This study explored how factors, including the function of bag limits, agency trust, satisfaction, hunting participation, and demographics, related to opinions about duck bag limits. The results are from a survey of 2014 Minnesota resident waterfowl hunters. Analyses identified four dimensions of attitudes about functions of bag limits, including that they: (a) are descriptive in defining the acceptable number of ducks that can be bagged, (b) are injunctive in establishing how many ducks should be allowed to be bagged, (c) ensure fair opportunities for all hunters to bag ducks, and (d) reflect biological limitations to protect waterfowl populations. Descriptive and fairness functions of bag limits were related to opinions about bag limits, as were factors related to agency trust, satisfaction, ducks bagged, experience with more restrictive bag limits, hunter age, and hunting group membership. Agencies may increase support by building trust and emphasizing the descriptive and fairness functions of regulations.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/10871209.2017.1345021","usgsCitation":"Schroeder, S., Fulton, D.C., Lawrence, J.S., and Cordts, S.D., 2017, How hunter perceptions of wildlife regulations, agency trust, and satisfaction affect attitudes about duck bag limits: Human Dimensions of Wildlife, v. 22, no. 5, p. 454-475, https://doi.org/10.1080/10871209.2017.1345021.","productDescription":"22 p.","startPage":"454","endPage":"475","ipdsId":"IP-083734","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":348256,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"22","issue":"5","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a07e8a2e4b09af898c8cb92","contributors":{"authors":[{"text":"Schroeder, Susan A.","contributorId":78235,"corporation":false,"usgs":true,"family":"Schroeder","given":"Susan A.","affiliations":[],"preferred":false,"id":719409,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fulton, David C. 0000-0001-5763-7887 dcf@usgs.gov","orcid":"https://orcid.org/0000-0001-5763-7887","contributorId":2208,"corporation":false,"usgs":true,"family":"Fulton","given":"David","email":"dcf@usgs.gov","middleInitial":"C.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":719408,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lawrence, Jeffrey S.","contributorId":171470,"corporation":false,"usgs":false,"family":"Lawrence","given":"Jeffrey","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":719410,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cordts, Steven D.","contributorId":171471,"corporation":false,"usgs":false,"family":"Cordts","given":"Steven","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":719411,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70193043,"text":"70193043 - 2017 - Automated quantification of surface water inundation in wetlands using optical satellite imagery","interactions":[],"lastModifiedDate":"2017-11-12T11:13:09","indexId":"70193043","displayToPublicDate":"2017-08-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Automated quantification of surface water inundation in wetlands using optical satellite imagery","docAbstract":"We present a fully automated and scalable algorithm for quantifying surface water inundation in wetlands. Requiring no external training data, our algorithm estimates sub-pixel water fraction (SWF) over large areas and long time periods using Landsat data. We tested our SWF algorithm over three wetland sites across North America, including the Prairie Pothole Region, the Delmarva Peninsula and the Everglades, representing a gradient of inundation and vegetation conditions. We estimated SWF at 30-m resolution with accuracies ranging from a normalized root-mean-square-error of 0.11 to 0.19 when compared with various high-resolution ground and airborne datasets. SWF estimates were more sensitive to subtle inundated features compared to previously published surface water datasets, accurately depicting water bodies, large heterogeneously inundated surfaces, narrow water courses and canopy-covered water features. Despite this enhanced sensitivity, several sources of errors affected SWF estimates, including emergent or floating vegetation and forest canopies, shadows from topographic features, urban structures and unmasked clouds. The automated algorithm described in this article allows for the production of high temporal resolution wetland inundation data products to support a broad range of applications.
","language":"English","publisher":"MDPI","doi":"10.3390/rs9080807","usgsCitation":"DeVries, B., Huang, C., Lang, M.W., Jones, J., Huang, W., Creed, I., and Carroll, M.L., 2017, Automated quantification of surface water inundation in wetlands using optical satellite imagery: Remote Sensing, v. 9, no. 8, Article 807; 22 p., https://doi.org/10.3390/rs9080807.","productDescription":"Article 807; 22 p.","ipdsId":"IP-087428","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"links":[{"id":469631,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs9080807","text":"Publisher Index Page"},{"id":348619,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"9","issue":"8","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-08-07","publicationStatus":"PW","scienceBaseUri":"5a096bb1e4b09af898c94143","contributors":{"authors":[{"text":"DeVries, Ben 0000-0003-2136-3401","orcid":"https://orcid.org/0000-0003-2136-3401","contributorId":198971,"corporation":false,"usgs":false,"family":"DeVries","given":"Ben","email":"","affiliations":[{"id":7261,"text":"Department of Geographical Sciences, University of Maryland, College Park, MD, 20742","active":true,"usgs":false}],"preferred":false,"id":717737,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Huang, Chengquan 0000-0003-0055-9798","orcid":"https://orcid.org/0000-0003-0055-9798","contributorId":198972,"corporation":false,"usgs":false,"family":"Huang","given":"Chengquan","email":"","affiliations":[{"id":7261,"text":"Department of Geographical Sciences, University of Maryland, College Park, MD, 20742","active":true,"usgs":false}],"preferred":false,"id":717738,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lang, Megan W.","contributorId":196284,"corporation":false,"usgs":false,"family":"Lang","given":"Megan","email":"","middleInitial":"W.","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":717739,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jones, John W. 0000-0001-6117-3691 jwjones@usgs.gov","orcid":"https://orcid.org/0000-0001-6117-3691","contributorId":2220,"corporation":false,"usgs":true,"family":"Jones","given":"John","email":"jwjones@usgs.gov","middleInitial":"W.","affiliations":[{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":717736,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Huang, Wenli 0000-0001-9608-1690","orcid":"https://orcid.org/0000-0001-9608-1690","contributorId":198973,"corporation":false,"usgs":false,"family":"Huang","given":"Wenli","email":"","affiliations":[{"id":7261,"text":"Department of Geographical Sciences, University of Maryland, College Park, MD, 20742","active":true,"usgs":false}],"preferred":false,"id":717740,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Creed, Irena F.","contributorId":81209,"corporation":false,"usgs":false,"family":"Creed","given":"Irena F.","affiliations":[{"id":27655,"text":"Department of Biology, University of Western Ontario, London, ON Canada","active":true,"usgs":false}],"preferred":false,"id":717741,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Carroll, Mark L.","contributorId":145826,"corporation":false,"usgs":false,"family":"Carroll","given":"Mark","email":"","middleInitial":"L.","affiliations":[{"id":16246,"text":"Biospheric Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA","active":true,"usgs":false},{"id":7239,"text":"Science Systems and Applications, Inc.","active":true,"usgs":false},{"id":16247,"text":"Sigma Space Corp, NASA Goddard Space Flight Center, Greenbelt, MD, USA","active":true,"usgs":false}],"preferred":false,"id":721689,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70189800,"text":"sir20165169 - 2017 - Simulated groundwater flow paths, travel time, and advective transport of nitrogen in the Kirkwood-Cohansey aquifer system, Barnegat Bay–Little Egg Harbor Watershed, New Jersey","interactions":[],"lastModifiedDate":"2017-09-25T13:08:39","indexId":"sir20165169","displayToPublicDate":"2017-07-31T16:00:00","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":"2016-5169","title":"Simulated groundwater flow paths, travel time, and advective transport of nitrogen in the Kirkwood-Cohansey aquifer system, Barnegat Bay–Little Egg Harbor Watershed, New Jersey","docAbstract":"Elevated concentrations of nitrogen in groundwater that discharges to surface-water bodies can degrade surface-water quality and habitats in the New Jersey Coastal Plain. An analysis of groundwater flow in the Kirkwood-Cohansey aquifer system and deeper confined aquifers that underlie the Barnegat Bay–Little Egg Harbor (BB-LEH) watershed and estuary was conducted by using groundwater-flow simulation, in conjunction with a particle-tracking routine, to provide estimates of groundwater flow paths and travel times to streams and the BB-LEH estuary.
Water-quality data from the Ambient Groundwater Quality Monitoring Network, a long-term monitoring network of wells distributed throughout New Jersey, were used to estimate the initial nitrogen concentration in recharge for five different land-use classes—agricultural cropland or pasture, agricultural orchard or vineyard, urban non-residential, urban residential, and undeveloped. Land use at the point of recharge within the watershed was determined using a geographic information system (GIS). Flow path starting locations were plotted on land-use maps for 1930, 1973, 1986, 1997, and 2002. Information on the land use at the time and location of recharge, time of travel to the discharge location, and the point of discharge were determined for each simulated flow path. Particle-tracking analysis provided the link from the point of recharge, along the particle flow path, to the point of discharge, and the particle travel time. The travel time of each simulated particle established the recharge year. Land use during the year of recharge was used to define the nitrogen concentration associated with each flow path. The recharge-weighted average nitrogen concentration for all flow paths that discharge to the Toms River upstream from streamflow-gaging station 01408500 or to the BB-LEH estuary was calculated.
Groundwater input into the Barnegat Bay–Little Egg Harbor estuary from two main sources— indirect discharge from base flow to streams that eventually flow into the bay and groundwater discharge directly into the estuary and adjoining coastal wetlands— is summarized by quantity, travel time, and estimated nitrogen concentration. Simulated average groundwater discharge to streams in the watershed that flow into the BB-LEH estuary is approximately 400 million gallons per day. Particle-tracking results indicate that the travel time of 56 percent of this discharge is less than 7 years. Fourteen percent of the groundwater discharge to the streams in the BB-LEH watershed has a travel time of less than 7 years and originates in urban land. Analysis of flow-path simulations indicate that approximately 13 percent of the total groundwater flow through the study area discharges directly to the estuary and adjoining coastal wetlands (approximately 64 million gallons per day). The travel time of 19 percent of this discharge is less than 7 years. Ten percent of this discharge (1 percent of the total groundwater flow through the study area) originates in urban areas and has a travel time of less than 7 years. Groundwater that discharges to the streams that flow into the BB-LEH, in general, has shorter travel times, and a higher percentage of it originates in urban areas than does direct groundwater discharge to the Barnegat Bay–Little Egg Harbor estuary.
The simulated average nitrogen concentration in groundwater that discharges to the Toms River, upstream from streamflow-gaging station 01408500 was computed and compared to summary concentrations determined from analysis of multiple surface-water samples. The nitrogen concentration in groundwater that discharges directly to the estuary and adjoining coastal wetlands is a current data gap. The particle tracking methodology used in this study provides an estimate of this concentration.\"
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165169","collaboration":"Prepared in cooperation with the Barnegat Bay Partnership","usgsCitation":"Voronin, L.M., and Cauller, S.J., 2017, Simulated groundwater flow paths, travel time, and advective transport of nitrogen in the Kirkwood-Cohansey aquifer system, Barnegat Bay–Little Egg Harbor Watershed, New Jersey: U.S. Geological Survey Scientific Investigations Report 2016–5169, 17 p., https://doi.org/10.3133/sir20165169.","productDescription":"v, 17 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-077222","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":344342,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5169/sir20165169.pdf","text":"Report","size":"24.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5169"},{"id":346055,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7P55M0W","text":"USGS data release","description":"USGS data release","linkHelpText":"MODPATH particle-tracking analysis of groundwater flow and travel times to the Barnegat Bay-Little Egg Harbor estuary and streams within the Barnegat Bay-Little Egg Harbor watershed, New Jersey"},{"id":344341,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5169/coverthb.jpg"}],"country":"United States","state":"New Jersey","otherGeospatial":"Kirkwood-Cohansey Aquifer System","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.5,\n 40.25\n ],\n [\n -73.75,\n 40.25\n ],\n [\n -73.75,\n 39.5\n ],\n [\n -74.5,\n 39.5\n ],\n [\n -74.5,\n 40.25\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Jersey Water Science Center
U.S. Geological Survey
3450 Princeton Pike, Suite 110
Lawrenceville, NJ 08648
The U.S. Geological Survey, in cooperation with the Delaware Department of Agriculture, developed a network of wells to monitor groundwater quality in the surficial aquifer of the Delaware Coastal Plain. Well-drained soils, a flat landscape, and accessible water in the Delaware Coastal Plain make for a productive agricultural setting. As such, agriculture is one of the largest industries in the State of Delaware. This setting enables the transport of chemicals from agriculture and other land uses to shallow groundwater. Efforts to mitigate nutrient transport to groundwater by the implementation of agricultural best management practices (BMPs) have been ongoing for several decades. To measure the effectiveness of BMPs on a regional scale, a network of 48 wells was designed to measure shallow groundwater quality (particularly nitrate) over time near agricultural land in the Delaware Coastal Plain. Water characteristics, major ions, nutrients, and dissolved gases were measured in groundwater samples collected from network wells during fall 2014. Wells were organized into three groups based on their geochemical similarity and these groups were used to describe nitrate and chloride concentrations and factors that affect the variability among the groups. The results from this study are intended to establish waterquality conditions in 2014 to enable comparison of future conditions and evaluate the effectiveness of agricultural BMPs on a regional scale.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175054","collaboration":"Prepared in cooperation with the Delaware Department of Agriculture","usgsCitation":"Fleming, B.J., Mensch, L.L., Denver, J.M., Cruz, R.M., and Nardi, M.R., 2017, Water quality in the surficial aquifer near agricultural areas in the Delaware Coastal Plain, 2014: U.S. Geological Survey Scientific Investigations Report 2017–5054, 28 p., https://doi.org/10.3133/sir20175054.","productDescription":"viii, 28 p.","numberOfPages":"40","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-081046","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"links":[{"id":344332,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5054/coverthb.jpg"},{"id":344333,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5054/sir20175054.pdf","text":"Report","size":"3.86 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U.S. Geological Survey
5522 Research Park Drive
Baltimore, MD 21228
A sound understanding of sources contributing to instream sediment flux in a watershed is important when developing total maximum daily load (TMDL) management strategies designed to reduce suspended sediment in streams. Sediment fingerprinting and sediment budget approaches are two techniques that, when used jointly, can qualify and quantify the major sources of sediment in a given watershed. The sediment fingerprinting approach uses trace element concentrations from samples in known potential source areas to determine a clear signature of each potential source. A mixing model is then used to determine the relative source contribution to the target suspended sediment samples.
The computational steps required to apportion sediment for each target sample are quite involved and time intensive, a problem the Sediment Source Assessment Tool (Sed_SAT) addresses. Sed_SAT is a user-friendly statistical model that guides the user through the necessary steps in order to quantify the relative contributions of sediment sources in a given watershed. The model is written using the statistical software R (R Core Team, 2016b) and utilizes Microsoft Access® as a user interface but requires no prior knowledge of R or Microsoft Access® to successfully run the model successfully. Sed_SAT identifies outliers, corrects for differences in size and organic content in the source samples relative to the target samples, evaluates the conservative behavior of tracers used in fingerprinting by applying a “Bracket Test,” identifies tracers with the highest discriminatory power, and provides robust error analysis through a Monte Carlo simulation following the mixing model. Quantifying sediment source contributions using the sediment fingerprinting approach provides local, State, and Federal land management agencies with important information needed to implement effective strategies to reduce sediment. Sed_SAT is designed to assist these agencies in applying the sediment fingerprinting approach to quantify sediment sources in the sediment TMDL framework.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171062","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Gorman Sanisaca, L.E., Gellis, A.C., and Lorenz, D.L., 2017, Determining the sources of fine-grained sediment using the Sediment Source Assessment Tool (Sed_SAT): U.S. Geological Survey Open File Report 2017–1062, 104 p., https://doi.org/10.3133/ofr20171062.","productDescription":"Report: viii, 104 p.; Application Site","numberOfPages":"116","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-079059","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"links":[{"id":438259,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F76Q1VBX","text":"USGS data release","linkHelpText":"Sediment Source Assessment Tool (Sed_SAT)"},{"id":344315,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1062/coverthb2.jpg"},{"id":344316,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1062/ofr20171062.pdf","text":"Report","size":"18.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1062"},{"id":344317,"rank":3,"type":{"id":4,"text":"Application Site"},"url":"https://doi.org/10.5066/F76Q1VBX","text":"Sed_Sat Software","linkHelpText":"- Determining the Sources of Fine-Grained Sediment Using the Sediment Source Assessment Tool (Sed_SAT)"}],"contact":"Director, MD-DE-DC Water Science Center
U.S. Geological Survey
5522 Research Park Drive
Baltimore, MD 21228
The unique hydrologic conditions characterizing riparian ecosystems in dryland (arid and semi-arid) areas help maintain high biodiversity and support high levels of primary productivity compared to associated uplands. In western North America, many riparian ecosystems have been damaged by altered flow regimes (e.g., impoundments and diversions) and over utilization of water resources (e.g., groundwater pumping for agriculture and human consumption). This has led some state and national governments to provide occasional environmental flows to address the declining condition of such riparian systems. In a historic agreement between the United States and Mexico, 130 million cubic meters (mcm) of water was released to the lower Colorado River Delta in Mexico, with the intent to evaluate the hydrological and biological response of the ecosystem. We used the Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI) to estimate long term (2000–2014) and short term (pre- and post-pulse; 2013 and 2014) evapotranspiration (ET; used herein as an indicator of plant health) of the delta’s riparian corridor. We found the pulse flow helped reverse a decline in ET from 2011 to 2013, with a small, but statistically significant increase in 2014 (P < 0.05). ET was greater than 100 mcm in all years analyzed (even in years without surface flows) and exceeded surface flows in all years except 2000 (result of excess flows following an El Niño cycle in 1997) and 2014 (year of the pulse flow). Based on groundwater salinities and MODIS ET estimates, we estimated groundwater flow into the delta to be ∼103 mcm. Shallow groundwater salinities in the riparian zone increased from 1.30 g L−1 in the most upstream reach to 2.77 g L−1 in the most downstream reach we measured, partly due to uptake of water by riparian vegetation and partly to intrusion of saline agricultural return flows. The disparity between surface flows and ET can likely be explained by the predominantly phreatophytic plants characterizing the area, which draw water from the aquifer. These results also suggest that the deteriorated condition of vegetation within the riparian zone might not be reversed by a single pulse event and could instead require subsequent pulse flows as a long term strategy to restore vegetation in this riparian ecosystem.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoleng.2016.10.056","usgsCitation":"Jarchow, C.J., Nagler, P.L., Glenn, E., Ramirez-Hernandez, J., and Rodriguez-Burgueno, E., 2017, Evapotranspiration by remote sensing: An analysis of the Colorado River Delta before and after the Minute 319 pulse flow to Mexico: Ecological Engineering, v. 106, no. B, p. 725-732, https://doi.org/10.1016/j.ecoleng.2016.10.056.","productDescription":"8 p.","startPage":"725","endPage":"732","ipdsId":"IP-071895","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":469660,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecoleng.2016.10.056","text":"Publisher Index Page"},{"id":344416,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.11886596679688,\n 32.132594234149906\n ],\n [\n -114.67941284179688,\n 32.132594234149906\n ],\n [\n -114.67941284179688,\n 32.72375394304274\n ],\n [\n -115.11886596679688,\n 32.72375394304274\n ],\n [\n -115.11886596679688,\n 32.132594234149906\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"106","issue":"B","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"597afba6e4b0a38ca2750b58","contributors":{"authors":[{"text":"Jarchow, Christopher J. 0000-0002-0424-4104 cjarchow@usgs.gov","orcid":"https://orcid.org/0000-0002-0424-4104","contributorId":5813,"corporation":false,"usgs":true,"family":"Jarchow","given":"Christopher","email":"cjarchow@usgs.gov","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":706594,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nagler, Pamela L. 0000-0003-0674-103X pnagler@usgs.gov","orcid":"https://orcid.org/0000-0003-0674-103X","contributorId":1398,"corporation":false,"usgs":true,"family":"Nagler","given":"Pamela","email":"pnagler@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":706595,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Glenn, Edward P.","contributorId":56542,"corporation":false,"usgs":false,"family":"Glenn","given":"Edward P.","affiliations":[{"id":13060,"text":"Department of Soil, Water and Environmental Science, University of Arizona","active":true,"usgs":false}],"preferred":false,"id":706596,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ramirez-Hernandez, Jorge","contributorId":195176,"corporation":false,"usgs":false,"family":"Ramirez-Hernandez","given":"Jorge","email":"","affiliations":[],"preferred":false,"id":706597,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rodriguez-Burgueno, Eliana 0000-0002-5590-6606","orcid":"https://orcid.org/0000-0002-5590-6606","contributorId":176492,"corporation":false,"usgs":false,"family":"Rodriguez-Burgueno","given":"Eliana","email":"","affiliations":[],"preferred":false,"id":706598,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70189208,"text":"ds1058 - 2017 - Drilling, construction, geophysical log data, and lithologic log for boreholes USGS 142 and USGS 142A, Idaho National Laboratory, Idaho","interactions":[],"lastModifiedDate":"2017-08-28T13:23:25","indexId":"ds1058","displayToPublicDate":"2017-07-27T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"1058","title":"Drilling, construction, geophysical log data, and lithologic log for boreholes USGS 142 and USGS 142A, Idaho National Laboratory, Idaho","docAbstract":"Starting in 2014, the U.S. Geological Survey in cooperation with the U.S. Department of Energy, drilled and constructed boreholes USGS 142 and USGS 142A for stratigraphic framework analyses and long-term groundwater monitoring of the eastern Snake River Plain aquifer at the Idaho National Laboratory in southeast Idaho. Borehole USGS 142 initially was cored to collect rock and sediment core, then re-drilled to complete construction as a screened water-level monitoring well. Borehole USGS 142A was drilled and constructed as a monitoring well after construction problems with borehole USGS 142 prevented access to upper 100 feet (ft) of the aquifer. Boreholes USGS 142 and USGS 142A are separated by about 30 ft and have similar geology and hydrologic characteristics. Groundwater was first measured near 530 feet below land surface (ft BLS) at both borehole locations. Water levels measured through piezometers, separated by almost 1,200 ft, in borehole USGS 142 indicate upward hydraulic gradients at this location. Following construction and data collection, screened water-level access lines were placed in boreholes USGS 142 and USGS 142A to allow for recurring water level measurements.
Borehole USGS 142 was cored continuously, starting at the first basalt contact (about 4.9 ft BLS) to a depth of 1,880 ft BLS. Excluding surface sediment, recovery of basalt, rhyolite, and sediment core at borehole USGS 142 was approximately 89 percent or 1,666 ft of total core recovered. Based on visual inspection of core and geophysical data, material examined from 4.9 to 1,880 ft BLS in borehole USGS 142 consists of approximately 45 basalt flows, 16 significant sediment and (or) sedimentary rock layers, and rhyolite welded tuff. Rhyolite was encountered at approximately 1,396 ft BLS. Sediment layers comprise a large percentage of the borehole between 739 and 1,396 ft BLS with grain sizes ranging from clay and silt to cobble size. Sedimentary rock layers had calcite cement. Basalt flows ranged in thickness from about 2 to 100 ft and varied from highly fractured to dense, and ranged from massive to diktytaxitic to scoriaceous, in texture.
Geophysical logs were collected on completion of drilling at boreholes USGS 142 and USGS 142A. Geophysical logs were examined with available core material to describe basalt, sediment and sedimentary rock layers, and rhyolite. Natural gamma logs were used to confirm sediment layer thickness and location; neutron logs were used to examine basalt flow units and changes in hydrogen content; gamma-gamma density logs were used to describe general changes in rock properties; and temperature logs were used to understand hydraulic gradients for deeper sections of borehole USGS 142. Gyroscopic deviation was measured to record deviation from true vertical at all depths in boreholes USGS 142 and USGS 142A.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1058","collaboration":"Prepared in cooperation with the U.S. Department of Energy DOE/ID-22243","usgsCitation":"Twining, B.V., Hodges, M.K.V., Schusler, Kyle, and Mudge, Christopher, 2017, Drilling, construction, geophysical log data, and lithologic log for boreholes USGS 142 and USGS 142A, Idaho National Laboratory, Idaho: U.S. Geological Survey Data Series 1058 (DOE/ID-22243), 21 p., plus appendixes, https://doi.org/10.3133/ds1058.","productDescription":"Report: v, 21 p.; Appendices A-C","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-079458","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":344347,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1058/ds1058.pdf","text":"Report","size":"1.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1058"},{"id":344346,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1058/coverthb.jpg"},{"id":344348,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/1058/ds1058_appendix.A.pdf","text":"Appendix A","size":"350 KB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1058 Appendix A"},{"id":344349,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/1058/ds1058_appendix.B.pdf","text":"Appendix B","size":"130 KB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1058 Appendix B"},{"id":344350,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/1058/ds1058_appendix.C.pdf","text":"Appendix C","size":"15 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1058 Appendix C"}],"country":"United States","state":"Idaho","otherGeospatial":"Idaho National Laboratory","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.75,\n 44.25\n ],\n [\n -112.25,\n 44.25\n ],\n [\n -112.25,\n 43.3\n ],\n [\n -113.75,\n 43.3\n ],\n [\n -113.75,\n 44.25\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702
In the southwestern U.S., many riparian ecosystems have been altered by dams, water diversions, and other anthropogenic activities. This is particularly true of the Colorado River, where numerous dams and agricultural diversions have affected this water course, especially south of the U.S.–Mexico border. In the spring of 2014, 130 million cubic meters of water was released to the lower Colorado River Delta in Mexico. To understand the impact of this pulse flow release on vegetation in the delta’s riparian corridor, we analyzed a modified form of Landsat 8 Operational Land Imager (OLI) Normalized Difference Vegetation Index (NDVI*) data. We assessed greenup during the growing period and estimated actual evapotranspiration (ETa) for the period prior to (yr. 2013) and following (i.e., yr. 2014 and 2015) the pulse flow. We found a significant increase in NDVI* from 2013 to 2014 (P < 0.05) and a decrease from 2014 to 2015; however, 2015 levels were still significantly higher than in 2013. ETa was also higher in 2014 vs. 2013, with an estimated 74.5 million cubic meters in 2013 and 88.9 in 2014. The most intense greening occurred in the zone of inundation but also extended into the non-flooded part of the riparian zone, indicating replenishment of groundwater. These findings suggest the peak response by vegetation to the flow lasted about one year, followed by a decrease in NDVI*. As a long term solution to the declining condition of vegetation, additional pulse releases are likely needed for restoration and survival of riparian plant communities in the Colorado River Delta.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoleng.2016.08.007","usgsCitation":"Jarchow, C.J., Nagler, P.L., and Glenn, E., 2017, Greenup and evapotranspiration following the Minute 319 pulse flow to Mexico: An analysis using Landsat 8 Normalized Difference Vegetation Index (NDVI) data: Ecological Engineering, v. 106, no. B, p. 776-783, https://doi.org/10.1016/j.ecoleng.2016.08.007.","productDescription":"8 p.","startPage":"776","endPage":"783","ipdsId":"IP-074636","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":469656,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecoleng.2016.08.007","text":"Publisher Index Page"},{"id":344415,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.11886596679688,\n 32.132594234149906\n ],\n [\n -114.67941284179688,\n 32.132594234149906\n ],\n [\n -114.67941284179688,\n 32.72375394304274\n ],\n [\n -115.11886596679688,\n 32.72375394304274\n ],\n [\n -115.11886596679688,\n 32.132594234149906\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"106","issue":"B","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"597afba2e4b0a38ca2750b36","contributors":{"authors":[{"text":"Jarchow, Christopher J. 0000-0002-0424-4104 cjarchow@usgs.gov","orcid":"https://orcid.org/0000-0002-0424-4104","contributorId":5813,"corporation":false,"usgs":true,"family":"Jarchow","given":"Christopher","email":"cjarchow@usgs.gov","middleInitial":"J.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":false,"id":706599,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nagler, Pamela L. 0000-0003-0674-103X pnagler@usgs.gov","orcid":"https://orcid.org/0000-0003-0674-103X","contributorId":1398,"corporation":false,"usgs":true,"family":"Nagler","given":"Pamela","email":"pnagler@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":706600,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Glenn, Edward P.","contributorId":56542,"corporation":false,"usgs":false,"family":"Glenn","given":"Edward P.","affiliations":[{"id":13060,"text":"Department of Soil, Water and Environmental Science, University of Arizona","active":true,"usgs":false}],"preferred":false,"id":706601,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70189531,"text":"ofr20171084 - 2017 - Streamflow investigations on a reach of Hobble Creek near Springville, Utah","interactions":[],"lastModifiedDate":"2017-07-27T14:10:50","indexId":"ofr20171084","displayToPublicDate":"2017-07-27T00:00:00","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":"2017-1084","title":"Streamflow investigations on a reach of Hobble Creek near Springville, Utah","docAbstract":"The Central Utah Water Conservancy District (CUWCD) is proposing to deliver supplemental flow to Hobble Creek from Strawberry Reservoir through the Mapleton-Springville Lateral pipeline. A substantial portion of the supplemental water is intended to benefit June Sucker recovery and other fish and wildlife along Hobble Creek. The objective of this study was to determine gains or losses of water in a section of Hobble Creek between the Island Dam and the Swenson Dam (the primary study reach) during different seasons and flow conditions.
Paired measurements of flow in Hobble Creek were made during June to November 2016, at sites bracketing the primary study reach from site HC3 to HC6. These measurements showed increased streamflow in this reach that ranged from 6.1 cubic feet per second (ft3/s) to 9.3 ft3/s. During August and November, two sets of measurements were made at several locations along the study reach to document baseline conditions, and then an additional amount of water (a pulse of about 9–10 ft3/s) from Strawberry Reservoir through the Mapleton-Springville Lateral pipeline, was added to the reach. During the August 23 measurements, the average change at the upstream site (HC3) relative to the pulse was 9.3 ft3/s, and the average change at the downstream site (HC6) was about 8.4 ft3/s, leaving about 0.9 ft3/s of the additional water unaccounted for at site HC6. However, there was no significant difference between the net streamflow volume at sites HC3 and HC6 associated with the pulse that would indicate water was being lost. During the November 7–9 streamflow measurements, the average change in discharge at site HC3 relative to an increase in flow from the Mapleton-Springville Lateral pipeline (the pulse) was 9.6 ft3/s, and the average change at site HC6 was about 9.8 ft3/s. On the basis of these measurements it appears that the entire amount of the pulse added to the stream at site HC3 was accounted for at site HC6. Additionally, there was no significant difference between the net streamflow volume at sites HC3 and HC8 associated with the pulse that would indicate water was being lost.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171084","collaboration":"Prepared in cooperation with the Central Utah Water Conservancy District","usgsCitation":"Gerner, S.J., 2017, Streamflow investigations on a reach of Hobble Creek near Springville, Utah: U.S. Geological Survey Open-File Report 2017–1084, 9 p., https://doi.org/10.3133/ofr20171084.","productDescription":"iv, 10 p.","numberOfPages":"18","onlineOnly":"Y","ipdsId":"IP-083190","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":344300,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1084/ofr.20171084.pdf","text":"Report","size":"2.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1084"},{"id":344298,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1084/coverthb.jpg"}],"country":"United States","state":"Utah","city":"Springville","otherGeospatial":"Hobble Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.65834426879881,\n 40.1338721947653\n ],\n [\n -111.55157089233398,\n 40.1338721947653\n ],\n [\n -111.55157089233398,\n 40.181627516058576\n ],\n [\n -111.65834426879881,\n 40.181627516058576\n ],\n [\n -111.65834426879881,\n 40.1338721947653\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Five passive membrane samplers were deployed for 28 continuous days at select sites along and near the west Maui coastline to assess organic compounds and contaminant inputs to diverse, shallow coral reef ecosystems. Daily and weekly fluctuations in such inputs were captured on the membranes using integrative sampling. The distribution of organic compounds observed at these five coastal sites showed considerable variation; with high concentrations of terrestrially sourced organic compounds such as C29 sterols and high molecular weight n-alkanes at the strongly groundwater-influenced Kahekili vent site. In comparison, the coastal sites were presumably influenced more by seasonal surface and stream water runoff and therefore had marine-sourced organic compounds and fewer pharmaceuticals and personal care products. The direct correlation to upstream land-use practices was not obvious and may require additional wet-season sampling. Pharmaceuticals and personal care products as well as flame retardants were detected at all sites, and the Kahekili vent site had the highest number of detections. Planned future work must also determine the organic compound and contaminant concentrations adsorbed onto water column particulate matter, because it may also be an important vector for contaminant transport to coral reef ecosystems. The impact of contaminants per individual (such as fecundity and metabolism) as well as per community (such as species abundance and diversity) is necessary for an accurate assessment of environmental stress. Results presented herein provide current contaminant inputs to select nearshore environments along the west Maui coastline captured during the dry season, and they can be useful to aid potential future evaluations and (or) comparisons.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171097","collaboration":"Prepared in cooperation with U.S. Environmental Protection Agency and the State of Hawaii Department of Health","usgsCitation":"Campbell, P.L., Prouty, N.G., Storlazzi, C.D., and D’Antonio, N.L., 2017, The use of passive membrane samplers to assess organic contaminant inputs at five coastal sites in west Maui, Hawaii: U.S. Geological Survey Open-File Report 2017-1097, 19 p., https://doi.org/10.3133/ofr20171097.","productDescription":"vi, 19 p.","numberOfPages":"26","onlineOnly":"Y","ipdsId":"IP-076397","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":344370,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1097/coverthb.jpg"},{"id":344371,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1097/ofr.20171097.pdf","text":"Report","size":"500 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1097"}],"country":"United States","state":"Hawaii","otherGeospatial":"Maui","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -156.72718048095703,\n 20.80394129420893\n ],\n [\n -156.5994644165039,\n 20.80394129420893\n ],\n [\n -156.5994644165039,\n 20.966248568790633\n ],\n [\n -156.72718048095703,\n 20.966248568790633\n ],\n [\n -156.72718048095703,\n 20.80394129420893\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Pacific Coastal and Marine Science Center
U.S. Geological Survey
Pacific Science Center
2885 Mission St.
Santa Cruz, CA 95060
The Paleocene-Eocene Thermal Maximum (PETM) was an interval of extreme warmth that caused disruption of marine and terrestrial ecosystems on a global scale. Here we examine the sediments, flora, and fauna from an expanded section at Mattawoman Creek-Billingsley Road (MCBR) in Maryland and explore the impact of warming at a nearshore shallow marine (30–100 m water depth) site in the Salisbury Embayment. Observations indicate that at the onset of the PETM, the site abruptly shifted from an open marine to prodelta setting with increased terrestrial and fresh water input. Changes in microfossil biota suggest stratification of the water column and low-oxygen bottom water conditions in the earliest Eocene. Formation of authigenic carbonate through microbial diagenesis produced an unusually large bulk carbon isotope shift, while the magnitude of the corresponding signal from benthic foraminifera is similar to that at other marine sites. This proves that the landward increase in the magnitude of the carbon isotope excursion measured in bulk sediment is not due to a near instantaneous release of 12C-enriched CO2. We conclude that the MCBR site records nearshore marine response to global climate change that can be used as an analog for modern coastal response to global warming.
","language":"English","publisher":"AGU Publications","doi":"10.1002/2017PA003096","usgsCitation":"Self-Trail, J., Robinson, M.M., Bralower, T., Sessa, J.A., Hajek, E.A., Kump, L.R., Trampush, S.M., Willard, D.A., Edwards, L.E., Powars, D.S., and Wandless, G.A., 2017, Shallow marine response to global climate change during the Paleocene-Eocene Thermal Maximum, Salisbury Embayment, USA: Paleoceanography, v. 32, no. 7, p. 710-728, https://doi.org/10.1002/2017PA003096.","productDescription":"19 p.","startPage":"710","endPage":"728","ipdsId":"IP-079165","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":344319,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland, New Jersey, Pennsylvania, Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78.134765625,\n 38\n ],\n [\n -73,\n 38\n ],\n [\n -73,\n 41\n ],\n [\n -78.134765625,\n 41\n ],\n [\n -78.134765625,\n 38\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"32","issue":"7","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-17","publicationStatus":"PW","scienceBaseUri":"5979aa51e4b0ec1a488b8bd9","contributors":{"authors":[{"text":"Self-Trail, Jean 0000-0002-3018-4985 jstrail@usgs.gov","orcid":"https://orcid.org/0000-0002-3018-4985","contributorId":147370,"corporation":false,"usgs":true,"family":"Self-Trail","given":"Jean","email":"jstrail@usgs.gov","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":706366,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Robinson, Marci M. 0000-0002-9200-4097 mmrobinson@usgs.gov","orcid":"https://orcid.org/0000-0002-9200-4097","contributorId":2082,"corporation":false,"usgs":true,"family":"Robinson","given":"Marci","email":"mmrobinson@usgs.gov","middleInitial":"M.","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"preferred":true,"id":706367,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bralower, Timothy J.","contributorId":195144,"corporation":false,"usgs":false,"family":"Bralower","given":"Timothy J.","affiliations":[],"preferred":false,"id":706368,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sessa, Jocelyn A.","contributorId":195145,"corporation":false,"usgs":false,"family":"Sessa","given":"Jocelyn","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":706369,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hajek, Elizabeth A.","contributorId":195146,"corporation":false,"usgs":false,"family":"Hajek","given":"Elizabeth","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":706370,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kump, Lee R.","contributorId":195147,"corporation":false,"usgs":false,"family":"Kump","given":"Lee","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":706371,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Trampush, Sheila M.","contributorId":195148,"corporation":false,"usgs":false,"family":"Trampush","given":"Sheila","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":706372,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Willard, Debra A. 0000-0003-4878-0942 dwillard@usgs.gov","orcid":"https://orcid.org/0000-0003-4878-0942","contributorId":2076,"corporation":false,"usgs":true,"family":"Willard","given":"Debra","email":"dwillard@usgs.gov","middleInitial":"A.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":24693,"text":"Climate Research and Development","active":true,"usgs":true}],"preferred":true,"id":706373,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Edwards, Lucy E. 0000-0003-4075-3317 leedward@usgs.gov","orcid":"https://orcid.org/0000-0003-4075-3317","contributorId":2647,"corporation":false,"usgs":true,"family":"Edwards","given":"Lucy","email":"leedward@usgs.gov","middleInitial":"E.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":706374,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Powars, David S. 0000-0002-6787-8964 dspowars@usgs.gov","orcid":"https://orcid.org/0000-0002-6787-8964","contributorId":1181,"corporation":false,"usgs":true,"family":"Powars","given":"David","email":"dspowars@usgs.gov","middleInitial":"S.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":706375,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Wandless, Gregory A.","contributorId":195149,"corporation":false,"usgs":false,"family":"Wandless","given":"Gregory","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":706376,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70189772,"text":"70189772 - 2017 - Topographic, edaphic, and vegetative controls on plant-available water","interactions":[],"lastModifiedDate":"2017-12-12T12:46:04","indexId":"70189772","displayToPublicDate":"2017-07-26T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1447,"text":"Ecohydrology","active":true,"publicationSubtype":{"id":10}},"title":"Topographic, edaphic, and vegetative controls on plant-available water","docAbstract":"Soil moisture varies within landscapes in response to vegetative, physiographic, and climatic drivers, which makes quantifying soil moisture over time and space difficult. Nevertheless, understanding soil moisture dynamics for different ecosystems is critical, as the amount of water in a soil determines a myriad ecosystem services and processes such as net primary productivity, runoff, microbial decomposition, and soil fertility. We investigated the patterns and variability in in situ soil moisture measurements converted to plant-available water across time and space under different vegetative cover types and topographic positions at the Marcell Experimental Forest (Minnesota, USA). From 0 – 228.6 cm soil depth, plant-available water was significantly higher under the hardwoods (12%), followed by the aspen (8%) and red pine (5%) cover types. Across the same soil depth, toeslopes were wetter (mean plant-available water = 10%) than ridges and backslopes (mean plant-available water was 8%), although these differences were not statistically significant (p < 0.05). Using a mixed model of fixed and random effects, we found that cover type, soil texture, and time were related to plant-available water and that topography was not significantly related to plant-available water within this low-relief landscape. Additionally, during the three-year monitoring period, red pine and quaking aspen sites experienced plant-available water levels that may be considered limiting to plant growth and function. Given that increasing temperatures and more erratic precipitation patterns associated with climate change may result in decreased soil moisture in this region, these species may be sensitive and vulnerable to future shifts in climate.
","language":"English","publisher":"Wiley","doi":"10.1002/eco.1897","usgsCitation":"Dymond, S.F., Bradford, J.B., Bolstad, P.V., Kolka, R.K., Sebestyen, S.D., and DeSutter, T.S., 2017, Topographic, edaphic, and vegetative controls on plant-available water: Ecohydrology, v. 10, no. 8, p. 1-12, https://doi.org/10.1002/eco.1897.","productDescription":"e1897; 12 p.","startPage":"1","endPage":"12","ipdsId":"IP-078723","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":344327,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","issue":"8","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-09-14","publicationStatus":"PW","scienceBaseUri":"5979aa53e4b0ec1a488b8bf0","contributors":{"authors":[{"text":"Dymond, Salli F.","contributorId":195124,"corporation":false,"usgs":false,"family":"Dymond","given":"Salli","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":706300,"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":706299,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bolstad, Paul V.","contributorId":195125,"corporation":false,"usgs":false,"family":"Bolstad","given":"Paul","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":706301,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kolka, Randall K.","contributorId":16150,"corporation":false,"usgs":false,"family":"Kolka","given":"Randall","email":"","middleInitial":"K.","affiliations":[{"id":13259,"text":"USDA Forest Service Northern Research Station","active":true,"usgs":false}],"preferred":false,"id":706302,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sebestyen, Stephen D.","contributorId":195126,"corporation":false,"usgs":false,"family":"Sebestyen","given":"Stephen","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":706303,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"DeSutter, Thomas S.","contributorId":195127,"corporation":false,"usgs":false,"family":"DeSutter","given":"Thomas","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":706304,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70189819,"text":"70189819 - 2017 - It takes more than water: Restoring the Colorado River Delta","interactions":[],"lastModifiedDate":"2019-06-03T11:23:38","indexId":"70189819","displayToPublicDate":"2017-07-26T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1454,"text":"Ecological Engineering","active":true,"publicationSubtype":{"id":10}},"title":"It takes more than water: Restoring the Colorado River Delta","docAbstract":"Environmental flows have become important tools for restoring rivers and associated riparian ecosystems (Arthington, 2012; Glenn et al., 2017). In March 2014, the United States and Mexico initiated a bold effort in restoration, delivering from Morelos Dam a “pulse flow” of water into the Colorado River in its delta for the purpose of learning about its environmental effects (Flessa et al., 2013; Bark et al., 2016). Specifically, scientists evaluated whether the pulse flow, albeit minuscule compared to historical floods, could provide the ecological functions needed to establish native, flood-dependent vegetation to restore natural habitat along the riparian corridor.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecoleng.2017.05.028","usgsCitation":"Pitt, J., Kendy, E., Schlatter, K., Hinojosa-Huerta, O., Flessa, K.W., Shafroth, P.B., Ramirez-Hernandez, J., Nagler, P.L., and Glenn, E., 2017, It takes more than water: Restoring the Colorado River Delta: Ecological Engineering, v. 106, no. B, p. 629-632, https://doi.org/10.1016/j.ecoleng.2017.05.028.","productDescription":"4 p.","startPage":"629","endPage":"632","ipdsId":"IP-086432","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":344366,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Colorado River Delta","volume":"106","issue":"B","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5979aa4de4b0ec1a488b8bc3","contributors":{"authors":[{"text":"Pitt, Jennifer","contributorId":195174,"corporation":false,"usgs":false,"family":"Pitt","given":"Jennifer","email":"","affiliations":[],"preferred":false,"id":706460,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kendy, Eloise","contributorId":195175,"corporation":false,"usgs":false,"family":"Kendy","given":"Eloise","email":"","affiliations":[],"preferred":false,"id":706463,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schlatter, Karen","contributorId":176222,"corporation":false,"usgs":false,"family":"Schlatter","given":"Karen","email":"","affiliations":[],"preferred":false,"id":706466,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hinojosa-Huerta, Osvel","contributorId":195177,"corporation":false,"usgs":false,"family":"Hinojosa-Huerta","given":"Osvel","email":"","affiliations":[],"preferred":false,"id":706465,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Flessa, Karl W.","contributorId":175308,"corporation":false,"usgs":false,"family":"Flessa","given":"Karl","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":706461,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shafroth, Patrick B. 0000-0002-6064-871X shafrothp@usgs.gov","orcid":"https://orcid.org/0000-0002-6064-871X","contributorId":2000,"corporation":false,"usgs":true,"family":"Shafroth","given":"Patrick","email":"shafrothp@usgs.gov","middleInitial":"B.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":706462,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ramirez-Hernandez, Jorge","contributorId":195176,"corporation":false,"usgs":false,"family":"Ramirez-Hernandez","given":"Jorge","email":"","affiliations":[],"preferred":false,"id":706464,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Nagler, Pamela L. 0000-0003-0674-103X pnagler@usgs.gov","orcid":"https://orcid.org/0000-0003-0674-103X","contributorId":1398,"corporation":false,"usgs":true,"family":"Nagler","given":"Pamela","email":"pnagler@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":706459,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Glenn, Edward P.","contributorId":56542,"corporation":false,"usgs":false,"family":"Glenn","given":"Edward P.","affiliations":[{"id":13060,"text":"Department of Soil, Water and Environmental Science, University of Arizona","active":true,"usgs":false}],"preferred":false,"id":706467,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70189795,"text":"70189795 - 2017 - Climate and soil texture influence patterns of forb species richness and composition in big sagebrush plant communities across their spatial extent in the western US","interactions":[],"lastModifiedDate":"2017-08-03T08:53:33","indexId":"70189795","displayToPublicDate":"2017-07-25T00:00:00","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":"Climate and soil texture influence patterns of forb species richness and composition in big sagebrush plant communities across their spatial extent in the western US","docAbstract":"Article for outlet: Plant Ecology. Abstract: Big sagebrush (Artemisia tridentata Nutt.) plant communities are widespread non-forested drylands in western North American and similar to all shrub steppe ecosystems world-wide are composed of a shrub overstory layer and a forb and graminoid understory layer. Forbs account for the majority of plant species diversity in big sagebrush plant communities and are important for ecosystem function. Few studies have explored the geographic patterns of forb species richness and composition and their relationships with environmental variables in these communities. Our objectives were to examine the small and large-scale spatial patterns in forb species richness and composition and the influence of environmental variables. We sampled forb species richness and composition along transects at 15 field sites in Colorado, Idaho, Montana, Nevada, Oregon, Utah, and Wyoming, built species-area relationships to quantify differences in forb species richness at sites, and used Principal Components Analysis and nonmetric multidimensional scaling to identify relationships among environmental variables and forb species richness and composition. We found that species richness was most strongly correlated with soil texture, while species composition was most related to climate. The combination of climate and soil texture influences water availability, with important consequences for forb species richness and composition, which suggests climate-change induced modification of soil water availability may have important implications for plant species diversity in the future. Our paper is the first to our knowledge to examine forb biodiversity patterns in big sagebrush ecosystems in relation to environmental factors across the big sagebrush region.","language":"English","publisher":"Springer","doi":"10.1007/s11258-017-0743-9","usgsCitation":"Pennington, V.E., Palmquist, K.A., Bradford, J.B., and Lauenroth, W.K., 2017, Climate and soil texture influence patterns of forb species richness and composition in big sagebrush plant communities across their spatial extent in the western US: Plant Ecology, v. 218, no. 8, p. 957-970, https://doi.org/10.1007/s11258-017-0743-9.","productDescription":"14 p.","startPage":"957","endPage":"970","ipdsId":"IP-081502","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":344313,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Idaho, Montana, Nevada, Oregon, Utah, 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University Avenue, Laramie, WY 82071, USA","active":true,"usgs":false}],"preferred":false,"id":706411,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Palmquist, Kyle A.","contributorId":169517,"corporation":false,"usgs":false,"family":"Palmquist","given":"Kyle","email":"","middleInitial":"A.","affiliations":[{"id":7098,"text":"University of Wyoming, Department of Botany, 1000 E. University Avenue, Laramie, WY 82071, USA","active":true,"usgs":false}],"preferred":false,"id":706412,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":706410,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lauenroth, William K.","contributorId":80982,"corporation":false,"usgs":false,"family":"Lauenroth","given":"William","email":"","middleInitial":"K.","affiliations":[{"id":7098,"text":"University of Wyoming, Department of Botany, 1000 E. University Avenue, Laramie, WY 82071, USA","active":true,"usgs":false}],"preferred":false,"id":706413,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70189748,"text":"70189748 - 2017 - Knowing requires data","interactions":[],"lastModifiedDate":"2017-09-25T13:51:18","indexId":"70189748","displayToPublicDate":"2017-07-24T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3825,"text":"Groundwater","active":true,"publicationSubtype":{"id":10}},"title":"Knowing requires data","docAbstract":"Groundwater-flow models are often calibrated using a limited number of observations relative to the unknown inputs required for the model. This is especially true for models that simulate groundwater surface-water interactions. In this case, subsurface temperature sensors can be an efficient means for collecting long-term data that capture the transient nature of physical processes such as seepage losses. Continuous and spatially dense network of diverse observation data can be used to improve knowledge of important physical drivers, conceptualize and calibrate variably saturated groundwater flow models. An example is presented for which the results of such analysis were used to help guide irrigation districts and water management decisions on costly upgrades to conveyance systems to improve water usage, farm productivity and restoration efforts to improve downstream water quality and ecosystems.","language":"English","publisher":"Wiley","doi":"10.1111/gwat.12553","usgsCitation":"Naranjo, R.C., 2017, Knowing requires data: Groundwater, v. 55, no. 5, p. 674-677, https://doi.org/10.1111/gwat.12553.","productDescription":"4 p.","startPage":"674","endPage":"677","ipdsId":"IP-087078","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":344272,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"55","issue":"5","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2017-07-11","publicationStatus":"PW","scienceBaseUri":"59770748e4b0ec1a48889f2a","contributors":{"authors":[{"text":"Naranjo, Ramon C. 0000-0003-4469-6831 rnaranjo@usgs.gov","orcid":"https://orcid.org/0000-0003-4469-6831","contributorId":3391,"corporation":false,"usgs":true,"family":"Naranjo","given":"Ramon","email":"rnaranjo@usgs.gov","middleInitial":"C.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":706181,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70188012,"text":"ofr20171056 - 2017 - A method for addressing differences in concentrations of fipronil and three degradates obtained by two different laboratory methods","interactions":[],"lastModifiedDate":"2024-02-06T15:35:02.097116","indexId":"ofr20171056","displayToPublicDate":"2017-07-21T09:00:00","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":"2017-1056","title":"A method for addressing differences in concentrations of fipronil and three degradates obtained by two different laboratory methods","docAbstract":"In October 2012, the U.S. Geological Survey (USGS) began measuring the concentration of the pesticide fipronil and three of its degradates (desulfinylfipronil, fipronil sulfide, and fipronil sulfone) by a new laboratory method using direct aqueous-injection liquid chromatography tandem mass spectrometry (DAI LC–MS/MS). This method replaced the previous method—in use since 2002—that used gas chromatography/mass spectrometry (GC/MS). The performance of the two methods is not comparable for fipronil and the three degradates. Concentrations of these four chemical compounds determined by the DAI LC–MS/MS method are substantially lower than the GC/MS method. A method was developed to correct for the difference in concentrations obtained by the two laboratory methods based on a methods comparison field study done in 2012. Environmental and field matrix spike samples to be analyzed by both methods from 48 stream sites from across the United States were sampled approximately three times each for this study. These data were used to develop a relation between the two laboratory methods for each compound using regression analysis. The relations were used to calibrate data obtained by the older method to the new method in order to remove any biases attributable to differences in the methods. The coefficients of the equations obtained from the regressions were used to calibrate over 16,600 observations of fipronil, as well as the three degradates determined by the GC/MS method retrieved from the USGS National Water Information System. The calibrated values were then compared to over 7,800 observations of fipronil and to the three degradates determined by the DAI LC–MS/MS method also retrieved from the National Water Information System. The original and calibrated values from the GC/MS method, along with measures of uncertainty in the calibrated values and the original values from the DAI LC–MS/MS method, are provided in an accompanying data release.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171056","collaboration":"National Water-Quality Assessment Project","usgsCitation":"Crawford, C.G., and Martin, J.D., 2017, A method for addressing differences in concentrations of fipronil and three degradates obtained by two different laboratory methods: U.S. Geological Survey Open-File Report 2017–1056, 26 p., https://doi.org/10.3133/ofr20171056.","productDescription":"Report: vi, 26 p.; Data Release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-085104","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"links":[{"id":343953,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7QC01QR","text":"USGS data release","description":"USGS data release","linkHelpText":"A Method for Addressing Differences in Concentrations of Fipronil and Three Degradates Obtained by Two Different Laboratory Methods"},{"id":342897,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1056/ofr20171056.pdf","text":"Report","size":"1.16 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1056"},{"id":342896,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1056/coverthb.jpg"}],"contact":"National Water-Quality Assessment Project
U.S. Geological Survey
5957 Lakeside Boulevard
Indianapolis, IN 46278
In this study, we combined two 1 km actual evapotranspiration datasets (ET), one obtained from a root zone water balance model and another from an energy balance model, to partition annual ET into green (rainfall-based) and blue (surface water/groundwater) sources. Time series maps of green water ET (GWET) and blue water ET (BWET) are produced for the conterminous United States (CONUS) over 2001–2015. Our results indicate that average green and blue water for all land cover types in CONUS accounts for nearly 70% and 30% of the total ET, respectively. The ET in the eastern US arises mostly from GWET, and in the western US, it is mostly BWET. Analysis of the BWET in the 16 irrigated areas in CONUS revealed interesting results. While the magnitude of the BWET gradually showed a decline from west to east, the increase in coefficient of variation from west to east confirmed greater use of supplemental irrigation in the central and eastern US. We also established relationships between different hydro-climatology zones and their blue water requirements. This study provides insights on the relative contributions and the spatiotemporal dynamics of GWET and BWET, which could lead to improved water resources management.
Worldwide populations of freshwater eels have declined with one of the contributing causes related to mortality during passage through hydropower turbines. An inherent trade‐off underlies turbine management where the competing demand for more hydropower comes at the expense of eel survival. A win–win solution exists when an option performs better on all competing demands compared to other options. A predictive model for eel migration based on a recent telemetry study was used to develop decision rules for turbine management in the Shenandoah River system. The performance of alternative decision rules was compared to the status quo policy to search for win–win solutions. Decision rules were defined by the probability of eel movement and were evaluated by the probabilities of false positive and false negative errors. The exact value of the cut‐off probability used in the decision rule will need to be determined through negotiation between stakeholders, but a range of cut‐off probabilities resulted in a win–win situation with both reduced eel mortality and increased turbine operation relative to the current shutdown strategy. Monitoring the implementation is needed to evaluate and update the predictive model and to refine the decision rule. Although the decision is framed for the Shenandoah River system, the analytical approach could be used to develop decision rules for turbine shutdown policy in other areas.
","language":"English","publisher":"Wiley","doi":"10.1002/rra.3182","usgsCitation":"Smith, D.R., Paul L. Fackler, Eyler, S.M., Villegas, L., and Welsh, S., 2017, Optimization of decision rules for hydroelectric operation to reduce both eel mortality and unnecessary turbine shutdown: A search for a win-win solution: Rivers Research and Applications, v. 33, no. 8, p. 1279-1285, https://doi.org/10.1002/rra.3182.","productDescription":"7 p.","startPage":"1279","endPage":"1285","ipdsId":"IP-084849","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":377523,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia, West Virginia","otherGeospatial":"Shenandoah watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78.75,\n 38.86751337001198\n ],\n [\n -78.8763427734375,\n 38.974357249228206\n ],\n [\n -79.07684326171875,\n 38.739088441876866\n ],\n [\n -79.29931640625,\n 38.41271038284709\n ],\n [\n -79.4586181640625,\n 38.16911413556086\n ],\n [\n -79.25537109375,\n 38.07620357665235\n ],\n [\n -78.70330810546875,\n 38.8504034216919\n ],\n [\n -78.75,\n 38.86751337001198\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"33","issue":"8","noUsgsAuthors":false,"publicationDate":"2017-07-20","publicationStatus":"PW","contributors":{"authors":[{"text":"Smith, David R. 0000-0001-6074-9257 drsmith@usgs.gov","orcid":"https://orcid.org/0000-0001-6074-9257","contributorId":168442,"corporation":false,"usgs":true,"family":"Smith","given":"David","email":"drsmith@usgs.gov","middleInitial":"R.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":796346,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Paul L. Fackler","contributorId":238522,"corporation":false,"usgs":false,"family":"Paul L. Fackler","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":796347,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eyler, Sheila M.","contributorId":238523,"corporation":false,"usgs":false,"family":"Eyler","given":"Sheila","email":"","middleInitial":"M.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":796348,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Villegas, Laura","contributorId":238524,"corporation":false,"usgs":false,"family":"Villegas","given":"Laura","email":"","affiliations":[{"id":7091,"text":"North Carolina State University","active":true,"usgs":false}],"preferred":false,"id":796349,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Welsh, Stuart A. 0000-0003-0362-054X swelsh@usgs.gov","orcid":"https://orcid.org/0000-0003-0362-054X","contributorId":152088,"corporation":false,"usgs":true,"family":"Welsh","given":"Stuart A.","email":"swelsh@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":796350,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70206544,"text":"70206544 - 2017 - Hydrologic impacts of changes in climate and glacier extent in the Gulf of Alaska watershed","interactions":[],"lastModifiedDate":"2019-11-08T09:46:41","indexId":"70206544","displayToPublicDate":"2017-07-20T09:39:21","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":"Hydrologic impacts of changes in climate and glacier extent in the Gulf of Alaska watershed","docAbstract":"High‐resolution regional‐scale hydrologic models were used to quantify the response of late 21st century runoff from the Gulf of Alaska (GOA) watershed to changes in regional climate and glacier extent. NCEP Climate Forecast System Reanalysis data were combined with five Coupled Model Intercomparison Project Phase 5 general circulation models (GCMs) for two representative concentration pathway (RCP) scenarios (4.5 and 8.5) to develop meteorological forcing for the period 2070–2099. A hypsographic model was used to estimate future glacier extent given assumed equilibrium line altitude (ELA) increases of 200 and 400 m. GCM predictions show an increase in annual precipitation of 12% for RCP 4.5 and 21% for RCP 8.5, and an increase in annual temperature of 2.5°C for RCP 4.5 and 4.3°C for RCP 8.5, averaged across the GOA. Scenarios with perturbed climate and glaciers predict annual GOA‐wide runoff to increase by 9% for RCP4.5/ELA200 case and 14% for the RCP8.5/ELA400 case. The glacier runoff decreased by 14% for RCP4.5/ELA200 and by 34% for the RCP8.5/ELA400 case. Intermodel variability in annual runoff was found to be approximately twice the variability in precipitation input. Additionally, there are significant changes in runoff partitioning and increases in snowpack runoff are dominated by increases in rain‐on‐snow events. We present results aggregated across the entire GOA and also for individual watersheds to illustrate the range in hydrologic regime changes and explore the sensitivities of these results by independently perturbing only climate forcings and only glacier cover.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2016WR020033","usgsCitation":"Beamer, J., Hill, D., Mcgrath, D., Arendt, A.A., and Kienholz, C., 2017, Hydrologic impacts of changes in climate and glacier extent in the Gulf of Alaska watershed: Water Resources Research, v. 53, no. 9, p. 7502-7520, https://doi.org/10.1002/2016WR020033.","productDescription":"19 p.","startPage":"7502","endPage":"7520","ipdsId":"IP-081123","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"links":[{"id":369083,"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 -163.65234374999997,\n 59.80063426102869\n ],\n [\n -134.560546875,\n 50.736455137010665\n ],\n [\n -123.662109375,\n 52.74959372674114\n ],\n [\n -137.197265625,\n 64.92354174306496\n ],\n [\n -163.65234374999997,\n 59.80063426102869\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"53","issue":"9","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Beamer, Jordan","contributorId":220414,"corporation":false,"usgs":false,"family":"Beamer","given":"Jordan","affiliations":[{"id":34888,"text":"Oregon Water Resources Department","active":true,"usgs":false}],"preferred":false,"id":774924,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hill, Dave","contributorId":220415,"corporation":false,"usgs":false,"family":"Hill","given":"Dave","email":"","affiliations":[{"id":6680,"text":"Oregon State University","active":true,"usgs":false}],"preferred":false,"id":774925,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":774923,"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":774926,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kienholz, Christian","contributorId":220416,"corporation":false,"usgs":false,"family":"Kienholz","given":"Christian","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":774927,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70189067,"text":"sir20175056 - 2017 - Water-quality models to assess algal community dynamics, water quality, and fish habitat suitability for two agricultural land-use dominated lakes in Minnesota, 2014","interactions":[],"lastModifiedDate":"2017-07-21T10:09:46","indexId":"sir20175056","displayToPublicDate":"2017-07-20T00:00:00","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":"2017-5056","title":"Water-quality models to assess algal community dynamics, water quality, and fish habitat suitability for two agricultural land-use dominated lakes in Minnesota, 2014","docAbstract":"Fish habitat can degrade in many lakes due to summer blue-green algal blooms. Predictive models are needed to better manage and mitigate loss of fish habitat due to these changes. The U.S. Geological Survey (USGS), in cooperation with the Minnesota Department of Natural Resources, developed predictive water-quality models for two agricultural land-use dominated lakes in Minnesota—Madison Lake and Pearl Lake, which are part of Minnesota’s sentinel lakes monitoring program—to assess algal community dynamics, water quality, and fish habitat suitability of these two lakes under recent (2014) meteorological conditions. The interaction of basin processes to these two lakes, through the delivery of nutrient loads, were simulated using CE-QUAL-W2, a carbon-based, laterally averaged, two-dimensional water-quality model that predicts distribution of temperature and oxygen from interactions between nutrient cycling, primary production, and trophic dynamics.
The CE-QUAL-W2 models successfully predicted water temperature and dissolved oxygen on the basis of the two metrics of mean absolute error and root mean square error. For Madison Lake, the mean absolute error and root mean square error were 0.53 and 0.68 degree Celsius, respectively, for the vertical temperature profile comparisons; for Pearl Lake, the mean absolute error and root mean square error were 0.71 and 0.95 degree Celsius, respectively, for the vertical temperature profile comparisons. Temperature and dissolved oxygen were key metrics for calibration targets. These calibrated lake models also simulated algal community dynamics and water quality. The model simulations presented potential explanations for persistently large total phosphorus concentrations in Madison Lake, key differences in nutrient concentrations between these lakes, and summer blue-green algal bloom persistence.
Fish habitat suitability simulations for cool-water and warm-water fish indicated that, in general, both lakes contained a large proportion of good-growth habitat and a sustained period of optimal growth habitat in the summer, without any periods of lethal oxythermal habitat. For Madison and Pearl Lakes, examples of important cool-water fish, particularly game fish, include northern pike (Esox lucius), walleye (Sander vitreus), and black crappie (Pomoxis nigromaculatus); examples of important warm-water fish include bluegill (Lepomis macrochirus), largemouth bass (Micropterus salmoides), and smallmouth bass (Micropterus dolomieu). Sensitivity analyses were completed to understand lake response effects through the use of controlled departures on certain calibrated model parameters and input nutrient loads. These sensitivity analyses also operated as land-use change scenarios because alterations in agricultural practices, for example, could potentially increase or decrease nutrient loads.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175056","collaboration":"Prepared in cooperation with the Minnesota Department of Natural Resources","usgsCitation":"Smith, E.A., Kiesling, R.L., and Ziegeweid, J.R., 2017, Water-quality models to assess algal community dynamics, water quality, and fish habitat suitability for two agricultural land-use dominated lakes in Minnesota, 2014: U.S. Geological Survey Scientific Investigations Report 2017–5056, 65 p., https://doi.org/10.3133/sir20175056.","productDescription":"x, 65 p.","numberOfPages":"80","onlineOnly":"Y","ipdsId":"IP-079529","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"links":[{"id":344145,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5056/sir20175056.pdf","text":"Report","size":"2.69 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 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U.S. Geological Survey
2280 Woodale Drive
Mounds View, Minnesota 55112
The five saltiest springs in the Sierra Nevada in California are found between 38.5° and 38.8° N. latitude, on the South Fork American River; on Caples Creek, a tributary of the Silver Fork American River; and on the North Fork Mokelumne River. The springs issue from Cretaceous granitic rocks in the bottoms of these major canyons, between 1,200- and 2,200-m elevation. All of these springs were well known to Native Americans, who excavated meter-sized basins in the granitic rock, within which they produced salt by evaporation near at least four of the five spring sites. The spring waters are dominated by Cl, Na, and Ca; are enriched relative to seawater in Ca, Li, and As; and are depleted in SO4, Mg, and K. Tritium analyses indicate that the spring waters have had little interaction with rainfall since about 1954. The waters are apparently an old groundwater of meteoric origin that resided at depth before moving up along fractures to the surface of the exhumed granitic rocks. However, along the way these waters incorporated salts from depth, the origin of which could have been either from marine sedimentary rocks intruded by the granitic magmas or from fluid inclusions in the granitic rocks. Prolonged storage at depth fostered water-rock interactions that undoubtedly modified the fluid compositions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175053","usgsCitation":"Moore, J.G., Diggles, M.F., Evans, W.C., and Klemic, K., 2017, The saltiest springs in the Sierra Nevada, California: U.S. Geological Survey Scientific Investigations Report 2017–5053, 21 p., 2 appendixes, https://doi.org/10.3133/sir20175053.","productDescription":"v, 21 p.","numberOfPages":"32","onlineOnly":"Y","ipdsId":"IP-079045","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":344092,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5053/coverthb.jpg"},{"id":344093,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5053/sir20175053.pdf","text":"Report","size":"2.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5053"}],"country":"United States","state":"California","otherGeospatial":"Sierra Nevada","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.5,\n 39.06\n ],\n [\n -120,\n 39.06\n ],\n [\n -120,\n 38.416667\n ],\n [\n -120.5,\n 38.416667\n ],\n [\n -120.5,\n 39.06\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Volcano Science Center - Menlo Park
U.S. Geological Survey
345 Middlefield Road, MS 910
Menlo Park, CA 94025
The U.S. Fish and Wildlife Service confirmed that white sturgeon (Acipenser transmontanus) recently spawned in the lower San Joaquin River, California. Decreases in the San Francisco Bay estuary white sturgeon population have led to an increased effort to understand their migration behavior and habitat preferences. The preferred spawning habitat of other white sturgeon (for example, those in the Columbia and Klamath Rivers) is thought to be areas that have high water velocity, deep pools, and coarse bed material. Coarse bed material (pebbles and cobbles), in particular, is important for the survival of white sturgeon eggs and larvae. Knowledge of the physical characteristics of the lower San Joaquin River can be used to preserve sturgeon spawning habitat and lead to management decisions that could help increase the San Francisco Bay estuary white sturgeon population.
Between 2011 and 2014, the U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service, assessed selected reaches and tributaries of the lower river in relation to sturgeon spawning habitat by (1) describing selected spawning reaches in terms of habitat-related physical characteristics (such as water depth and velocity, channel slope, and bed material) of the lower San Joaquin River between its confluences with the Stanislaus and Merced Rivers, (2) describing variations in these physical characteristics during wet and dry years, and (3) identifying potential reasons for these variations.
The lower San Joaquin River was divided into five study reaches. Although data were collected from all study reaches, three subreaches where the USFWS collected viable eggs at multiple sites in 2011–12 from Orestimba Creek to Sturgeon Bend were of special interest. Water depth and velocity were measured using two different approaches—channel cross sections and longitudinal profiles—and data were collected using an acoustic Doppler current profiler.
During the first year of data collection (water year 2011), runoff was greatest, and gaged streamflow, measured as discharge, peaked at 875 cubic meters per second in the lower San Joaquin River. Also during that year, water velocity was generally between 0.6 and 0.9 meters per second, and depth was typically between 2.5 and 4.5 meters, but water depth exceeded 6 meters in several pools. Water year 2011 was classified as a “wet” year. Later water years were classified as either “dry” (water year 2012) or “critical” (water years 2013 and 2014). During the drier years, water was shallower, and velocities were slower. The streambed aggraded in several areas during the study. At Sturgeon Bend, for example, which had the deepest pool measured in 2011 (maximum depth was 14 meters), about 8 meters of sediment was deposited by 2014.
The bed of the lower San Joaquin River was predominately sand, except in areas downstream from the mouth of Del Puerto Creek. A large amount of sand, gravel, and cobble was deposited at the mouth of Del Puerto Creek, and in the 9.5 kilometers downstream from the mouth of Del Puerto Creek, we encountered several gravel bars and patches of gravel-size (8–64 millimeters) bed material. Del Puerto and Orestimba Creeks drain from the Coast Ranges on the west side of the river. Only small quantities of gravel-size bed material were observed in the reach downstream from Orestimba Creek, indicating Orestimba Creek does not deliver much coarse sediment to the lower San Joaquin River. Del Puerto Creek appeared to be the primary source of gravels suitable for white sturgeon spawning in the lower San Joaquin River, and thus, it is important for the long-term spawning success of sturgeon in the San Joaquin River.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175069","collaboration":"Prepared in cooperation with the United States Fish and Wildlife Service","usgsCitation":"Marineau, M.D., Wright, S.A., Whealdon-Haught, D.R., Kinzel, P.J., 2017, Physical characteristics of the lower San Joaquin River, California, in relation to white sturgeon spawning habitat, 2011–14: U.S. Geological Survey Scientific Investigation Report 2017–5069, 47 p., https://doi.org/10.3133/sir20175069.","productDescription":"vii, 47 p.","numberOfPages":"60","onlineOnly":"Y","ipdsId":"IP-051877","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":438264,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7W66HWW","text":"USGS data release","linkHelpText":"Depth and Velocity Data in the Lower San Joaquin River, California, 2011-2014"},{"id":344080,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5069/sir20175069.pdf","text":"Report","size":"16 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5069"},{"id":344079,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5069/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Joaquin River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.794677734375,\n 41.95949009892467\n ],\n [\n -121.46484375,\n 41.376808565702355\n ],\n [\n -121.97021484374999,\n 41.64007838467894\n ],\n [\n -122.58544921875,\n 41.64007838467894\n ],\n [\n -123.00292968749999,\n 41.16211393939692\n ],\n [\n -122.71728515624999,\n 40.713955826286046\n ],\n [\n -123.50830078125,\n 40.51379915504413\n ],\n [\n -123.28857421875,\n 40.01078714046552\n ],\n [\n -122.80517578125,\n 39.7240885773337\n ],\n [\n -123.1787109375,\n 39.436192999314095\n ],\n [\n -122.607421875,\n 39.11301365149975\n ],\n [\n -121.39892578125,\n 37.07271048132943\n ],\n [\n -119.81689453125,\n 34.65128519895413\n ],\n [\n -118.740234375,\n 34.50655662164561\n ],\n [\n -117.42187500000001,\n 34.994003757575776\n ],\n [\n -118.16894531249999,\n 36.26199220445664\n ],\n [\n -119.520263671875,\n 37.86618078529668\n ],\n [\n -120.28930664062499,\n 39.38526381099774\n ],\n [\n -120.091552734375,\n 39.51251701659638\n ],\n [\n -120.47607421874999,\n 40.455307212131494\n ],\n [\n -120.157470703125,\n 41.15384235711447\n ],\n [\n -120.16845703125,\n 41.983994270935625\n ],\n [\n -120.794677734375,\n 41.95949009892467\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Montana is rich in minerals, energy, and soils, as well as prairies, forests, mountains, rivers, lakes, fish, and wildlife. Many enterprises that drive the economy are based on natural resources, including tourism, hunting, fishing, agriculture, and energy development. The outdoor-recreation economy alone supports 64,000 Montana jobs and generates nearly \\$6 billion each year in economic activity.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20173052","usgsCitation":"U.S. Geological Survey, 2017, Biological and ecological science for Montana—The Treasure State: \nU.S. Geological Survey Fact Sheet 2017-3052, 2 p., https://doi.org/10.3133/fs20173052.","productDescription":"2 p.","ipdsId":"IP-087719","costCenters":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"links":[{"id":344004,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2017/3052/coverthb.jpg"},{"id":344005,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2017/3052/fs20173052.pdf","text":"Report","size":"1.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2017-3052"}],"country":"United 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\"}}]}","contact":"Ecosystems Mission Area
https://www.usgs.gov/ask/
1-888-ASK-USGS (1-888-275-8747)
Groundwater has been the primary source of domestic, agricultural, and municipal water supplies in the southwestern Mojave Desert, California, since the early 1900s. Increased demands on water supplies have caused groundwater-level declines of more than 100 feet (ft) in some areas of this desert between the 1950s and the 1990s (Stamos and others, 2001; Sneed and others, 2003). These water-level declines have caused the aquifer system to compact, resulting in land subsidence. Differential land subsidence (subsidence occurring at different rates across the landscape) can alter surface drainage routes and damage surface and subsurface infrastructure. For example, fissuring across State Route 247 at Lucerne Lake has required repairs as has pipeline infrastructure near Troy Lake.
Land subsidence within the Mojave River and Morongo Groundwater Basins of the southwestern Mojave Desert has been evaluated using InSAR, ground-based measurements, geology, and analyses of water levels between 1992 and 2009 (years in which InSAR data were collected). The results of the analyses were published in three USGS reports— Sneed and others (2003), Stamos and others (2007), and Solt and Sneed (2014). Results from the latter two reports were integrated with results from other USGS/ MWA cooperative groundwater studies into the broader scoped USGS Mojave Groundwater Resources Web site (http://ca.water.usgs.gov/ mojave/). This fact sheet combines the detailed analyses from the three subsidence reports, distills them into a longer-term context, and provides an assessment of options for future monitoring.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20173053","usgsCitation":"Brandt, Justin, and Sneed, Michelle, 2017, Land subsidence in the southwestern Mojave Desert, California, 1992–2009: U.S. Geological Survey Fact Sheet 2017-3053, 6 p., https://doi.org/10.3133/fs20173053.","productDescription":"6 p. ","ipdsId":"IP-072664","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":344070,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2017/3053/fs20173053.pdf","text":"Report","size":"1.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2017-3053"},{"id":344069,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2017/3053/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Mojave Desert","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.49053955078125,\n 34.04128062212254\n ],\n [\n -116.30126953125,\n 34.04128062212254\n ],\n [\n -116.30126953125,\n 35.099686964274724\n ],\n [\n -117.49053955078125,\n 35.099686964274724\n ],\n [\n -117.49053955078125,\n 34.04128062212254\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"U.S. Geological Survey
6000 J Street, Placer Hall,
California State University, Sacramento
Sacramento, CA 95819
https://ca.water.usgs.gov/mojave
The increasing demands on groundwater for water supply in desert areas in California and the western United States have resulted in the need to better understand groundwater sources, availability, and sustainability. This is true for a 650-square-mile area that encompasses the Antelope Valley, El Mirage Valley, and Upper Mojave River Valley groundwater basins, about 50 miles northeast of Los Angeles, California, in the western part of the Mojave Desert. These basins have been adjudicated to ensure that groundwater rights are allocated according to legal judgments. In an effort to assess if the boundary between the Antelope Valley and El Mirage Valley groundwater basins could be better defined, the U.S. Geological Survey began a cooperative study in 2014 with the Mojave Water Agency to better understand the hydrogeology in the area and investigate potential controls on groundwater flow and availability, including basement topography.
Recharge is sporadic and primarily from small ephemeral washes and streams that originate in the San Gabriel Mountains to the south; estimates range from about 400 to 1,940 acre-feet per year. Lateral underflow from adjacent basins has been considered minor in previous studies; underflow from the Antelope Valley to the El Mirage Valley groundwater basin has been estimated to be between 100 and 1,900 acre-feet per year. Groundwater discharge is primarily from pumping, mostly by municipal supply wells. Between October 2013 and September 2014, the municipal pumpage in the Antelope Valley and El Mirage Valley groundwater basins was reported to be about 800 and 2,080 acre-feet, respectively.
This study was motivated by the results from a previously completed regional gravity study, which suggested a northeast-trending subsurface basement ridge and saddle approximately 3.5 miles west of the boundary between the Antelope Valley and El Mirage Valley groundwater basins that might influence groundwater flow. To better define potential basement structures that could affect groundwater flow between the groundwater basins in the study area, gravity data were collected using more closely spaced measurements in September 2014. Groundwater-level data was gathered and collected from March 2014 through March 2015 to determine depth to water and direction of groundwater flow. The gravity and groundwater-level data showed that the saturated thickness of the alluvium was about 2,000 feet thick to the east and about 130 feet thick above the northward-trending basement ridge near Llano, California. Although it was uncertain whether the basement ridge affects the groundwater system, a potential barrier to groundwater flow could be created if the water table fell below the altitude of the basement ridge, effectively causing the area to the west of the basement ridge to become hydraulically isolated from the area to the east. In addition, the direction of regional-groundwater flow likely will be influenced by future changes in the number and distribution of pumping wells and the thickness of the saturated alluvium from which water is withdrawn. Three-dimensional animations were created to help visualize the relation between the basins’ basement topography and the groundwater system in the area. Further studies that could help to more accurately define the basins and evaluate the groundwater-flow system include exploratory drilling of multi-depth monitoring wells; collection of depth-dependent water-quality samples; and linking together existing, but separate, groundwater-flow models from the Antelope Valley and El Mirage Valley groundwater basins into a single, calibrated groundwater-flow model.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175065","collaboration":"Prepared in cooperation with the Mojave Water Agency","usgsCitation":"Stamos, C.L., Christensen, A.H., and Langenheim, V.E., 2017, Preliminary hydrogeologic assessment near the boundary of the Antelope Valley and El Mirage Valley groundwater basins, California: U.S. Geological Survey Scientific Investigations Report 2017–5065, 44 p., https://doi.org/10.3133/sir20175065.","productDescription":"Report: vii, 44 p.; 2 Figures","onlineOnly":"Y","ipdsId":"IP-064470","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":343370,"rank":4,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/sir/2017/5065/sir20175065_fig14_dewatering.mp4","text":"Figure 14.","size":"18 MB","description":"SIR 2017-5065 Animation","linkHelpText":"- Animation showing the potential dewatering of the saturated alluvium starting with the 2014–15 water-table altitude and assuming an incremental 16.4 feet (5 meter) drop per frame of the water table, near Piñon Hills, California."},{"id":343369,"rank":3,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/sir/2017/5065/sir20175065_fig13_gravity.mp4","text":"Figure 13.","size":"11 MB","description":"SIR 2017-5065 Animation","linkHelpText":"- Animation showing the altitude of the top of the basement rocks based on the gravity data and altitude of the water table in 2014–15, near Piñon Hills, California. "},{"id":343217,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5065/sir20175065.pdf","text":"Report","size":"9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5065"},{"id":343216,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5065/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Antelope Valley groundwater basin, El Mirage Valley groundwater basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.033333,\n 34.366667\n ],\n [\n -117.5,\n 34.366667\n ],\n [\n -117.5,\n 34.75\n ],\n [\n -118.033333,\n 34.75\n ],\n [\n -118.033333,\n 34.366667\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819