6897975322717\n ],\n [\n -92.4884033203125,\n 38.90813299596705\n ],\n [\n -92.57080078125,\n 38.96368010198575\n ],\n [\n -92.74108886718749,\n 38.98503278695909\n ],\n [\n -92.87841796875,\n 38.997841307500714\n ],\n [\n -92.92236328125,\n 39.091699613104595\n ],\n [\n -92.9058837890625,\n 39.17691709496078\n ],\n [\n -92.8619384765625,\n 39.2407625100131\n ],\n [\n -92.9608154296875,\n 39.317300373271024\n ],\n [\n -93.0926513671875,\n 39.38101803294523\n ],\n [\n -93.2025146484375,\n 39.40224434029275\n ],\n [\n -93.350830078125,\n 39.30454987014581\n ],\n [\n -93.482666015625,\n 39.287545585410435\n ],\n [\n -93.70788574218749,\n 39.223742741391305\n ],\n [\n -93.98803710937499,\n 39.15136267949029\n ],\n [\n -95.2349853515625,\n 38.25112269630296\n ],\n [\n -95.2789306640625,\n 36.45221769643571\n ],\n [\n -95.0152587890625,\n 35.30840140169162\n ],\n [\n -94.19128417968749,\n 35.35321610123823\n ],\n [\n -93.834228515625,\n 35.47409160773029\n ],\n [\n -93.482666015625,\n 35.40696093270201\n ],\n [\n -93.16955566406249,\n 35.25459097465022\n ],\n [\n -93.065185546875,\n 35.15584570226544\n ],\n [\n -92.6641845703125,\n 35.08845057036537\n ],\n [\n -92.55432128906249,\n 34.95349314197422\n ],\n [\n -92.427978515625,\n 34.836349990763864\n ],\n [\n -92.1148681640625,\n 34.8183131456094\n ],\n [\n -90.3515625,\n 35.97800618085566\n ],\n [\n -89.35729980468749,\n 37.01132594307015\n ],\n [\n -89.4561767578125,\n 37.25656608611523\n ],\n [\n -89.4287109375,\n 37.37015718405753\n ],\n [\n -89.46716308593749,\n 37.45741810262938\n ],\n [\n -89.5166015625,\n 37.58811876638322\n ],\n [\n -89.56054687499999,\n 37.71859032558816\n ],\n [\n -89.70886230468749,\n 37.82280243352756\n ],\n [\n -89.8187255859375,\n 37.900865092570065\n ],\n [\n -89.9560546875,\n 37.97451499202459\n ],\n [\n -90.164794921875,\n 38.07836562996712\n ],\n [\n -90.2801513671875,\n 38.14751758025121\n ],\n [\n -90.3680419921875,\n 38.268375880204744\n ],\n [\n -90.32409667968749,\n 38.40194908237822\n ],\n [\n -90.252685546875,\n 38.53097889440024\n ],\n [\n -90.2032470703125,\n 38.62974534092597\n ],\n [\n -90.19775390625,\n 38.70694605159386\n ],\n [\n -90.1263427734375,\n 38.81831117374662\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
401 Hardin Road
Little Rock, AR 72211
Despite widespread and ongoing implementation of conservation practices throughout the Chesapeake Bay watershed, water quality continues to be degraded by excess sediment and nutrient inputs. While the Chesapeake Bay Program has developed and maintains a large-scale and long-term monitoring network to detect improvements in water quality throughout the watershed, fewer resources have been allocated for monitoring smaller watersheds, even though water-quality improvements that may result from the implementation of conservation practices are likely to be first detected at smaller watershed scales.
In 2010, the U.S. Geological Survey partnered with the U.S. Environmental Protection Agency and the U.S. Department of Agriculture to initiate water-quality monitoring in four selected small watersheds that were targeted for increased implementation of conservation practices. Smith Creek watershed is an agricultural watershed in the Shenandoah Valley of Virginia that is dominated by cattle and poultry production, and the Upper Chester River watershed is an agricultural watershed on the Eastern Shore of Maryland that is dominated by row-cropping activities. The Conewago Creek watershed is an agricultural watershed in southeastern Pennsylvania that is characterized by mixed agricultural activities. The fourth watershed, Difficult Run, is a suburban watershed in northern Virginia that is dominated by medium density residential development. The objective of this study was to investigate spatial and temporal variations in water chemistry and suspended sediment in these four relatively small watersheds that represent a range of land-use patterns and underlying geology to (1) characterize current water-quality conditions in these watersheds, and (2) identify the dominant sources, sinks, and transport processes in each watershed.
The general study design involved two components. The first included intensive routine water-quality monitoring at an existing streamgage within each study area (including continuous water-quality monitoring as well as discrete water-quality sampling) to develop a detailed understanding of the temporal and hydrologic variability in stream chemistry and sediment transport in each watershed. The second component involved extensive water-quality monitoring at various sites throughout each watershed to develop a detailed understanding of spatial patterns. Both components were used to improve understanding of sources and transport processes affecting stream chemistry, including nutrients and suspended sediments, and their implications for detecting long-term trends related to best management practices. This report summarizes the results of monitoring that was performed from April 2010 through September 2013.
Summaries for each of the four small watersheds are presented below. Each watershed has a more descriptive and detailed section in the report, but these summaries may be particularly useful for some watershed managers and stakeholders desiring slightly less technical detail.
Smith Creek is a 105.39-mi2 watershed within the Shenandoah Valley that drains to the North Fork Shenandoah River. The long-term Smith Creek base-flow index is 72.3 percent, indicating that on average, approximately 72 percent of Smith Creek flow was base flow, which suggests that Smith Creek streamflow is dominated by groundwater discharge rather than stormwater runoff. A series of cluster and principal components analyses demonstrated that the majority of the variability in Smith Creek water quality could be attributed to hydrologic and seasonal variability. Statistically significant positive correlations with flow were observed for turbidity, suspended sediments, total nitrogen, ammonium, orthophosphate, iron, total phosphorus, and the ratio of calcium to magnesium. Statistically significant inverse correlations with flow were observed for specific conductance, magnesium, δ15N of nitrate, pH, bicarbonate, calcium, and δ18O of nitrate. Of particular note, flow and nitrate were not statistically significantly correlated, likely because of the relatively complex concentration-discharge relationship observed in continuous and discrete datasets. Statistically significant seasonal patterns were observed for numerous water-quality constituents: water temperature, turbidity, orthophosphate, total phosphorus, suspended-sediment concentration, and silica were higher during the warm season, but pH, dissolved oxygen, and sulfate were higher during the cool season. Surrogate regression models were developed to compute sediment and nutrient loads in Smith Creek using the continuous water-quality monitors. The mean Smith Creek in-stream sediment load was approximately 6,900 tons per year, with nearly 90 percent of the sediment load over the 3-year study period contributed during the eight largest storm events during that period. The Smith Creek total phosphorus load was approximately 21,000 pounds of phosphorus per year, with the majority of the load contributed during stormflow periods, although a substantial phosphorus load still occurs during base-flow conditions. The Smith Creek total nitrogen load was approximately 400,000 pounds per year, with total nitrogen accumulation less dominated by stormflow contributions (as was the case for sediment and total phosphorus) and strongly affected by base-flow export of nitrogen from the basin.
Extensive water-quality monitoring throughout the Smith Creek watershed revealed how the complex geology and hydrology interacted to result in variable water chemistry. During relatively dry and low base-flow periods, much of the discharge in Smith Creek was contributed by a single dominant spring—Lacey Spring. During wetter base-flow periods, the flows in Smith Creek were largely generated by a mixture of headwater springs and forested mountain tributaries with very different geochemical composition. The headwater springs generally issued from limestone bedrock and were characterized as having relatively high nitrate, specific conductance, calcium, and magnesium, as well as relatively low concentrations of phosphorus, ammonium, iron, and manganese. The undeveloped, high-gradient, forested mountain sites were generally characterized by low ionic strength waters with low nutrient concentrations. Nitrate isotope data from the limestone springs generally were consistent with manure-derived nitrogen sources (such as cattle and poultry), although the possibility of other mixed sources cannot be excluded. Nitrate isotope data from the undeveloped, high-gradient forested mountain sites were more consistent with nitrogen from undisturbed soils, atmospheric deposition, or nitrogen fixation. Regardless of the nitrogen source, oxygen isotope data indicate that the nitrate was largely a result of nitrification. Land-use data indicate that manure sources of nitrogen dominated watershed nitrogen inputs. Phosphorus sources were less well studied. The presence of a single point-source discharge near the town of New Market contributed the majority of the phosphorus to Smith Creek under base-flow conditions, but nonpoint sources of phosphorus dominated the loading to Smith Creek during stormflow periods.
Implementation of conservation practices increased in the Smith Creek watershed during the study period, and even though a broad range of practice types was implemented, the most common practices included stream fencing (for cattle exclusion), the development of nutrient management plans, conservation crop rotation, and the planting of cover crops. While the implementation of these conservation practices is encouraging, results indicate small increases in nitrate concentrations at the streamgage over the last 29 years, concurrent with small decreases in nitrate fluxes. It will likely be years before the cumulative effect of these practices can be detected in the Smith Creek water quality, and the magnitude of the effect of these conservation practices detected in Smith Creek will depend largely on whether nutrient loading (of manure and commercial fertilizer) is reduced over time.
The Upper Chester River watershed includes the 36-square-mile (mi2) watershed area around several nontidal tributaries that drain into the tidal Chester River. The streamgage is on Chesterville Branch, the largest nontidal tributary (approximately 6.12 mi2) and is the site for continuous water-quality monitoring for this project. The base-flow index at Chesterville Branch is about 72 percent and indicates that, as in most of the Coastal Plain, groundwater is the greatest contributor to streamflow. As such, more than 90 percent of the nitrogen in the stream is in the form of nitrate from groundwater. Continuous and discrete data collected at Chesterville Branch show the effects of streamflow and season on water quality. Significantly positive correlations with flow were observed for ammonium, dissolved and total phosphorus, sediment, and turbidity as runoff carried these constituents from the land surface into Chesterville Branch. Other constituents that increased significantly with flow include potassium, sulfate, iron, and manganese, which are likely contributed from near-stream areas and ponds with high organic-matter content. Total nitrogen, pH, and specific conductance, along with chemical constituents associated with groundwater inputs including nitrate, calcium, ratio of calcium to magnesium, silica, bicarbonate, and sodium, were negatively correlated with flow because concentrations of these constituents were diluted by runoff.
Seasonal differences in water chemistry, which are most likely related to increased biologic effects on the uptake and release of chemicals in the stream and near-stream areas, also were observed. Water temperature, orthophosphate, δ15N of nitrate, bicarbonate, sodium, and the ratio of sodium to chloride were higher during the warm season, and dissolved oxygen, total nitrogen, nitrate, magnesium, sulfate, and manganese were higher during the cool season.
Surrogate-regression models developed by using continuous water-quality data showed that the annual sediment load for the 2013 water year was about 2,600 tons, with more than 90 percent of this sediment contributed during two storms. The total phosphorus load in 2013 was about 13,000 pounds with more than 90 percent contributed during the same two storms as sediment. The load of total nitrogen, 140,000 pounds, accumulated steadily throughout the 2013 water year as nitrate in groundwater continuously discharged into the stream. The same two large storms that contributed 90 percent of the suspended-sediment and total phosphorus load only contributed about 20 percent of the annual total nitrogen load.
Extensive water-quality monitoring of stream base flow throughout the Upper Chester River watershed identified how differences in land use and hydrogeology affected water chemistry. In parts of the watershed with well-drained soil and thick sandy aquifer sediments, concentrations of nitrate and other chemicals associated with fertilizer and lime application increased in streams as agricultural land use increased. More than 90 percent of the nitrogen in streams from these areas was in the form of nitrate, and concentrations ranged from about 5 milligrams per liter (mg/L) to 8 mg/L as nitrogen in the two largest tributaries. Stream nitrate concentrations were about 1 mg/L as nitrogen where soils were more poorly drained, the surficial aquifer sediments were thinner, and forests and wetlands were more widespread than agriculture. Nitrate isotope data were consistent with inorganic fertilizers ± atmospheric deposition and N2 fixation as sources of nitrogen, and with nitrification as the dominant nitrate-forming process. Nitrate reduction was indicated by elevated δ15N and δ18O values in some samples from streams draining watersheds with poorly drained soils. An analysis of land-use data and SPARROW modeling input data attributed almost 90 percent of the nitrogen sources in the Upper Chester River watershed to inorganic fertilizer and fixation of atmospheric nitrogen by legumes, which is in agreement with the isotopic characteristics of nitrate in this watershed. Local sources of manure are limited in this area. Total phosphorus concentrations during base flow ranged from below detection to about 0.2 mg/L. Stream phosphorus concentrations during base flow were generally lower than those measured during storms because most phosphorus transport likely occurs as phosphorus attached to sediment particles during runoff. Because manure is not widely used in this area, the major source of phosphorus is likely fertilizer.
The implementation of conservation practices in the Upper Chester River watershed increased substantially during the study period, with a total implementation of 1,194 U.S. Department of Agriculture-compliant practices. The most frequently used practices were oriented towards nutrient and sediment control, including cover crops, nutrient management planning, conservation crop rotation, conservation tillage, and irrigation management. The current Chesapeake Bay model for this area predicts that implementation of best management practices should result in a 13-percent decrease in overall delivery of nitrogen to the Upper Chester River. Because most nitrogen travels through the groundwater system for years to decades before being discharged to streams, the time period of monitoring was not sufficient to see the effects of these practices on water quality. The magnitude of the effect that may eventually be detected will depend on the degree to which nitrate leaching into the groundwater system is reduced over time. Loadings of phosphorus and sediment are primarily transported during large runoff events and are difficult to control and analyze for trends because of their timing and episodic nature.
Conewago Creek has two primary monitoring locations—one near the middle of the 47-mi2 watershed and the other near the outlet just upstream of the Susquehanna River. The base-flow index was 47.3 percent for 2012–2013, indicating that on average, approximately 53 percent of the streamflow in Conewago Creek exited the watershed as surface flow, which suggests that the stormwater runoff was somewhat greater than groundwater discharge (base flow). A series of cluster and principal components analyses demonstrated that the majority of the variability in the Conewago Creek water quality could be attributed to hydrologic and seasonal variability. Statistically significant positive correlations with flow were observed at both monitoring sites for ammonium, total phosphorus, orthophosphate, iron, and manganese; additionally, at the upstream monitoring station, total nitrogen demonstrated a statistically significant positive correlation with flow. Statistically significant inverse correlations with flow were observed at both sites for water temperature, specific conductance (at the downstream site only), sulfate, chloride, calcium, and magnesium. Statistically significant seasonal patterns were observed for several water-quality constituents. Water temperature, phosphorus (upstream site only), and orthophosphate were higher during the warm season, and nitrate and total nitrogen (upstream site only) were higher during the cool season.
Surrogate regression models were developed to compute sediment and nutrient load in Conewago Creek by using the continuous water-quality monitors and water-quality samples. Conewago Creek sediment load was approximately 9,900 tons in 2012 and approximately 18,900 tons in 2013, with nearly 80 percent of the sediment load in 2013 contributed by the three largest storm events. Annual total nitrogen loads could not be estimated due to poor model performance. The addition of continued monitoring or a continuously recording nitrate sensor could improve estimates of total nitrogen loads. During 2012 and 2013, phosphorus loads in Conewago Creek were approximately 50,000 pounds in each year.
Combining data from one high-flow synoptic sampling with the data from routine sampling revealed how the geology and hydrology interact to result in variable water chemistry throughout the Conewago Creek watershed. The areas above the upstream gage in the headwaters are generally underlain by forested non-carbonate bedrock and are characterized by relatively low nitrate, specific conductance, calcium, and magnesium, as well as relatively low concentrations of phosphorus, ammonium, iron, and manganese. The more developed, agricultural areas below the upstream site were generally characterized by higher ionic strength waters with higher nutrient and metal concentrations. An analysis of land-use data and SPAtially Referenced Regressions On Watershed (SPARROW) modeling data indicates that manure sources of nitrogen dominate the input of nitrogen to the watershed.
Implementation of conservation practices increased in the Conewago Creek watershed during the study period, and while a broad range of practice types were implemented, the most common practices included residue and tillage management, cover crops, nutrient management, terracing, and stream fencing (for animal exclusion or bank restoration). While the implementation of these conservation practices is encouraging, the cumulative effects of these practices probably will not be detected in Conewago Creek water quality for several years. The magnitude of the effects of these conservation practices on water quality in Conewago Creek will depend largely on the extent to which nutrient loading (septic, manure, and commercial fertilizer) and sediment-producing activities are reduced over time.
The Difficult Run watershed is a 57.82-mi2 watershed that drains to the Potomac River. The long-term Difficult Run base-flow index (from 1936 to 2010) was 57.9, indicating that approximately 58 percent of streamflow exited the watershed as base flow and 42 percent as stormflow; however, with continued development and urbanization of the watershed, the base-flow index has decreased to 50 percent during the last 20 years. This base-flow index was less than those of the other watersheds evaluated in this study, likely because the Difficult Run watershed largely is underlain by crystalline piedmont metamorphic rocks and has a greater proportion of impervious urban land cover. A series of cluster and principal components analyses indicated that most of the variability in Difficult Run water quality could be attributed to hydrologic variability and seasonality. Statistically significant positive correlations with flow were observed for turbidity, dissolved oxygen, suspended sediments, ammonium, orthophosphate, iron, and total phosphorus. Statistically significant inverse correlations with flow were observed for water temperature, pH, specific conductance, bicarbonate, calcium, magnesium, nitrate, δ15N of nitrate, and silica. Statistically significant seasonal patterns were observed for numerous water-quality constituents: water temperature, ammonium, orthophosphate, and δ15N of nitrate were higher during the warm season, and dissolved oxygen, nitrate, and manganese were higher during the cool season. Surrogate regression models were developed to compute sediment and nutrient loading rates. The Difficult Run sediment load was approximately 8,000 tons per year, with greater than 95 percent of the sediment load in the 2013 water year contributed by the seven largest storm events. The total phosphorus load in Difficult Run was approximately 14,000 pounds of phosphorus per year, with the majority of the load contributed during stormflow periods. The total nitrogen load in Difficult Run is estimated to have been approximately 140,000 pounds per year, with total nitrogen accumulation less dominated by stormflow contributions than that of phosphorus and strongly affected by base-flow export of nitrogen from the basin.
Extensive water-quality monitoring throughout the Difficult Run watershed revealed relatively uniform generation of flow per unit of watershed area, as well as spatial variation in water quality that is strongly related to land-use activities. Elevated nitrate concentrations were observed in a subset of monitoring sites that are inversely correlated with population density and positively correlated to the septic system density within each subwatershed. The majority of the elevated nitrate concentrations for these sites are hypothesized to be caused by nitrate leaching from septic systems, more so than homeowner fertilizer usage among these subwatersheds that have lower population densities than other parts of the watershed. Nitrate isotope data, temporal patterns in the water-quality data, mass-balance computations, and a separate land-use analysis all generally indicate that leachate from septic systems was the likely source of the elevated nitrate. Another group of water-quality sites have relatively low nitrogen concentrations, are located in areas that are served by city sewer lines, and have experienced stream restoration activities. A final group of sites drained the areas with the highest imperviousness and had strongly elevated specific conductance, chloride, and sodium, which were likely caused by a combination of road salting and other anthropogenic sources draining these urbanized areas in the watershed. A fourth group of sites represents a mixture of water sources and had water quality similar to that at the Difficult Run streamgage. Analysis of the nitrate isotope data generally indicates a broad range of composition indicative of mixed natural and anthropogenic nitrogen sources. Implementation of conservation practices increased in the Difficult Run watershed during the study period, and while a broad range of practice types was implemented, the most common practices included stream restoration. While the implementation of these conservation practices is encouraging, the cumulative effect of these practices probably will not be detected in Difficult Run water quality for several years.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165093","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency Chesapeake Bay Program","usgsCitation":"Hyer, K.E., Denver, J.M., Langland, M.J., Webber, J.S., Böhlke, J.K., Hively, W.D., and Clune, J.W., 2016, Spatial and temporal variation of stream chemistry associated with contrasting geology and land-use patterns in the Chesapeake Bay watershed—Summary of results from Smith Creek, Virginia; Upper Chester River, Maryland; Conewago Creek, Pennsylvania; and Difficult Run, Virginia, 2010–2013: U.S. Geological Survey Scientific Investigations Report 2016–5093, 211 p., https://dx.doi.org/10.3133/sir20165093.","productDescription":"Report: xix, 211 p.","startPage":"1","endPage":"211","numberOfPages":"236","onlineOnly":"N","ipdsId":"IP-067371","costCenters":[{"id":614,"text":"Virginia Water Science 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U.S. Geological Survey
1730 East Parham Road
Richmond, VA 23228
Alaska has considerable potential for undiscovered mineral resources. This report evaluates potential for undiscovered critical minerals in Alaska. Critical minerals are those for which the United States imports more than half of its total supply and which are largely derived from nations that cannot be considered reliable trading partners. In this report, estimated resource potential and certainty for the state of Alaska are analyzed and mapped for the following six selected mineral deposit groups that may contain one or more critical minerals: (1) rare earth elements-thorium-yttrium-niobium(-uranium-zirconium) [REE-Th-Y-Nb(-U-Zr)] deposits associated with peralkaline to carbonatitic igneous intrusive rocks; (2) placer and paleoplacer gold (Au) deposits that in some places might also produce platinum group elements (PGE), chromium (Cr), tin (Sn), tungsten (W), silver (Ag), or titanium (Ti); (3) platinum group elements(-cobalt-chromium-nickel-titanium-vanadium) [PGE(-Co-Cr-Ni-Ti-V)] deposits associated with mafic to ultramafic intrusive rocks; (4) carbonate-hosted copper(-cobalt-silver-germanium-gallium) [Cu(-Co-Ag-Ge-Ga)] deposits; (5) sandstone-hosted uranium(-vanadium-copper) [U(-V-Cu)] deposits; and (6) tin-tungsten-molybdenum(-tantalum-indium-fluorspar) [Sn-W-Mo(-Ta-In-fluorspar)] deposits associated with specialized granites.
This study used a data-driven, geographic information system (GIS)-implemented method to identify areas that have mineral resource potential in Alaska. This method systematically and simultaneously analyzes geoscience data from multiple geospatially referenced datasets and uses individual subwatersheds (12-digit hydrologic units) as the spatial unit of classification. The final map output uses a red, yellow, green, and gray color scheme to portray estimated relative potential (High, Medium, Low, Unknown) for each of the six groups of mineral deposit types, and it indicates the relative certainty (High, Medium, Low) of that estimate for each 12-digit hydrologic unit through color shading. Accompanying tables describe the data layers employed to score favorability for the presence of each mineral deposit group, the values assigned for specific analysis parameters, and the relative weighting of each data layer that contributes to estimated measures of potential and certainty. Core datasets used include the Alaska Geochemical Database, Version 2.0 (AGDB2); the Alaska Division of Geological & Geophysical Surveys (ADGGS) web-based geochemical database; the digital “Geologic Map of Alaska;” the Alaska Resource Data File (ARDF); and aerial gamma-ray surveys flown as part of the National Uranium Resource Evaluation (NURE) Program by the U.S. Department of Energy.
Maps accompanying this report illustrate the scores for estimated mineral resource potential for the six deposit groups for the state of Alaska. Areas that have known potential, as well as new areas that were not previously known to have potential, for the targeted minerals and deposit groups are identified and described. Numerous areas in Alaska, some of them large, have high potential for one or more of the selected groups of deposit types within Alaska.
Matthew Granitto, Timothy S. Hayes, James V. Jones, III, Susan M. Karl, Keith A. Labay, Jeffrey L. Mauk, Jeanine M. Schmidt, Nora B. Shew, Erin Todd, Bronwen Wang, Melanie B. Werdon, and Douglas B. Yager
Alaska Science Center staff
U.S. Geological Survey
4210 University Dr.
Anchorage, AK 99508
Alaska Mineral Resources
Alaska Science Center
The U.S. Geological Survey, in cooperation with the Missouri Department of Natural Resources, designed and operates a series of monitoring stations on streams and springs throughout Missouri known as the Ambient Water-Quality Monitoring Network. During water year 2015 (October 1, 2014, through September 30, 2015), data were collected at 74 stations—72 Ambient Water-Quality Monitoring Network stations and 2 U.S. Geological Survey National Stream Quality Assessment Network stations. Dissolved oxygen, specific conductance, water temperature, suspended solids, suspended sediment, Escherichia coli bacteria, fecal coliform bacteria, dissolved nitrate plus nitrite as nitrogen, total phosphorus, dissolved and total recoverable lead and zinc, and select pesticide compound summaries are presented for 71 of these stations. The stations primarily have been classified into groups corresponding to the physiography of the State, primary land use, or unique station types. In addition, a summary of hydrologic conditions in the State including peak streamflows, monthly mean streamflows, and 7-day low flows is presented.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1023","collaboration":"Prepared in cooperation with the Missouri Department of Natural Resources","usgsCitation":"Barr, M.N., and Heimann, D.C., 2016, Quality of surface water in Missouri, water year 2015: U.S. Geological Survey Data Series 1023, 22 p., https://dx.doi.org/10.3133/ds1023.","productDescription":"v, 22 p.","numberOfPages":"32","onlineOnly":"Y","ipdsId":"IP-077875","costCenters":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"links":[{"id":330865,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1023/ds1023.pdf","text":"Report","size":"5.00 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1023"},{"id":330864,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1023/coverthb.jpg"}],"country":"United 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\"}}]}","contact":"Director, Missouri Water Science Center
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401
The Delaware River Basin (DRB) was selected as a Focus Area Study in 2011 by the U.S. Geological Survey (USGS) as part of the USGS National Water Census. The National Water Census is a USGS research program that focuses on national water availability and use and then develops new water accounting tools and assesses water availability at both the regional and national scales. One of the water management needs that the DRB study addressed, and that was identified by stakeholder groups from the DRB, was to improve the integration of state water use and water-supply data and to provide the compiled water use information to basin users. This water use information was also used in the hydrologic modeling and ecological components of the study.
Instream and offstream water use was calculated for 2010 for the DRB based on information received from Delaware, New Jersey, New York, and Pennsylvania. Water withdrawal, interbasin transfers, return flow, and hydroelectric power generation release data were compiled for 11 categories by hydrologic subregion, basin, subbasin, and subwatershed. Data availability varied by state. Site-specific data were used whenever possible to calculate public supply, irrigation (golf courses, nurseries, sod farms, and crops), aquaculture, self-supplied industrial, commercial, mining, thermoelectric, and hydroelectric power withdrawals. Where site-specific data were not available, primarily for crop irrigation, livestock, and domestic use, various techniques were used to estimate water withdrawals.
Total water withdrawals in the Delaware River Basin were calculated to be about 7,130 million gallons per day (Mgal/d) in 2010. Calculations of withdrawals by source indicate that freshwater withdrawals were about 4,130 Mgal/d (58 percent of the total) and the remaining 3,000 Mgal/d (42 percent) were from saline water. Total surface-water withdrawals were calculated to be 6,590 Mgal/d, or 92 percent of the total; about 54 percent (3,590 Mgal/d) of surface water withdrawn was freshwater. Total groundwater withdrawals were calculated to be 545 Mgal/d (8 percent of the total), all of which was freshwater. During 2010, calculated withdrawals by category, in decreasing order, were: thermoelectric power, 4,910 Mgal/d; public supply, 1,490 Mgal/d; self-supplied industrial, 350 Mgal/d; irrigation, 175 Mgal/d; self-supplied domestic, 117 Mgal/d; mining, 41.3 Mgal/d; aquaculture, 19.3 Mgal/d; livestock, 6.72 Mgal/d, and commercial, 5.89 Mgal/d. The amount of instream use for hydroelectric power generation purposes in 2010 was reported to be 273 Mgal/d for the Wallenpaupack Plant and 127 Mgal/d for the Mongaup River system.
Total return flows in the DRB were 2,960 Mgal/d in 2010. Although municipal wastewater-treatment plants accounted for 539 (97 percent) of the return-flow sites, they accounted for about 70 percent of the total return flows in the DRB. There was limited information on return flows from thermoelectric power.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155142","usgsCitation":"Hutson, S.S., Linsey, K.S., Ludlow, R.A., Reyes, Betzaida, and Shourds, J.L., 2016, Estimated use of water in the Delaware River Basin in Delaware, New Jersey, New York, and Pennsylvania, 2010: U.S. Geological Survey Scientific Investigations Report 2015–5142, 76 p., https://dx.doi.org/10.3133/sir20155142.","productDescription":"Report: vii, 76 p.; 2 Appendixes; Data Release","numberOfPages":"88","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-058986","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"links":[{"id":438513,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7TM787C","text":"USGS data release","linkHelpText":"Estimated Use of Water by Subbasin (HUC8 and HUC12) in the Delaware River Basin, 2010"},{"id":330727,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5142/sir20155142_appendix3.xlsx","text":"Appendix 3","size":"269 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2015-5142 Appendix 3","linkHelpText":"- Delaware River Basin Water Use by Subbasin, 2010"},{"id":330724,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5142/coverthb.jpg"},{"id":330725,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5142/sir20155142.pdf","text":"Report","size":"57.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5142"},{"id":330726,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5142/sir20155142_appendix2.docx","text":"Appendix 2","size":"2.49 MB docx","description":"SIR 2015-5142 Appendix 2","linkHelpText":"- Hydrologic Subbasins, Watersheds, and Subwatersheds in the Delaware River Basin"},{"id":330728,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7TM787C","text":"USGS data release","description":"USGS data release","linkHelpText":"Estimated Use of Water by Subbasin (HUC8) and Subwatershed (HUC12) in the Delaware River Basin, 2010"}],"country":"United States","state":"Delaware, New Jersey, New York, Pennsylvania","otherGeospatial":"Delaware River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.652099609375,\n 39.18117526158749\n ],\n [\n -74.50927734375,\n 40.195659093364654\n ],\n [\n -74.586181640625,\n 41.36856413680967\n ],\n [\n -74.300537109375,\n 42.09822241118974\n ],\n [\n -74.619140625,\n 42.53689200787315\n ],\n [\n -75.498046875,\n 42.10637370579324\n ],\n [\n -75.9375,\n 41.12074559016745\n ],\n [\n -76.607666015625,\n 40.36328834091583\n ],\n [\n -75.860595703125,\n 39.715638134796336\n ],\n [\n -75.43212890625,\n 38.685509760012\n ],\n [\n -75.069580078125,\n 38.77121637244273\n ],\n [\n -74.652099609375,\n 39.18117526158749\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Coordinator—National Water Census
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1770 Corporate Drive, Suite 500
Norcross, GA 30093
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