The San Francisco estuary is commonly defined to include San Francisco Bay (bay) and the adjacent Sacramento–San Joaquin River Delta (delta). The U.S. Geological Survey (USGS) has operated a high-frequency (15-minute sampling interval) water-quality monitoring network in San Francisco Bay since the late 1980s (Buchanan and others, 2014). This network includes 19 stations at which sustained measurements have been made in the bay; currently, 8 stations are in operation (fig. 1). All eight stations are equipped with specific conductance (which can be related to salinity) and water-temperature sensors. Water quality in the bay constantly changes as ocean tides force seawater in and out of the bay, and river inflows—the most significant coming from the delta—vary on time scales ranging from those associated with storms to multiyear droughts. This monitoring network was designed to observe and characterize some of these changes in the bay across space and over time. The data demonstrate a high degree of variability in both specific conductance and temperature at time scales from tidal to annual and also reveal longer-term changes that are likely to influence overall environmental health in the bay.
In water year (WY) 2015 (October 1, 2014, through September 30, 2015), as in the preceding water year (Downing-Kunz and others, 2015), the high-frequency measurements revealed record-high values of specific conductance and water temperature at several stations during a period of reduced freshwater inflow from the delta and other tributaries because of persistent, severe drought conditions in California. This report briefly summarizes observations for WY 2015 and compares them to previous years that had different levels of freshwater inflow.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171022","issn":"2331-1258 (online)","usgsCitation":"Work, P.A., Downing-Kunz, M.A., and Livsey, D., 2017, Record-high specific conductance and water temperature in San Francisco Bay during water year 2015: U.S. Geological Survey Open-File Report 2017–1022, 4 p., https://doi.org/10.3133/ofr20171022.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"Y","ipdsId":"IP-079162","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":552,"text":"San Francisco Bay-Delta","active":false,"usgs":true}],"links":[{"id":335947,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1022/coverthb.jpg"},{"id":335948,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1022/ofr20171022.pdf","text":"Report","size":"1.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1022"}],"country":"United States","state":"California","otherGeospatial":"Sacramento-San Joaquin River Delta, San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.9,\n 37.4\n ],\n [\n -122.5,\n 37.4\n ],\n [\n -122.5,\n 38.1\n ],\n [\n -121.9,\n 38.1\n ],\n [\n -121.9,\n 37.4\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, CA 95819
We tested the efficacy of a vertically oriented field of pulsed direct current (VEPDC) created by an array of vertical electrodes for guiding downstream-moving juvenile Sea Lampreys Petromyzon marinus to a bypass channel in an artificial flume at water velocities of 10–50 cm/s. Sea Lampreys were more likely to be captured in the bypass channel than in other sections of the flume regardless of electric field status (on or off) or water velocity. Additionally, Sea Lampreys were more likely to be captured in the bypass channel when the VEPDC was active; however, an interaction between the effects of VEPDC and water velocity was observed, as the likelihood of capture decreased with increases in water velocity. The distribution of Sea Lampreys shifted from right to left across the width of the flume toward the bypass channel when the VEPDC was active at water velocities less than 25 cm/s. The VEPDC appeared to have no effect on Sea Lamprey distribution in the flume at water velocities greater than 25 cm/s. We also conducted separate tests to determine the threshold at which Sea Lampreys would become paralyzed. Individuals were paralyzed at a mean power density of 37.0 µW/cm3. Future research should investigate the ability of juvenile Sea Lampreys to detect electric fields and their specific behavioral responses to electric field characteristics so as to optimize the use of this technology as a nonphysical guidance tool across variable water velocities.
","language":"English","publisher":"American Fisheries Society","doi":"10.1080/00028487.2016.1256834","usgsCitation":"Miehls, S.M., Johnson, N., and Haro, A., 2017, Electrical guidance efficiency of downstream-migrating juvenile Sea Lamprey decreases with increasing water velocity: Transactions of the American Fisheries Society, v. 146, no. 2, p. 299-307, https://doi.org/10.1080/00028487.2016.1256834.","productDescription":"9 p.","startPage":"299","endPage":"307","ipdsId":"IP-080796","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":438434,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7707ZNJ","text":"USGS data release","linkHelpText":"Assessment of pulsed DC electric field to guide downstream migrating sea lamprey in experimental flume at USGS Conte Anadromous Fish Lab, Turners Falls, MA (December 2013)"},{"id":336007,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"146","issue":"2","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-13","publicationStatus":"PW","scienceBaseUri":"58aeb138e4b01ccd54f9ee10","contributors":{"authors":[{"text":"Miehls, Scott M. 0000-0002-5546-1854 smiehls@usgs.gov","orcid":"https://orcid.org/0000-0002-5546-1854","contributorId":5007,"corporation":false,"usgs":true,"family":"Miehls","given":"Scott","email":"smiehls@usgs.gov","middleInitial":"M.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":670118,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Nicholas S. 0000-0002-7419-6013 njohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-7419-6013","contributorId":150983,"corporation":false,"usgs":true,"family":"Johnson","given":"Nicholas S.","email":"njohnson@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":670120,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Haro, Alexander 0000-0002-7188-9172 aharo@usgs.gov","orcid":"https://orcid.org/0000-0002-7188-9172","contributorId":139198,"corporation":false,"usgs":true,"family":"Haro","given":"Alexander","email":"aharo@usgs.gov","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":670119,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70179709,"text":"sir20165177 - 2017 - Characterization of streamflow, suspended sediment, and nutrients entering Galveston Bay from the Trinity River, Texas, May 2014–December 2015","interactions":[],"lastModifiedDate":"2017-02-21T15:20:47","indexId":"sir20165177","displayToPublicDate":"2017-02-21T14:45:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-5177","title":"Characterization of streamflow, suspended sediment, and nutrients entering Galveston Bay from the Trinity River, Texas, May 2014–December 2015","docAbstract":"The U.S. Geological Survey (USGS), in cooperation with the Texas Water Development Board and the Galveston Bay Estuary Program, collected streamflow and water-quality data at USGS streamflow-gaging stations in the lower Trinity River watershed from May 2014 to December 2015 to characterize and improve the current understanding of the quantity and quality of freshwater inflow entering Galveston Bay from the Trinity River. Continuous streamflow records at four USGS streamflow-gaging stations were compared to quantify differences in streamflow magnitude between upstream and downstream reaches of the lower Trinity River. Water-quality conditions were characterized from discrete nutrient and sediment samples collected over a range of hydrologic conditions at USGS streamflow-gaging station 08067252 Trinity River at Wallisville, Tex. (hereinafter referred to as the “Wallisville site”), approximately 4 river miles upstream from where the Trinity River enters Galveston Bay.
Based on streamflow records, annual mean outflow from Livingston Dam into the lower Trinity River was 2,240 cubic feet per second (ft3/s) in 2014 and 22,400 ft3/s in 2015, the second lowest and the highest, respectively, during the entire period of record (1966–2015). During this study, only about 54 percent of the total volume measured at upstream sites was accounted for at the Wallisville site as the Trinity River enters Galveston Bay. This difference in water volumes between upstream sites and the Wallisville site indicates that at high flows a large part of the volume released from Lake Livingston does not reach Galveston Bay through the main channel of the Trinity River. These findings indicate that water likely flows into wetlands and water bodies surrounding the main channel of the Trinity River before reaching the Wallisville site and is being stored or discharged through other channels that flow directly into Galveston Bay.
To characterize suspended-sediment concentrations and loads in Trinity River inflow to Galveston Bay, a regression model was developed to estimate suspended-sediment concentrations by using acoustic backscatter data as a surrogate. The model yielded an adjusted coefficient of determination value of 0.92 and a root mean square error of 1.65 milligrams per liter (mg/L). The mean absolute percentage error between measured and estimated suspended-sediment concentration was 35 percent. During this study, estimated suspended-sediment concentrations ranged from 2 to 701 mg/L, with a mean of 97 mg/L. Suspended-sediment concentrations varied in response to changes in discharge, with peak suspended-sediment concentrations occurring 1 to 2 days before the peak discharge for each event. The total suspended-sediment load at the Wallisville site during May 2014–December 2015 was approximately 2,200,000 tons, with a minimum monthly suspended-sediment load of 100 tons in October 2014 and a maximum monthly load of 441,000 tons in November 2015.
Results from nutrient samples collected at the Wallisville site indicate that total nitrogen and total phosphorus concentrations fluctuated at a similar rate, with the highest nutrient concentrations occurring during periods of high flow corresponding to releases from Lake Livingston. The mean concentrations of total nitrogen and total phosphorus were approximately 75 percent higher during high flow releases than during periods of low flow, overshadowing variations in nutrient concentrations caused by seasonality at the Wallisville site.
Results from the study indicate nutrient delivery to Galveston Bay from the main channel of the Trinity River is likely controlled primarily by high-flow releases from Lake Livingston. For most samples collected at the Wallisville site, organic nitrogen was the predominant form of nitrogen; however, when discharge increased because of releases from Lake Livingston, the percentage of organic nitrogen typically decreased and the percentage of nitrate increased. The concentrations of total phosphorus also increased during high-flow events, likely as a result of suspended sediment within Lake Livingston releases and mobilization of sediment particles in the river channel and flood plain during these periods of high flow. The predominant source of phosphorous to Galveston Bay from the Trinity River is in particulate form closely tied to suspended-sediment concentrations. The changes in nutrient concentration and composition caused by releases from Lake Livingston during this study indicate the reservoir may play an important role in the delivery of nutrients into Galveston Bay. Further study is required to better understand the processes in Lake Livingston influencing the characteristics of nutrient and sediment inflow to Galveston Bay. With phosphorous concentrations correlated to suspended-sediment concentrations (coefficient of determination value of 0.75) and with the concentrations of nutrients changing as the discharge changes, the diversion of water and suspended sediment into surrounding wetlands and channels outside of the main channel of the Trinity River may play a large role in regulating nutrient inputs into Galveston Bay.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165177","isbn":"978-1-4113-4107-4","collaboration":"Prepared in cooperation with the Texas Water Development Board and the Galveston Bay Estuary Program ","usgsCitation":"Lucena, Zulimar, and Lee, M.T., 2017, Characterization of streamflow, suspended sediment, and nutrients entering Galveston Bay from the Trinity River, Texas, May 2014–December 2015: U.S. Geological Survey Scientific Investigations Report 2016–5177, 38 p., https://doi.org/10.3133/sir20165177.\n","productDescription":"vii, 37 p.","numberOfPages":"49","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-077707","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":335588,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5177/sir20165177.pdf","text":"Report","size":"11.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5177"},{"id":335587,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5177/coverthb.jpg"}],"country":"United States","state":"Texas","otherGeospatial":"Galveston Bay, Trinity River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -95.15533447265625,\n 29.7596087873038\n ],\n [\n -94.58953857421875,\n 29.7596087873038\n ],\n [\n -94.58953857421875,\n 30.982318643027536\n ],\n [\n -95.15533447265625,\n 30.982318643027536\n ],\n [\n -95.15533447265625,\n 29.7596087873038\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, X 78754
https://tx.usgs.gov/
Trends in long-term water-quality and streamflow data from six water-quality-monitoring stations within three major river basins in Massachusetts and Rhode Island that flow into Narragansett Bay and Little Narragansett Bay were evaluated for water years 1979–2015. In this study, conducted by the U.S. Geological Survey in cooperation with the Rhode Island Department of Environmental Management, the Rhode Island Water Resources Board, and the U.S. Environmental Protection Agency, water-quality and streamflow data were evaluated with a Weighted Regressions on Time, Discharge, and Season smoothing method, which removes the effects of year-to-year variation in water-quality conditions due to variations in streamflow (discharge). Trends in annual mean, annual median, annual maximum, and annual 7-day minimum flows at four continuous streamgages were evaluated by using a time-series smoothing method for water years 1979–2015.
Water quality at all monitoring stations changed over the study period. Decreasing trends in flow-normalized nutrient concentrations and loads were observed during the period at most monitoring stations for total nitrogen, nitrite plus nitrate, and total phosphorus. Average flow-normalized loads for water years 1979–2015 decreased in the Blackstone River by up to 46 percent in total nitrogen, 17 percent in nitrite plus nitrate, and 69 percent in total phosphorus. The other rivers also had decreasing flow-normalized trends in nutrient concentrations and loads, except for the Pawtuxet River, which had an increasing trend in nitrite plus nitrate. Increasing trends in flow-normalized chloride concentrations and loads were observed during the study period at all of the rivers, with increases of more than 200 percent in the Blackstone River.
Small increasing trends in annual mean daily streamflow were observed in 3 of the 4 rivers, with increases of 1.2 to 11 percent; however, the trends were not significant. All 4 rivers had decreases in streamflow for the annual 7-day minimums, but only 3 of the 4 rivers had decreases that were significant (34 to 54 percent). The Branch River had decreasing annual mean daily streamflow (7.5 percent) and the largest decrease in the annual 7-day minimum streamflow. The Blackstone and Pawtuxet Rivers had the largest increases in annual maximum daily flows but had decreases in the annual 7-day minimum flows.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165178","isbn":"978-1-4113-4102-9","collaboration":"Prepared in cooperation with the Rhode Island Department of Environmental Management, the Rhode Island Water Resources Board, and the U.S. Environmental Protection Agency ","usgsCitation":"Savoie, J.G., Mullaney, J.R., and Bent, G.C., 2017, Analysis of trends of water quality and streamflow in the Blackstone, Branch, Pawtuxet, and Pawcatuck Rivers, Massachusetts and Rhode Island, 1979 to 2015: U.S. Geological Survey Scientific Investigations Report 2016–5178, 43 p., https://doi.org/10.3133/sir20165178.","productDescription":"v, 43 p.","numberOfPages":"54","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-075513","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":335759,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5178/coverthb.jpg"},{"id":335760,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5178/sir20165178.pdf","text":"Report","size":"2.60 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5178"}],"country":"United States","state":"Massachusetts, Rhode Island","otherGeospatial":"Blackstone River, Branch River, Pawcatuck River. Pawtuxet River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72.04833984375,\n 41.269549502842565\n ],\n [\n -71.35345458984375,\n 41.269549502842565\n ],\n [\n -71.35345458984375,\n 42.10433598038485\n ],\n [\n -72.04833984375,\n 42.10433598038485\n ],\n [\n -72.04833984375,\n 41.269549502842565\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Or visit our Web site at:
http://newengland.water.usgs.gov
Disentangling the role that multiple interacting factors have on species responses to shifting climate poses a significant challenge. However, our ability to do so is of utmost importance to predict the effects of climate change on species distributions. We examined how populations of three species of wetland-breeding amphibians, which varied in life history requirements, responded to a six-year period of extremely variable precipitation. This interval was punctuated by both extensive drought and heavy precipitation and flooding, providing a natural experiment to measure community responses to environmental perturbations. We estimated occurrence dynamics using a discrete hidden Markov modeling approach that incorporated information regarding habitat state and predator–prey interactions. This approach allowed us to measure how metapopulation dynamics of each amphibian species was affected by interactions among weather, wetland hydroperiod, and co-occurrence with fish predators. The pig frog, a generalist, proved most resistant to perturbations, with both colonization and persistence being unaffected by seasonal variation in precipitation or co-occurrence with fishes. The ornate chorus frog, an ephemeral wetland specialist, responded positively to periods of drought owing to increased persistence and colonization rates during periods of low-rainfall. Low probabilities of occurrence of the ornate chorus frog in long-duration wetlands were driven by interactions with predators due to low colonization rates when fishes were present. The mole salamander was most sensitive to shifts in water availability. In our study area, this species never occurred in short-duration wetlands and persistence probabilities decreased during periods of drought. At the same time, negative effects occurred with extreme precipitation because flooding facilitated colonization of fishes to isolated wetlands and mole salamanders did not colonize wetlands once fishes were present. We demonstrate that the effects of changes in water availability depend on interactions with predators and wetland type and are influenced by the life history of each of our species. The dynamic species occurrence modeling approach we used offers promise for other systems when the goal is to disentangle the complex interactions that determine species responses to environmental variability.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/eap.1442","usgsCitation":"Davis, C.L., Miller, D.A., Walls, S.C., Barichivich, W.J., Riley, J.W., and Brown, M.E., 2017, Species interactions and the effects of climate variability on a wetland amphibian metacommunity: Ecological Applications, v. 27, no. 1, p. 285-296, https://doi.org/10.1002/eap.1442.","productDescription":"12 p.","startPage":"285","endPage":"296","ipdsId":"IP-070788","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":335901,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"St. Marks National Wildlife Refuge","volume":"27","issue":"1","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-04","publicationStatus":"PW","scienceBaseUri":"58ad5fc0e4b01ccd54f8b50f","contributors":{"authors":[{"text":"Davis, Courtney L.","contributorId":181922,"corporation":false,"usgs":false,"family":"Davis","given":"Courtney","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":670047,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Miller, David A.W. davidmiller@usgs.gov","contributorId":4043,"corporation":false,"usgs":true,"family":"Miller","given":"David","email":"davidmiller@usgs.gov","middleInitial":"A.W.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":670048,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Walls, Susan C. 0000-0001-7391-9155 swalls@usgs.gov","orcid":"https://orcid.org/0000-0001-7391-9155","contributorId":2310,"corporation":false,"usgs":true,"family":"Walls","given":"Susan","email":"swalls@usgs.gov","middleInitial":"C.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":false,"id":670046,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barichivich, William J. 0000-0003-1103-6861 wbarichivich@usgs.gov","orcid":"https://orcid.org/0000-0003-1103-6861","contributorId":3697,"corporation":false,"usgs":true,"family":"Barichivich","given":"William","email":"wbarichivich@usgs.gov","middleInitial":"J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":670049,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Riley, Jeffrey W. 0000-0001-5525-3134 jriley@usgs.gov","orcid":"https://orcid.org/0000-0001-5525-3134","contributorId":3605,"corporation":false,"usgs":true,"family":"Riley","given":"Jeffrey","email":"jriley@usgs.gov","middleInitial":"W.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":670050,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Brown, Mary E. 0000-0002-5580-137X","orcid":"https://orcid.org/0000-0002-5580-137X","contributorId":181924,"corporation":false,"usgs":true,"family":"Brown","given":"Mary","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":670051,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70182145,"text":"70182145 - 2017 - Early detection monitoring for larval dreissenid mussels: How much plankton sampling is enough?","interactions":[],"lastModifiedDate":"2017-02-27T10:59:16","indexId":"70182145","displayToPublicDate":"2017-02-17T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1552,"text":"Environmental Monitoring and Assessment","onlineIssn":"1573-2959","printIssn":"0167-6369","active":true,"publicationSubtype":{"id":10}},"title":"Early detection monitoring for larval dreissenid mussels: How much plankton sampling is enough?","docAbstract":"The development of quagga and zebra mussel (dreissenids) monitoring programs in the Pacific Northwest provides a unique opportunity to evaluate a regional invasive species detection effort early in its development. Recent studies suggest that the ecological and economic costs of a dreissenid infestation in the Pacific Northwest of the USA would be significant. Consequently, efforts are underway to monitor for the presence of dreissenids. However, assessments of whether these efforts provide for early detection are lacking. We use information collected from 2012 to 2014 to characterize the development of larval dreissenid monitoring programs in the states of Idaho, Montana, Oregon, and Washington in the context of introduction and establishment risk. We also estimate the effort needed for high-probability detection of rare planktonic taxa in four Columbia and Snake River reservoirs and assess whether the current level of effort provides for early detection. We found that the effort expended to monitor for dreissenid mussels increased substantially from 2012 to 2014, that efforts were distributed across risk categories ranging from high to very low, and that substantial gaps in our knowledge of both introduction and establishment risk exist. The estimated volume of filtered water required to fully census planktonic taxa or to provide high-probability detection of rare taxa was high for the four reservoirs examined. We conclude that the current level of effort expended does not provide for high-probability detection of larval dreissenids or other planktonic taxa when they are rare in these reservoirs. We discuss options to improve early detection capabilities.","language":"English","publisher":"Springer International Publishing","doi":"10.1007/s10661-016-5737-x","usgsCitation":"Counihan, T.D., and Bollens, S., 2017, Early detection monitoring for larval dreissenid mussels: How much plankton sampling is enough?: Environmental Monitoring and Assessment, v. 189, no. 98, p. 1-14, https://doi.org/10.1007/s10661-016-5737-x.","productDescription":"Report: 14 p. ","startPage":"1","endPage":"14","ipdsId":"IP-073726","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":335805,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho, Oregon, Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.98095703125,\n 46.9502622421856\n ],\n [\n -122.93701171874999,\n 44.653024159812\n ],\n [\n -115.64208984374999,\n 44.512176171071054\n ],\n [\n -115.653076171875,\n 46.93526088057719\n ],\n [\n -122.98095703125,\n 46.9502622421856\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"189","issue":"98","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-06","publicationStatus":"PW","scienceBaseUri":"58a819b8e4b025c46429afca","contributors":{"authors":[{"text":"Counihan, Timothy D. 0000-0003-4967-6514 tcounihan@usgs.gov","orcid":"https://orcid.org/0000-0003-4967-6514","contributorId":4211,"corporation":false,"usgs":true,"family":"Counihan","given":"Timothy","email":"tcounihan@usgs.gov","middleInitial":"D.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":669786,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bollens, Stephen M.","contributorId":181850,"corporation":false,"usgs":false,"family":"Bollens","given":"Stephen M.","affiliations":[],"preferred":false,"id":669787,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70182151,"text":"70182151 - 2017 - A river-scale Lagrangian experiment examining controls on phytoplankton dynamics in the presence and absence of treated wastewater effluent high in ammonium","interactions":[],"lastModifiedDate":"2017-05-09T10:45:03","indexId":"70182151","displayToPublicDate":"2017-02-17T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2620,"text":"Limnology and Oceanography","active":true,"publicationSubtype":{"id":10}},"title":"A river-scale Lagrangian experiment examining controls on phytoplankton dynamics in the presence and absence of treated wastewater effluent high in ammonium","docAbstract":"Phytoplankton are critical component of the food web in most large rivers and estuaries, and thus identifying dominant controls on phytoplankton abundance and species composition is important to scientists, managers, and policymakers. Recent studies from a variety of systems indicate that ammonium ( NH+4) in treated wastewater effluent decreases primary production and alters phytoplankton species composition. However, these findings are based mainly on laboratory and enclosure studies, which may not adequately represent natural systems. To test effects of effluent high in ammonium on phytoplankton at the ecosystem scale, we conducted whole-river–scale experiments by halting discharges to the Sacramento River from the regional wastewater treatment plant (WWTP), and used a Lagrangian approach to compare changes in phytoplankton abundance and species composition in the presence (+EFF) and absence (−EFF) of effluent. Over 5 d of downstream travel from 20 km above to 50 km below the WWTP, chlorophyll concentrations declined from 15–25 to ∼2.5 μg L−1, irrespective of effluent addition. Benthic diatoms were dominant in most samples. We found no significant difference in phytoplankton abundance or species composition between +EFF and −EFF conditions. Moreover, greatest declines in chlorophyll occurred upstream of the WWTP where NH+4 concentrations were low. Grazing by clams and zooplankton could not account for observed losses, suggesting other factors such as hydrodynamics and light limitation were responsible for phytoplankton declines. These results highlight the advantages of conducting ecosystem-scale, Lagrangian-based experiments to understand the dynamic and complex interplay between physical, chemical, and biological factors that control phytoplankton populations.
","language":"English","publisher":"American Society of Limnology and Oceanography","publisherLocation":"Lawrence, KS","doi":"10.1002/lno.10497","usgsCitation":"Kraus, T.E., Carpenter, K.D., Bergamaschi, B.A., Parker, A., Stumpner, E.B., Downing, B.D., Travis, N., Wilkerson, F., Kendall, C., and Mussen, T., 2017, A river-scale Lagrangian experiment examining controls on phytoplankton dynamics in the presence and absence of treated wastewater effluent high in ammonium: Limnology and Oceanography, v. 62, no. 3, p. 1234-1253, https://doi.org/10.1002/lno.10497.","productDescription":"20 p.","startPage":"1234","endPage":"1253","ipdsId":"IP-069386","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":470064,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/lno.10497","text":"Publisher Index Page"},{"id":335806,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.75,\n 38.616667\n ],\n [\n -121.416667,\n 38.616667\n ],\n [\n -121.416667,\n 38.116667\n ],\n [\n -121.75,\n 38.116667\n ],\n [\n -121.75,\n 38.616667\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"62","issue":"3","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-04","publicationStatus":"PW","scienceBaseUri":"58a819b6e4b025c46429afc2","contributors":{"authors":[{"text":"Kraus, Tamara E. 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C.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":669797,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carpenter, Kurt D. 0000-0002-6231-8335 kdcar@usgs.gov","orcid":"https://orcid.org/0000-0002-6231-8335","contributorId":127442,"corporation":false,"usgs":true,"family":"Carpenter","given":"Kurt","email":"kdcar@usgs.gov","middleInitial":"D.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":669798,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bergamaschi, Brian A. 0000-0002-9610-5581 bbergama@usgs.gov","orcid":"https://orcid.org/0000-0002-9610-5581","contributorId":140776,"corporation":false,"usgs":true,"family":"Bergamaschi","given":"Brian","email":"bbergama@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":669799,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Parker, Alexander","contributorId":181853,"corporation":false,"usgs":false,"family":"Parker","given":"Alexander","affiliations":[],"preferred":false,"id":669834,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stumpner, Elizabeth B. 0000-0003-2356-2244 estumpner@usgs.gov","orcid":"https://orcid.org/0000-0003-2356-2244","contributorId":181854,"corporation":false,"usgs":true,"family":"Stumpner","given":"Elizabeth","email":"estumpner@usgs.gov","middleInitial":"B.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":669801,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Downing, Bryan D. 0000-0002-2007-5304 bdowning@usgs.gov","orcid":"https://orcid.org/0000-0002-2007-5304","contributorId":1449,"corporation":false,"usgs":true,"family":"Downing","given":"Bryan","email":"bdowning@usgs.gov","middleInitial":"D.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":669802,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Travis, Nicole","contributorId":181855,"corporation":false,"usgs":false,"family":"Travis","given":"Nicole","email":"","affiliations":[],"preferred":false,"id":669835,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wilkerson, Frances","contributorId":152296,"corporation":false,"usgs":false,"family":"Wilkerson","given":"Frances","email":"","affiliations":[{"id":18901,"text":"San Francisco State University, Romberg Tiburon Center","active":true,"usgs":false}],"preferred":false,"id":669804,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kendall, Carol 0000-0002-0247-3405 ckendall@usgs.gov","orcid":"https://orcid.org/0000-0002-0247-3405","contributorId":1462,"corporation":false,"usgs":true,"family":"Kendall","given":"Carol","email":"ckendall@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":669805,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Mussen, Timothy","contributorId":181857,"corporation":false,"usgs":false,"family":"Mussen","given":"Timothy","affiliations":[],"preferred":false,"id":669836,"contributorType":{"id":1,"text":"Authors"},"rank":10}]}} ,{"id":70180166,"text":"ofr20171010 - 2017 - Saltwater intrusion in the Floridan aquifer system near downtown Brunswick, Georgia, 1957–2015","interactions":[],"lastModifiedDate":"2017-02-17T09:15:57","indexId":"ofr20171010","displayToPublicDate":"2017-02-16T16:45:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-1010","title":"Saltwater intrusion in the Floridan aquifer system near downtown Brunswick, Georgia, 1957–2015","docAbstract":"The Floridan aquifer system (FAS) consists of the Upper Floridan aquifer (UFA), an intervening confining unit of highly variable properties, and the Lower Floridan aquifer (LFA). The UFA and LFA are primarily composed of Paleocene- to Oligocene-age carbonate rocks that include, locally, Upper Cretaceous rocks. The FAS extends from coastal areas in southeastern South Carolina and continues southward and westward across the coastal plain of Georgia and Alabama, and underlies all of Florida. The thickness of the FAS varies from less than 100 feet (ft) in aquifer outcrop areas of South Carolina to about 1,700 ft near the city of Brunswick, Georgia.
Locally, in southeastern Georgia and the Brunswick– Glynn County area, the UFA consists of an upper water-bearing zone (UWBZ) and a lower water-bearing zone (LWBZ), as identified by Wait and Gregg (1973), with aquifer test data indicating the upper zone has higher productivity than the lower zone. Near the city of Brunswick, the LFA is composed of two permeable zones: an early middle Eocene-age upper permeable zone (UPZ) and a highly permeable lower zone of limestone (LPZ) of Paleocene and Late Cretaceous age that includes a deeply buried, cavernous, saline water-bearing unit known as the Fernandina permeable zone. Maslia and Prowell (1990) inferred the presence of major northeast–southwest trending faults through the downtown Brunswick area based on structural analysis of geophysical data, northeastward elongation of the potentiometric surface of the UFA, and breaches in the local confining unit that influence the area of chloride contamination. Pronounced horizontal and vertical hydraulic head gradients, caused by pumping in the UFA, allow saline water from the FPZ to migrate upward into the UFA through this system of faults and conduits.
Saltwater was first detected in the FAS in wells completed in the UFA near the southern part of the city of Brunswick in late 1957. By the 1970s, a plume of groundwater with high chloride concentrations had migrated northward toward two major industrial pumping centers, and since 1965, chloride concentrations have steadily increased in the northern part of the city. In 1978, data obtained from a 2,720-ft-deep test well (33H188) drilled south of the city showed water with a chloride concentration of 33,000 milligrams per liter (mg/L), suggesting the saltwater source was located below the UFA in the Fernandina permeable zone (FPZ) of the LFA.
All U.S. Geological Survey (USGS) data collected for this study, including groundwater levels in wells and water-chemistry data, are available in the USGS National Water Information System.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171010","collaboration":"In cooperation with the Brunswick-Glynn County Joint Water and Sewer Commission","usgsCitation":"Cherry, G.S., and Peck, M.F., 2017, Saltwater intrusion in the Floridan aquifer system near downtown Brunswick, Georgia, 1957–2015: U.S. Geological Survey Open-File Report 2017–2010, 10 p., https://doi.org/10.3133/ofr20171010.","productDescription":"10 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-075326","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":334883,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1010/ofr20171010.pdf","text":"Report","size":"1.61 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1010"},{"id":334882,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1010/coverthb1.jpg"}],"country":"United States","state":"Georgia","city":"Brunswick","otherGeospatial":"Floridan Aquifer System","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.53263092041016,\n 31.11262192177511\n ],\n [\n -81.46190643310547,\n 31.11262192177511\n ],\n [\n -81.46190643310547,\n 31.207516037787602\n ],\n [\n -81.53263092041016,\n 31.207516037787602\n ],\n [\n -81.53263092041016,\n 31.11262192177511\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Stephenson Center, Suite 129
Columbia, SC 29210
Or visit the South Atlantic Water Science Center Website at
https://www.usgs.gov/water/southatlantic/
A methodology for developing a representative set of storm scenarios based on historical wave buoy and tide gauge data for a region at the Chandeleur Islands, Louisiana, was developed by the U.S. Geological Survey. The total water level was calculated for a 10-year period and analyzed against existing topographic data to identify when storm-induced wave action would affect island morphology. These events were categorized on the basis of the threshold of total water level and duration to create a set of storm scenarios that were simulated, using a high-fidelity, process-based, morphologic evolution model, on an idealized digital elevation model of the Chandeleur Islands. The simulated morphological changes resulting from these scenarios provide a range of impacts that can help coastal managers determine resiliency of proposed or existing coastal structures and identify vulnerable areas within those structures.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171009","usgsCitation":"Mickey, R.C., Long, J.W., Plant, N.G., Thompson, D.M., and Dalyander, P.S., 2017, A methodology for modeling barrier island storm-impact scenarios (ver. 1.1, March 2017): U.S. Geological Survey Open-File Report 2017–1009, 17 p., https://doi.org/10.3133/ofr20171009.","productDescription":"iv, 17 p.","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":337876,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2017/1009/versionHist.txt","linkFileType":{"id":2,"text":"txt"}},{"id":334864,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1009/coverthb2.jpg"},{"id":334865,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1009/ofr20171009.pdf","text":"Report","size":"2.15 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1009"},{"id":334866,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F72F7KJK","text":"USGS data release","description":"USGS data release","linkHelpText":"Storm-Impact Scenario XBeach Model Input and Results"}],"country":"United States","state":"Louisiana","otherGeospatial":"Chandeleur Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.116667,\n 31\n ],\n [\n -86.95,\n 31\n ],\n [\n -86.95,\n 28.583333\n ],\n [\n -89.116667,\n 28.583333\n ],\n [\n -89.116667,\n 31\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: Originally posted February 16, 2017; Version 1.1: March 29, 2017","contact":"Director, St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
http://coastal.er.usgs.gov/
Digital flood-inundation maps for a 4.1-mile reach of the Big Blue River at Shelbyville, Indiana, were created by the U.S. Geological Survey (USGS) in cooperation with the Indiana Office of Community and Rural Affairs. The floodinundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at https://water. usgs.gov/osw/flood_inundation/, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage on the Big Blue River at Shelbyville, Ind. (station number 03361500). Near-real-time stages at this streamgage may be obtained from the USGS National Water Information System at https://waterdata. usgs.gov/ or the National Weather Service (NWS) Advanced Hydrologic Prediction Service at https://water.weather.gov/ ahps/, which also forecasts flood hydrographs at this site (SBVI3). Flood profiles were computed for the stream reach by means of a one-dimensional step-backwater model. The hydraulic model was calibrated by using the most current stage-discharge relation at the Big Blue River at Shelbyville, Ind., streamgage. The calibrated hydraulic model was then used to compute 12 water-surface profiles for flood stages referenced to the streamgage datum and ranging from 9.0 feet, or near bankfull, to 19.4 feet, the highest stage of the current stage-discharge rating curve. The simulated water-surface profiles were then combined with a Geographic Information System digital elevation model (derived from light detection and ranging [lidar] data having a 0.98-foot vertical accuracy and 4.9-foot horizontal resolution) to delineate the area flooded at each water level. The availability of these maps, along with Internet information regarding current stage from the USGS streamgage at the Big Blue River at Shelbyville, Ind., and forecasted stream stages from the NWS, will provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures as well as for post-flood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165166","collaboration":"Prepared in cooperation with the Indiana Office of Community and Rural Affairs","usgsCitation":"Fowler, K.K., 2017, Flood-inundation maps for the Big Blue River at Shelbyville, Indiana: U.S. Geological Survey Scientific Investigations Report 2016–5166, 11 p., https://doi.org/10.3133/sir20165166.","productDescription":"Report: vi, 11 p.; Data Release","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-077203","costCenters":[{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true}],"links":[{"id":335209,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7WH2N48","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":" Big Blue River at Shelbyville, Indiana, flood-inundation geospatial datasets"},{"id":335207,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5166/coverthb.jpg"},{"id":335208,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5166/sir20165166.pdf","text":"Report","size":"1.48 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5166"}],"country":"United States","state":"Indiana","city":"Shelbyville","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -85.8248519897461,\n 39.504305605954634\n ],\n [\n -85.7457160949707,\n 39.504305605954634\n ],\n [\n -85.7457160949707,\n 39.5546183524477\n ],\n [\n -85.8248519897461,\n 39.5546183524477\n ],\n [\n -85.8248519897461,\n 39.504305605954634\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Indiana Water Science Center
U.S. Geological Survey
5957 Lakeside Boulevard
Indianapolis, IN 46278–1996
Glacier hypsometry provides a first‐order approach for assessing a glacier's response to climate forcings. We couple the Randolph Glacier Inventory to a suite of in situ observations and climate model output to examine potential change for the ∼27,000 glaciers in Alaska and northwest Canada through the end of the 21st century. By 2100, based on Representative Concentration Pathways (RCPs) 4.5–8.5 forcings, summer temperatures are predicted to increase between +2.1 and +4.6°C, while solid precipitation (snow) is predicted to decrease by −6 to −11%, despite a +9 to +21% increase in total precipitation. Snow is predicted to undergo a pronounced decrease in the fall, shifting the start of the accumulation season back by ∼1 month. In response to these forcings, the regional equilibrium line altitude (ELA) may increase by +105 to +225 m by 2100. The mass balance sensitivity to this increase is highly variable, with the most substantive impact for glaciers with either limited elevation ranges (often small (<1 km2) glaciers, which account for 80% of glaciers in the region) or those with top‐heavy geometries, like icefields. For more than 20% of glaciers, future ELAs, given RCP 6.0 forcings, will exceed the maximum elevation of the glacier, resulting in their eventual demise, while for others, accumulation area ratios will decrease by >60%. Our results highlight the first‐order control of hypsometry on individual glacier response to climate change, and the variability that hypsometry introduces to a regional response to a coherent climate perturbation.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2016EF000479","usgsCitation":"Mcgrath, D., Sass, L., O’Neel, S., Arendt, A.A., and Kienholz, C., 2017, Hypsometric control on glacier mass balance sensitivity in Alaska and northwest Canada: Earth's Future, v. 5, no. 3, p. 324-336, https://doi.org/10.1002/2016EF000479.","productDescription":"13 p.","startPage":"324","endPage":"336","ipdsId":"IP-080924","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":470065,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016ef000479","text":"Publisher Index Page"},{"id":369088,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","state":"Alaska, British Columbia, Yukon","otherGeospatial":"Gulf of Alaska watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -162.7734375,\n 60.108670463036\n ],\n [\n -130.869140625,\n 51.781435604431195\n ],\n [\n -123.134765625,\n 55.02802211299252\n ],\n [\n -123.04687499999999,\n 56.36525013685606\n ],\n [\n -128.671875,\n 66.75724984139227\n ],\n [\n -136.669921875,\n 66.44310650816469\n ],\n [\n -162.7734375,\n 60.108670463036\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"5","issue":"3","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-23","publicationStatus":"PW","contributors":{"authors":[{"text":"Mcgrath, Daniel 0000-0002-9462-6842 dmcgrath@usgs.gov","orcid":"https://orcid.org/0000-0002-9462-6842","contributorId":145635,"corporation":false,"usgs":true,"family":"Mcgrath","given":"Daniel","email":"dmcgrath@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":774886,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sass, Louis C. 0000-0003-4677-029X lsass@usgs.gov","orcid":"https://orcid.org/0000-0003-4677-029X","contributorId":3555,"corporation":false,"usgs":true,"family":"Sass","given":"Louis C.","email":"lsass@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":774887,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O’Neel, Shad 0000-0002-9185-0144 soneel@usgs.gov","orcid":"https://orcid.org/0000-0002-9185-0144","contributorId":166740,"corporation":false,"usgs":true,"family":"O’Neel","given":"Shad","email":"soneel@usgs.gov","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":774888,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Arendt, Anthony A.","contributorId":200572,"corporation":false,"usgs":false,"family":"Arendt","given":"Anthony","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":774889,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kienholz, C.","contributorId":146539,"corporation":false,"usgs":false,"family":"Kienholz","given":"C.","email":"","affiliations":[{"id":13097,"text":"Geophysical Institute, University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":774890,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70182087,"text":"70182087 - 2017 - Evaluation of nutria (Myocastor coypus) detection methods in Maryland, USA","interactions":[],"lastModifiedDate":"2018-03-29T13:47:36","indexId":"70182087","displayToPublicDate":"2017-02-16T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Evaluation of nutria (Myocastor coypus) detection methods in Maryland, USA","title":"Evaluation of nutria (Myocastor coypus) detection methods in Maryland, USA","docAbstract":"Nutria (Myocaster coypus), invasive, semi-aquatic rodents native to South America, were introduced into Maryland near Blackwater National Wildlife Refuge (BNWR) in 1943. Irruptive population growth, expansion, and destructive feeding habits resulted in the destruction of thousands of acres of emergent marshes at and surrounding BNWR. In 2002, a partnership of federal, state and private entities initiated an eradication campaign to protect remaining wetlands from further damage and facilitate the restoration of coastal wetlands throughout the Chesapeake Bay region. Program staff removed nearly 14,000 nutria from five infested watersheds in a systematic trapping and hunting program between 2002 and 2014. As part of ongoing surveillance activities, the Chesapeake Bay Nutria Eradication Project uses a variety of tools to detect and remove nutria. Project staff developed a floating raft, or monitoring platform, to determine site occupancy. These platforms are placed along waterways and checked periodically for evidence of nutria visitation. We evaluated the effectiveness of monitoring platforms and three associated detection methods: hair snares, presence of scat, and trail cameras. Our objectives were to (1) determine if platform placement on land or water influenced nutria visitation rates, (2) determine if the presence of hair snares influenced visitation rates, and (3) determine method-specific detection probabilities. Our analyses indicated that platforms placed on land were 1.5–3.0 times more likely to be visited than those placed in water and that platforms without snares were an estimated 1.7–3.7 times more likely to be visited than those with snares. Although the presence of snares appears to have discouraged visitation, seasonal variation may confound interpretation of these results. Scat was the least effective method of determining nutria visitation, while hair snares were as effective as cameras. Estimated detection probabilities provided by occupancy modeling were 0.73 for hair snares, 0.71 for cameras and 0.40 for scat. We recommend the use of hair snares on monitoring platforms as they are the most cost-effective and reliable detection method available at this time. Future research should focus on determining the cause for the observed decrease in nutria visits after snares were applied.
","language":"English","publisher":"Springer","doi":"10.1007/s10530-016-1312-1","usgsCitation":"Pepper, M.A., Herrmann, V., Hines, J.E., Nichols, J.D., and Kendrot, S.R., 2017, Evaluation of nutria (Myocastor coypus) detection methods in Maryland, USA: Biological Invasions, v. 19, no. 3, p. 831-841, https://doi.org/10.1007/s10530-016-1312-1.","productDescription":"11 p.","startPage":"831","endPage":"841","ipdsId":"IP-080917","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":335674,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland","otherGeospatial":"Wicomico River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.7723617553711,\n 38.272419002497735\n ],\n [\n -75.6748580932617,\n 38.272419002497735\n ],\n [\n -75.6748580932617,\n 38.347580040410506\n ],\n [\n -75.7723617553711,\n 38.347580040410506\n ],\n [\n -75.7723617553711,\n 38.272419002497735\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"19","issue":"3","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-07","publicationStatus":"PW","scienceBaseUri":"58a6c828e4b025c464286258","contributors":{"authors":[{"text":"Pepper, Margaret A.","contributorId":181781,"corporation":false,"usgs":false,"family":"Pepper","given":"Margaret","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":669510,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Herrmann, Valentine","contributorId":181782,"corporation":false,"usgs":false,"family":"Herrmann","given":"Valentine","email":"","affiliations":[],"preferred":false,"id":669511,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hines, James E. 0000-0001-5478-7230 jhines@usgs.gov","orcid":"https://orcid.org/0000-0001-5478-7230","contributorId":146530,"corporation":false,"usgs":true,"family":"Hines","given":"James","email":"jhines@usgs.gov","middleInitial":"E.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":669509,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nichols, James D. 0000-0002-7631-2890 jnichols@usgs.gov","orcid":"https://orcid.org/0000-0002-7631-2890","contributorId":140652,"corporation":false,"usgs":true,"family":"Nichols","given":"James","email":"jnichols@usgs.gov","middleInitial":"D.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":669512,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kendrot, Stephen R","contributorId":181783,"corporation":false,"usgs":false,"family":"Kendrot","given":"Stephen","email":"","middleInitial":"R","affiliations":[],"preferred":false,"id":669513,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70181023,"text":"fs20173008 - 2017 - Refining previous estimates of groundwater outflows from the Medina/Diversion Lake system, San Antonio area, Texas","interactions":[],"lastModifiedDate":"2017-02-15T18:02:00","indexId":"fs20173008","displayToPublicDate":"2017-02-15T16:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-3008","title":"Refining previous estimates of groundwater outflows from the Medina/Diversion Lake system, San Antonio area, Texas","docAbstract":"In 2016, the U.S. Geological Survey (USGS), in cooperation with the San Antonio Water System, began a study to refine previously derived estimates of groundwater outflows from Medina and Diversion Lakes in south-central Texas near San Antonio. When full, Medina and Diversion Lakes (hereinafter referred to as the Medina/Diversion Lake system) (fig. 1) impound approximately 255,000 acre-feet and 2,555 acre-feet of water, respectively.
Most recharge to the Edwards aquifer occurs as seepage from streams as they cross the outcrop (recharge zone) of the aquifer (Slattery and Miller, 2017). Groundwater outflows from the Medina/Diversion Lake system have also long been recognized as a potentially important additional source of recharge. Puente (1978) published methods for estimating monthly and annual estimates of the potential recharge to the Edwards aquifer from the Medina/Diversion Lake system. During October 1995–September 1996, the USGS conducted a study to better define short-term rates of recharge and to reduce the error and uncertainty associated with estimates of monthly recharge from the Medina/Diversion Lake system (Lambert and others, 2000). As a followup to that study, Slattery and Miller (2017) published estimates of groundwater outflows from detailed water budgets for the Medina/Diversion Lake system during 1955–1964, 1995–1996, and 2001–2002. The water budgets were compiled for selected periods during which time the water-budget components were inferred to be relatively stable and the influence of precipitation, stormwater runoff, and changes in storage were presumably minimal. Linear regression analysis techniques were used by Slattery and Miller (2017) to assess the relation between the stage in Medina Lake and groundwater outflows from the Medina/Diversion Lake system.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20173008","collaboration":"Prepared in cooperation with the San Antonio Water System","usgsCitation":"Slattery, R.N., Asquith, W.H., and Gordon, J.D., 2017, Refining previous estimates of groundwater outflows from the Medina/Diversion Lake system, San Antonio area, Texas: U.S. Geological Survey Fact Sheet 2017–3008, 2 p., https://doi.org/10.3133/fs20173008.","productDescription":"Report: 2 p.; Data Release","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-082626","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":335145,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7ZS2TNF","text":"USGS Data Release","description":"USGS data release","linkHelpText":"Reanalysis of the Medina/Diversion Lake System Water-Budget, with Estimated Recharge to Edwards Aquifer, San Antonio Area, Texas"},{"id":335296,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/publication/sir20045209","text":"SIR 2004–5209","size":"4.22 MB","description":"SIR 2004–5209"},{"id":335143,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2017/3008/coverthb.jpg"},{"id":335144,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2017/3008/fs20173008.pdf","text":"Fact Sheet","size":"332 KB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2017–3008"}],"country":"United States","state":"Texas","otherGeospatial":" Medina River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99.05,\n 29.5\n ],\n [\n -98.85,\n 29.5\n ],\n [\n -98.85,\n 29.7\n ],\n [\n -99.05,\n 29.7\n ],\n [\n -99.05,\n 29.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754
Great Lakes tributaries are known to deliver waterborne pathogens from a host of sources. To examine the hydrologic, land cover, and seasonal patterns of waterborne pathogens (i.e. protozoa (2), pathogenic bacteria (4) human viruses, (8) and bovine viruses (8)) eight rivers were monitored in the Great Lakes Basin over 29 months from February 2011 to June 2013. Sampling locations represented a wide variety of land cover classes from urban to agriculture to forest. A custom automated pathogen sampler was deployed at eight sampling locations which provided unattended, flow-weighted, large-volume (120–1630 L) sampling. Human and bovine viruses and pathogenic bacteria were detected by real-time qPCR in 16%, 14%, and 1.4% of 290 samples collected while protozoa were never detected. The most frequently detected pathogens were: bovine polyomavirus (11%), and human adenovirus C, D, F (9%). Human and bovine viruses were present in 16.9% and 14.8% of runoff-event samples (n = 189) resulting from precipitation and snowmelt, and 13.9% and 12.9% of low-flow samples (n = 101), respectively, indicating multiple delivery mechanisms could be influential. Data indicated human and bovine virus prevalence was different depending on land cover within the watershed. Occurrence, concentration, and flux of human viruses were greatest in samples from the three sampling locations with greater than 25% urban influence than those with less than 25% urban influence. Similarly, occurrence, concentration, and flux of bovine viruses were greatest in samples from the two sampling locations with greater than 50 cattle/km2 than those with less than 50 cattle/km2. In seasonal analysis, human and bovine viruses occurred more frequently in spring and winter seasons than during the fall and summer. Concentration, occurrence, and flux in the context of hydrologic condition, seasonality, and land use must be considered for each watershed individually to develop effective watershed management strategies for pathogen reduction.
","language":"English","publisher":"International Water Association","publisherLocation":"Oxford","doi":"10.1016/j.watres.2017.01.060","usgsCitation":"Lenaker, P.L., Corsi, S., Borchardt, M.A., Spencer, S.K., Baldwin, A.K., and Lutz, M.A., 2017, Hydrologic, land cover, and seasonal patterns of waterborne pathogens in Great Lakes tributaries: Water Research, v. 113, p. 11-21, https://doi.org/10.1016/j.watres.2017.01.060.","productDescription":"11 p.","startPage":"11","endPage":"21","ipdsId":"IP-079348","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":470067,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1016/j.watres.2017.01.060","text":"External Repository"},{"id":335540,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Great Lakes tributaries","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.97802734375,\n 39.825413103424786\n ],\n [\n -81.5625,\n 39.825413103424786\n ],\n [\n -81.5625,\n 47.27922900257082\n ],\n [\n -89.97802734375,\n 47.27922900257082\n ],\n [\n -89.97802734375,\n 39.825413103424786\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"113","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58a576bae4b057081a24ed16","contributors":{"authors":[{"text":"Lenaker, Peter L. 0000-0002-9469-6285 plenaker@usgs.gov","orcid":"https://orcid.org/0000-0002-9469-6285","contributorId":5572,"corporation":false,"usgs":true,"family":"Lenaker","given":"Peter","email":"plenaker@usgs.gov","middleInitial":"L.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":669263,"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":669264,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Borchardt, Mark A. 0000-0002-6471-2627","orcid":"https://orcid.org/0000-0002-6471-2627","contributorId":151033,"corporation":false,"usgs":false,"family":"Borchardt","given":"Mark","email":"","middleInitial":"A.","affiliations":[{"id":6684,"text":"USDA Forest Service, Southern Research Station, Aiken, SC","active":true,"usgs":false}],"preferred":false,"id":669265,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Spencer, Susan K.","contributorId":181738,"corporation":false,"usgs":false,"family":"Spencer","given":"Susan","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":669266,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"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":669268,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lutz, Michelle A. malutz@usgs.gov","contributorId":131020,"corporation":false,"usgs":true,"family":"Lutz","given":"Michelle","email":"malutz@usgs.gov","middleInitial":"A.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":669267,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70181999,"text":"70181999 - 2017 - Water quality data for national-scale aquatic research: The Water Quality Portal","interactions":[],"lastModifiedDate":"2017-03-29T15:05:03","indexId":"70181999","displayToPublicDate":"2017-02-15T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Water quality data for national-scale aquatic research: The Water Quality Portal","docAbstract":"Aquatic systems are critical to food, security, and society. But, water data are collected by hundreds of research groups and organizations, many of which use nonstandard or inconsistent data descriptions and dissemination, and disparities across different types of water observation systems represent a major challenge for freshwater research. To address this issue, the Water Quality Portal (WQP) was developed by the U.S. Environmental Protection Agency, the U.S. Geological Survey, and the National Water Quality Monitoring Council to be a single point of access for water quality data dating back more than a century. The WQP is the largest standardized water quality data set available at the time of this writing, with more than 290 million records from more than 2.7 million sites in groundwater, inland, and coastal waters. The number of data contributors, data consumers, and third-party application developers making use of the WQP is growing rapidly. Here we introduce the WQP, including an overview of data, the standardized data model, and data access and services; and we describe challenges and opportunities associated with using WQP data. We also demonstrate through an example the value of the WQP data by characterizing seasonal variation in lake water clarity for regions of the continental U.S. The code used to access, download, analyze, and display these WQP data as shown in the figures is included as supporting information.
","language":"English","publisher":"Wiley","doi":"10.1002/2016WR019993","usgsCitation":"Read, E.K., Carr, L., DeCicco, L.A., Dugan, H., Hanson, P.C., Hart, J.A., Kreft, J., Read, J.S., and Winslow, L., 2017, Water quality data for national-scale aquatic research: The Water Quality Portal: Water Resources Research, v. 53, no. 2, p. 1735-1745, https://doi.org/10.1002/2016WR019993.","productDescription":"11 p.","startPage":"1735","endPage":"1745","ipdsId":"IP-082664","costCenters":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"links":[{"id":470070,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016wr019993","text":"Publisher Index Page"},{"id":335451,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"53","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-12","publicationStatus":"PW","scienceBaseUri":"58a576bae4b057081a24ed19","contributors":{"authors":[{"text":"Read, Emily K. 0000-0002-9617-9433 eread@usgs.gov","orcid":"https://orcid.org/0000-0002-9617-9433","contributorId":5815,"corporation":false,"usgs":true,"family":"Read","given":"Emily","email":"eread@usgs.gov","middleInitial":"K.","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true},{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true}],"preferred":false,"id":669232,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carr, Lindsay 0000-0002-5799-6297 lcarr@usgs.gov","orcid":"https://orcid.org/0000-0002-5799-6297","contributorId":181732,"corporation":false,"usgs":true,"family":"Carr","given":"Lindsay","email":"lcarr@usgs.gov","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":669233,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeCicco, Laura A. 0000-0002-3915-9487 ldecicco@usgs.gov","orcid":"https://orcid.org/0000-0002-3915-9487","contributorId":174716,"corporation":false,"usgs":true,"family":"DeCicco","given":"Laura","email":"ldecicco@usgs.gov","middleInitial":"A.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":5054,"text":"Office of Water Information","active":true,"usgs":true},{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true}],"preferred":true,"id":669234,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Dugan, Hilary","contributorId":150191,"corporation":false,"usgs":false,"family":"Dugan","given":"Hilary","affiliations":[{"id":17938,"text":"Center for Limnology University of Wisconsin, Madison, WI 53706, US","active":true,"usgs":false}],"preferred":false,"id":669235,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hanson, Paul C.","contributorId":35634,"corporation":false,"usgs":false,"family":"Hanson","given":"Paul","email":"","middleInitial":"C.","affiliations":[{"id":12951,"text":"Center for Limnology, University of Wisconsin Madison","active":true,"usgs":false}],"preferred":false,"id":669236,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hart, Julia A. 0000-0002-0183-8070","orcid":"https://orcid.org/0000-0002-0183-8070","contributorId":181733,"corporation":false,"usgs":false,"family":"Hart","given":"Julia","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":669237,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kreft, James 0000-0001-8088-7788 jkreft@usgs.gov","orcid":"https://orcid.org/0000-0001-8088-7788","contributorId":181734,"corporation":false,"usgs":true,"family":"Kreft","given":"James","email":"jkreft@usgs.gov","affiliations":[{"id":37316,"text":"WMA - Integrated Information Dissemination Division","active":true,"usgs":true}],"preferred":true,"id":669238,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Read, Jordan S. 0000-0002-3888-6631 jread@usgs.gov","orcid":"https://orcid.org/0000-0002-3888-6631","contributorId":4453,"corporation":false,"usgs":true,"family":"Read","given":"Jordan","email":"jread@usgs.gov","middleInitial":"S.","affiliations":[{"id":5054,"text":"Office of Water Information","active":true,"usgs":true},{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":669239,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Winslow, Luke 0000-0002-8602-5510 lwinslow@usgs.gov","orcid":"https://orcid.org/0000-0002-8602-5510","contributorId":168947,"corporation":false,"usgs":true,"family":"Winslow","given":"Luke","email":"lwinslow@usgs.gov","affiliations":[{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true},{"id":5054,"text":"Office of Water Information","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":true,"id":669240,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70182044,"text":"70182044 - 2017 - Aridity increases below-ground niche breadth in grass communities","interactions":[],"lastModifiedDate":"2017-03-22T14:47:13","indexId":"70182044","displayToPublicDate":"2017-02-15T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3086,"text":"Plant Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Aridity increases below-ground niche breadth in grass communities","docAbstract":"Aridity is an important environmental filter in the assembly of plant communities worldwide. The extent to which root traits mediate responses to aridity, and how they are coordinated with leaf traits, remains unclear. Here, we measured variation in root tissue density (RTD), specific root length (SRL), specific leaf area (SLA), and seed size within and among thirty perennial grass communities distributed along an aridity gradient spanning 190–540 mm of climatic water deficit (potential minus actual evapotranspiration). We tested the hypotheses that traits exhibited coordinated variation (1) among species, as well as (2) among communities varying in aridity, and (3) functional diversity within communities declines with increasing aridity, consistent with the “stress-dominance” hypothesis. Across communities, SLA and RTD exhibited a coordinated response to aridity, shifting toward more conservative (lower SLA, higher RTD) functional strategies with increasing aridity. The response of SRL to aridity was more idiosyncratic and was independent of variation in SLA and RTD. Contrary to the stress-dominance hypothesis, the diversity of SRL values within communities increased with aridity, while none of the other traits exhibited significant diversity responses. These results are consistent with other studies that have found SRL to be independent of an SLA–RTD axis of functional variation and suggest that the dynamic nature of soil moisture in arid environments may facilitate a wider array of resource capture strategies associated with variation in SRL.
","language":"English","publisher":"Springer","doi":"10.1007/s11258-016-0696-4","usgsCitation":"Butterfield, B.J., Bradford, J.B., Munson, S.M., and Gremer, J., 2017, Aridity increases below-ground niche breadth in grass communities: Plant Ecology, v. 218, no. 4, p. 385-394, https://doi.org/10.1007/s11258-016-0696-4.","productDescription":"9 p.","startPage":"385","endPage":"394","ipdsId":"IP-081529","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":335626,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"218","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-06","publicationStatus":"PW","scienceBaseUri":"58a576b9e4b057081a24ed10","chorus":{"doi":"10.1007/s11258-016-0696-4","url":"http://dx.doi.org/10.1007/s11258-016-0696-4","publisher":"Springer Nature","authors":"Butterfield Bradley J., Bradford John B., Munson Seth M., Gremer Jennifer R.","journalName":"Plant Ecology","publicationDate":"1/6/2017","auditedOn":"2/15/2017","publiclyAccessibleDate":"1/6/2017"},"contributors":{"authors":[{"text":"Butterfield, Bradley J. 0000-0003-0974-9811","orcid":"https://orcid.org/0000-0003-0974-9811","contributorId":167009,"corporation":false,"usgs":false,"family":"Butterfield","given":"Bradley","email":"","middleInitial":"J.","affiliations":[{"id":24591,"text":"Merriam-Powell Center for Environmental Research and Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, USA","active":true,"usgs":false}],"preferred":false,"id":669369,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bradford, John B. 0000-0001-9257-6303 jbradford@usgs.gov","orcid":"https://orcid.org/0000-0001-9257-6303","contributorId":611,"corporation":false,"usgs":true,"family":"Bradford","given":"John","email":"jbradford@usgs.gov","middleInitial":"B.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":669367,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Munson, Seth M. 0000-0002-2736-6374 smunson@usgs.gov","orcid":"https://orcid.org/0000-0002-2736-6374","contributorId":1334,"corporation":false,"usgs":true,"family":"Munson","given":"Seth","email":"smunson@usgs.gov","middleInitial":"M.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":669368,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gremer, Jennifer R.","contributorId":181751,"corporation":false,"usgs":false,"family":"Gremer","given":"Jennifer R.","affiliations":[],"preferred":false,"id":669370,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70176352,"text":"70176352 - 2017 - Lithological influences on contemporary and long-term regolith weathering at the Luquillo Critical Zone Observatory","interactions":[],"lastModifiedDate":"2020-12-16T17:00:43.828181","indexId":"70176352","displayToPublicDate":"2017-02-15T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1759,"text":"Geochimica et Cosmochimica Acta","active":true,"publicationSubtype":{"id":10}},"title":"Lithological influences on contemporary and long-term regolith weathering at the Luquillo Critical Zone Observatory","docAbstract":"Lithologic differences give rise to the differential weatherability of the Earth’s surface and globally variable silicate weathering fluxes, which provide an important negative feedback on climate over geologic timescales. To isolate the influence of lithology on weathering rates and mechanisms, we compare two nearby catchments in the Luquillo Critical Zone Observatory in Puerto Rico, which have similar climate history, relief and vegetation, but differ in bedrock lithology. Regolith and pore water samples with depth were collected from two ridgetops and at three sites along a slope transect in the volcaniclastic Bisley catchment and compared to existing data from the granitic Río Icacos catchment. The depth variations of solid-state and pore water chemistry and quantitative mineralogy were used to calculate mass transfer (tau) and weathering solute profiles, which in turn were used to determine weathering mechanisms and to estimate weathering rates.
Regolith formed on both lithologies is highly leached of most labile elements, although Mg and K are less depleted in the granitic than in the volcaniclastic profiles, reflecting residual biotite in the granitic regolith not present in the volcaniclastics. Profiles of both lithologies that terminate at bedrock corestones are less weathered at depth, near the rock-regolith interfaces. Mg fluxes in the volcaniclastics derive primarily from dissolution of chlorite near the rock-regolith interface and from dissolution of illite and secondary phases in the upper regolith, whereas in the granitic profile, Mg and K fluxes derive from biotite dissolution. Long-term mineral dissolution rates and weathering fluxes were determined by integrating mass losses over the thickness of solid-state weathering fronts, and are therefore averages over the timescale of regolith development. Resulting long-term dissolution rates for minerals in the volcaniclastic regolith include chlorite: 8.9 × 10−14 mol m−2 s−1, illite: 2.1 × 10−14 mol m−2 s−1 and kaolinite: 4.0 × 10−14 mol m−2 s−1. Long-term weathering fluxes are several orders of magnitude lower in the granitic regolith than in the volcaniclastic, despite higher abundances of several elements in the granitic regolith. Contemporary weathering fluxes were determined from net (rain-corrected) solute profiles and thus represent rates over the residence time of water in the regolith. Contemporary weathering fluxes within the granitic regolith are similar to the long-term fluxes. In contrast, the long-term fluxes are faster than the contemporary fluxes in the volcaniclastic regolith. Contemporary fluxes in the granitic regolith are generally also slightly faster than in the volcaniclastic. The differences in weathering fluxes over space and time between these two watersheds indicate significant lithologic control of chemical weathering mechanisms and rates.
","language":"English","publisher":"Geochemical Society, Meteoritical Society","publisherLocation":"Amsterdam","doi":"10.1016/j.gca.2016.09.038","usgsCitation":"Buss, H.L., Lara, M.C., Moore, O., Kurtz, A.C., Schulz, M., and White, A.F., 2017, Lithological influences on contemporary and long-term regolith weathering at the Luquillo Critical Zone Observatory: Geochimica et Cosmochimica Acta, v. 196, p. 224-251, https://doi.org/10.1016/j.gca.2016.09.038.","productDescription":"28 p.","startPage":"224","endPage":"251","ipdsId":"IP-072854","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":470071,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://hdl.handle.net/1983/931dd02e-8852-4ce1-9deb-527305408c12","text":"Publisher Index Page"},{"id":335558,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Puerto Rico","otherGeospatial":"Bisley watersheds","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -65.75,\n 18.333333\n ],\n [\n -65.733333,\n 18.333333\n ],\n [\n -65.733333,\n 18.3\n ],\n [\n -65.75,\n 18.3\n ],\n [\n -65.75,\n 18.333333\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"196","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58a576bbe4b057081a24ed1c","contributors":{"authors":[{"text":"Buss, Heather L. 0000-0002-1852-3657","orcid":"https://orcid.org/0000-0002-1852-3657","contributorId":15478,"corporation":false,"usgs":true,"family":"Buss","given":"Heather","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":648469,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lara, Maria Chapela","contributorId":174514,"corporation":false,"usgs":false,"family":"Lara","given":"Maria","email":"","middleInitial":"Chapela","affiliations":[{"id":7172,"text":"University of Bristol, U.K. and University of Oregon, Eugene","active":true,"usgs":false}],"preferred":false,"id":648470,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moore, Oliver","contributorId":174515,"corporation":false,"usgs":false,"family":"Moore","given":"Oliver","email":"","affiliations":[{"id":7172,"text":"University of Bristol, U.K. and University of Oregon, Eugene","active":true,"usgs":false}],"preferred":false,"id":648471,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kurtz, Andrew C.","contributorId":174516,"corporation":false,"usgs":false,"family":"Kurtz","given":"Andrew","email":"","middleInitial":"C.","affiliations":[{"id":13570,"text":"Boston University","active":true,"usgs":false}],"preferred":false,"id":648472,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schulz, Marjorie S. 0000-0001-5597-6447 mschulz@usgs.gov","orcid":"https://orcid.org/0000-0001-5597-6447","contributorId":3720,"corporation":false,"usgs":true,"family":"Schulz","given":"Marjorie S.","email":"mschulz@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":648468,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"White, Arthur F. afwhite@usgs.gov","contributorId":3718,"corporation":false,"usgs":true,"family":"White","given":"Arthur","email":"afwhite@usgs.gov","middleInitial":"F.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":648473,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70178565,"text":"70178565 - 2017 - Preferential flow, diffuse flow, and perching in an interbedded fractured-rock unsaturated zone","interactions":[],"lastModifiedDate":"2017-02-24T10:34:07","indexId":"70178565","displayToPublicDate":"2017-02-15T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1923,"text":"Hydrogeology Journal","active":true,"publicationSubtype":{"id":10}},"title":"Preferential flow, diffuse flow, and perching in an interbedded fractured-rock unsaturated zone","docAbstract":"Layers of strong geologic contrast within the unsaturated zone can control recharge and contaminant transport to underlying aquifers. Slow diffuse flow in certain geologic layers, and rapid preferential flow in others, complicates the prediction of vertical and lateral fluxes. A simple model is presented, designed to use limited geological site information to predict these critical subsurface processes in response to a sustained infiltration source. The model is developed and tested using site-specific information from the Idaho National Laboratory in the Eastern Snake River Plain (ESRP), USA, where there are natural and anthropogenic sources of high-volume infiltration from floods, spills, leaks, wastewater disposal, retention ponds, and hydrologic field experiments. The thick unsaturated zone overlying the ESRP aquifer is a good example of a sharply stratified unsaturated zone. Sedimentary interbeds are interspersed between massive and fractured basalt units. The combination of surficial sediments, basalts, and interbeds determines the water fluxes through the variably saturated subsurface. Interbeds are generally less conductive, sometimes causing perched water to collect above them. The model successfully predicts the volume and extent of perching and approximates vertical travel times during events that generate high fluxes from the land surface. These developments are applicable to sites having a thick, geologically complex unsaturated zone of substantial thickness in which preferential and diffuse flow, and perching of percolated water, are important to contaminant transport or aquifer recharge.
","language":"English","publisher":"Springer","doi":"10.1007/s10040-016-1496-6","usgsCitation":"Nimmo, J.R., Creasey, K.M., Perkins, K., and Mirus, B.B., 2017, Preferential flow, diffuse flow, and perching in an interbedded fractured-rock unsaturated zone: Hydrogeology Journal, v. 25, no. 2, p. 421-444, https://doi.org/10.1007/s10040-016-1496-6.","productDescription":"24 p.","startPage":"421","endPage":"444","ipdsId":"IP-065100","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":335550,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Eastern Snake River Plain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.333333,\n 44.083333\n ],\n [\n -112.333333,\n 44.083333\n ],\n [\n -112.333333,\n 43.25\n ],\n [\n -113.333333,\n 43.25\n ],\n [\n -113.333333,\n 44.083333\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"25","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-26","publicationStatus":"PW","scienceBaseUri":"58a576bee4b057081a24ed30","contributors":{"authors":[{"text":"Nimmo, John R. 0000-0001-8191-1727 jrnimmo@usgs.gov","orcid":"https://orcid.org/0000-0001-8191-1727","contributorId":757,"corporation":false,"usgs":true,"family":"Nimmo","given":"John","email":"jrnimmo@usgs.gov","middleInitial":"R.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":654384,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Creasey, Kaitlyn M kcreasey@usgs.gov","contributorId":5799,"corporation":false,"usgs":true,"family":"Creasey","given":"Kaitlyn","email":"kcreasey@usgs.gov","middleInitial":"M","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":654385,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Perkins, Kimberlie 0000-0001-8349-447X kperkins@usgs.gov","orcid":"https://orcid.org/0000-0001-8349-447X","contributorId":138544,"corporation":false,"usgs":true,"family":"Perkins","given":"Kimberlie","email":"kperkins@usgs.gov","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":654386,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mirus, Benjamin B. 0000-0001-5550-014X bbmirus@usgs.gov","orcid":"https://orcid.org/0000-0001-5550-014X","contributorId":4064,"corporation":false,"usgs":true,"family":"Mirus","given":"Benjamin","email":"bbmirus@usgs.gov","middleInitial":"B.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":5077,"text":"Northwest Regional Director's Office","active":true,"usgs":true},{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true}],"preferred":true,"id":654387,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70195966,"text":"70195966 - 2017 - Enhanced coal-dependent methanogenesis coupled with algal biofuels: Potential water recycle and carbon capture","interactions":[],"lastModifiedDate":"2018-03-09T15:29:45","indexId":"70195966","displayToPublicDate":"2017-02-15T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2033,"text":"International Journal of Coal Geology","active":true,"publicationSubtype":{"id":10}},"title":"Enhanced coal-dependent methanogenesis coupled with algal biofuels: Potential water recycle and carbon capture","docAbstract":"Many coal beds contain microbial communities that can convert coal to natural gas (coalbed methane). Native microorganisms were obtained from Powder River Basin (PRB) coal seams with a diffusive microbial sampler placed downhole and used as an inoculum for enrichments with different nutrients to investigate microbially-enhanced coalbed methane production (MECoM). Coal-dependent methanogenesis more than doubled when yeast extract (YE) and several less complex components (proteins and amino acids) were added to the laboratory microcosms. Stimulated coal-dependent methanogenesis with peptone was 86% of that with YE while glutamate-stimulated activity was 65% of that with YE, and a vitamin mix had only 33% of the YE stimulated activity. For field application of MECoM, there is interest in identifying cost-effective alternatives to YE and other expensive nutrients. In laboratory studies, adding algal extract (AE) with lipids removed stimulated coal-dependent methanogenesis and the activity was 60% of that with YE at 27 d and almost 90% of YE activity at 1406 d. Analysis of British Thermal Unit (BTU) content of coal (a measure of potential energy yield) from long-term incubations indicated > 99.5% of BTU content remained after coalbed methane (CBM) stimulation with either AE or YE. Thus, the coal resource remains largely unchanged following stimulated microbial methane production. Algal CBM stimulation could lead to technologies that utilize coupled biological systems (photosynthesis and methane production) that sustainably enhance CBM production and generate algal biofuels while also sequestering carbon dioxide (CO2).
","language":"English","publisher":"Elsevier","doi":"10.1016/j.coal.2017.01.001","usgsCitation":"Barnhart, E.P., Davis, K.J., Varonka, M., Orem, W.H., Cunningham, A.B., Ramsay, B.D., and Fields, M.W., 2017, Enhanced coal-dependent methanogenesis coupled with algal biofuels: Potential water recycle and carbon capture: International Journal of Coal Geology, v. 171, p. 69-75, https://doi.org/10.1016/j.coal.2017.01.001.","productDescription":"7 p.","startPage":"69","endPage":"75","ipdsId":"IP-060264","costCenters":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"links":[{"id":461731,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.coal.2017.01.001","text":"Publisher Index Page"},{"id":352385,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"171","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afee8d3e4b0da30c1bfc4b4","contributors":{"authors":[{"text":"Barnhart, Elliott P. 0000-0002-8788-8393 epbarnhart@usgs.gov","orcid":"https://orcid.org/0000-0002-8788-8393","contributorId":5385,"corporation":false,"usgs":true,"family":"Barnhart","given":"Elliott","email":"epbarnhart@usgs.gov","middleInitial":"P.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":730713,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Davis, Katherine J.","contributorId":203246,"corporation":false,"usgs":false,"family":"Davis","given":"Katherine","email":"","middleInitial":"J.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":730714,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Varonka, Matthew S. 0000-0003-3620-5262","orcid":"https://orcid.org/0000-0003-3620-5262","contributorId":203231,"corporation":false,"usgs":true,"family":"Varonka","given":"Matthew S.","affiliations":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":730715,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Orem, William H. 0000-0003-4990-0539 borem@usgs.gov","orcid":"https://orcid.org/0000-0003-4990-0539","contributorId":577,"corporation":false,"usgs":true,"family":"Orem","given":"William","email":"borem@usgs.gov","middleInitial":"H.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":730716,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cunningham, Alfred B.","contributorId":172389,"corporation":false,"usgs":false,"family":"Cunningham","given":"Alfred","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":730717,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ramsay, Bradley D.","contributorId":203232,"corporation":false,"usgs":false,"family":"Ramsay","given":"Bradley","email":"","middleInitial":"D.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":730718,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Fields, Matthew W.","contributorId":172391,"corporation":false,"usgs":false,"family":"Fields","given":"Matthew","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":730719,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70181778,"text":"70181778 - 2017 - Reconciling catch differences from multiple fishery independent gill net surveys","interactions":[],"lastModifiedDate":"2017-02-14T10:41:06","indexId":"70181778","displayToPublicDate":"2017-02-14T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1661,"text":"Fisheries Research","active":true,"publicationSubtype":{"id":10}},"title":"Reconciling catch differences from multiple fishery independent gill net surveys","docAbstract":"Fishery independent gill net surveys provide valuable demographic information for population assessment and resource management, but relative to net construction, the effects of ancillary species, and environmental variables on focal species catch rates are poorly understood. In response, we conducted comparative deployments with three unique, inter-agency, survey gill nets used to assess walleye Sander vitreus in Lake Erie. We used an information-theoretic approach with Akaike’s second-order information criterion (AICc) to evaluate linear mixed models of walleye catch as a function of net type (multifilament and two types of monofilament netting), mesh size (categorical), Secchi depth, temperature, water depth, catch of ancillary species, and interactions among selected variables. The model with the greatest weight of evidence showed that walleye catches were positively associated with potential prey and intra-guild predators and negatively associated with water depth and temperature. In addition, the multifilament net had higher average walleye catches than either of the two monofilament nets. Results from this study both help inform decisions about proposed gear changes to stock assessment surveys in Lake Erie, and advance our understanding of how multispecies associations explain variation in gill net catches. Of broader interest to fishery-independent gill net studies, effects of abiotic variables and ancillary species on focal specie’s catch rates were small in comparison with net characteristics of mesh size or twine type.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.fishres.2016.12.004","usgsCitation":"Kraus, R.T., Vandergoot, C., Kocovsky, P.M., Rogers, M.W., Cook, H., and Brenden, T.O., 2017, Reconciling catch differences from multiple fishery independent gill net surveys: Fisheries Research, v. 188, p. 17-22, https://doi.org/10.1016/j.fishres.2016.12.004.","productDescription":"6 p.","startPage":"17","endPage":"22","ipdsId":"IP-069874","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":470072,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.fishres.2016.12.004","text":"Publisher Index Page"},{"id":438437,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F75D8Q1G","text":"USGS data release","linkHelpText":"Gill net catch data in Lake Erie, 2010-2013"},{"id":335324,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Lake Erie","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.5078125,\n 42.581399679665054\n ],\n [\n -80.71105957031249,\n 42.66628070564928\n ],\n [\n -80.947265625,\n 42.69051116998238\n ],\n [\n -81.3262939453125,\n 42.67839711889055\n ],\n [\n -81.6558837890625,\n 42.53689200787315\n ],\n [\n -82.37548828125,\n 42.17561739661684\n ],\n [\n -82.84790039062499,\n 42.020732852644294\n ],\n [\n -83.133544921875,\n 42.13082130188811\n ],\n [\n -83.4027099609375,\n 41.92680320648791\n ],\n [\n -83.5235595703125,\n 41.68932225997044\n ],\n [\n -83.045654296875,\n 41.43449030894922\n ],\n [\n -82.529296875,\n 41.36444153054222\n ],\n [\n -81.749267578125,\n 41.46742831254425\n ],\n [\n -80.5352783203125,\n 41.97174336327968\n ],\n [\n -80.5078125,\n 42.581399679665054\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"188","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58a4252be4b0c825128ad3ea","contributors":{"authors":[{"text":"Kraus, Richard T. 0000-0003-4494-1841 rkraus@usgs.gov","orcid":"https://orcid.org/0000-0003-4494-1841","contributorId":2609,"corporation":false,"usgs":true,"family":"Kraus","given":"Richard","email":"rkraus@usgs.gov","middleInitial":"T.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":668497,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vandergoot, Christopher 0000-0003-4128-3329 cvandergoot@usgs.gov","orcid":"https://orcid.org/0000-0003-4128-3329","contributorId":178356,"corporation":false,"usgs":true,"family":"Vandergoot","given":"Christopher","email":"cvandergoot@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":668498,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kocovsky, Patrick M. 0000-0003-4325-4265 pkocovsky@usgs.gov","orcid":"https://orcid.org/0000-0003-4325-4265","contributorId":3429,"corporation":false,"usgs":true,"family":"Kocovsky","given":"Patrick","email":"pkocovsky@usgs.gov","middleInitial":"M.","affiliations":[{"id":251,"text":"Ecosystems Mission Area","active":false,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":668499,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rogers, Mark W. 0000-0001-7205-5623 mwrogers@usgs.gov","orcid":"https://orcid.org/0000-0001-7205-5623","contributorId":4590,"corporation":false,"usgs":true,"family":"Rogers","given":"Mark","email":"mwrogers@usgs.gov","middleInitial":"W.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":668500,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cook, H. 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Pelinovsky and C. Kharif, second edition, Springer International Publishing, 2016; ISBN: 978-3-319-21574-7, ISBN (eBook): 978-3-319-21575-4
The second edition of “Extreme Ocean Waves” published by Springer is an update of a collection of 12 papers edited by Efim Pelinovsky and Christian Kharif following the April 2007 meeting of the General Assembly of the European Geosciences Union. In this edition, three new papers have been added and three more have been substantially revised. Color figures are now included, which greatly aids in reading several of the papers, and is especially helpful in visualizing graphs as in the paper on symbolic computation of nonlinear wave resonance (Tobisch et al.). A note on terminology: extreme waves in this volume broadly encompass different types of waves, including deep-water and shallow-water rogue waves (which are alternatively termed freak waves), and internal waves. One new paper on tsunamis (Viroulet et al.) is now included in the second edition of this volume. Throughout the book, the reader will find a combination of laboratory, theoretical, and statistical/empirical treatment necessary for the complete examination of this subject. In the Introduction, the editors underscore the importance of studying extreme waves, documenting a dramatic instance of damaging extreme waves that recently occurred in 2014.
","language":"English","publisher":"Springer","doi":"10.1007/s00024-017-1486-1","usgsCitation":"Geist, E.L., 2017, Book review: Extreme ocean waves: Pure and Applied Geophysics, v. 174, no. 3, p. 1519-1519, https://doi.org/10.1007/s00024-017-1486-1.","productDescription":"1 p.","startPage":"1519","endPage":"1519","ipdsId":"IP-082925","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":461749,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00024-017-1486-1","text":"Publisher Index Page"},{"id":335395,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"174","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-13","publicationStatus":"PW","scienceBaseUri":"58a42528e4b0c825128ad3e0","contributors":{"authors":[{"text":"Geist, Eric L. 0000-0003-0611-1150 egeist@usgs.gov","orcid":"https://orcid.org/0000-0003-0611-1150","contributorId":1956,"corporation":false,"usgs":true,"family":"Geist","given":"Eric","email":"egeist@usgs.gov","middleInitial":"L.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":668643,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70181760,"text":"70181760 - 2017 - Climate change and the eco-hydrology of fire: Will area burned increase in a warming western USA?","interactions":[],"lastModifiedDate":"2017-02-13T15:58:32","indexId":"70181760","displayToPublicDate":"2017-02-13T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1450,"text":"Ecological Applications","active":true,"publicationSubtype":{"id":10}},"title":"Climate change and the eco-hydrology of fire: Will area burned increase in a warming western USA?","docAbstract":"Wildfire area is predicted to increase with global warming. Empirical statistical models and process-based simulations agree almost universally. The key relationship for this unanimity, observed at multiple spatial and temporal scales, is between drought and fire. Predictive models often focus on ecosystems in which this relationship appears to be particularly strong, such as mesic and arid forests and shrublands with substantial biomass such as chaparral. We examine the drought–fire relationship, specifically the correlations between water-balance deficit and annual area burned, across the full gradient of deficit in the western USA, from temperate rainforest to desert. In the middle of this gradient, conditional on vegetation (fuels), correlations are strong, but outside this range the equivalence hotter and drier equals more fire either breaks down or is contingent on other factors such as previous-year climate. This suggests that the regional drought–fire dynamic will not be stationary in future climate, nor will other more complex contingencies associated with the variation in fire extent. Predictions of future wildfire area therefore need to consider not only vegetation changes, as some dynamic vegetation models now do, but also potential changes in the drought–fire dynamic that will ensue in a warming climate.
","language":"English","publisher":"Ecological Society of America","publisherLocation":"Washington, D.C.","doi":"10.1002/eap.1420","usgsCitation":"McKenzie, D., and Littell, J.S., 2017, Climate change and the eco-hydrology of fire: Will area burned increase in a warming western USA?: Ecological Applications, v. 27, no. 1, p. 26-36, https://doi.org/10.1002/eap.1420.","productDescription":"11 p.","startPage":"26","endPage":"36","ipdsId":"IP-073768","costCenters":[{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true}],"links":[{"id":335295,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Western United 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\"}}]}","volume":"27","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-12-21","publicationStatus":"PW","scienceBaseUri":"58a2d3abe4b0c825128699e9","contributors":{"authors":[{"text":"McKenzie, Donald","contributorId":181509,"corporation":false,"usgs":false,"family":"McKenzie","given":"Donald","affiliations":[],"preferred":false,"id":668427,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Littell, Jeremy S. 0000-0002-5302-8280 jlittell@usgs.gov","orcid":"https://orcid.org/0000-0002-5302-8280","contributorId":4428,"corporation":false,"usgs":true,"family":"Littell","given":"Jeremy","email":"jlittell@usgs.gov","middleInitial":"S.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":668426,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70181753,"text":"70181753 - 2017 - Using management to address vegetation stress related to land-use and climate change","interactions":[],"lastModifiedDate":"2017-05-24T10:41:44","indexId":"70181753","displayToPublicDate":"2017-02-13T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3271,"text":"Restoration Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Using management to address vegetation stress related to land-use and climate change","docAbstract":"While disturbances such as fire, cutting, and grazing can be an important part of the conservation of natural lands, some adjustments to management designed to mimic natural disturbance may be necessary with ongoing and projected climate change. Stressed vegetation that is incapable of regeneration will be difficult to maintain if adults are experiencing mortality, and/or if their early life-history stages depend on disturbance. A variety of active management strategies employing disturbance are suggested, including resisting, accommodating, or directing vegetation change by manipulating management intensity and frequency. Particularly if land-use change is the main cause of vegetation stress, amelioration of these problems using management may help vegetation resist change (e.g. strategic timing of water release if a water control structure is available). Managers could direct succession by using management to push vegetation toward a new state. Despite the historical effects of management, some vegetation change will not be controllable as climates shift, and managers may have to accept some of these changes. Nevertheless, proactive measures may help managers achieve important conservation goals in the future.
","language":"English","publisher":"Society for Ecological Restoration","publisherLocation":"Cambridge, MA","doi":"10.1111/rec.12507","usgsCitation":"Middleton, B.A., Boudell, J., and Fisichelli, N., 2017, Using management to address vegetation stress related to land-use and climate change: Restoration Ecology, v. 25, no. 3, p. 326-329, https://doi.org/10.1111/rec.12507.","productDescription":"4 p.","startPage":"326","endPage":"329","ipdsId":"IP-076897","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":335228,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"25","issue":"3","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-06","publicationStatus":"PW","scienceBaseUri":"58a2d3b0e4b0c825128699ef","contributors":{"authors":[{"text":"Middleton, Beth A. 0000-0002-1220-2326 middletonb@usgs.gov","orcid":"https://orcid.org/0000-0002-1220-2326","contributorId":2029,"corporation":false,"usgs":true,"family":"Middleton","given":"Beth","email":"middletonb@usgs.gov","middleInitial":"A.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":668371,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boudell, Jere","contributorId":181496,"corporation":false,"usgs":false,"family":"Boudell","given":"Jere","affiliations":[],"preferred":false,"id":668372,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fisichelli, Nicholas","contributorId":168824,"corporation":false,"usgs":false,"family":"Fisichelli","given":"Nicholas","affiliations":[{"id":25366,"text":"National Park Service, Climate Change Response Program","active":true,"usgs":false}],"preferred":false,"id":668373,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70179367,"text":"sir20165180 - 2017 - Hydrogeology and simulation of groundwater flow and analysis of projected water use for the Canadian River alluvial aquifer, western and central Oklahoma","interactions":[],"lastModifiedDate":"2017-03-27T13:31:09","indexId":"sir20165180","displayToPublicDate":"2017-02-13T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-5180","title":"Hydrogeology and simulation of groundwater flow and analysis of projected water use for the Canadian River alluvial aquifer, western and central Oklahoma","docAbstract":"This report describes a study of the hydrogeology and simulation of groundwater flow for the Canadian River alluvial aquifer in western and central Oklahoma conducted by the U.S. Geological Survey in cooperation with the Oklahoma Water Resources Board. The report (1) quantifies the groundwater resources of the Canadian River alluvial aquifer by developing a conceptual model, (2) summarizes the general water quality of the Canadian River alluvial aquifer groundwater by using data collected during August and September 2013, (3) evaluates the effects of estimated equal proportionate share (EPS) on aquifer storage and streamflow for time periods of 20, 40, and 50 years into the future by using numerical groundwater-flow models, and (4) evaluates the effects of present-day groundwater pumping over a 50-year period and sustained hypothetical drought conditions over a 10-year period on stream base flow and groundwater in storage by using numerical flow models. The Canadian River alluvial aquifer is a Quaternary-age alluvial and terrace unit consisting of beds of clay, silt, sand, and fine gravel sediments unconformably overlying Tertiary-, Permian-, and Pennsylvanian-age sedimentary rocks. For groundwater-flow modeling purposes, the Canadian River was divided into Reach I, extending from the Texas border to the Canadian River at the Bridgeport, Okla., streamgage (07228500), and Reach II, extending downstream from the Canadian River at the Bridgeport, Okla., streamgage (07228500), to the confluence of the river with Eufaula Lake. The Canadian River alluvial aquifer spans multiple climate divisions, ranging from semiarid in the west to humid subtropical in the east. The average annual precipitation in the study area from 1896 to 2014 was 34.4 inches per year (in/yr).
A hydrogeologic framework of the Canadian River alluvial aquifer was developed that includes the areal and vertical extent of the aquifer and the distribution, texture variability, and hydraulic properties of aquifer materials. The aquifer areal extent ranged from less than 0.2 to
8.5 miles wide. The maximum aquifer thickness was 120 feet (ft), and the average aquifer thickness was 50 ft. Average horizontal hydraulic conductivity for the Canadian River alluvial aquifer was calculated to be 39 feet per day, and the maximum horizontal hydraulic conductivity was calculated to be 100 feet per day.
Recharge rates to the Canadian River alluvial aquifer were estimated by using a soil-water-balance code to estimate the spatial distribution of groundwater recharge and a water-table fluctuation method to estimate localized recharge rates. By using daily precipitation and temperature data from 39 climate stations, recharge was estimated to average 3.4 in/yr, which corresponds to 8.7 percent of precipitation as recharge for the Canadian River alluvial aquifer from 1981 to 2013. The water-table fluctuation method was used at one site where continuous water-level observation data were available to estimate the percentage of precipitation that becomes groundwater recharge. Estimated annual recharge at that site was 9.7 in/yr during 2014.
Groundwater flow in the Canadian River alluvial aquifer was identified and quantified by a conceptual flow model for the period 1981–2013. Inflows to the Canadian River alluvial aquifer include recharge to the water table from precipitation, lateral flow from the surrounding bedrock, and flow from the Canadian River, whereas outflows include flow to the Canadian River (base-flow gain), evapotranspiration, and groundwater use. Total annual recharge inflows estimated by the soil-water-balance code were multiplied by the area of each reach and then averaged over the simulated period to produce an annual average of 28,919 acre-feet per year (acre-ft/yr) for Reach I and 82,006 acre-ft/yr for Reach II. Stream base flow to the Canadian River was estimated to be the largest outflow of groundwater from the aquifer, measured at four streamgages, along with evapotranspiration and groundwater use, which were relatively minor discharge components.
Objectives for the numerical groundwater-flow models included simulating groundwater flow in the Canadian River alluvial aquifer from 1981 to 2013 to address groundwater use and drought scenarios, including calculation of the EPS pumping rates. The EPS for the alluvial and terrace aquifers is defined by the Oklahoma Water Resources Board as the amount of fresh water that each landowner is allowed per year per acre of owned land to maintain a saturated thickness of at least 5 ft in at least 50 percent of the overlying land of the groundwater basin for a minimum of 20 years.
The groundwater-flow models were calibrated to water-table altitude observations, streamgage base flows, and base-flow gain to the Canadian River. The Reach I water-table altitude observation root-mean-square error was 6.1 ft, and 75 percent of residuals were within ±6.7 ft of observed measurements. The average simulated stream base-flow residual at the Bridgeport streamgage (07228500) was 8.8 cubic feet per second (ft3/s), and 75 percent of residuals were within ±30 ft3/s of observed measurements. Simulated base-flow gain in Reach I was 8.8 ft3/s lower than estimated base-flow gain. The Reach II water-table altitude observation root-mean-square error was 4 ft, and 75 percent of residuals were within ±4.3 ft of the observations. The average simulated stream base-flow residual in Reach II was between 35 and 132 ft3/s. The average simulated base-flow gain residual in Reach II was between 11.3 and 61.1 ft3/s.
Several future predictive scenarios were run, including estimating the EPS pumping rate for 20-, 40-, and 50-year life of basin scenarios, determining the effects of current groundwater use over a 50-year period into the future, and evaluating the effects of a sustained drought on water availability for both reaches. The EPS pumping rate was determined to be 1.35 acre-feet per acre per year ([acre-ft/acre]/yr) in Reach I and 3.08 (acre-ft/acre)/yr in Reach II for a 20-year period. For the 40- and 50-year periods, the EPS rate was determined to be
1.34 (acre-ft/acre)/yr in Reach I and 3.08 (acre-ft/acre)/yr in Reach II. Storage changes decreased in tandem with simulated groundwater pumping and were minimal after the first 15 simulated years for Reach I and the first 8 simulated years for Reach II.
Groundwater pumping at year 2013 rates for a period of 50 years resulted in a 0.2-percent decrease in groundwater-storage volumes in Reach I and a 0.6-percent decrease in the groundwater-storage volumes in Reach II. The small changes in storage are due to groundwater use by pumping, which composes a small percentage of the total groundwater-flow model budgets for Reaches I and II.
A sustained drought scenario was used to evaluate the effects of a hypothetical 10-year drought on water availability. A 10-year period was chosen where the effects of drought conditions would be simulated by decreasing recharge by 75 percent. In Reach I, average simulated stream base flow at the Bridgeport streamgage (07228500) decreased by 58 percent during the hypothetical 10-year drought compared to average simulated stream base flow during the nondrought period. In Reach II, average simulated stream base flows at the Purcell streamgage (07229200) and Calvin streamgage (07231500) decreased by 64 percent and 54 percent, respectively. In Reach I, the groundwater-storage drought scenario resulted in a storage decline of 30 thousand acre-feet, or an average decline in the water table of
1.2 ft. In Reach II, the groundwater-storage drought scenario resulted in a storage decline of 71 thousand acre-feet, or an average decline in the water table of 2.0 ft.
Director, Oklahoma Water Science Center
U.S. Geological Survey
202 NW 66th, Bldg 7
Oklahoma City, OK 73116
Shawnee Reservoir (locally known as Shawnee Twin Lakes) is a man-made reservoir on South Deer Creek with a drainage area of 32.7 square miles in Pottawatomie County, Oklahoma. The reservoir consists of two lakes connected by an equilibrium channel. The southern lake (Shawnee City Lake Number 1) was impounded in 1935, and the northern lake (Shawnee City Lake Number 2) was impounded in 1960. Shawnee Reservoir serves as a municipal water supply, and water is transferred about 9 miles by gravity to a water treatment plant in Shawnee, Oklahoma. Secondary uses of the reservoir are for recreation, fish and wildlife habitat, and flood control. Shawnee Reservoir has a normal-pool elevation of 1,069.0 feet (ft) above North American Vertical Datum of 1988 (NAVD 88). The auxiliary spillway, which defines the flood-pool elevation, is at an elevation of 1,075.0 ft.
The U.S. Geological Survey (USGS), in cooperation with the City of Shawnee, has operated a real-time stage (water-surface elevation) gage (USGS station 07241600) at Shawnee Reservoir since 2006. For the period of record ending in 2016, this gage recorded a maximum stage of 1,078.1 ft on May 24, 2015, and a minimum stage of 1,059.1 ft on April 10–11, 2007. This gage did not report reservoir storage prior to this report (2016) because a sufficiently detailed and thoroughly documented bathymetric (reservoir-bottom elevation) survey and corresponding stage-storage relation had not been published. A 2011 bathymetric survey with contours delineated at 5-foot intervals was published in Oklahoma Water Resources Board (2016), but that publication did not include a stage-storage relation table. The USGS, in cooperation with the City of Shawnee, performed a bathymetric survey of Shawnee Reservoir in 2016 and released the bathymetric-survey data in 2017. The purposes of the bathymetric survey were to (1) develop a detailed bathymetric map of the reservoir and (2) determine the relations between stage and reservoir storage capacity and between stage and reservoir surface area. The bathymetric map may serve as a baseline to which temporal changes in storage capacity, due to sedimentation and other factors, can be compared. The stage-storage relation may be used in the reporting of real-time Shawnee Reservoir storage capacity at USGS station 07241600 to support water-resource management decisions by the City of Shawnee.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3374","collaboration":"Prepared in cooperation with the City of Shawnee","usgsCitation":"Ashworth, C.E., Smith, S.J., and Smith, K.A., 2017, Bathymetry and capacity of Shawnee Reservoir, Oklahoma, 2016: U.S. Geological Survey Scientific Investigations Map 3374, 1 sheet, https://doi.org/10.3133/sim3374.","productDescription":"Sheet: 42.0 x 36.0 inches; Data Release","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-080842","costCenters":[{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"links":[{"id":335148,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3374/coverthb.jpg"},{"id":335150,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F72805SC","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"Bathymetry and Capacity of Shawnee Reservoir, Oklahoma, 2016"},{"id":335149,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3374/sim3374.pdf","text":"Map","size":"4.48 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3374"}],"country":"United States","state":"Oklahoma","otherGeospatial":"Shawnee reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.125,\n 35.372222\n ],\n [\n -97.125,\n 35.302778\n ],\n [\n -97.052778,\n 35.302778\n ],\n [\n -97.052778,\n 35.372222\n ],\n [\n -97.125,\n 35.372222\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oklahoma Water Science Center
U.S. Geological Survey
202 NW 66th, Bldg 7
Oklahoma City, OK 73116