Lago La Plata is operated by the Puerto Rico Aqueduct and Sewer Authority (PRASA) and is part of the San Juan Metropolitan Water District. The reservoir serves a population of about 425,000 people. During 2013 the reservoir provided 0.307 million cubic meters (Mm3 ) of water per day (about 81 million gallons per day), which is equivalent to 31 percent of the total water demand for the metropolitan area (Wanda L. Molina, U.S. Geological Survey, written commun., 2015). The dam was constructed in 1974 and is located about 5 kilometers (km) south of the town of Toa Alta and 5 km north of the town of Naranjito (fig. 1). The drainage area upstream from the Lago La Plata dam is about 469 square kilometers (km2 ). The storage capacity at construction in 1974 was 26.84 Mm3 with a spillway elevation of 47.12 meters (m) above mean sea level (msl). Storage capacity was increased to 40.21 Mm3 in 1989 after the installation of bascule gates to provide a normal dam pool elevation at 52 m above msl (Puerto Rico Electric and Power Authority, 1979). The maximum height of the dam is about 40 m above the river bottom near the dam, and the intake structure consists of six 1.82-m-diameter ports facing upstream, with 6-m vertical spacing that begins at an elevation of 19 m above msl. The U.S. Geological Survey (USGS), in cooperation with the PRASA, conducted a bathymetric survey of the Lago La Plata reservoir during March and April 2015. The hydrographic survey was designed to provide an update of the reservoir storage capacity and sedimentation rate. Areas with substantial sediment accumulation are also discussed in this report. The results of the survey were used to prepare a bathymetric map showing the reservoir bottom (fig. 2) referenced with respect to the spillway elevation. This report also includes a summary of a previous bathymetric survey conducted in 2006 (Soler-López, 2008).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3369","collaboration":"Prepared in cooperation with the Puerto Rico Aqueduct and Sewer Authority (PRASA)","usgsCitation":"Gómez-Fragoso, Julieta, 2016, Sedimentation survey of Lago La Plata, Toa Alta, Puerto Rico, March–April 2015: U.S. Geological Survey Scientific Investigations Map 3369, 1 sheet, https://dx.doi.org/10.3133/sim3369.","productDescription":"29.00 x 30.50 inches","numberOfPages":"1","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-071332","costCenters":[{"id":156,"text":"Caribbean Water Science Center","active":true,"usgs":true}],"links":[{"id":438522,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7PZ56XZ","text":"USGS data release","linkHelpText":"Data and shapefiles for the sedimentation survey of Lago La Plata, Toa Alta, Puerto Rico"},{"id":330426,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3369/coverthb.jpg"},{"id":330427,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3369/sim3369.pdf","text":"Report","size":"1.23","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3369"},{"id":330428,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7PZ56XZ","text":"USGS data release ","description":"USGS data release","linkHelpText":"Spatial data for the sedimentation survey of Lago La Plata, Toa Alta, Puerto Rico, March-April 2015"}],"country":"United States","state":"Puerto Rico","otherGeospatial":"Lago La Plata","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -66.24996185302734,\n 18.289504907462902\n ],\n [\n -66.24996185302734,\n 18.34654185709673\n ],\n [\n -66.19829177856445,\n 18.34654185709673\n ],\n [\n -66.19829177856445,\n 18.289504907462902\n ],\n [\n -66.24996185302734,\n 18.289504907462902\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
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4446 Pet Lane, Suite 108
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https://www.usgs.gov/water/caribbeanflorida
Nutrients, particularly nitrogen and phosphorus, are a leading cause of water-quality impairment in Kansas and the Nation. Indian Creek is one of the most urban drainage basins in Johnson County, Kansas, and environmental and biological conditions are affected by contaminants from point and other urban sources. The Johnson County Douglas L. Smith Middle Basin (hereinafter Middle Basin) wastewater treatment facility (WWTF) is the largest point-source discharge on Indian Creek. A second facility, the Tomahawk Creek WWTF, discharges into Indian Creek approximately 11.6 kilometers downstream from the Middle Basin WWTF. To better characterize the spatiotemporal variability of nutrients in Indian Creek, the U.S. Geological Survey, in cooperation with the Kansas Department of Health and Environment and Johnson County Wastewater, collected high-resolution spatial and temporal (a large number of samples collected over the entire reach or at single locations over a long period of time) inorganic nutrient (nitrate plus nitrite and orthophosphorus) data using a combination of discrete samples and sensor-measured data during 2012 through 2015.
Nutrient patterns observed in Indian Creek along the upstream-downstream gradient during wastewater effluent dominated streamflow conditions were largely affected by the WWTFs and by travel time of the parcels of water. Nitrate plus nitrite concentrations in the Middle Basin WWTF effluent and at downstream sites varied by as much as 6 milligrams per liter over a 24-hour period. The cyclical variability in the Middle Basin WWTF effluent generated a nitrate plus nitrite pulse that could be tracked for approximately 11.5 kilometers downstream in Indian Creek, until the effect was masked by the Tomahawk Creek WWTF effluent discharge. All longitudinal surveys showed the same general patterns along the upstream-downstream gradient, though streamflows, wastewater effluent contributions to streamflow, and nutrient concentrations spanned a wide range. Differences in orthophosphorus and nitrate plus nitrite patterns were clear along the upstream-downstream gradient in Indian Creek, and orthophosphorus concentrations were not as variable as nitrate plus nitrite concentrations. In general, nitrate plus nitrite concentrations decreased downstream from the Middle Basin WWTF to minima near the confluence with Tomahawk Creek, increased downstream from the Tomahawk Creek WWTF, and then varied little within the study reach. Orthophosphorus concentrations generally decreased downstream from the Middle Basin WWTF.
Despite the marked variability in nitrate plus nitrite concentrations caused by the Middle Basin WWTF effluent discharges, decreases in nitrate plus nitrite concentrations were discernable along the study reach between the two WWTFs. Decreases in nitrate plus nitrite concentrations along study reach were less variable than the cyclical variability typically measured, reiterating the effect of the Middle Basin WWTF effluent discharges on the spatiotemporal variability of nitrate plus nitrite in Indian Creek. Although decreases and rates of change in nitrate plus nitrite concentration were similar between the upper and lower reaches of Indian Creek, relations with initial nitrate plus nitrite concentrations and seasonal patterns were different between the upper (from College to the Marty study sites) and lower reaches (from Marty to the Mission Farms study sites) and did not reflect patterns observed for the overall reach. Quantifying the decreases in nitrate plus nitrite concentration caused by dilution and other in-stream processes were beyond the scope of this study, and were limited by available data. The data that are available suggest that dilution and other in-stream processes play a role in decreasing nitrate plus nitrite concentrations downstream from the Middle Basin WWTF in Indian Creek.
Analysis of the spatiotemporal variability of nutrients focused on below-normal and normal streamflow conditions, when streamflow and nutrient conditions in Indian Creek were largely controlled by WWTF effluent flows and nutrient removal processes. Spatial and temporal data indicate there are decreases in nutrient concentrations along the upstream-downstream gradient in Indian Creek, but quantifying decreases is complicated by the variability in nutrient concentrations caused by the WWTFs. During below-normal and normal streamflow conditions, Indian Creek nutrient concentrations downstream from the Middle Basin WWTF primarily reflect effluent concentrations in the hours or days before depending on relative distance downstream.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165147","collaboration":"Prepared in cooperation with the Kansas Department of Health and Environment and Johnson County Wastewater","usgsCitation":"Foster, G.M, Graham, J.L., Williams, T.J., and King, L.R., 2016, Spatiotemporal variability of inorganic nutrients during wastewater effluent dominated streamflow conditions in Indian Creek, Johnson County, Kansas, 2012–15: U.S. Geological Survey Scientific Investigations Report 2016–5147, 37 p., https://dx.doi.org/10.3133/sir20165147.","productDescription":"Report: v, 36 p.; Appendixes 1-4; Data Releases","numberOfPages":"48","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-077541","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":438525,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7445JN8","text":"USGS data release","linkHelpText":"Water-quality data from four Indian Creek sites, Johnson County, Kansas, July 22-25, 2014 and August 21-27, 2015"},{"id":438524,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F77W69CP","text":"USGS data release","linkHelpText":"Spatial water-quality data for Indian Creek, Johnson County, Kansas, May 23, 2013, July 23, 2014, July 30, 2015, and August 26, 2015"},{"id":330584,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F77W69CP","text":"USGS data release - Spatial water-quality data for Indian Creek, Johnson County, Kansas, May 23, 2013, July 23, 2014, July 30, 2015, and August 26, 2015"},{"id":330581,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5147/sir20165147_appendix.pdf","text":"Appendixes 1–4","size":"698 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5147 Appendixes 1–4"},{"id":330585,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7445JN8","text":"USGS data release - Water-quality data from four Indian Creek sites, Johnson County, Kansas, July 22-25, 2014 and August 21-27, 2015"},{"id":330579,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5147/coverthb.jpg"},{"id":330580,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5147/sir20165147.pdf","text":"Report","size":"3.59 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5147"}],"country":"United States","state":"Kansas","county":"Johnson County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-94.6075,39.0437],[-94.6075,39.0399],[-94.6082,38.8463],[-94.6084,38.8341],[-94.6102,38.7376],[-95.0572,38.7395],[-95.0558,38.9816],[-95.0477,38.9778],[-95.0383,38.9771],[-95.0312,38.9773],[-95.0292,38.9813],[-95.0271,38.9881],[-95.0249,38.9962],[-95.0189,38.9987],[-95.0135,38.9991],[-95.0077,38.998],[-94.9946,38.9976],[-94.9899,38.997],[-94.9841,38.995],[-94.9789,38.9926],[-94.9755,38.9885],[-94.9704,38.9851],[-94.9645,38.9832],[-94.9575,38.982],[-94.9527,38.9828],[-94.9479,38.9845],[-94.9448,38.9871],[-94.9423,38.9898],[-94.9386,38.9933],[-94.9367,38.9964],[-94.9335,38.9995],[-94.9264,38.9998],[-94.9217,38.9996],[-94.9176,38.9977],[-94.9209,38.9919],[-94.923,38.9856],[-94.9207,38.9837],[-94.9164,38.9859],[-94.9115,38.9889],[-94.9078,38.9924],[-94.9014,39.0022],[-94.8989,39.0053],[-94.8945,39.0102],[-94.8919,39.0155],[-94.891,39.021],[-94.8875,39.0313],[-94.8824,39.0379],[-94.8768,39.0441],[-94.8681,39.052],[-94.8631,39.0564],[-94.8488,39.0578],[-94.8318,39.0546],[-94.8131,39.0486],[-94.8038,39.0456],[-94.7197,39.0435],[-94.6693,39.0433],[-94.6075,39.0437]]]},\"properties\":{\"name\":\"Johnson\",\"state\":\"KS\"}}]}","contact":"Director, Kansas Water Science Center
U.S. Geological Survey
4821 Quail Crest Place
Lawrence, KS 66049
In the Prairie Pothole Region of North America, disturbances to wetlands that disrupt water-level fluctuations in response to wet–dry climatic conditions have the potential to alter natural vegetative communities in favor of species that proliferate in stable environments, such as cattail (Typha spp.). We evaluated the effect of water-level dynamics during a recent fluctuation in wet–dry conditions on cattail coverage within semipermanently and permanently ponded wetlands situated in watersheds with different land use and amounts of wetland drainage. We found that ponded water depth increase was significantly greater in wetlands where water levels were not near the spill point of the topographic basin, where banks were steeper, and in larger wetlands where past dry conditions had less influence on change in pond area. Proportion of the wetland covered by cattail was negatively correlated with increased water depth, bank slope and pond area. Our observations provide evidence that cattail coverage in prairie wetlands is regulated by water-level fluctuations and that land use surrounding the wetland might have an indirect effect on cattail coverage by altering water-level response to wet–dry climate conditions. For example, drainage of smaller wetlands into larger wetlands that are characterized by more permanent hydroperiods, leads to stabilized water levels near their spill point and is therefore a potential mechanism for increased cattail abundance in the northern prairie region.
","language":"English","publisher":"Springer","doi":"10.1007/s11273-016-9485-z","usgsCitation":"Wiltermuth, M.T., and Anteau, M.J., 2016, Is consolidation drainage an indirect mechanism for increased abundance of cattail in northern prairie wetlands?: Wetlands Ecology and Management, v. 24, no. 5, p. 533-544, https://doi.org/10.1007/s11273-016-9485-z.","productDescription":"12 p.","startPage":"533","endPage":"544","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066549","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":330569,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Dakota","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.08447265624999,\n 49.023461463214126\n ],\n [\n -97.2509765625,\n 49.03786794532644\n ],\n [\n -97.09716796875,\n 48.76343113791796\n ],\n [\n -97.18505859374999,\n 48.42920055556841\n ],\n [\n -97.119140625,\n 48.03401915864286\n ],\n [\n -96.94335937499999,\n 47.81315451752768\n ],\n [\n -96.83349609375,\n 47.56170075451973\n ],\n [\n -96.83349609375,\n 47.010225655683485\n ],\n [\n -96.83349609375,\n 46.84516443029276\n ],\n [\n -96.83349609375,\n 46.483264729155586\n ],\n [\n -96.61376953125,\n 46.28622391806706\n ],\n [\n -96.56982421875,\n 45.920587344733654\n ],\n [\n -97.8662109375,\n 45.9511496866914\n ],\n [\n -100.52490234375,\n 45.9511496866914\n ],\n [\n -100.8984375,\n 46.5739667965278\n ],\n [\n -101.162109375,\n 47.100044694025215\n ],\n [\n -101.337890625,\n 47.487513008956554\n ],\n [\n -101.62353515625,\n 47.487513008956554\n ],\n [\n -102.26074218749999,\n 47.5913464767971\n ],\n [\n -102.76611328125,\n 47.82790816919329\n ],\n [\n -103.16162109375,\n 48.09275716032736\n ],\n [\n -103.64501953125,\n 48.21003212234042\n ],\n [\n -104.0625,\n 48.19538740833338\n ],\n [\n -104.08447265624999,\n 49.023461463214126\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"24","issue":"5","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-25","publicationStatus":"PW","scienceBaseUri":"5818582de4b0bb36a4c6fa09","chorus":{"doi":"10.1007/s11273-016-9485-z","url":"http://dx.doi.org/10.1007/s11273-016-9485-z","publisher":"Springer Nature","authors":"Wiltermuth Mark T., Anteau Michael J.","journalName":"Wetlands Ecology and Management","publicationDate":"3/25/2016","auditedOn":"8/1/2016","publiclyAccessibleDate":"3/25/2016"},"contributors":{"authors":[{"text":"Wiltermuth, Mark T. 0000-0002-8871-2816 mwiltermuth@usgs.gov","orcid":"https://orcid.org/0000-0002-8871-2816","contributorId":708,"corporation":false,"usgs":true,"family":"Wiltermuth","given":"Mark","email":"mwiltermuth@usgs.gov","middleInitial":"T.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":652475,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anteau, Michael J. 0000-0002-5173-5870 manteau@usgs.gov","orcid":"https://orcid.org/0000-0002-5173-5870","contributorId":3427,"corporation":false,"usgs":true,"family":"Anteau","given":"Michael","email":"manteau@usgs.gov","middleInitial":"J.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":652476,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70192934,"text":"70192934 - 2016 - Loads of nitrate, phosphorus, and total suspended solids from Indiana watersheds","interactions":[],"lastModifiedDate":"2017-10-30T11:11:51","indexId":"70192934","displayToPublicDate":"2016-10-30T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3159,"text":"Proceedings of the Indiana Academy of Science","active":true,"publicationSubtype":{"id":10}},"title":"Loads of nitrate, phosphorus, and total suspended solids from Indiana watersheds","docAbstract":"Transport of excess nutrients and total suspended solids (TSS) such as sediment by freshwater systems has led to degradation of aquatic ecosystems around the world. Nutrient and TSS loads from Midwestern states to the Mississippi River are a major contributor to the Gulf of Mexico Hypoxic Zone, an area of very low dissolved oxygen concentration in the Gulf of Mexico. To better understand Indiana’s contribution of nutrients and TSS to the Mississippi River, annual loads of nitrate plus nitrite as nitrogen, total phosphorus, and TSS were calculated for nine selected watersheds in Indiana using the load estimation model, S-LOADEST. Discrete water-quality samples collected monthly by the Indiana Department of Environmental Management’s Fixed Stations Monitoring Program from 2000–2010 and concurrent discharge data from the U. S. Geological Survey streamflow gages were used to create load models. Annual nutrient and TSS loads varied across Indiana by watershed and hydrologic condition. Understanding the loads from large river sites in Indiana is important for assessing contributions of nutrients and TSS to the Mississippi River Basin and in determining the effectiveness of best management practices in the state. Additionally, evaluation of loads from smaller upstream watersheds is important to characterize improvements at the local level and to identify priorities for reduction.","language":"English","publisher":"Indiana Academy of Sciences","usgsCitation":"Bunch, A.R., 2016, Loads of nitrate, phosphorus, and total suspended solids from Indiana watersheds: Proceedings of the Indiana Academy of Science, v. 125, p. 137-150.","productDescription":"14 p.","startPage":"137","endPage":"150","numberOfPages":"14","ipdsId":"IP-070855","costCenters":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":347653,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":347652,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.indianaacademyofscience.org/publications/proceedings"}],"volume":"125","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59f83a3be4b063d5d3098102","contributors":{"authors":[{"text":"Bunch, Aubrey R. 0000-0002-2453-3624 aurbunch@usgs.gov","orcid":"https://orcid.org/0000-0002-2453-3624","contributorId":4351,"corporation":false,"usgs":true,"family":"Bunch","given":"Aubrey","email":"aurbunch@usgs.gov","middleInitial":"R.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true},{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":717378,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70177152,"text":"sir20165154 - 2016 - Hydrogeologic framework of LaSalle County, Illinois","interactions":[],"lastModifiedDate":"2016-11-01T10:45:34","indexId":"sir20165154","displayToPublicDate":"2016-10-28T09:30:00","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":"2016-5154","title":"Hydrogeologic framework of LaSalle County, Illinois","docAbstract":"Water-supply needs in LaSalle County in northern Illinois are met by surface water and groundwater. Water-supply needs are expected to increase to serve future residential and mining uses. Available information on water use, geology, surface-water and groundwater hydrology, and water quality provides a hydrogeologic framework for LaSalle County that can be used to help plan the future use of the water resources.
The Illinois, Fox, and Vermilion Rivers are the primary surface-water bodies in LaSalle County. These and other surface-water bodies are used for wastewater disposal in the county. The Vermilion River is used as a drinking-water supply in the southern part of the county. Water from the Illinois and Fox Rivers also is used for the generation of electric power.
Glacial drift aquifers capable of yielding sufficient water for public supply are expected to be present in the Illinois River Valley in the western part of the county, the Troy Bedrock Valley in the northwestern part of the county, and in the Ticona Bedrock Valley in the south-central part of the county. Glacial drift aquifers capable of yielding sufficient water for residential supply are present in most of the county, although well yield often needs to be improved by using large-diameter wells. Arsenic concentrations above health-based standards have been detected in some wells in this aquifer. These aquifers are a viable source for additional water supply in some areas, but would require further characterization prior to full development.
Shallow bedrock deposits comprising the sandstone units of the Ancell Group, the Prairie du Chien Group, dolomite of the Galena and Platteville Groups, and Silurian-aged dolomite are utilized for water supply where these units are at or near the bedrock surface or where overlain by Pennsylvanian-aged deposits. The availability of water from the shallow bedrock deposits depends primarily on the geologic unit analyzed. All these deposits can yield sufficient water for residential supply in at least some parts of the county, and sandstone deposits in the Ancell and Prairie du Chien Groups can yield sufficient water for residential or public supply in much of the county.
The Cambrian-Ordovician aquifer system comprises the most widespread, productive aquifers in northern Illinois and is used for water supply by a number of municipalities in the county. Water levels in the aquifer system have declined by as much as 300 feet in parts of LaSalle County. The aquifer contains naturally occurring concentrations of radium that are higher than established health guidelines in much of the county.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165154","collaboration":"Prepared in cooperation with the LaSalle County Board and Northwestern University ","usgsCitation":"Kay, R.T., and Bailey, C.R., 2016, Hydrogeologic framework of LaSalle County, Illinois: U.S. Geological Survey Scientific Investigations Report 2016–5154, 97 p., https://dx.doi.org/10.3133/sir20165154.","productDescription":"vii, 97 p.","numberOfPages":"110","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-075663","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":330347,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5154/coverthb3.jpg"},{"id":330348,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5154/sir20165154.pdf","text":"Report","size":"11.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5154"}],"country":"United States","state":"Illinois","county":"LaSalle County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-88.602,41.6331],[-88.6001,41.5454],[-88.5975,41.4565],[-88.5943,41.3697],[-88.59,41.2826],[-88.5892,41.1959],[-88.5873,41.1106],[-88.7007,41.1095],[-88.8148,41.1084],[-88.9306,41.1067],[-88.9313,41.0164],[-88.9314,40.9279],[-89.0476,40.9261],[-89.0482,40.9261],[-89.0479,40.9833],[-89.0495,41.0155],[-89.0529,41.0595],[-89.0468,41.0622],[-89.0477,41.1053],[-89.1617,41.1048],[-89.1637,41.1928],[-89.1645,41.2799],[-89.165,41.3099],[-89.1649,41.3221],[-89.1654,41.3661],[-89.1664,41.4079],[-89.1668,41.4542],[-89.1672,41.4964],[-89.1676,41.5418],[-89.168,41.5845],[-89.1672,41.629],[-89.0529,41.6273],[-89.0099,41.6271],[-88.9381,41.6291],[-88.8158,41.6321],[-88.712,41.6324],[-88.602,41.6331]]]},\"properties\":{\"name\":\"La Salle\",\"state\":\"IL\"}}]}","contact":"Director, Illinois Water Science Center
U.S. Geological Survey
405 N Goodwin
Urbana, IL 61801
Or visit our Web site at:
http://il.water.usgs.gov
With growing climate change concerns and energy constraints, there is an increasing need for renewable energy sources within the United States and globally. Looking forward, offshore wind-energy infrastructure (OWEI) has the potential to produce a significant proportion of the power needed to reach our Nation’s renewable energy goal. Offshore wind-energy sites can capitalize open areas within Federal waters that have persistent, high winds with large energy production potential. Although there are few locations in the California Current System (CCS) where it would be acceptable to build pile-mounted wind turbines in waters less than 50 m deep, the development of technology able to support deep-water OWEI (>200 m depth) could enable wind-energy production in the CCS. As with all human-use of the marine environment, understanding the potential impacts of wind-energy infrastructure on the marine ecosystem is an integral part of offshore wind-energy research and planning. Herein, we present a comprehensive database to quantify marine bird vulnerability to potential OWEI in the CCS (see https://doi.org/10.5066/F79C6VJ0). These data were used to quantify marine bird vulnerabilities at the population level. For 81 marine bird species present in the CCS, we created three vulnerability indices: Population Vulnerability, Collision Vulnerability, and Displacement Vulnerability. Population Vulnerability was used as a scaling factor to generate two comprehensive indicies: Population Collision Vulnerability (PCV) and Population Displacement Vulnerability (PDV). Within the CCS, pelicans, terns (Forster’s [Sterna forsteri], Caspian [Hydroprogne caspia], Elegant [Thalasseus elegans], and Least Tern [Sternula antillarum]), gulls (Western [Larus occidentalis] and Bonaparte’s Gull [Chroicocephalus philadelphia]), South Polar Skua (Stercorarius maccormicki), and Brandt’s Cormorant (Phalacrocorax penicillatus) had the greatest PCV scores. Brown Pelican (Pelicanus occidentalis) had the greatest overall PCV score. Some alcids (Scripps’s Murrelet [Synthliboramphus scrippsi], Marbled Murrelet [Brachyramphus marmoratus], and Tufted Puffin [Fratercula cirrhata]), terns (Elegant and Least Lern), and loons (Yellow-billed [Gavia adamsii] and Common Loon [G. immer]) had the greatest PDV scores. Ashy Storm-Petrel (Oceanodroma homochroa) had the greatest overall PDV score. To help inform decisions that will impact seabird conservation, vulnerability assessment results can now be combined with recent marine bird at-sea distribution and abundance data for the CCS to evaluate vulnerability areas where OWEI development is being considered. Lastly, it is important to note that as new information about seabird behavior and populations in the CCS becomes available, this database can be easily updated and modified.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161154","collaboration":"Prepared in cooperation with Bureau of Ocean Energy Management (OCS Study, BOEM 2016-043)","usgsCitation":"Adams, J., Kelsey, E.C., Felis, J.J., and Pereksta, D.M., 2017, Collision and displacement vulnerability among marine birds of the California Current System associated with offshore wind energy infrastructure (ver. 1.1, July 2017): U.S. Geological Survey Open-File Report 2016-1154, 116 p., https://doi.org/10.3133/ofr20161154.","productDescription":"Report: vi, 116 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-071912","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":438527,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F79C6VJ0","text":"USGS data release","linkHelpText":"Data for calculating population, collision and displacement vulnerability among marine birds of the California Current System associated with offshore wind energy infrastructure (ver. 2.0, June 2017)"},{"id":341751,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1154/coverthb.jpg"},{"id":344436,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1154/ofr20161154.pdf","text":"Report","size":"2.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1154"},{"id":344437,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2016/1154/ofr20161154_revision history.docx","size":"153 KB docx","description":"OFR 2016-1154 Revision History"}],"edition":"Version 1.0: Originally posted October 27, 2016; Version 1.1: July 2017","contact":"Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
Consistent and reliable sediment data are needed by Federal, State, and local government agencies responsible for monitoring water quality, planning river restoration, quantifying sediment budgets, and evaluating the effectiveness of sediment reduction strategies. Heightened concerns about excessive sediment in rivers and the challenge to reduce costs and eliminate data gaps has guided Federal and State interests in pursuing alternative methods for measuring suspended and bedload sediment. Simple and dependable data collection and estimation techniques are needed to generate hydraulic and water-quality information for areas where data are unavailable or difficult to collect.
The U.S. Geological Survey, in cooperation with the Minnesota Pollution Control Agency and the Minnesota Department of Natural Resources, completed a study to evaluate the use of dimensionless sediment rating curves (DSRCs) to accurately predict suspended-sediment concentrations (SSCs), bedload, and annual sediment loads for selected rivers and streams in Minnesota based on data collected during 2007 through 2013. This study included the application of DSRC models developed for a small group of streams located in the San Juan River Basin near Pagosa Springs in southwestern Colorado to rivers in Minnesota. Regionally based DSRC models for Minnesota also were developed and compared to DSRC models from Pagosa Springs, Colorado, to evaluate which model provided more accurate predictions of SSCs and bedload in Minnesota.
Multiple measures of goodness-of-fit were developed to assess the effectiveness of DSRC models in predicting SSC and bedload for rivers in Minnesota. More than 600 dimensionless ratio values of SSC, bedload, and streamflow were evaluated and delineated according to Pfankuch stream stability categories of “good/fair” and “poor” to develop four Minnesota-based DSRC models. The basis for Pagosa Springs and Minnesota DSRC model effectiveness was founded on measures of goodness-of-fit that included proximity of the model(s) fitted line to the 95-percent confidence intervals of the site-specific model, Nash-Sutcliffe Efficiency values, model biases, and deviation of annual sediment loads from each model to the annual sediment loads calculated from measured data.
Composite plots comparing Pagosa Springs DSRCs, Minnesota DSRCs, site-specific regression models, and measured data indicated that regionally developed DSRCs (Minnesota DSRC models) more closely approximated measured data for nearly every site. Pagosa Springs DSRC models had markedly larger exponents (slopes) when compared to the Minnesota DSRC models and the site-specific regression models, and over-represent SSC and bedload at streamflows exceeding bankfull. The Nash-Sutcliffe Efficiency values for the Minnesota DSRC model for suspended-sediment concentrations closely matched Nash-Sutcliffe Efficiency values of the site-specific regression models for 12 out of 16 sites. Nash-Sutcliffe Efficiency values associated with Minnesota DSRCs were greater than those associated with Pagosa Springs DSRCs for every site except the Whitewater River near Beaver, Minnesota site. Pagosa Springs DSRC models were less accurate than the mean of the measured data at predicting SSC values for one-half of the sites for good/fair stability sites and one-half of the sites for poor stability sites. Relative model biases were calculated and determined to be substantial (greater than 5 percent) for Pagosa Springs and Minnesota models, with Minnesota models having a lower mean model bias. For predicted annual suspended-sediment loads (SSL), the Minnesota DSRC models for good/fair and poor stream stability sites more closely approximated the annual SSLs calculated from the measured data as compared to the Pagosa Springs DSRC model.
Results of data analyses indicate that DSRC models developed using data collected in Minnesota were more effective at compensating for differences in individual stream characteristics across a variety of basin sizes and flow regimes than DSRC models developed using data collected for Pagosa Springs, Colorado. Minnesota DSRC models retained a substantial portion of the unique sediment signatures for most rivers, although deviations were observed for streams with limited sediment supply and for rivers in southeastern Minnesota, which had markedly larger regression exponents. Compared to Pagosa Springs DSRC models, Minnesota DSRC models had regression slopes that more closely matched the slopes of site-specific regression models, had greater Nash-Sutcliffe Efficiency values, had lower model biases, and approximated measured annual sediment loads more closely. The results presented in this report indicate that regionally based DSRCs can be used to estimate reasonably accurate values of SSC and bedload.
Practitioners are cautioned that DSRC reliability is dependent on representative measures of bankfull streamflow, SSC, and bedload. It is, therefore, important that samples of SSC and bedload, which will be used for estimating SSC and bedload at the bankfull streamflow, are collected over a range of conditions that includes the ascending and descending limbs of the event hydrograph. The use of DSRC models may have substantial limitations for certain conditions. For example, DSRC models should not be used to predict SSC and sediment loads for extreme streamflows, such as those that exceed twice the bankfull streamflow value because this constitutes conditions beyond the realm of current (2016) empirical modeling capability. Also, if relations between SSC and streamflow and between bedload and streamflow are not statistically significant, DSRC models should not be used to predict SSC or bedload, as this could result in large errors. For streams that do not violate these conditions, DSRC estimates of SSC and bedload can be used for stream restoration planning and design, and for estimating annual sediment loads for streams where little or no sediment data are available.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165146","collaboration":"Prepared in cooperation with the Minnesota Pollution Control Agency and the Minnesota Department of Natural Resources","usgsCitation":"Ellison, C.A., Groten, J.T., Lorenz, D.L., and Koller, K.S., 2016, Application of dimensionless sediment rating curves to predict suspended-sediment concentrations, bedload, and annual sediment loads for rivers in Minnesota (ver. 1.1, January 2020): U.S. Geological Survey Scientific Investigations Report 2016–5146, 68 p., https://dx.doi.org/10.3133/sir20165146.","productDescription":"Report: ix, 68 p.; 3 Appendix Tables","startPage":"1","endPage":"68","numberOfPages":"82","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-078848","costCenters":[{"id":392,"text":"Minnesota Water Science 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\"}}]}","contact":"Director, Minnesota Water Science Center
U.S. Geological Survey
2280 Woodale Drive
Mounds View, Minnesota 55112
A comprehensive survey of dissolved organic carbon (DOC) and chromophoric dissolved organic matter (CDOM) was conducted in the Canada and Makarov Basins and adjacent seas during 2010–2012 to investigate the dynamics of dissolved organic matter (DOM) in the Arctic Ocean. Sources and distributions of DOM in polar surface waters were very heterogeneous and closely linked to hydrological conditions. Canada Basin surface waters had relatively low DOC concentrations (69 ± 6 μmol L−1), CDOM absorption (a325: 0.32 ± 0.07 m−1) and CDOM-derived lignin phenols (3 ± 0.4 nmol L−1), and high spectral slope values (S275–295: 31.7 ± 2.3 μm−1), indicating minor terrigenous inputs and evidence of photochemical alteration in the Beaufort Gyre. By contrast, surface waters of the Makarov Basin had elevated DOC (108 ± 9 μmol L−1) and lignin phenol concentrations (15 ± 3 nmol L−1), high a325 values (1.36 ± 0.18 m−1), and low S275–295 values (22.8 ± 0.8 μm−1), indicating pronounced Siberian river inputs associated with the Transpolar Drift and minor photochemical alteration. Observations near the Mendeleev Plain suggested limited interactions of the Transpolar Drift with Canada Basin waters, a scenario favoring export of Arctic DOM to the North Atlantic. The influence of sea-ice melt on DOM was region-dependent, resulting in an increase (Beaufort Sea), a decrease (Bering-Chukchi Seas), and negligible change (deep basins) in surface DOC concentrations and a325 values. Halocline structures differed between basins, but the Canada Basin upper halocline and Makarov Basin halocline were comparable in their average DOC (65–70 μmol L−1) and lignin phenol concentrations (3–4 nmol L−1) and S275–295 values (22.9–23.7 μm−1). Deep-water DOC concentrations decreased by 6–8 μmol L−1 with increasing depth, water mass age, nutrient concentrations, and apparent oxygen utilization. Maximal estimates of DOC degradation rates (0.036–0.039 μmol L−1 yr−1) in the deep Arctic were lower than those in other ocean basins, possibly due to low water temperatures. DOC concentrations in bottom waters (>2500 m; 46 ± 2 μmol L−1) of the Canada and Makarov Basins were slightly lower than those reported for deep waters of the Eurasian Basin and Nordic Seas. Elevated a325 values (by 10–20%) were observed near the seafloor, indicating biological activity in Arctic basin sediments.
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A. C.","contributorId":176459,"corporation":false,"usgs":false,"family":"van Heuven","given":"Steven","email":"","middleInitial":"M. A. C.","affiliations":[],"preferred":false,"id":652395,"contributorType":{"id":1,"text":"Authors"},"rank":88},{"text":"Vandemark, Douglas","contributorId":171879,"corporation":false,"usgs":false,"family":"Vandemark","given":"Douglas","email":"","affiliations":[{"id":12667,"text":"University of New Hampshire","active":true,"usgs":false}],"preferred":false,"id":652396,"contributorType":{"id":1,"text":"Authors"},"rank":89},{"text":"Ward, Brian","contributorId":176460,"corporation":false,"usgs":false,"family":"Ward","given":"Brian","affiliations":[],"preferred":false,"id":652397,"contributorType":{"id":1,"text":"Authors"},"rank":90},{"text":"Watson, Andrew J.","contributorId":176461,"corporation":false,"usgs":false,"family":"Watson","given":"Andrew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":652398,"contributorType":{"id":1,"text":"Authors"},"rank":91},{"text":"Xu, Suqing","contributorId":176462,"corporation":false,"usgs":false,"family":"Xu","given":"Suqing","email":"","affiliations":[],"preferred":false,"id":652399,"contributorType":{"id":1,"text":"Authors"},"rank":92}]}} ,{"id":70177921,"text":"70177921 - 2016 - Environmental factors influence lesser scaup migration chronology and population monitoring","interactions":[],"lastModifiedDate":"2018-02-06T12:40:06","indexId":"70177921","displayToPublicDate":"2016-10-27T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2508,"text":"Journal of Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Environmental factors influence lesser scaup migration chronology and population monitoring","docAbstract":"Identifying environmental metrics specific to lesser scaup (Aythya affinis; scaup) spring migration chronology may help inform development of conservation, management and population monitoring. Our objective was to determine how environmental conditions influence spring migration of lesser scaup to assess the effectiveness of the Waterfowl Breeding Population and Habitat Survey in accurately estimating scaup populations. We first compared peak timing of mallard (Anas platyrhynchos) and scaup migration from weekly ground surveys in North Dakota, USA because the Waterfowl Breeding Population and Habitat Survey is designed to capture annual mallard migration. As predicted, we detected that peak timing of scaup and mallard migrations differed in 25 of 36 years investigated (1980–2010). We marked scaup with satellite transmitters (n = 78; 7,403 locations) at Long Point, Lake Erie, Ontario, Canada; Pool 19 of the Mississippi River, Iowa and Illinois, USA; and Presque Isle Bay, Lake Erie, Pennsylvania, USA. We tested the assumption that our marked scaup were representative of the continental population using the traditional survey area by comparing timing of migration of marked birds and scaup counted in the North Dakota Game and Fish Department survey. We detected a strong positive correlation between marked scaup and the survey data, which indicated that marked scaup were representative of the population. We subsequently used our validated sample of marked scaup to investigate the effects of annual variation in temperature, precipitation, and ice cover on spring migration chronology in the traditional and eastern survey areas of the Waterfowl Breeding Population and Habitat Survey, 2005–2010. We evaluated competing environmental models to explain variation in timing and rate of scaup migration at large-scale and local levels. Spring migration of scaup occurred earlier and faster during springs with warmer temperatures and greater precipitation, variables known to influence energy budgets and wetland availability. Our results suggest that surveys designed to index abundance of breeding mallards is imprecise for estimating scaup abundance, and inaccurate at estimating breeding population size by survey stratum.
","language":"English","publisher":"Wildlife Society","publisherLocation":"Washington, D.C.","doi":"10.1002/jwmg.21131","usgsCitation":"Finger, T.A., Afton, A.D., Schummer, M.L., Petrie, S.A., Badzinski, S.S., Johnson, M.A., Szymanski, M.L., Jacobs, K.J., Olsen, G.H., and Mitchell, M., 2016, Environmental factors influence lesser scaup migration chronology and population monitoring: Journal of Wildlife Management, v. 80, no. 8, p. 1437-1449, https://doi.org/10.1002/jwmg.21131.","productDescription":"13 p.","startPage":"1437","endPage":"1449","ipdsId":"IP-068193","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":330488,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","volume":"80","issue":"8","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2016-08-22","publicationStatus":"PW","scienceBaseUri":"5813125de4b0b5a0c12ab662","contributors":{"authors":[{"text":"Finger, Taylor A.","contributorId":176345,"corporation":false,"usgs":false,"family":"Finger","given":"Taylor","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":652253,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Afton, Alan D. 0000-0002-0436-8588 aafton@usgs.gov","orcid":"https://orcid.org/0000-0002-0436-8588","contributorId":139582,"corporation":false,"usgs":false,"family":"Afton","given":"Alan","email":"aafton@usgs.gov","middleInitial":"D.","affiliations":[{"id":368,"text":"Louisiana Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"preferred":false,"id":652254,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schummer, Michael L.","contributorId":176347,"corporation":false,"usgs":false,"family":"Schummer","given":"Michael","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":652255,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Petrie, Scott A.","contributorId":141223,"corporation":false,"usgs":false,"family":"Petrie","given":"Scott","email":"","middleInitial":"A.","affiliations":[{"id":13717,"text":"Long Point Waterfowl","active":true,"usgs":false}],"preferred":false,"id":652256,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Badzinski, Shannon S.","contributorId":176348,"corporation":false,"usgs":false,"family":"Badzinski","given":"Shannon","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":652257,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Johnson, Michael A.","contributorId":174789,"corporation":false,"usgs":false,"family":"Johnson","given":"Michael","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":652258,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Szymanski, Michael L.","contributorId":176349,"corporation":false,"usgs":false,"family":"Szymanski","given":"Michael","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":652259,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jacobs, Kevin J.","contributorId":176350,"corporation":false,"usgs":false,"family":"Jacobs","given":"Kevin","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":652260,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Olsen, Glenn H. 0000-0002-7188-6203 golsen@usgs.gov","orcid":"https://orcid.org/0000-0002-7188-6203","contributorId":40918,"corporation":false,"usgs":true,"family":"Olsen","given":"Glenn","email":"golsen@usgs.gov","middleInitial":"H.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":652252,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Mitchell, M.E.","contributorId":176351,"corporation":false,"usgs":false,"family":"Mitchell","given":"M.E.","affiliations":[],"preferred":false,"id":652285,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70177782,"text":"ds1025 - 2016 - Water-level data for the Albuquerque Basin and adjacent areas, central New Mexico, period of record through September 30, 2015","interactions":[],"lastModifiedDate":"2021-08-26T14:14:58.18205","indexId":"ds1025","displayToPublicDate":"2016-10-27T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1025","displayTitle":"Water-Level Data for the Albuquerque Basin and Adjacent Areas, Central New Mexico, Period of Record Through September 30, 2015","title":"Water-level data for the Albuquerque Basin and adjacent areas, central New Mexico, period of record through September 30, 2015","docAbstract":"The Albuquerque Basin, located in central New Mexico, is about 100 miles long and 25–40 miles wide. The basin is hydrologically defined as the extent of consolidated and unconsolidated deposits of Tertiary and Quaternary age that encompasses the structural Rio Grande Rift between San Acacia to the south and Cochiti Lake to the north. Drinking-water supplies throughout the basin were obtained solely from groundwater resources until December 2008, when the Albuquerque Bernalillo County Water Utility Authority (ABCWUA) began treatment and distribution of surface water from the Rio Grande through the San Juan-Chama Drinking Water Project. A 20-percent population increase in the basin from 1990 to 2000 and a 22-percent population increase from 2000 to 2010 may have resulted in an increased demand for water in areas within the basin.
An initial network of wells was established by the U.S. Geological Survey (USGS) in cooperation with the City of Albuquerque from April 1982 through September 1983 to monitor changes in groundwater levels throughout the Albuquerque Basin. In 1983, this network consisted of 6 wells with analog-to-digital recorders and 27 wells where water levels were measured monthly. The network currently (2015) consists of 124 wells and piezometers. (A piezometer is a specialized well open to a specific depth in the aquifer, often of small diameter and nested with other piezometers open to different depths.) The USGS, in cooperation with the ABCWUA, currently (2015) measures and reports water levels from the 124 wells and piezometers in the network; this report presents water-level data collected by USGS personnel at those 124 sites through water year 2015 (October 1, 2014, through September 30, 2015).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1025","isbn":"978-1-4113-4091-6","collaboration":"Prepared in cooperation with the Albuquerque Bernalillo County Water Utility Authority","usgsCitation":"Beman, J.E., and Bryant, C.F., 2016, Water-level data for the Albuquerque Basin and adjacent areas, central New Mexico, period of record through September 30, 2015 (ver. 1.1, August 2021): U.S. Geological Survey Data Series 1025, 39 p., https://doi.org/10.3133/ds1025.","productDescription":"iv, 39 p.","numberOfPages":"47","onlineOnly":"Y","ipdsId":"IP-079076","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":388365,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/ds/1025/versionHist.txt","text":"Version History","linkFileType":{"id":2,"text":"txt"},"description":"DS 1025 Version History"},{"id":388364,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1025/ds1025.pdf","text":"Report","size":"5.06 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1025"},{"id":330503,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1025/coverthb2.jpg"}],"country":"United States","state":"New Mexico","otherGeospatial":"Albuquerque Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -107.5,\n 34.2\n ],\n [\n -107.5,\n 35.75\n ],\n [\n -106,\n 35.75\n ],\n [\n -106,\n 34.2\n ],\n [\n -107.5,\n 34.2\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.1: August 2021","contact":"Director, New Mexico Water Science Center
U.S. Geological Survey
6700 Edith Blvd. NE
Albuquerque, NM 87113
Information on low-flow characteristics of streams is essential for the management of water resources. This report provides equations for estimating the 1-, 7-, and 30-day mean low flows for a recurrence interval of 10 years and the harmonic-mean flow at ungaged, unregulated stream sites in Indiana. These equations were developed using the low-flow statistics and basin characteristics for 108 continuous-record streamgages in Indiana with at least 10 years of daily mean streamflow data through the 2011 climate year (April 1 through March 31). The equations were developed in cooperation with the Indiana Department of Environmental Management.
Regression techniques were used to develop the equations for estimating low-flow frequency statistics and the harmonic-mean flows on the basis of drainage-basin characteristics. A geographic information system was used to measure basin characteristics for selected streamgages. A final set of 25 basin characteristics measured at all the streamgages were evaluated to choose the best predictors of the low-flow statistics.
Logistic-regression equations applicable statewide are presented for estimating the probability that selected low-flow frequency statistics equal zero. These equations use the explanatory variables total drainage area, average transmissivity of the full thickness of the unconsolidated deposits within 1,000 feet of the stream network, and latitude of the basin outlet. The percentage of the streamgage low-flow statistics correctly classified as zero or nonzero using the logistic-regression equations ranged from 86.1 to 88.9 percent.
Generalized-least-squares regression equations applicable statewide for estimating nonzero low-flow frequency statistics use total drainage area, the average hydraulic conductivity of the top 70 feet of unconsolidated deposits, the slope of the basin, and the index of permeability and thickness of the Quaternary surficial sediments as explanatory variables. The average standard error of prediction of these regression equations ranges from 55.7 to 61.5 percent.
Regional weighted-least-squares regression equations were developed for estimating the harmonic-mean flows by dividing the State into three low-flow regions. The Northern region uses total drainage area and the average transmissivity of the entire thickness of unconsolidated deposits as explanatory variables. The Central region uses total drainage area, the average hydraulic conductivity of the entire thickness of unconsolidated deposits, and the index of permeability and thickness of the Quaternary surficial sediments. The Southern region uses total drainage area and the percent of the basin covered by forest. The average standard error of prediction for these equations ranges from 39.3 to 66.7 percent.
The regional regression equations are applicable only to stream sites with low flows unaffected by regulation and to stream sites with drainage basin characteristic values within specified limits. Caution is advised when applying the equations for basins with characteristics near the applicable limits and for basins with karst drainage features and for urbanized basins. Extrapolations near and beyond the applicable basin characteristic limits will have unknown errors that may be large. Equations are presented for use in estimating the 90-percent prediction interval of the low-flow statistics estimated by use of the regression equations at a given stream site.
The regression equations are to be incorporated into the U.S. Geological Survey StreamStats Web-based application for Indiana. StreamStats allows users to select a stream site on a map and automatically measure the needed basin characteristics and compute the estimated low-flow statistics and associated prediction intervals.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165102","collaboration":"Prepared in cooperation with the Indiana Department of Environmental Management","usgsCitation":"Martin, G.R., Fowler, K.K., and Arihood, L.D., 2016, Estimating selected low-flow frequency statistics and harmonic-mean flows for ungaged, unregulated streams in Indiana (ver 1.1, October 2016): U.S. Geological Survey Scientific Investigations Report 2016–5102, 45 p., https://dx.doi.org/10.3133/sir20165102.","productDescription":"Report: vii, 45 p.; Metadata; Read Me File; Spatial Data","numberOfPages":"58","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-066895","costCenters":[{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true}],"links":[{"id":327994,"rank":5,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sir/2016/5102/readme.pdf","text":"Additional information about SIR 2016–5102 - read me 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\"}}]}","edition":"Version 1.0: Originally posted September 6, 2016; Version 1.1: October 24, 2016","contact":"Director, Indiana-Kentucky Water Science Center
U.S. Geological Survey
5957 Lakeside Blvd
Indianapolis, IN 46278
In January 2014, a storage tank leaked, spilling a large quantity of 4-methylcyclohexane methanol into the Elk River in West Virginia and contaminating the water supply for more than 300,000 people. In response, the West Virginia Legislature passed Senate Bill 373, which requires the West Virginia Department of Health and Human Resources (WVDHHR) to assess the susceptibility and vulnerability of public surface-water-influenced groundwater supply sources (SWIGS) and surface-water intakes statewide. In response to this mandate for reassessing SWIGS statewide, the U.S. Geological Survey (USGS), in cooperation with the WVDHHR, Bureau of Public Health, Office of Environmental Health Services, compiled available data and summarized the results of previous groundwater studies to provide the WVDHHR with data that could be used as part of the process for assessing and determining SWIGS.
\nExisting geologic, hydrologic, well-construction, water-quality, and other related data and information from previous U.S. Geological Survey (USGS) hydrogeologic studies and the USGS National Water Information System (NWIS) database, in conjunction with data from the West Virginia Bureau for Public Health (WVBPH) Department of Health and Human Resources (WVDHHR) and the West Virginia Department of Environmental Protection database and files, were collected, compiled, and analyzed to help the WVDHHR to better assess public groundwater supply wells that may meet the definition of a surface-water-influenced- groundwater supply (SWIGS).
\nIn this study, measures of intrinsic susceptibility, which are characterized by the physical properties that affect the ease with which water moves through the unsaturated zone and, subsequently, into the saturated zone within an aquifer, showed that karst limestone aquifers are the aquifers most intrinsically susceptible to contamination within the State of West Virginia. Karst limestone aquifers are present within Cambrian- and Ordovician-age formations within West Virginia’s eastern panhandle and in Mississippian-age limestones within the Greenbrier River valley. Solution development within these limestone aquifers allows rapid recharge and flow of groundwater within the aquifer, both of which allow surface contaminants to easily enter the aquifer and travel long distances in a short period of time.
\nAlluvial aquifers bordering the Ohio River in western West Virginia are also potentially highly susceptible to contamination because these alluvial aquifers can receive significant recharge from the adjacent Ohio River. Any potential contaminants that may be present in the river have the potential to enter the aquifer and contaminate wells completed within the sand and gravel alluvial sediments within which the wells are completed. These same alluvial sediments, however, help to retard the movement of bacteria and other potentially pathogenic organisms, such as Cryptosporidia and Giardia lamblia, into the aquifer. As a result, samples from alluvial aquifers bordering the Ohio River and elsewhere within the State do not commonly test positive for indicator bacteria, such as total coliform, fecal coliform, or Escherichia coli (E. coli). The alluvial sediments do not, however, provide assimilative capacity with respect to water soluble compounds such as nitrate and certain volatile and semi-volatile organic compounds. Therefore, the Ohio River alluvial aquifers are highly susceptible to organic compounds present in the river or on the land surface near a well. These aquifers are also susceptible to nitrate contamination from fertilizers, pesticides, and manure, which are commonly used on the fertile agricultural soils present on terraces along the Ohio River.
\nAbandoned-coal-mine aquifers, which are typically used as a source of groundwater in southern West Virginia, are moderately susceptible to contamination. The vast network of voids from mine entries provide vast storage for groundwater in abandoned mine aquifers, and fracturing of overburden strata, which is common in areas of past or current mining, can allow rapid infiltration of contaminants to the aquifer. Where streams cross over below-drainage underground coal mines, there is an increased potential for contamination of coal-mine aquifers. As a result, above-drainage underground coal mines, those mines that are present at an elevation above local tributary drainage, are probably less susceptible to contamination than are below-drainage underground coal mines. Public groundwater supplies in abandoned coal mines need to be evaluated on a case-by-case basis to assess the potential for recharge of contaminated surface water to enter below-drainage underground coal-mine aquifers and to assess potential hydraulic conductivity to nearby surface-water bodies, such as lakes, ponds, rivers, or streams.
\nFractured-rock aquifers compose an additional major type of aquifer within the State of West Virginia. Owing to their low permeability and their typically small groundwater capture areas, fractured-rock aquifers within the State of West Virginia typically have low susceptibility to contamination. However, there are exceptions, and wells completed in fractured-rock aquifers that are in close proximity to streams may be adversely affected by induced recharge from the stream. Where such systems are present, frequent bacterial testing of the source water can be used to ascertain the potential for microbial contamination of the aquifer.
\nIntrinsic susceptibility alone does not fully predict whether or not a well is vulnerable to contamination, only that the hydrogeologic terrain is suitable for rapid transport of pathogenic organisms or chemical compounds to and within the aquifer. However, contaminants may or may not be present in the recharge water to an individual well or well field. Therefore, an assessment of potential contaminant sources, such as nearby gas wells, landfills, underground storage tanks, above ground storage tanks, major transportation corridors, surface or underground coal mines, and flood plains, is needed to assess vulnerability. The assessments need to be conducted on a case-by-case basis or, as has been done in this study, by collecting and compiling the number of potential contaminant sources that may be present in the source-water-protection area for an individual public groundwater supply source.
\nGroundwater public-supply systems in areas of high intrinsic susceptibility and with a large number of potential contaminant sources within the recharge or source-water-protection area of individual wells or well fields are potentially vulnerable to contamination and probably warrant further evaluation as potential SWIGS. However, measures can be taken to educate the local population and initiate safety protocols and protective strategies to appropriately manage contaminant sources to prevent release of contaminants to the aquifer, therefore, reducing vulnerability of these systems to contamination. However, each public groundwater supply source needs to be assessed on an individual basis. Data presented in this report can be used to categorize and prioritize wells and springs that have a high potential for intrinsic susceptibility or vulnerability to contamination.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165048","collaboration":"Prepared in cooperation with the West Virginia Department of Health and Human Resources, Bureau of Public Health, Office of Environmental Health Services","usgsCitation":"Kozar, M.D., and Paybins, K.S., 2016, Assessment of hydrogeologic terrains, well-construction characteristics, groundwater hydraulics, and water-quality and microbial data for determination of surface-water-influenced groundwater supplies in West Virginia (ver. 1.1, October 2016): U.S. Geological Survey Scientific Investigations Report 2016–5048, 55 p., https://dx.doi.org/10.3133/sir20165048.","productDescription":"Report: vii, 54 p.; 2 Figures; 3 Appendixes","numberOfPages":"67","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-065870","costCenters":[{"id":642,"text":"West Virginia Water Science Center","active":true,"usgs":true}],"links":[{"id":325448,"rank":3,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/sir/2016/5048/sir20165048_figure3A.pdf","text":"Figure 3A -","size":"16.3 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"Major Geologic Formations in West Virginia"},{"id":325450,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5048/sir20165048_appendix1.xlsx","text":"Appendix 1 - ","size":"168 KB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"Description of 324 wells in West Virginia sampled as part of the U.S. Geological Survey and West Virginia Department of Environmental Protection statewide Ambient Groundwater Quality Monitoring Network"},{"id":325449,"rank":4,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/sir/2016/5048/sir20165048_figure3B.pdf","text":"Figure 3B -","size":"745 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"Major geologic formations in the study area of the Blue Ridge Physiographic Province USGS National Water Quality Assessment study in Virginia and North Carolina"},{"id":325446,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5048/coverthb2.jpg"},{"id":325452,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5048/sir20165048_appendix3.xlsx","text":"Appendix 3 - ","size":"111 KB","linkHelpText":" Permit data for public groundwater supplies in West Virginia with accompanying counts of number of potential sources of contamination within the respective source-water-protection area for each public groundwater supply source"},{"id":325447,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5048/sir20165048.pdf","text":"Report","size":"25.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5048"},{"id":325451,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5048/sir20165048_appendix2.xlsx","text":"Appendix 2 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Virginia\",\"nation\":\"USA \"}}]}","edition":"Version 1.0: Originally posted August 30, 2016; Version 1.1: October 24, 2016","contact":"Director, West Virginia Water Science Center
U.S. Geological Survey
11 Dunbar Street
Charleston, WV 25301
http://wv.usgs.gov
Treated effluent discharged from municipal wastewater-treatment plants to the Assabet River in central Massachusetts includes phosphorus, which leads to increased growth of nuisance aquatic plants that decrease the river’s water quality and aesthetics in impounded reaches during the growing season. To improve the river’s water quality and aesthetics, the U.S. Environmental Protection Agency approved a total maximum daily load for phosphorus in 2004 that directed the wastewater-treatment plants to reduce the amount of total phosphorus discharged to the river by 2012. The permitted total phosphorus monthly average of 0.75 milligrams per liter during the aquatic plant growing season (April 1 through October 31) was reduced by the total maximum daily load to a target of 0.1 milligrams per liter by 2012, and the nongrowing-season limit was unchanged at 1.0 milligrams per liter.
From October 2008 through April 2014, the U.S. Geological Survey, in cooperation with the Massachusetts Department of Environmental Protection, measured streamflow and collected weekly flow-proportional, composite samples of water from the Assabet River for analysis of concentrations of total phosphorus and orthophosphate. Streamflow and concentration data were used to estimate total phosphorus and orthophosphate loads in the river. The purpose of this monitoring effort was to evaluate phosphorus concentrations and loads in the river before, during, and after the wastewater-treatment-plant upgrades and to assess the effects of seasonal differences in permitted discharges. The locations of water-quality-monitoring stations, with respect to the Hudson and Ben Smith impoundments, enabled examination of effects of phosphorus entering and leaving the impoundments.
Annual median concentrations of total phosphorus in wastewater-treatment plants were reduced by more than 80 percent with the plant upgrades. Measured instream annual median concentrations of total phosphorus in the Assabet River decreased by about 38 to 50 percent at three of the four monitoring stations following the wastewater-treatment-plant upgrades. At the station farthest upstream, the median total phosphorus concentration remained unchanged throughout the study; this may be attributed to the site location and potential resuspension of particulate organic matter during periods of increased streamflow. Annual median loads from the wastewater-treatment plants were reduced by up to 91 percent following the upgrades, instream annual median total phosphorus loads at the three downstream stations decreased by 71 to 76 percent, and instream orthophosphate loads at the three downstream stations decreased by 79 to 87 percent.
Seasonal fluctuations (growing versus nongrowing) of total phosphorus and orthophosphate were observed instream before the upgrades. However, after the upgrades, fluctuations in phosphorus released from the treatment plants were slight and seasonal changes were typically not observed instream.
Annual loads entering and leaving the two impoundments were inconclusive in determining whether the impoundments were sources or sinks of total phosphorus during the study. Total phosphorus loads entering the Hudson impoundment were consistently greater than those leaving; however, there was uncertainty about the loads at the monitoring station upstream from this impoundment. At the Ben Smith impoundment, total phosphorus and orthophosphate loads downstream were slightly greater than those upstream from the impoundment, but the differences may reflect additions from tributaries and overland runoff.
Estimated instream total phosphorus concentrations and loads indicated that the decreases in total phosphorus in wastewater-treatment-plant discharges were accompanied by reductions measured in the Assabet River. A statistical analysis which incorporates the effect of varying flow conditions demonstrated significant reductions in total phosphorus concentrations after the wastewater-treatment-plant upgrades at three of the four instream monitoring stations. No significant change was observed at the most upstream location, the Assabet River at Port Street at Hudson, Massachusetts (station number 01096835), which may have been affected by flow-related resuspension of particulate phosphorus.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165063","isbn":"978-1-4113-4059-6","collaboration":"Prepared in cooperation with the Massachusetts Department of Environmental Protection","usgsCitation":"Savoie, J.G., DeSimone, L.A., Mullaney, J.R., Zimmerman, M.J., and Waldron, M.C., 2016, Changes in phosphorus concentrations and loads in the Assabet River, Massachusetts, October 2008 through April 2014: U.S. Geological Survey Scientific Investigations Report 2016–5063, 40 p., https://dx.doi.org/10.3133/sir20165063.","productDescription":"Report: ix, 40 p.; Data Release","numberOfPages":"54","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-056167","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":438530,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F72R3PR3","text":"USGS data release","linkHelpText":"Streamflow and total phosphorus and orthophosphate data for samples collected in and near the Assabet River, Massachusetts, October 2008 through April 2014"},{"id":329393,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F72R3PR3","text":"USGS data release","description":"USGS data release","linkHelpText":"Streamflow and Total Phosphorus and Orthophosphate Data for Samples Collected In and Near the Assabet River, Massachusetts, October 2008 Through April 2014"},{"id":329392,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5063/sir20165063.pdf","text":"Report","size":"10.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5063"},{"id":329391,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5063/coverthb3.jpg"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Assabet River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.67068481445312,\n 42.245801966774025\n ],\n [\n -71.67068481445312,\n 42.476148570254516\n ],\n [\n -71.36032104492188,\n 42.476148570254516\n ],\n [\n -71.36032104492188,\n 42.245801966774025\n ],\n [\n -71.67068481445312,\n 42.245801966774025\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Or visit our Web site at:
http://newengland.water.usgs.gov
Adaptive radiation involving a colonizing phenotype that rapidly evolves into at least one other ecological variant, or ecotype, has been observed in a variety of freshwater fishes in post-glacial environments. However, few studies consider how phenotypic traits vary with regard to neutral genetic partitioning along ecological gradients. Here, we present the first detailed investigation of lake trout Salvelinus namaycushthat considers variation as a cline rather than discriminatory among ecotypes. Genetic and phenotypic traits organized along common ecological gradients of water depth and geographic distance provide important insights into diversification processes in a lake with high levels of human disturbance from over-fishing.
Four putative lake trout ecotypes could not be distinguished using population genetic methods, despite morphological differences. Neutral genetic partitioning in lake trout was stronger along a gradient of water depth, than by locality or ecotype. Contemporary genetic migration patterns were consistent with isolation-by-depth. Historical gene flow patterns indicated colonization from shallow to deep water. Comparison of phenotypic (Pst) and neutral genetic variation (Fst) revealed that morphological traits related to swimming performance (e.g., buoyancy, pelvic fin length) departed more strongly from neutral expectations along a depth gradient than craniofacial feeding traits. Elevated phenotypic variance with increasing water depth in pelvic fin length indicated possible ongoing character release and diversification. Finally, differences in early growth rate and asymptotic fish length across depth strata may be associated with limiting factors attributable to cold deep-water environments.
We provide evidence of reductions in gene flow and divergent natural selection associated with water depth in Lake Superior. Such information is relevant for documenting intraspecific biodiversity in the largest freshwater lake in the world for a species that recently lost considerable genetic diversity and is now in recovery. Unknown is whether observed patterns are a result of an early stage of incipient speciation, gene flow-selection equilibrium, or reverse speciation causing formerly divergent ecotypes to collapse into a single gene pool.
Rapid population growth since the 1930s in Ocean County and vicinity, New Jersey, has placed increasing demands upon the area’s freshwater resources. To examine effects of groundwater withdrawals, a three-dimensional groundwater-flow model was developed to simulate the groundwater-flow systems of five area aquifers: the unconfined Kirkwood-Cohansey aquifer system and Vincentown aquifer, and three confined aquifers— the Rio Grande water-bearing zone, the Atlantic City 800-foot sand, and the Piney Point aquifer. The influence of withdrawals is evaluated by using transient groundwater-flow model simulations that incorporate three withdrawal schemes. These are (1) no-withdrawal conditions; (2) 2000–03 withdrawal conditions, using reported monthly withdrawals at all production wells from January 2000 through December 2003; and (3) maximum-allocation withdrawal conditions using the maximum withdrawal allowed by New Jersey Department of Environmental Protection permits at each well. Particle tracking analysis, using results from model simulations, delineated particle flow paths from production wells to the point of recharge, and estimated particle travel times.
Compared with no-withdrawal conditions, 2000–03 withdrawal conditions reduced the amount of groundwater flow out of the Kirkwood-Cohansey aquifer system into streams, increased the net flow of water into other layers, reduced net flow into or out of storage, and reduced flow from the Kirkwood-Cohansey aquifer system to constant head cells.
Freshwater discharging to the Barnegat Bay-Little Egg Harbor estuary from streams and groundwater is essential to maintaining the ecology of the bay. Examination of selected stress periods indicates that simulated base flow in streams flowing into the Barnegat Bay-Little Egg Harbor estuary is reduced by as much as 49 cubic feet per second for 2000 to 2003 withdrawal conditions when compared with no-withdrawal conditions.
In the three confined aquifers, water levels during periods of low recharge and high withdrawals, and high recharge and low withdrawals, were examined to determine seasonal effects on the confined flow systems. The simulated potentiometric surface of the Rio Grande water-bearing zone and the Atlantic City 800-foot sand during selected stress periods indicates substantial declines from no-withdrawal conditions to 2000–03 conditions as a result of groundwater withdrawals. Cones of depression in Toms River Township, Seaside Heights and Seaside Park Boroughs, and Barnegat Light Borough developed in the potentiometric surface of the Piney Point aquifer in response to withdrawals.
Maximum-allocation withdrawals decreased flow out of the Kirkwood-Cohansey aquifer system to constant head cells, increased flow out of the aquifer system to adjacent and lower layers, and reduced groundwater discharge to streams when compared with 2000–03 withdrawal conditions. Increases in withdrawals from the Rio Grande water-bearing zone, the Atlantic City 800-foot sand, and the Piney Point aquifer result in an increase in simulated net groundwater flow into these aquifers. Base-flow reduction from 2000–03 conditions to maximum-allocation conditions of 25 to 29 cubic feet per second in all streams draining to the Barnegat Bay-Little Egg Harbor also is indicated. Potentiometric surfaces of the Rio Grande water-bearing zone, Atlantic City 800-foot sand, and the Piney Point aquifer during two stress periods of simulated maximum-allocation withdrawal conditions indicated the expansion of several cones of depression developed during 2000–03 withdrawals.
Simulation of average 2000–03 withdrawal conditions indicated the extent to which the groundwater-flow system is susceptible to potential saltwater intrusion into near-shore wells. Travel time from recharge to discharge location ranged from 11 to approximately 50,700 years in near-shore Kirkwood-Cohansey aquifer system wells. Those in Seaside Heights Borough, in Island Beach State Park (Berkeley Township), and in Ship Bottom Borough have particle travel times from 140 to 12,000 years and flow paths that originated under Barnegat Bay or the Atlantic Ocean from the simulation of average maximum-allocation withdrawal conditions.
Travel time along flow paths to wells screened in the Rio Grande water-bearing zone and the Atlantic City 800-foot sand from recharge to discharge point ranged from nearly 530 years to greater than 3.73 million years from the simulation of average 2000–03 withdrawal conditions. Particle tracking indicated that most wells screened in these aquifers derived a large part of their recharge from the Oswego River Basin, with a small portion of flow originating either beneath Barnegat Bay or to the east beneath the Atlantic Ocean. Travel time along flow paths that start beneath either Barnegat Bay or the Atlantic Ocean ranged from 2,300 to approximately 134,000 years from the simulation of average maximum-allocation withdrawal conditions.\"
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165035","collaboration":"Prepared in cooperation with the New Jersey Department of Environmental Protection","usgsCitation":"Cauller, S.J., Voronin, L.M., and Chepiga, M.M., 2016, Simulated effects of groundwater withdrawals from aquifers in Ocean County and vicinity, New Jersey: U.S. Geological Survey Scientific Investigations Report 2016–5035, 77 p., https://dx.doi.org/10.3133/sir20165035.","productDescription":"x, 77 p.","numberOfPages":"92","onlineOnly":"Y","ipdsId":"IP-020396","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":438535,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7H99392","text":"USGS data release","linkHelpText":"MODFLOW2005 model used to simulate the effects of groundwater withdrawals from aquifers in Ocean County and vicinity, New Jersey"},{"id":330264,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5035/coverthb.jpg"},{"id":330265,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5035/sir20165035.pdf","text":"Report","size":"47.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5035 Report"},{"id":332215,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7H99392"}],"country":"United States","state":"New Jersey","county":"Ocean County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.03549194335938,\n 40.10118506258701\n ],\n [\n -74.04647827148438,\n 40.10538669840983\n ],\n [\n -74.0643310546875,\n 40.092781012494065\n ],\n [\n -74.09042358398438,\n 40.10013461308659\n ],\n [\n -74.08905029296875,\n 40.12219064672336\n ],\n [\n -74.19754028320312,\n 40.20195268954057\n ],\n [\n -74.33212280273438,\n 40.22397567550632\n ],\n [\n -74.55459594726562,\n 40.08122374895389\n ],\n [\n -74.53399658203125,\n 39.68393975392731\n ],\n [\n -74.45709228515625,\n 39.577114881737586\n ],\n [\n -74.4158935546875,\n 39.536880650643056\n ],\n [\n -74.410400390625,\n 39.49874248613119\n ],\n [\n -74.3609619140625,\n 39.487084981687495\n ],\n [\n -74.32525634765625,\n 39.49556336059472\n ],\n [\n -74.2401123046875,\n 39.46058338433589\n ],\n [\n -74.02999877929686,\n 39.74521015328692\n ],\n [\n -73.9764404296875,\n 40.091730433255\n ],\n [\n -74.03549194335938,\n 40.10118506258701\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Jersey Water Science Center
U.S. Geological Survey
3450 Princeton Pike, Suite 110
Lawrenceville, NJ 08648
http://nj.usgs.gov
Managed aquifer recharge is used to augment natural recharge to aquifers. It can be used to replenish aquifers depleted by pumping or to store water during wetter years for withdrawal during drier years. Infiltration from ponds is a commonly used, inexpensive approach for managed aquifer recharge.
At some managed aquifer-recharge sites, the time when infiltrated water arrives at the water table is not always clearly shown by water-level data. As part of site characterization and operation, it can be desirable to track downward movement of infiltrated water through the unsaturated zone to identify when it arrives at the water table.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161180","collaboration":"Prepared in cooperation with the Antelope Valley-East Kern Water Agency","usgsCitation":"Nawikas, J.M, O’Leary, D.R., Izbicki, J.A., and Burgess, M.K., 2016, Selected techniques for monitoring water movement through unsaturated alluvium during managed aquifer recharge: U.S. Geological Survey Open-File Report 2016–5105, 8 p., https://dx.doi.org/10.3133/ofr20161180.","productDescription":"8 p.","numberOfPages":"8","onlineOnly":"Y","ipdsId":"IP-060596","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":329775,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1180/coverthb.jpg"},{"id":329776,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1180/ofr20161180.pdf","text":"Report","size":"2.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1180"}],"country":"United States","state":"California","otherGeospatial":"Antelope Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.795166015625,\n 34.474863669009004\n ],\n [\n -117.20214843749999,\n 34.474863669009004\n ],\n [\n -117.20214843749999,\n 35.106428057364255\n ],\n [\n -118.795166015625,\n 35.106428057364255\n ],\n [\n -118.795166015625,\n 34.474863669009004\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Joseph Nawikas
4165 Spruance Road, Suite 200
San Diego, CA 92101
(619) 225-6148
jnawika@usgs.gov
Plastic debris is a growing contaminant of concern in freshwater environments, yet sources, transport, and fate remain unclear. This study characterized the quantity and morphology of floating micro- and macroplastics in 29 Great Lakes tributaries in six states under different land covers, wastewater effluent contributions, population densities, and hydrologic conditions. Tributaries were sampled three or four times each using a 333 μm mesh neuston net. Plastic particles were sorted by size, counted, and categorized as fibers/lines, pellets/beads, foams, films, and fragments. Plastics were found in all 107 samples, with a maximum concentration of 32 particles/m3 and a median of 1.9 particles/m3. Ninety-eight percent of sampled plastic particles were less than 4.75 mm in diameter and therefore considered microplastics. Fragments, films, foams, and pellets/beads were positively correlated with urban-related watershed attributes and were found at greater concentrations during runoff-event conditions. Fibers, the most frequently detected particle type, were not associated with urban-related watershed attributes, wastewater effluent contribution, or hydrologic condition. Results from this study add to the body of information currently available on microplastics in different environmental compartments, including unique contributions to quantify their occurrence and variability in rivers with a wide variety of different land-use characteristics while highlighting differences between surface samples from rivers compared with lakes.
","language":"English","publisher":"ACS Publications","doi":"10.1021/acs.est.6b02917","usgsCitation":"Baldwin, A.K., Corsi, S., and Mason, S.A., 2016, Plastic debris in 29 Great Lakes tributaries: Relations to watershed attributes and hydrology: Environmental Science & Technology, v. 50, no. 19, p. 10377-10385, https://doi.org/10.1021/acs.est.6b02917.","productDescription":"9 p.","startPage":"10377","endPage":"10385","ipdsId":"IP-074452","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":470494,"rank":4,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1021/acs.est.6b02917","text":"Publisher Index Page"},{"id":438536,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7ZC80ZP","text":"USGS data release","linkHelpText":"Microplastics in 29 Great Lakes tributaries (2014-15)"},{"id":330332,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7ZC80ZP"},{"id":330289,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.87841796875,\n 41.07935114946899\n ],\n [\n -92.87841796875,\n 46.7549166192819\n ],\n [\n -77.47558593749999,\n 46.7549166192819\n ],\n [\n -77.47558593749999,\n 41.07935114946899\n ],\n [\n -92.87841796875,\n 41.07935114946899\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"50","issue":"19","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-14","publicationStatus":"PW","scienceBaseUri":"5810c529e4b0f497e7972c22","contributors":{"authors":[{"text":"Baldwin, Austin K. 0000-0002-6027-3823 akbaldwi@usgs.gov","orcid":"https://orcid.org/0000-0002-6027-3823","contributorId":4515,"corporation":false,"usgs":true,"family":"Baldwin","given":"Austin","email":"akbaldwi@usgs.gov","middleInitial":"K.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":651801,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Corsi, Steven R. 0000-0003-0583-5536 srcorsi@usgs.gov","orcid":"https://orcid.org/0000-0003-0583-5536","contributorId":172002,"corporation":false,"usgs":true,"family":"Corsi","given":"Steven R.","email":"srcorsi@usgs.gov","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":651802,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mason, Sherri A.","contributorId":176172,"corporation":false,"usgs":false,"family":"Mason","given":"Sherri","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":651803,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70175133,"text":"cir1423 - 2016 - Wyoming Landscape Conservation Initiative—A case study in partnership development","interactions":[],"lastModifiedDate":"2016-10-24T11:25:37","indexId":"cir1423","displayToPublicDate":"2016-10-21T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1423","title":"Wyoming Landscape Conservation Initiative—A case study in partnership development","docAbstract":"The Wyoming Landscape Conservation Initiative (WLCI) is a successful example of collaboration between science and natural resource management at the landscape scale. In southwestern Wyoming, expanding energy and mineral development, urban growth, and other changes in land use over recent decades, combined with landscape-scale drivers such as climate change and invasive species, have presented compelling challenges to resource managers and a diverse group of Federal, State, industry, and non-governmental organizations, as well as citizen stakeholders. To address these challenges, the WLCI was established as a collaborative forum and interagency partnership to develop and implement science-based conservation actions. About a decade after being established, this report documents the establishment and history of the WLCI, focusing on the path to success of the initiative and providing insights and details that may be useful in developing similar partnerships in other locations. Not merely retrospective, the elements of the WLCI that are presented herein are still in play, still evolving, and still contributing to the resolution of compelling conservation challenges in the Western United States.
The U.S. Geological Survey has developed many successful longstanding partnerships, of which the WLCI is one example.
“As the Nation’s largest water, earth, and biological science and civilian mapping agency, the U.S. Geological Survey collects, monitors, analyzes, and provides scientific understanding about natural resource conditions, issues, and problems. The diversity of our scientific expertise enables us to carry out large-scale, multi-disciplinary investigations and provide impartial scientific information to resource managers, planners, and other customers” (U.S. Geological Survey, 2016).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1423","usgsCitation":"D’Erchia, Frank, 2016, Wyoming Landscape Conservation Initiative—A case study in partnership development: U.S. Geological Survey Circular 1423, 17 p., https://dx.doi.org/10.3133/cir1423.","productDescription":"vi, 17 p.","numberOfPages":"28","onlineOnly":"Y","ipdsId":"IP-075303","costCenters":[{"id":5077,"text":"Northwest Regional Director's Office","active":true,"usgs":true}],"links":[{"id":329717,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1423/cir1423.pdf","text":"Report","size":"7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Circular 1423"},{"id":329716,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1423/coverthb.jpg"}],"country":"United 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Geological Survey
Northwest Region
909 1st Ave.
Seattle, Washington 98104
https://www.usgs.gov/science
/regions/northwest
Hydration of silicic volcanic glass forms perlite, a dusky, porous form of altered glass characterized by abundant “onion-skin” fractures. The timing and temperature of perlite formation are enigmatic and could plausibly occur during eruption, during post-eruptive cooling, or much later at ambient temperatures. To learn more about the origin of natural perlite, and to fingerprint the hydration waters, we investigated perlitic glass from several synglacial and interglacial rhyolitic lavas and tuffs from the Yellowstone volcanic system. Perlitic cores are surrounded by a series of conchoidal cracks that separate 30- to 100-µm-thick slivers, likely formed in response to hydration-induced stress. H2O and D/H profiles confirm that most D/H exchange happens together with rapid H2O addition but some smoother D/H variations may suggest separate minor exchange by deuterium atom interdiffusion following hydration. The hydrated rinds (2–3 wt% H2O) transition rapidly (within 30 µm, or by 1 wt% H2O per 10 µm) to unhydrated glass cores. This is consistent with quenched “hydration fronts” where H2O diffusion coefficients are strongly dependent on H2O concentrations. The chemical, δ18O, and δD systematics of bulk glass records last equilibrium between ~110 and 60 °C without chemical exchange but with some δ18O exchange. Similarly, the δ18O of water extracted from glass by rapid heating suggests that water was added to the glass during cooling at <200 °C. Our observations support fast hydration at temperatures as low as 60 °C; prolonged exposure to high temperature of 175°–225° during water addition is less likely as the glass would lose alkalies and should alter to clays within days. A compilation of low-temperature hydration diffusion coefficients suggests ~2 orders of magnitude higher rates of diffusion at 60–110 °C temperatures, compared with values expected from extrapolation of high-temperature (>400 °C) experimental data. The thick hydration rinds in perlites, measuring hundreds of microns, preserve the original D/H values of hydrating water as a recorder of paleoclimate conditions. Measured δD values in perlitic lavas are −150 to −191 or 20–40 ‰ lower than glass hydrated by modern Yellowstone waters. This suggests that Yellowstone perlites record the low-δD signature of glacial ice. Cooling calculations, combined with the observed high water diffusion coefficients noted for 60–150 °C, suggest that if sufficient hot water or steam is available, any rhyolite flow greater than ~5 m thick can develop the observed ~250-µm hydration rinds within the expected timescale of cooling (weeks–years). As the process of hydration involves shattering of 30- to 100-µm-thick slivers to expose unhydrated rhyolite glass, the time required for hydration may be even shorter. Rapid hydration and formation of relatively thick-walled glass shards allow perlites to provide a snapshot view of the meteoric water (and thus climate) at the time of initial alteration. Perlites retain their initial hydration D/H signal better than thin-walled ash, which in contrast hydrates over many thousands of years with time-averaged precipitation.
","language":"English","publisher":"Springer","doi":"10.1007/s00410-016-1293-1","usgsCitation":"Bindeman, I.N., and Lowenstern, J.B., 2016, Low-δD hydration rinds in Yellowstone perlites record rapid syneruptive hydration during glacial and interglacial conditions: Contributions to Mineralogy and Petrology, v. 171, p. 1-24, https://doi.org/10.1007/s00410-016-1293-1.","productDescription":"Article 89; 24 p.","startPage":"1","endPage":"24","ipdsId":"IP-075820","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":329731,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"171","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-15","publicationStatus":"PW","scienceBaseUri":"58088685e4b0f497e78e24b5","contributors":{"authors":[{"text":"Bindeman, Ilya N.","contributorId":175500,"corporation":false,"usgs":false,"family":"Bindeman","given":"Ilya","email":"","middleInitial":"N.","affiliations":[{"id":6604,"text":"University of Oregon","active":true,"usgs":false}],"preferred":false,"id":651264,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lowenstern, Jacob B. 0000-0003-0464-7779 jlwnstrn@usgs.gov","orcid":"https://orcid.org/0000-0003-0464-7779","contributorId":2755,"corporation":false,"usgs":true,"family":"Lowenstern","given":"Jacob","email":"jlwnstrn@usgs.gov","middleInitial":"B.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":651263,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ]}