This research considers the applicability of different vegetation indices at 30 m resolution for mapping and monitoring desert wetland (cienega) health and spatial extent through time at Cienega Creek in southeastern Arizona, USA. Multiple stressors including the risk of decadal-scale drought, the effects of current and predicted global warming, and continued anthropogenic pressures threaten aquatic habitats in the southwest and cienegas are recognized as important sites for conservation and restoration efforts. However, cienegas present a challenge to satellite-imagery based analysis due to their small size and mixed surface cover of open water, exposed soils, and vegetation. We created time series of five well-known vegetation indices using annual Landsat Thematic Mapper (TM) images retrieved during the April–June dry season, from 1984 to 2011 to map landscape-level distribution of wetlands and monitor the temporal dynamics of individual sites. Indices included the Normalized Difference Vegetation Index (NDVI), the Soil-Adjusted Vegetation Index (SAVI), the Normalized Difference Water Index (NDWI), and the Normalized Difference Infrared Index (NDII). One topographic index, the Topographic Wetness Index (TWI), was analyzed to examine the utility of topography in mapping distribution of cienegas. Our results indicate that the NDII, calculated using Landsat TM band 5, outperforms the other indices at differentiating cienegas from riparian and upland sites, and was the best means to analyze change. As such, it offers a critical baseline for future studies that seek to extend the analysis of cienegas to other regions and time scales, and has broader applicability to the remote sensing of wetland features in arid landscapes.
","language":"English","publisher":"Taylor and Francis","doi":"10.1080/15324982.2016.1170076","usgsCitation":"Wilson, N.R., Norman, L.M., Villarreal, M.L., Gass, L., Tiller, R., and Salywon, A., 2016, Comparison of remote sensing indices for monitoring of desert cienegas: Arid Land Research and Management, v. 30, no. 4, p. 460-478, https://doi.org/10.1080/15324982.2016.1170076.","productDescription":"19 p.","startPage":"460","endPage":"478","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068692","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":470807,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/15324982.2016.1170076","text":"Publisher Index Page"},{"id":324640,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Cienega Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.5667495727539,\n 31.894319802510566\n ],\n [\n -110.5667495727539,\n 31.970512683093744\n ],\n [\n -110.5063247680664,\n 31.970512683093744\n ],\n [\n -110.5063247680664,\n 31.894319802510566\n ],\n [\n -110.5667495727539,\n 31.894319802510566\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"30","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-18","publicationStatus":"PW","scienceBaseUri":"5774e32fe4b07dd077c5fbff","contributors":{"authors":[{"text":"Wilson, Natalie R. 0000-0001-5145-1221 nrwilson@usgs.gov","orcid":"https://orcid.org/0000-0001-5145-1221","contributorId":5770,"corporation":false,"usgs":true,"family":"Wilson","given":"Natalie","email":"nrwilson@usgs.gov","middleInitial":"R.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":629791,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Norman, Laura M. 0000-0002-3696-8406 lnorman@usgs.gov","orcid":"https://orcid.org/0000-0002-3696-8406","contributorId":967,"corporation":false,"usgs":true,"family":"Norman","given":"Laura","email":"lnorman@usgs.gov","middleInitial":"M.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":629792,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Villarreal, Miguel L. 0000-0003-0720-1422 mvillarreal@usgs.gov","orcid":"https://orcid.org/0000-0003-0720-1422","contributorId":1424,"corporation":false,"usgs":true,"family":"Villarreal","given":"Miguel","email":"mvillarreal@usgs.gov","middleInitial":"L.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":629793,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gass, Leila 0000-0002-3436-262X lgass@usgs.gov","orcid":"https://orcid.org/0000-0002-3436-262X","contributorId":3770,"corporation":false,"usgs":true,"family":"Gass","given":"Leila","email":"lgass@usgs.gov","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":629794,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Tiller, Ron","contributorId":169496,"corporation":false,"usgs":false,"family":"Tiller","given":"Ron","email":"","affiliations":[{"id":25532,"text":"Arizona Department of Transportation, Environmental Planning Group","active":true,"usgs":false}],"preferred":false,"id":629795,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Salywon, Andrew","contributorId":169497,"corporation":false,"usgs":false,"family":"Salywon","given":"Andrew","email":"","affiliations":[{"id":25533,"text":"Desert Botanical Garden","active":true,"usgs":false}],"preferred":false,"id":629796,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70171123,"text":"70171123 - 2016 - Assessing the relationship between groundwater nitrate and animal feeding operations in Iowa (USA)","interactions":[],"lastModifiedDate":"2016-08-12T09:55:23","indexId":"70171123","displayToPublicDate":"2016-06-29T15:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Assessing the relationship between groundwater nitrate and animal feeding operations in Iowa (USA)","docAbstract":"Nitrate-nitrogen is a common contaminant of drinking water in many agricultural areas of the United States of America (USA). Ingested nitrate from contaminated drinking water has been linked to an increased risk of several cancers, specific birth defects, and other diseases. In this research, we assessed the relationship between animal feeding operations (AFOs) and groundwater nitrate in private wells in Iowa. We characterized AFOs by swine and total animal units and type (open, confined, or mixed), and we evaluated the number and spatial intensities of AFOs in proximity to private wells. The types of AFO indicate the extent to which a facility is enclosed by a roof. Using linear regression models, we found significant positive associations between the total number of AFOs within 2 km of a well (p trend < 0.001), number of open AFOs within 5 km of a well (p trend < 0.001), and number of mixed AFOs within 30 km of a well (p trend < 0.001) and the log nitrate concentration. Additionally, we found significant increases in log nitrate in the top quartiles for AFO spatial intensity, open AFO spatial intensity, and mixed AFO spatial intensity compared to the bottom quartile (0.171 log(mg/L), 0.319 log(mg/L), and 0.541 log(mg/L), respectively; all p < 0.001). We also explored the spatial distribution of nitrate-nitrogen in drinking wells and found significant spatial clustering of high-nitrate wells (> 5 mg/L) compared with low-nitrate (≤ 5 mg/L) wells (p = 0.001). A generalized additive model for high-nitrate status identified statistically significant areas of risk for high levels of nitrate. Adjustment for some AFO predictor variables explained a portion of the elevated nitrate risk. These results support a relationship between animal feeding operations and groundwater nitrate concentrations and differences in nitrate loss from confined AFOs vs. open or mixed types.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2016.05.130","usgsCitation":"Zirkle, K.W., Nolan, B.T., Jones, R.R., Weyer, P.J., Ward, M.H., and Wheeler, D.C., 2016, Assessing the relationship between groundwater nitrate and animal feeding operations in Iowa (USA): Science of the Total Environment, v. 566-567, p. 1062-1068, https://doi.org/10.1016/j.scitotenv.2016.05.130.","productDescription":"7 p.","startPage":"1062","endPage":"1068","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-073078","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"links":[{"id":470809,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/4980257","text":"External Repository"},{"id":324635,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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,{"id":70162402,"text":"70162402 - 2016 - Macroinvertebrate and diatom metrics as indicators of water-quality conditions in connected depression wetlands in the Mississippi Alluvial Plain","interactions":[],"lastModifiedDate":"2016-08-12T10:03:33","indexId":"70162402","displayToPublicDate":"2016-06-29T13:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1699,"text":"Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"Macroinvertebrate and diatom metrics as indicators of water-quality conditions in connected depression wetlands in the Mississippi Alluvial Plain","docAbstract":"Methods for assessing wetland conditions must be established so wetlands can be monitored and ecological services can be protected. We evaluated biological indices compiled from macroinvertebrate and diatom metrics developed primarily for streams to assess their ability to indicate water quality in connected depression wetlands. We collected water-quality and biological samples at 24 connected depressions dominated by water tupelo (Nyssa aquatica) or bald cypress (Taxodium distichum) (water depths = 0.5–1.0 m). Water quality of the least-disturbed connected depressions was characteristic of swamps in the southeastern USA, which tend to have low specific conductance, nutrient concentrations, and pH. We compared 162 macroinvertebrate metrics and 123 diatom metrics with a water-quality disturbance gradient. For most metrics, we evaluated richness, % richness, abundance, and % relative abundance values. Three of the 4 macroinvertebrate metrics that were most beneficial for identifying disturbance in connected depressions decreased along the disturbance gradient even though they normally increase relative to stream disturbance. The negative relationship to disturbance of some taxa (e.g., dipterans, mollusks, and crustaceans) that are considered tolerant in streams suggests that the tolerance scale for some macroinvertebrates can differ markedly between streams and wetlands. Three of the 4 metrics chosen for the diatom index reflected published tolerances or fit the usual perception of metric response to disturbance. Both biological indices may be useful in connected depressions elsewhere in the Mississippi Alluvial Plain Ecoregion and could have application in other wetland types. Given the paradoxical relationship of some macroinvertebrate metrics to dissolved O2 (DO), we suggest that the diatom metrics may be easier to interpret and defend for wetlands with low DO concentrations in least-disturbed conditions.
","language":"English","publisher":"The University of Chicago Press","doi":"10.1086/687605","usgsCitation":"Justus, B., Burge, D., Cobb, J., Marsico, T., and Bouldin, J., 2016, Macroinvertebrate and diatom metrics as indicators of water-quality conditions in connected depression wetlands in the Mississippi Alluvial Plain: Freshwater Science, v. 35, no. 3, p. 1049-1061, https://doi.org/10.1086/687605.","productDescription":"13 p.","startPage":"1049","endPage":"1061","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-064764","costCenters":[{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true}],"links":[{"id":324613,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Arkansas","otherGeospatial":"Cache River Watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92,\n 34.5\n ],\n [\n -92,\n 36.5\n ],\n [\n -90.5,\n 36.5\n ],\n [\n -90.5,\n 34.5\n ],\n [\n -92,\n 34.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"35","issue":"3","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5774e344e4b07dd077c5fca8","contributors":{"authors":[{"text":"Justus, Billy bjustus@usgs.gov","contributorId":152446,"corporation":false,"usgs":true,"family":"Justus","given":"Billy","email":"bjustus@usgs.gov","affiliations":[{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true}],"preferred":true,"id":589403,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burge, David","contributorId":152447,"corporation":false,"usgs":false,"family":"Burge","given":"David","affiliations":[{"id":13476,"text":"Arkansas State University, State University, AR","active":true,"usgs":false}],"preferred":false,"id":589404,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cobb, Jennifer","contributorId":152448,"corporation":false,"usgs":false,"family":"Cobb","given":"Jennifer","email":"","affiliations":[{"id":13476,"text":"Arkansas State University, State University, AR","active":true,"usgs":false}],"preferred":false,"id":589405,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Marsico, Travis","contributorId":152449,"corporation":false,"usgs":false,"family":"Marsico","given":"Travis","affiliations":[{"id":13476,"text":"Arkansas State University, State University, AR","active":true,"usgs":false}],"preferred":false,"id":589406,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bouldin, Jennifer","contributorId":152450,"corporation":false,"usgs":false,"family":"Bouldin","given":"Jennifer","email":"","affiliations":[{"id":13476,"text":"Arkansas State University, State University, AR","active":true,"usgs":false}],"preferred":false,"id":589407,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70171068,"text":"70171068 - 2016 - On the sustainability of inland fisheries: Finding a future for the forgotten","interactions":[],"lastModifiedDate":"2018-04-24T13:51:53","indexId":"70171068","displayToPublicDate":"2016-06-29T11:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":698,"text":"Ambio","active":true,"publicationSubtype":{"id":10}},"title":"On the sustainability of inland fisheries: Finding a future for the forgotten","docAbstract":"At present, inland fisheries are not often a national or regional governance priority and as a result, inland capture fisheries are undervalued and largely overlooked. As such they are threatened in both developing and developed countries. Indeed, due to lack of reliable data, inland fisheries have never been part of any high profile global fisheries assessment and are notably absent from the Sustainable Development Goals. The general public and policy makers are largely ignorant of the plight of freshwater ecosystems and the fish they support, as well as the ecosystem services generated by inland fisheries. This ignorance is particularly salient given that the current emphasis on the food-water-energy nexus often fails to include the important role that inland fish and fisheries play in food security and supporting livelihoods in low-income food deficit countries. Developing countries in Africa and Asia produce about 11 million tonnes of inland fish annually, 90 % of the global total. The role of inland fisheries goes beyond just kilocalories; fish provide important micronutrients and essentially fatty acids. In some regions, inland recreational fisheries are important, generating much wealth and supporting livelihoods. The following three key recommendations are necessary for action if inland fisheries are to become a part of the food-water-energy discussion: invest in improved valuation and assessment methods, build better methods to effectively govern inland fisheries (requires capacity building and incentives), and develop approaches to managing waters across sectors and scales. Moreover, if inland fisheries are recognized as important to food security, livelihoods, and human well-being, they can be more easily incorporated in regional, national, and global policies and agreements on water issues. Through these approaches, inland fisheries can be better evaluated and be more fully recognized in broader water resource and aquatic ecosystem planning and decision-making frameworks, enhancing their value and sustainability for the future.
","language":"English","publisher":"Springer","doi":"10.1007/s13280-016-0787-4","usgsCitation":"Cooke, S., Allison, E.H., Beard, Arlinghaus, R., Arthington, A., Bartley, D., Cowx, I.G., Fuentevilla, C., Leonard, N.J., Lorenzen, K., Lynch, A., Nguyen, V., Youn, S., Tayor, W.W., and Welcomme, R., 2016, On the sustainability of inland fisheries: Finding a future for the forgotten: Ambio, v. 45, no. 7, p. 753-764, https://doi.org/10.1007/s13280-016-0787-4.","productDescription":"12 p.","startPage":"753","endPage":"764","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069471","costCenters":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":470812,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1007/s13280-016-0787-4","text":"External Repository"},{"id":324593,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"45","issue":"7","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-16","publicationStatus":"PW","scienceBaseUri":"5774e349e4b07dd077c5fccc","chorus":{"doi":"10.1007/s13280-016-0787-4","url":"http://dx.doi.org/10.1007/s13280-016-0787-4","publisher":"Springer Nature","authors":"Cooke Steven J., Allison Edward H., Beard T. Douglas, Arlinghaus Robert, Arthington Angela H., Bartley Devin M., Cowx Ian G., Fuentevilla Carlos, Leonard Nancy J., Lorenzen Kai, Lynch Abigail J., Nguyen Vivian M., Youn So-Jung, Taylor William W., Welcomme Robin L.","journalName":"Ambio","publicationDate":"6/16/2016","auditedOn":"2/15/2017","publiclyAccessibleDate":"6/16/2016"},"contributors":{"authors":[{"text":"Cooke, Steven J.","contributorId":56132,"corporation":false,"usgs":false,"family":"Cooke","given":"Steven J.","affiliations":[{"id":36574,"text":"Carleton University, Ottawa, Ontario","active":true,"usgs":false}],"preferred":false,"id":629728,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Allison, Edward H.","contributorId":169473,"corporation":false,"usgs":false,"family":"Allison","given":"Edward","email":"","middleInitial":"H.","affiliations":[{"id":25524,"text":"School of Marine and Environmental Affairs, University of Washington, Seattle, WA, 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Two types of passive samplers, polar organic chemical integrative samplers (POCIS) and semipermeable membrane devices (SPMDs), were simultaneously deployed at four sites in the basin during Mar. 2011–Mar. 2012 to measure the presence of pesticides, polybrominated diphenyl ethers (PBDEs), and polychlorinated biphenyls (PCBs). The year-round use of passive samplers is a novel approach and offers several new insights. Currently used pesticides and legacy contaminants, including many chlorinated pesticides and PBDEs, were present throughout the year in the basin’s streams. PCBs were not detected. Time-weighted average water concentrations for the 2-month deployment periods were estimated from concentrations of chemicals measured in the passive samplers. Currently used pesticide concentrations peaked during spring and were detected beyond their seasons of expected use. Summed concentrations of legacy contaminants in Neal Creek were highest during July–Sept., the period with the lowest streamflows. Endosulfan was the only pesticide detected in passive samplers at concentrations exceeding Oregon or U.S. Environmental Protection Agency water-quality thresholds. A Sensitive Pesticide Toxicity Index (SPTI) was used to estimate the relative acute potential toxicity among sample mixtures. The acute potential toxicity of the detected mixtures was likely greater for invertebrates than for fish and for all samples in Neal Creek compared to Rogers Creek, but the indices appear to be low overall (<0.1). Endosulfans and pyrethroid insecticides were the largest contributors to the SPTIs for both sites. SPTIs of some discrete (grab) samples from the basin that were used for comparison exceeded 0.1 when some insecticides (azinphos methyl, chlorpyrifos, malathion) were detected at concentrations near or exceeding acute water-quality thresholds. Early life stages and adults of several sensitive fish species, including salmonids, are present in surface waters of the basin throughout the year, including during periods of peak estimated potential toxicity. Based on these data, direct toxicity to salmonids from in-stream pesticide exposure is unlikely, but indirect impacts (reduced fitness due to cumulative exposures or negative impacts to invertebrate prey populations) are unknown.
","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0158175","usgsCitation":"Temple, W.B., Morace, J.L., Nilsen, E.B., Alvarez, D., and Masterson, K., 2016, Year-round monitoring of contaminants in Neal and Rogers Creeks, Hood River Basin, Oregon, 2011-12, and assessment of risks to salmonids: PLoS ONE, v. 11, no. 6, 32 p., https://doi.org/10.1371/journal.pone.0158175.","productDescription":"32 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070114","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":470814,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0158175","text":"Publisher Index Page"},{"id":324651,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Green Point Creek, Hood River basin, Neal Creek, Rogers Creek, West Fork Hood River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121,\n 46\n ],\n [\n -121,\n 45\n ],\n [\n -122,\n 45\n ],\n [\n -122,\n 46\n ],\n [\n -121,\n 46\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","issue":"6","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-27","publicationStatus":"PW","scienceBaseUri":"5774e35ce4b07dd077c5fd60","contributors":{"authors":[{"text":"Temple, Whitney B. wbtemple@usgs.gov","contributorId":4488,"corporation":false,"usgs":true,"family":"Temple","given":"Whitney","email":"wbtemple@usgs.gov","middleInitial":"B.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":641307,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Morace, Jennifer L. 0000-0002-8132-4044 jlmorace@usgs.gov","orcid":"https://orcid.org/0000-0002-8132-4044","contributorId":945,"corporation":false,"usgs":true,"family":"Morace","given":"Jennifer","email":"jlmorace@usgs.gov","middleInitial":"L.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":641308,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nilsen, Elena B. 0000-0002-0104-6321 enilsen@usgs.gov","orcid":"https://orcid.org/0000-0002-0104-6321","contributorId":923,"corporation":false,"usgs":true,"family":"Nilsen","given":"Elena","email":"enilsen@usgs.gov","middleInitial":"B.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":641309,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Alvarez, David 0000-0002-6918-2709 dalvarez@usgs.gov","orcid":"https://orcid.org/0000-0002-6918-2709","contributorId":150499,"corporation":false,"usgs":true,"family":"Alvarez","given":"David","email":"dalvarez@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":641310,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Masterson, Kevin","contributorId":172573,"corporation":false,"usgs":false,"family":"Masterson","given":"Kevin","email":"","affiliations":[{"id":27064,"text":"Oregon Department of Environmental Quality","active":true,"usgs":false}],"preferred":false,"id":641311,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70210807,"text":"70210807 - 2016 - Yellowstone River Compact Commission sixty-fifth annual report, 2016","interactions":[],"lastModifiedDate":"2020-06-29T15:11:20.447769","indexId":"70210807","displayToPublicDate":"2016-06-29T10:03:17","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5883,"text":"Cooperator Report","active":true,"publicationSubtype":{"id":1}},"displayTitle":"Yellowstone River Compact Commission Sixty-Fifth Annual Report, 2016","title":"Yellowstone River Compact Commission sixty-fifth annual report, 2016","docAbstract":"No abstract available.
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","language":"English","publisher":"Pergamon Press","doi":"10.1016/j.marpolbul.2016.02.076","usgsCitation":"Slonecker, E.T., Jones, D.K., and Pellerin, B.A., 2016, The new Landsat 8 potential for remote sensing of colored dissolved organic matter (CDOM): Marine Pollution Bulletin, v. 107, no. 2, p. 518-527, https://doi.org/10.1016/j.marpolbul.2016.02.076.","productDescription":"10 p.","startPage":"518","endPage":"527","ipdsId":"IP-069654","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":470815,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.marpolbul.2016.02.076","text":"Publisher Index Page"},{"id":438605,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7125QQM","text":"USGS data release","linkHelpText":"CDOM/fDOM and Landsat 8 Comparisons"},{"id":330242,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"107","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5809d7c4e4b0f497e78fca62","chorus":{"doi":"10.1016/j.marpolbul.2016.02.076","url":"http://dx.doi.org/10.1016/j.marpolbul.2016.02.076","publisher":"Elsevier BV","authors":"Slonecker E. Terrence, Jones Daniel K., Pellerin Brian A.","journalName":"Marine Pollution Bulletin","publicationDate":"6/2016","auditedOn":"3/21/2016","publiclyAccessibleDate":"3/4/2016"},"contributors":{"authors":[{"text":"Slonecker, E. Terrence 0000-0002-5793-0503 tslonecker@usgs.gov","orcid":"https://orcid.org/0000-0002-5793-0503","contributorId":168591,"corporation":false,"usgs":true,"family":"Slonecker","given":"E.","email":"tslonecker@usgs.gov","middleInitial":"Terrence","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":36171,"text":"National Civil Applications Center","active":true,"usgs":true}],"preferred":true,"id":651634,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, Daniel K. 0000-0003-0724-8001 dkjones@usgs.gov","orcid":"https://orcid.org/0000-0003-0724-8001","contributorId":4959,"corporation":false,"usgs":true,"family":"Jones","given":"Daniel","email":"dkjones@usgs.gov","middleInitial":"K.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":651652,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pellerin, Brian A. bpeller@usgs.gov","contributorId":1451,"corporation":false,"usgs":true,"family":"Pellerin","given":"Brian","email":"bpeller@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":false,"id":651653,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70182793,"text":"70182793 - 2016 - Effects of pulse and press drying disturbance on benthic stream communities","interactions":[],"lastModifiedDate":"2017-03-01T11:33:25","indexId":"70182793","displayToPublicDate":"2016-06-29T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1699,"text":"Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"Effects of pulse and press drying disturbance on benthic stream communities","docAbstract":"Natural disturbance is an integral component of most ecosystems and occurs in 3 different forms: pulse, press, and ramp. In lotic ecosystems, seasonal drought is a major form of disturbance, particularly in intermittent headwater streams, which often are reduced to pools that serve as refuges for biota. We used simulated intermittent stream pools to compare the effects of control, pulse, and press drying on growth and survival in 3 fish species (Lepomis megalotis, Campostoma anomalum, and Etheostoma spectabile) commonly found together in drought-prone streams in the Ozark Highlands, USA. We also compared effects on benthic community structure, including periphyton and chironomid density and sediment in deep (permanently watered) and shallow (intermittently dewatered) habitat. Only one species, L. megalotis, showed a significant reduction in length and mass growth in press drying compared with control treatments. Drying and type of drying had no effect on survival of any fish species. Drying and type of drying had strong overall effects on periphyton growth in shallow habitats, where ash-free dry mass decreased and the autotrophic index (the ratio of chlorophyll a to total biomass) increased significantly in drying relative to control and in press relative to pulse treatments. Drying negatively affected sediment accumulation in shallow habitat and chironomid density in deep habitat. Drying in intermittent streams has species-dependent effects on fish growth and benthic structure, and pulse and press drying differ in their effects on periphyton in these systems. These effects may have important consequences in seasonally drying streams as anthropogenic influence on stream drying increases.
","language":"English","publisher":"University of Chicago Press","doi":"10.1086/687843","usgsCitation":"Lynch, D.T., and Magoulick, D.D., 2016, Effects of pulse and press drying disturbance on benthic stream communities: Freshwater Science, v. 35, no. 3, p. 998-1009, https://doi.org/10.1086/687843.","productDescription":"12 p. ","startPage":"998","endPage":"1009","ipdsId":"IP-059893","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":336737,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"35","issue":"3","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58b7eba8e4b01ccd5500bb1d","contributors":{"authors":[{"text":"Lynch, Dustin T.","contributorId":145645,"corporation":false,"usgs":false,"family":"Lynch","given":"Dustin","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":680399,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Magoulick, Daniel D. 0000-0001-9665-5957 danmag@usgs.gov","orcid":"https://orcid.org/0000-0001-9665-5957","contributorId":2513,"corporation":false,"usgs":true,"family":"Magoulick","given":"Daniel","email":"danmag@usgs.gov","middleInitial":"D.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":673765,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70175475,"text":"70175475 - 2016 - Increased water deficit decreases Douglas fir growth throughout western US forests","interactions":[],"lastModifiedDate":"2016-08-26T11:04:58","indexId":"70175475","displayToPublicDate":"2016-06-28T18:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3165,"text":"Proceedings of the National Academy of Sciences of the United States of America","active":true,"publicationSubtype":{"id":10}},"title":"Increased water deficit decreases Douglas fir growth throughout western US forests","docAbstract":"Changes in tree growth rates can affect tree mortality and forest feedbacks to the global carbon cycle. As air temperature increases, evaporative demand also increases, increasing effective drought in forest ecosystems. Using a spatially comprehensive network of Douglas-fir (Pseudotsuga menziesii) chronologies from 122 locations that experience distinctly different climate in the western United States, we show that increased temperature decreases growth via vapor pressure deficit (VPD) across all latitudes. Under an ensemble of global circulation models, we project an increase in both the mean VPD associated with the lowest growth extremes and the probability of exceeding these VPD values. As temperature continues to increase in future decades, we can expect deficit-related stress to increase and consequently Douglas-fir growth to decrease throughout its US range.
","language":"English","publisher":"National Academy of Sciences of the United States","doi":"10.1073/pnas.1602384113","usgsCitation":"Restaino, C.M., Peterson, D.L., and Littell, J.S., 2016, Increased water deficit decreases Douglas fir growth throughout western US forests: Proceedings of the National Academy of Sciences of the United States of America, v. 113, no. 34, p. 9557-9562, https://doi.org/10.1073/pnas.1602384113.","productDescription":"6 p.","startPage":"9557","endPage":"9562","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-073677","costCenters":[{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true}],"links":[{"id":470816,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/5003285","text":"External Repository"},{"id":326464,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -128.2763671875,\n 51.536085601784755\n ],\n [\n -103.84277343749999,\n 50.401515322782366\n ],\n [\n -101.689453125,\n 38.37611542403604\n ],\n [\n -102.5244140625,\n 33.61461929233378\n ],\n [\n -104.1064453125,\n 31.31610138349565\n ],\n [\n -120.9375,\n 32.80574473290688\n ],\n [\n -125.2880859375,\n 39.16414104768742\n ],\n [\n -128.80371093749997,\n 50.62507306341435\n ],\n [\n -128.2763671875,\n 51.536085601784755\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"113","issue":"34","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-08-08","publicationStatus":"PW","scienceBaseUri":"57aef33ee4b0fc09faae0388","contributors":{"authors":[{"text":"Restaino, Christina M","contributorId":173657,"corporation":false,"usgs":false,"family":"Restaino","given":"Christina","email":"","middleInitial":"M","affiliations":[{"id":7214,"text":"University of California, Davis","active":true,"usgs":false}],"preferred":false,"id":645376,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peterson, David L.","contributorId":94643,"corporation":false,"usgs":false,"family":"Peterson","given":"David","email":"","middleInitial":"L.","affiliations":[{"id":12647,"text":"U.S. Forest Service, Pacific Northwest Research Station","active":true,"usgs":false}],"preferred":false,"id":645377,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Littell, Jeremy S. 0000-0002-5302-8280 jlittell@usgs.gov","orcid":"https://orcid.org/0000-0002-5302-8280","contributorId":4428,"corporation":false,"usgs":true,"family":"Littell","given":"Jeremy","email":"jlittell@usgs.gov","middleInitial":"S.","affiliations":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":645375,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70173894,"text":"70173894 - 2016 - Seasonal Variability in Vadose zone biodegradation at a crude oil pipeline rupture site","interactions":[],"lastModifiedDate":"2018-08-09T12:03:11","indexId":"70173894","displayToPublicDate":"2016-06-28T17:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3674,"text":"Vadose Zone Journal","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal Variability in Vadose zone biodegradation at a crude oil pipeline rupture site","docAbstract":"Understanding seasonal changes in natural attenuation processes is critical for evaluating source-zone longevity and informing management decisions. The seasonal variations of natural attenuation were investigated through measurements of surficial CO2 effluxes, shallow soil CO2 radiocarbon contents, subsurface gas concentrations, soil temperature, and volumetric water contents during a 2-yr period. Surficial CO2 effluxes varied seasonally, with peak values of total soil respiration (TSR) occurring in the late spring and summer. Efflux and radiocarbon data indicated that the fractional contributions of natural soil respiration (NSR) and contaminant soil respiration (CSR) to TSR varied seasonally. The NSR dominated in the spring and summer, and CSR dominated in the fall and winter. Subsurface gas concentrations also varied seasonally, with peak values of CO2 and CH4 occurring in the fall and winter. Vadose zone temperatures and subsurface CO2 concentrations revealed a correlation between contaminant respiration and temperature. A time lag of 5 to 7 mo between peak subsurface CO2 concentrations and peak surface efflux is consistent with travel-time estimates for subsurface gas migration. Periods of frozen soils coincided with depressed surface CO2 effluxes and elevated CO2 concentrations, pointing to the temporary presence of an ice layer that inhibited gas transport. Quantitative reactive transport simulations demonstrated aspects of the conceptual model developed from field measurements. Overall, results indicated that source-zone natural attenuation (SZNA) rates and gas transport processes varied seasonally and that the average annual SZNA rate estimated from periodic surface efflux measurements is 60% lower than rates determined from measurements during the summer.
","language":"English","publisher":"Soil Science Society of America","publisherLocation":"Fitchburg, WI","doi":"10.2136/vzj2015.09.0125","usgsCitation":"Sihota, N.J., Trost, J.J., Bekins, B., Berg, A.M., Delin, G.N., Mason, B.E., Warren, E., and Mayer, K.U., 2016, Seasonal Variability in Vadose zone biodegradation at a crude oil pipeline rupture site: Vadose Zone Journal, v. 15, no. 5, 14 p., https://doi.org/10.2136/vzj2015.09.0125.","productDescription":"14 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057205","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":324558,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"15","issue":"5","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-13","publicationStatus":"PW","scienceBaseUri":"577391a7e4b07657d1a88bd8","contributors":{"authors":[{"text":"Sihota, Natasha J.","contributorId":46431,"corporation":false,"usgs":true,"family":"Sihota","given":"Natasha","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":638902,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Trost, Jared J. 0000-0003-0431-2151 jtrost@usgs.gov","orcid":"https://orcid.org/0000-0003-0431-2151","contributorId":3749,"corporation":false,"usgs":true,"family":"Trost","given":"Jared","email":"jtrost@usgs.gov","middleInitial":"J.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":638901,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bekins, Barbara 0000-0002-1411-6018 babekins@usgs.gov","orcid":"https://orcid.org/0000-0002-1411-6018","contributorId":139407,"corporation":false,"usgs":true,"family":"Bekins","given":"Barbara","email":"babekins@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":638903,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Berg, Andrew M. 0000-0001-9312-240X aberg@usgs.gov","orcid":"https://orcid.org/0000-0001-9312-240X","contributorId":5642,"corporation":false,"usgs":true,"family":"Berg","given":"Andrew","email":"aberg@usgs.gov","middleInitial":"M.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":638904,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Delin, Geoffrey N. 0000-0001-7991-6158 delin@usgs.gov","orcid":"https://orcid.org/0000-0001-7991-6158","contributorId":2610,"corporation":false,"usgs":true,"family":"Delin","given":"Geoffrey","email":"delin@usgs.gov","middleInitial":"N.","affiliations":[{"id":5063,"text":"Central Water Science Field Team","active":true,"usgs":true}],"preferred":true,"id":638905,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mason, Brent E. bmason@usgs.gov","contributorId":5196,"corporation":false,"usgs":true,"family":"Mason","given":"Brent","email":"bmason@usgs.gov","middleInitial":"E.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":638906,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Warren, Ean ewarren@usgs.gov","contributorId":1351,"corporation":false,"usgs":true,"family":"Warren","given":"Ean","email":"ewarren@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":638907,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Mayer, K. Ulrich","contributorId":151069,"corporation":false,"usgs":false,"family":"Mayer","given":"K.","email":"","middleInitial":"Ulrich","affiliations":[{"id":18176,"text":"Department of Earth and Ocean Science, University of British Columbia, Vancouver, British Columbia, Canada","active":true,"usgs":false}],"preferred":false,"id":638908,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70170411,"text":"70170411 - 2016 - Spatiotemporal patterns of mercury accumulation in lake sediments of western North America","interactions":[],"lastModifiedDate":"2018-08-09T12:04:23","indexId":"70170411","displayToPublicDate":"2016-06-28T16:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Spatiotemporal patterns of mercury accumulation in lake sediments of western North America","docAbstract":"For the Western North America Mercury Synthesis, we compiled mercury records from 165 dated sediment cores from 138 natural lakes across western North America. Lake sediments are accepted as faithful recorders of historical mercury accumulation rates, and regional and sub-regional temporal and spatial trends were analyzed with descriptive and inferential statistics. Mercury accumulation rates in sediments have increased, on average, four times (4×) from 1850 to 2000 and continue to increase by approximately 0.2 μg/m2 per year. Lakes with the greatest increases were influenced by the Flin Flon smelter, followed by lakes directly affected by mining and wastewater discharges. Of lakes not directly affected by point sources, there is a clear separation in mercury accumulation rates between lakes with no/little watershed development and lakes with extensive watershed development for agricultural and/or residential purposes. Lakes in the latter group exhibited a sharp increase in mercury accumulation rates with human settlement, stabilizing after 1950 at five times (5×) 1850 rates. Mercury accumulation rates in lakes with no/little watershed development were controlled primarily by relative watershed size prior to 1850, and since have exhibited modest increases (in absolute terms and compared to that described above) associated with (regional and global) industrialization. A sub-regional analysis highlighted that in the ecoregion Northwestern Forest Mountains, <1% of mercury deposited to watersheds is delivered to lakes. Research is warranted to understand whether mountainous watersheds act as permanent sinks for mercury or if export of “legacy” mercury (deposited in years past) will delay recovery when/if emissions reductions are achieved.
Mercury (Hg) is considered a contaminant of global concern for coastal environments due to its toxicity, widespread occurrence in sediment, and bioaccumulation in tissue. Coastal New Jersey, USA, is characterized by shallow bays and wetlands that provide critical habitat for wildlife but share space with expanding urban landscapes. This study was designed as an assessment of the magnitude and distribution of Hg in coastal New Jersey sediments and critical species using publicly available data to highlight potential data gaps. Mercury concentrations in estuary sediments can exceed 2 μg/g and correlate with concentrations of other metals. Based on existing data, the concentrations of Hg in mussels in southern New Jersey are comparable to those observed in other urbanized Atlantic Coast estuaries. Lack of methylmercury data for sediments, other media, and tissues are data gaps needing to be filled for a clearer understanding of the impacts of Hg inputs to the ecosystem.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.marpolbul.2016.04.027","usgsCitation":"Ng, K., Szabo, Z., Reilly, P.A., Barringer, J., and Smalling, K., 2016, An assessment of mercury in estuarine sediment and tissue in Southern New Jersey using public domain data: Marine Pollution Bulletin, v. 107, no. 1, p. 22-35, https://doi.org/10.1016/j.marpolbul.2016.04.027.","productDescription":"14 p.","startPage":"22","endPage":"35","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069013","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":470819,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.marpolbul.2016.04.027","text":"Publisher Index Page"},{"id":324536,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Jersey","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.7015380859375,\n 39.24714385893248\n ],\n [\n -74.7015380859375,\n 40.12009038025332\n ],\n [\n -74.00665283203124,\n 40.12009038025332\n ],\n [\n -74.00665283203124,\n 39.24714385893248\n ],\n [\n -74.7015380859375,\n 39.24714385893248\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"107","issue":"1","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"577391a2e4b07657d1a88bbe","contributors":{"authors":[{"text":"Ng, Kara","contributorId":169541,"corporation":false,"usgs":false,"family":"Ng","given":"Kara","email":"","affiliations":[{"id":25560,"text":"The City College of New York, Division of Science","active":true,"usgs":false}],"preferred":false,"id":629961,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Szabo, Zoltan 0000-0002-0760-9607 zszabo@usgs.gov","orcid":"https://orcid.org/0000-0002-0760-9607","contributorId":138827,"corporation":false,"usgs":true,"family":"Szabo","given":"Zoltan","email":"zszabo@usgs.gov","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":629960,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Reilly, Pamela A. 0000-0002-2937-4490 jankowsk@usgs.gov","orcid":"https://orcid.org/0000-0002-2937-4490","contributorId":653,"corporation":false,"usgs":true,"family":"Reilly","given":"Pamela","email":"jankowsk@usgs.gov","middleInitial":"A.","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":629962,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barringer, Julia jbarring@usgs.gov","contributorId":169542,"corporation":false,"usgs":true,"family":"Barringer","given":"Julia","email":"jbarring@usgs.gov","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":true,"id":629963,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Smalling, Kelly L. 0000-0002-1214-4920 ksmall@usgs.gov","orcid":"https://orcid.org/0000-0002-1214-4920","contributorId":149769,"corporation":false,"usgs":true,"family":"Smalling","given":"Kelly L. ","email":"ksmall@usgs.gov","affiliations":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"preferred":false,"id":629964,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70169031,"text":"70169031 - 2016 - The role of ocean tides on groundwater-surface water exchange in a mangrove-dominated estuary: Shark River Slough, Florida Coastal Everglades, USA","interactions":[],"lastModifiedDate":"2025-05-13T16:48:37.177037","indexId":"70169031","displayToPublicDate":"2016-06-28T15:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1584,"text":"Estuaries and Coasts","active":true,"publicationSubtype":{"id":10}},"title":"The role of ocean tides on groundwater-surface water exchange in a mangrove-dominated estuary: Shark River Slough, Florida Coastal Everglades, USA","docAbstract":"Low-relief environments like the Florida Coastal Everglades (FCE) have complicated hydrologic systems where surface water and groundwater processes are intimately linked yet hard to separate. Fluid exchange within these lowhydraulic-gradient systems can occur across broad spatial and temporal scales, with variable contributions to material transport and transformation. Identifying and assessing the scales at which these processes operate is essential for accurate evaluations of how these systems contribute to global biogeochemical cycles. The distribution of 222Rn and 223,224,226Ra have complex spatial patterns along the Shark River Slough estuary (SRSE), Everglades, FL. High-resolution time-series measurements of 222Rn activity, salinity, and water level were used to quantify processes affecting radon fluxes out of the mangrove forest over a tidal cycle. Based on field data, tidal pumping through an extensive network of crab burrows in the lower FCE provides the best explanation for the high radon and fluid fluxes. Burrows are irrigated during rising tides when radon and other dissolved constituents are released from the mangrove soil. Flushing efficiency of the burrows—defined as the tidal volume divided by the volume of burrows— estimated for the creek drainage area vary seasonally from 25 (wet season) to 100 % (dry season) in this study. The tidal pumping of the mangrove forest soil acts as a significant vector for exchange between the forest and the estuary. Processes that enhance exchange of O2 and other materials across the sediment-water interface could have a profound impact on the environmental response to larger scale processes such as sea level rise and climate change. Compounding the material budgets of the SRSE are additional inputs from groundwater from the Biscayne Aquifer, which were identified using radium isotopes. Quantification of the deep groundwater component is not obtainable, but isotopic data suggest a more prevalent signal in the dry season. These findings highlight the important role that both tidal- and seasonal-scale forcings play on groundwater movement in low-gradient hydrologic systems.
","language":"English","publisher":"Springer","doi":"10.1007/s12237-016-0079-z","usgsCitation":"Smith, C.G., Price, R.M., Swarzenski, P.W., and Stalker, J.C., 2016, The role of ocean tides on groundwater-surface water exchange in a mangrove-dominated estuary: Shark River Slough, Florida Coastal Everglades, USA: Estuaries and Coasts, v. 39, no. 6, p. 1600-1616, https://doi.org/10.1007/s12237-016-0079-z.","productDescription":"17 p.","startPage":"1600","endPage":"1616","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067122","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":324525,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.3482666015625,\n 25.175116531621764\n ],\n [\n -81.3482666015625,\n 25.76526690492097\n ],\n [\n -80.4364013671875,\n 25.76526690492097\n ],\n [\n -80.4364013671875,\n 25.175116531621764\n ],\n [\n -81.3482666015625,\n 25.175116531621764\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"39","issue":"6","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2016-05-26","publicationStatus":"PW","scienceBaseUri":"577391a8e4b07657d1a88bdc","contributors":{"authors":[{"text":"Smith, Christopher G. 0000-0002-8075-4763 cgsmith@usgs.gov","orcid":"https://orcid.org/0000-0002-8075-4763","contributorId":3410,"corporation":false,"usgs":true,"family":"Smith","given":"Christopher","email":"cgsmith@usgs.gov","middleInitial":"G.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":622616,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Price, Rene M.","contributorId":52880,"corporation":false,"usgs":true,"family":"Price","given":"Rene","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":622617,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Swarzenski, Peter W. 0000-0003-0116-0578 pswarzen@usgs.gov","orcid":"https://orcid.org/0000-0003-0116-0578","contributorId":1070,"corporation":false,"usgs":true,"family":"Swarzenski","given":"Peter","email":"pswarzen@usgs.gov","middleInitial":"W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":622618,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Stalker, Jeremy C.","contributorId":167541,"corporation":false,"usgs":false,"family":"Stalker","given":"Jeremy","email":"","middleInitial":"C.","affiliations":[{"id":24739,"text":"Jacksonville State University","active":true,"usgs":false}],"preferred":false,"id":622619,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70170667,"text":"70170667 - 2016 - Characterizing supraglacial meltwater channel hydraulics on the Greenland Ice Sheet from in situ observations","interactions":[],"lastModifiedDate":"2016-11-09T10:11:38","indexId":"70170667","displayToPublicDate":"2016-06-28T13:15:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1425,"text":"Earth Surface Processes and Landforms","active":true,"publicationSubtype":{"id":10}},"title":"Characterizing supraglacial meltwater channel hydraulics on the Greenland Ice Sheet from in situ observations","docAbstract":"Supraglacial rivers on the Greenland ice sheet (GrIS) transport large volumes of surface meltwater toward the ocean, yet have received relatively little direct research. This study presents field observations of channel width, depth, velocity, and water surface slope for nine supraglacial channels on the southwestern GrIS collected between 23 July and 20 August, 2012. Field sites are located up to 74 km inland and span 494-1485 m elevation, and contain measured discharges larger than any previous in situ study: from 0.006 to 23.12 m3/s in channels 0.20 to 20.62 m wide. All channels were deeply incised with near vertical banks, and hydraulic geometry results indicate that supraglacial channels primarily accommodate greater discharges by increasing velocity. Smaller streams had steeper water surface slopes (0.74-8.83%) than typical in terrestrial settings, yielding correspondingly high velocities (0.40-2.60 m/s) and Froude numbers (0.45-3.11) with supercritical flow observed in 54% of measurements. Derived Manning's n values were larger and more variable than anticipated from channels of uniform substrate, ranging from 0.009 to 0.154 with a mean value of 0.035 +/- 0.027 despite the absence of sediment, debris, or other roughness elements. Ubiquitous micro-depressions in shallow sections of the channel bed may explain some of these roughness values. However, we find that other, unobserved sources of flow resistance likely contributed to these elevated n values: future work should explicitly consider additional sources of flow resistance beyond bed roughness in supraglacial channels. We conclude that hydraulic modelling for these channels must allow for both sub- and supercritical flow, and most importantly must refrain from assuming that all ice-substrate channels exhibit similar hydraulic behavior, especially for Froude numbers and Manning's n. Finally, this study highlights that further theoretical and empirical work on supraglacial channel hydraulics is necessary before broad scale understanding of ice sheet hydrology can be achieved. This article is protected by copyright. All rights reserved.
","language":"English","publisher":"John Wiley & Sons","doi":"10.1002/esp.3977","usgsCitation":"Gleason, C.J., Smith, L., Chu, V.W., Legleiter, C.J., Pitcher, L.H., Overstreet, B.T., Rennermalm, A.K., Forster, R.R., and Yang, K., 2016, Characterizing supraglacial meltwater channel hydraulics on the Greenland Ice Sheet from in situ observations: Earth Surface Processes and Landforms, v. 41, no. 14, p. 2111-2122, https://doi.org/10.1002/esp.3977.","productDescription":"12 p.","startPage":"2111","endPage":"2122","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-075253","costCenters":[{"id":5044,"text":"National Research Program - Central 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PSC"},"noUsgsAuthors":false,"publicationDate":"2016-07-10","publicationStatus":"PW","scienceBaseUri":"577391a2e4b07657d1a88bc0","contributors":{"authors":[{"text":"Gleason, Colin J.","contributorId":169003,"corporation":false,"usgs":false,"family":"Gleason","given":"Colin","email":"","middleInitial":"J.","affiliations":[{"id":13022,"text":"Department of Geography, University of California, Los Angeles","active":true,"usgs":false}],"preferred":false,"id":628024,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Smith, Laurence C.","contributorId":169004,"corporation":false,"usgs":false,"family":"Smith","given":"Laurence C.","affiliations":[{"id":13022,"text":"Department of Geography, University of California, Los Angeles","active":true,"usgs":false}],"preferred":false,"id":628025,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Chu, Vena W.","contributorId":169005,"corporation":false,"usgs":false,"family":"Chu","given":"Vena","email":"","middleInitial":"W.","affiliations":[{"id":12626,"text":"Department of Geography, University of California, Berkeley, CA 94720, USA","active":true,"usgs":false}],"preferred":false,"id":628026,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Legleiter, Carl J. 0000-0003-0940-8013 cjl@usgs.gov","orcid":"https://orcid.org/0000-0003-0940-8013","contributorId":169002,"corporation":false,"usgs":true,"family":"Legleiter","given":"Carl","email":"cjl@usgs.gov","middleInitial":"J.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":628023,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pitcher, Lincoln H.","contributorId":169006,"corporation":false,"usgs":false,"family":"Pitcher","given":"Lincoln","email":"","middleInitial":"H.","affiliations":[{"id":13022,"text":"Department of Geography, University of California, Los Angeles","active":true,"usgs":false}],"preferred":false,"id":628027,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Overstreet, Brandon T. 0000-0001-7845-6671","orcid":"https://orcid.org/0000-0001-7845-6671","contributorId":63257,"corporation":false,"usgs":true,"family":"Overstreet","given":"Brandon","email":"","middleInitial":"T.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":false,"id":628028,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Rennermalm, Asa K.","contributorId":169007,"corporation":false,"usgs":false,"family":"Rennermalm","given":"Asa","email":"","middleInitial":"K.","affiliations":[{"id":25395,"text":"Department of Geography, Rutgers University, New Brunswick","active":true,"usgs":false}],"preferred":false,"id":628029,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Forster, Richard R.","contributorId":169008,"corporation":false,"usgs":false,"family":"Forster","given":"Richard","email":"","middleInitial":"R.","affiliations":[{"id":25396,"text":"Department of Geography, University of Utah","active":true,"usgs":false}],"preferred":false,"id":628030,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Yang, Kang","contributorId":169009,"corporation":false,"usgs":false,"family":"Yang","given":"Kang","email":"","affiliations":[{"id":13022,"text":"Department of Geography, University of California, Los Angeles","active":true,"usgs":false}],"preferred":false,"id":628031,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70173940,"text":"70173940 - 2016 - Geology and biology of the \"Sticky Grounds,\" shelf-margin carbonate mounds, and mesophotic ecosystem in the eastern Gulf of Mexico","interactions":[],"lastModifiedDate":"2016-07-22T13:39:59","indexId":"70173940","displayToPublicDate":"2016-06-28T13:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1333,"text":"Continental Shelf Research","active":true,"publicationSubtype":{"id":10}},"title":"Geology and biology of the \"Sticky Grounds,\" shelf-margin carbonate mounds, and mesophotic ecosystem in the eastern Gulf of Mexico","docAbstract":"Shelf-margin carbonate mounds in water depths of 116–135 m in the eastern Gulf of Mexico along the central west Florida shelf were investigated using swath bathymetry, side-scan sonar, sub-bottom imaging, rock dredging, and submersible dives. These enigmatic structures, known to fisherman as the “Sticky Grounds”, trend along slope, are 5–15 m in relief with base diameters of 5–30 m, and suggest widespread potential for mesophotic reef habitat along the west Florida outer continental shelf. Possible origins are sea-level lowstand coral patch reefs, oyster reefs, or perhaps more recent post-lowstand biohermal development. Rock dredging recovered bioeroded carbonate-rock facies comprised of bored and cemented bioclastics. Rock sample components included calcified worm tubes, pelagic sediment, and oysters normally restricted to brackish nearshore areas. Several reef sites were surveyed at the Sticky Grounds during a cruise in August 2010 with the R/V Seward Johnson using the Johnson-Sea-Link II submersible to ground truth the swath-sonar maps and to quantify and characterize the benthic habitats, benthic macrofauna, fish populations, and coral/sponge cover. This study characterizes for the first time this mesophotic reef ecosystem and associated fish populations, and analyzes the interrelationships of the fish assemblages, benthic habitats and invertebrate biota. These highly eroded rock mounds provide extensive hard-bottom habitat for reef invertebrate species as well as essential fish habitat for reef fish and commercially/recreationally important fish species. The extent and significance of associated living resources with these bottom types is particularly important in light of the 2010 Deepwater Horizon oil spill in the northeastern Gulf and the proximity of the Loop Current. Mapping the distribution of these mesophotic-depth ecosystems is important for quantifying essential fish habitat and describing benthic resources. These activities can improve ecosystem management and planning of future oil and gas activities in this outer continental shelf region.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.csr.2016.06.015","usgsCitation":"Locker, S., Reed, J.K., Farrington, S., Harter, S., Hine, A.C., and Dunn, S., 2016, Geology and biology of the \"Sticky Grounds,\" shelf-margin carbonate mounds, and mesophotic ecosystem in the eastern Gulf of Mexico: Continental Shelf Research, v. 125, p. 71-87, https://doi.org/10.1016/j.csr.2016.06.015.","productDescription":"17 p.","startPage":"71","endPage":"87","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070404","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":470821,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.csr.2016.06.015","text":"Publisher Index Page"},{"id":324506,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -86.044921875,\n 30.06909396443887\n ],\n [\n -85.4296875,\n 29.420460341013133\n ],\n [\n -84.4189453125,\n 29.573457073017593\n ],\n [\n -83.935546875,\n 29.38217507514529\n ],\n [\n -83.4521484375,\n 28.76765910569123\n ],\n [\n -83.27636718749999,\n 28.033197847676377\n ],\n [\n -82.3974609375,\n 26.509904531413927\n ],\n [\n -82.08984375,\n 25.760319754713887\n ],\n [\n -82.6611328125,\n 25.284437746983055\n ],\n [\n -84.0234375,\n 24.886436490787712\n ],\n [\n -84.9462890625,\n 25.363882272740256\n ],\n [\n -86.0009765625,\n 26.27371402440643\n ],\n [\n -87.14355468749999,\n 26.902476886279807\n ],\n [\n -88.4619140625,\n 27.21555620902969\n ],\n [\n -89.912109375,\n 27.176469131898898\n ],\n [\n -91.4501953125,\n 26.86328062676624\n ],\n [\n -93.33984375,\n 26.745610382199022\n ],\n [\n -94.04296874999999,\n 26.745610382199022\n ],\n [\n -94.4384765625,\n 27.644606381943326\n ],\n [\n -94.4384765625,\n 28.613459424004414\n ],\n [\n -94.21875,\n 29.036960648558267\n ],\n [\n -92.5048828125,\n 28.9600886880068\n ],\n [\n -91.3623046875,\n 28.76765910569123\n ],\n [\n -89.47265625,\n 28.729130483430154\n ],\n [\n -88.59374999999999,\n 29.036960648558267\n ],\n [\n -88.06640625,\n 29.53522956294847\n ],\n [\n -87.0556640625,\n 29.6880527498568\n ],\n [\n -86.044921875,\n 30.06909396443887\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"125","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"577391a4e4b07657d1a88bc8","contributors":{"authors":[{"text":"Locker, Stanley D. slocker@usgs.gov","contributorId":5906,"corporation":false,"usgs":true,"family":"Locker","given":"Stanley D.","email":"slocker@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":639634,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reed, John K.","contributorId":172114,"corporation":false,"usgs":false,"family":"Reed","given":"John","email":"","middleInitial":"K.","affiliations":[{"id":26984,"text":"Harbor Branch Oceanographic Institute, Florida Atlantic University","active":true,"usgs":false}],"preferred":false,"id":639635,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Farrington, Stephanie","contributorId":172115,"corporation":false,"usgs":false,"family":"Farrington","given":"Stephanie","email":"","affiliations":[{"id":26984,"text":"Harbor Branch Oceanographic Institute, Florida Atlantic University","active":true,"usgs":false}],"preferred":false,"id":639636,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harter, Stacey","contributorId":172116,"corporation":false,"usgs":false,"family":"Harter","given":"Stacey","affiliations":[{"id":12555,"text":"NOAA Fisheries – Beaufort Laboratory, Beaufort, NC","active":true,"usgs":false}],"preferred":false,"id":639637,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hine, Albert C.","contributorId":87580,"corporation":false,"usgs":true,"family":"Hine","given":"Albert","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":639638,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dunn, Shane","contributorId":172117,"corporation":false,"usgs":false,"family":"Dunn","given":"Shane","email":"","affiliations":[{"id":7149,"text":"College of Marine Science, University of South Florida, St. Petersburg, FL","active":true,"usgs":false}],"preferred":false,"id":639639,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70170850,"text":"70170850 - 2016 - Impact of formation water geochemistry and crude oil biodegradation on microbial methanogenesis","interactions":[],"lastModifiedDate":"2016-06-28T11:41:03","indexId":"70170850","displayToPublicDate":"2016-06-28T12:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2958,"text":"Organic Geochemistry","active":true,"publicationSubtype":{"id":10}},"title":"Impact of formation water geochemistry and crude oil biodegradation on microbial methanogenesis","docAbstract":"Converting non-producible crude oil to CH4 via methanogenic crude oil biodegradation in oil reservoirs could serve as one way to increase our energy profile. Yet, field data supporting the direct relationship between methanogenesis and crude oil biodegradation are sparse. Indicators of methanogenesis, based on the formation water and gas geochemistry (e.g. alkalinity, δ13C–CO2) were compared with indicators of crude oil biodegradation (e.g. pristane/phytane and n-alkane ratios) from wells in the Wilcox Group of Louisiana to determine if increases in extent of methanogenesis were related to increases in extent of crude oil biodegradation.
\nShallow wells (393–442 m depth) contained highly biodegraded oils associated with low extent of methanogenesis, while the deepest (> 1208 m) wells contained minimally degraded oils and produced fluids suggesting a low extent of methanogenesis. Mid-depth wells (666–857 m) in the central field had the highest indicators of methanogenesis and contained moderately biodegraded oils. Little correlation existed between extents of crude oil biodegradation and methanogenesis across the whole transect (avg.R2 = 0.13). However, when wells with the greatest extent of crude oil biodegradation were eliminated (3 of 6 oilfields), better correlation between extent of methanogenesis and biodegradation (avg. R2 = 0.53) was observed. The results suggest that oil quality and salinity impact methanogenic crude oil biodegradation. Reservoirs indicating moderate extent of crude oil biodegradation and high extent of methanogenesis, such as the central field, would be good candidates for attempting to enhance methanogenic crude oil biodegradation as a result of the observations from the study.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.orggeochem.2016.05.008","usgsCitation":"Shelton, J., McIntosh, J.C., Warwick, P.D., and McCray, J.E., 2016, Impact of formation water geochemistry and crude oil biodegradation on microbial methanogenesis: Organic Geochemistry, v. 98, p. 105-117, https://doi.org/10.1016/j.orggeochem.2016.05.008.","productDescription":"13 p.","startPage":"105","endPage":"117","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-073458","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":470824,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.orggeochem.2016.05.008","text":"Publisher Index Page"},{"id":324501,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"98","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"577391a5e4b07657d1a88bce","contributors":{"authors":[{"text":"Shelton, Jenna L. 0000-0002-1377-0675 jlshelton@usgs.gov","orcid":"https://orcid.org/0000-0002-1377-0675","contributorId":5025,"corporation":false,"usgs":true,"family":"Shelton","given":"Jenna L.","email":"jlshelton@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":628816,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McIntosh, Jennifer C. 0000-0001-5055-4202","orcid":"https://orcid.org/0000-0001-5055-4202","contributorId":150557,"corporation":false,"usgs":false,"family":"McIntosh","given":"Jennifer","email":"","middleInitial":"C.","affiliations":[{"id":6624,"text":"University of Arizona, Laboratory of Tree-Ring Research","active":true,"usgs":false}],"preferred":false,"id":628817,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Warwick, Peter D. 0000-0002-3152-7783 pwarwick@usgs.gov","orcid":"https://orcid.org/0000-0002-3152-7783","contributorId":762,"corporation":false,"usgs":true,"family":"Warwick","given":"Peter","email":"pwarwick@usgs.gov","middleInitial":"D.","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":628818,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McCray, John E.","contributorId":139258,"corporation":false,"usgs":false,"family":"McCray","given":"John","email":"","middleInitial":"E.","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":628819,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70174171,"text":"70174171 - 2016 - Loss of genetic diversity and increased subdivision in an endemic Alpine Stonefly threatened by climate change","interactions":[],"lastModifiedDate":"2016-11-15T13:59:21","indexId":"70174171","displayToPublicDate":"2016-06-28T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Loss of genetic diversity and increased subdivision in an endemic Alpine Stonefly threatened by climate change","docAbstract":"Much remains unknown about the genetic status and population connectivity of high-elevation and high-latitude freshwater invertebrates, which often persist near snow and ice masses that are disappearing due to climate change. Here we report on the conservation genetics of the meltwater stonefly Lednia tumana (Ricker) of Montana, USA, a cold-water obligate species. We sequenced 1530 bp of mtDNA from 116 L. tumana individuals representing “historic” (>10 yr old) and 2010 populations. The dominant haplotype was common in both time periods, while the second-most-common haplotype was found only in historic samples, having been lost in the interim. The 2010 populations also showed reduced gene and nucleotide diversity and increased genetic isolation. We found lower genetic diversity in L. tumana compared to two other North American stonefly species, Amphinemura linda (Ricker) and Pteronarcys californica Newport. Our results imply small effective sizes, increased fragmentation, limited gene flow, and loss of genetic variation among contemporary L. tumana populations, which can lead to reduced adaptive capacity and increased extinction risk. This study reinforces concerns that ongoing glacier loss threatens the persistence of L. tumana, and provides baseline data and analysis of how future environmental change could impact populations of similar organisms.
","language":"English","publisher":"Public Library of Science","publisherLocation":"San Francisco, CA","doi":"10.1371/journal.pone.0157386","usgsCitation":"Jordan, S., Giersch, J., Muhlfeld, C.C., Hotalling, S., Fanning, L., Tappenbeck, T.H., and Luikart, G., 2016, Loss of genetic diversity and increased subdivision in an endemic Alpine Stonefly threatened by climate change: PLoS ONE, v. 11, no. 6, e0157386; 12 p., https://doi.org/10.1371/journal.pone.0157386.","productDescription":"e0157386; 12 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-069801","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":470827,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0157386","text":"Publisher Index Page"},{"id":324527,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.01562499999999,\n 49.009050809382046\n ],\n [\n -108.19335937499999,\n 48.99463598353405\n ],\n [\n -104.0625,\n 49.009050809382046\n ],\n [\n -104.0625,\n 44.99588261816546\n ],\n [\n -111.07177734375,\n 45.02695045318546\n ],\n [\n -111.07177734375,\n 44.49650533109345\n ],\n [\n -111.4013671875,\n 44.74673324024678\n ],\n [\n -111.46728515624999,\n 44.63739123445585\n ],\n [\n -111.55517578125,\n 44.55916341529182\n ],\n [\n -111.73095703125,\n 44.5278427984555\n ],\n [\n -112.0166015625,\n 44.5278427984555\n ],\n [\n -112.21435546875,\n 44.5435052132082\n ],\n [\n -112.39013671875,\n 44.449467536006935\n ],\n [\n -112.65380859375,\n 44.465151013519616\n ],\n [\n -112.8955078125,\n 44.37098696297173\n ],\n [\n -113.00537109375,\n 44.49650533109345\n ],\n [\n -113.09326171875,\n 44.6061127451739\n ],\n [\n -113.18115234375,\n 44.762336674810996\n ],\n [\n -113.48876953125,\n 44.809121700077355\n ],\n [\n -113.51074218749999,\n 44.99588261816546\n ],\n [\n -113.62060546875,\n 45.19752230305682\n ],\n [\n -113.73046875,\n 45.30580259943578\n ],\n [\n -113.7744140625,\n 45.506346901083425\n ],\n [\n -113.88427734374999,\n 45.61403741135093\n ],\n [\n -114.01611328125,\n 45.67548217560647\n ],\n [\n -114.12597656249999,\n 45.598665689820635\n ],\n [\n -114.2578125,\n 45.55252525134013\n ],\n [\n -114.3017578125,\n 45.49094569262732\n ],\n [\n -114.45556640625,\n 45.55252525134013\n ],\n [\n -114.54345703125,\n 45.644768217751924\n ],\n [\n -114.54345703125,\n 45.78284835197676\n ],\n [\n -114.45556640625,\n 45.81348649679971\n ],\n [\n -114.43359375,\n 45.920587344733654\n ],\n [\n -114.49951171875,\n 46.027481852486645\n ],\n [\n -114.49951171875,\n 46.164614496897094\n ],\n [\n -114.36767578124999,\n 46.27103747280261\n ],\n [\n -114.36767578124999,\n 46.37725420510028\n ],\n [\n -114.45556640625,\n 46.52863469527167\n ],\n [\n -114.47753906249999,\n 46.649436163350245\n ],\n [\n -114.63134765625001,\n 46.73986059969267\n ],\n [\n -114.7412109375,\n 46.73986059969267\n ],\n [\n -114.80712890625,\n 46.86019101567027\n ],\n [\n -114.9609375,\n 46.965259400349275\n ],\n [\n -115.24658203125,\n 47.15984001304432\n ],\n [\n -115.3564453125,\n 47.2195681123155\n ],\n [\n -115.48828125000001,\n 47.30903424774781\n ],\n [\n -115.7080078125,\n 47.44294999517949\n ],\n [\n -115.7080078125,\n 47.54687159892238\n ],\n [\n -115.77392578125,\n 47.65058757118734\n ],\n [\n -115.90576171874999,\n 47.79839667295524\n ],\n [\n -116.05957031249999,\n 47.945786463687185\n ],\n [\n -116.01562499999999,\n 49.009050809382046\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"11","issue":"6","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-27","publicationStatus":"PW","scienceBaseUri":"577391a6e4b07657d1a88bd4","contributors":{"authors":[{"text":"Jordan, Steve","contributorId":168297,"corporation":false,"usgs":false,"family":"Jordan","given":"Steve","email":"","affiliations":[{"id":25242,"text":"Department of Biology, Bucknell University, Lewisburg, Pennsylvania 17837, USA","active":true,"usgs":false}],"preferred":false,"id":641058,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Giersch, J. 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One set of equations was developed through a temporal analysis with a two-step least squares-quantile regression technique that measures the average effect of changes in the urbanization of the watersheds used in the study. The resulting equations can be used to adjust rural peak discharge quantiles for the effect of urbanization, and in this study the equations also were used to adjust the annual maximum peak discharges from the study watersheds to 2010 urbanization conditions.
The other set of equations was developed by a spatial analysis. This analysis used generalized least-squares regression to fit the peak discharge quantiles computed from the urbanization-adjusted annual maximum peak discharges from the study watersheds to drainage-basin characteristics. The peak discharge quantiles were computed by using the Expected Moments Algorithm following the removal of potentially influential low floods defined by a multiple Grubbs-Beck test. To improve the quantile estimates, regional skew coefficients were obtained from a newly developed regional skew model in which the skew increases with the urbanized land use fraction. The skew coefficient values for each streamgage were then computed as the variance-weighted average of at-site and regional skew coefficients. The drainage-basin characteristics used as explanatory variables in the spatial analysis include drainage area, the fraction of developed land, the fraction of land with poorly drained soils or likely water, and the basin slope estimated as the ratio of the basin relief to basin perimeter.
This report also provides the following: (1) examples to illustrate the use of the spatial and urbanization-adjustment equations for estimating peak discharge quantiles at ungaged sites and to improve flood-quantile estimates at and near a gaged site; (2) the urbanization-adjusted annual maximum peak discharges and peak discharge quantile estimates at streamgages from 181 watersheds including the 117 study watersheds and 64 additional watersheds in the study region that were originally considered for use in the study but later deemed to be redundant.
The urbanization-adjustment equations, spatial regression equations, and peak discharge quantile estimates developed in this study will be made available in the web application StreamStats, which provides automated regression-equation solutions for user-selected stream locations. Figures and tables comparing the observed and urbanization-adjusted annual maximum peak discharge records by streamgage are provided at https://doi.org/10.3133/sir20165050 for download.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165050","collaboration":"Prepared in cooperation with the Illinois Center for Transportation, the Illinois Department of Transportation, and the Federal Highway Administration","usgsCitation":"Over, T.M., Saito, R.J., Veilleux, A.G., O’Shea, P.S., Sharpe, J.B., Soong, D.T., and Ishii, A.L., 2016, Estimation of peak discharge quantiles for selected annual exceedance probabilities in northeastern Illinois (ver. 3.0, June 2021): U.S. Geological Survey Scientific Investigations Report 2016–5050, 50 p. with appendix, https://doi.org/10.3133/sir20165050.","productDescription":"Report: x, 51 p.; Tables; Companion Files; Version History","numberOfPages":"64","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-072125","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":386876,"rank":13,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2016/5050/versionHist.txt","text":"Version History","size":"20.7 kB","linkFileType":{"id":2,"text":"txt"},"description":"SIR 2016–5050 Version History"},{"id":386859,"rank":10,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2016/5050/sir20165050_table_13.csv","text":"Table 13","size":"4.33 kB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2016–5050 Table 13","linkHelpText":"— Components of variance of prediction for the selected spatial regression equations in this study in northeastern Illinois"},{"id":386858,"rank":9,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2016/5050/sir20165050_table_08.csv","text":"Table 8","size":"2.36 kB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2016–5050 Table 8","linkHelpText":"— Quantile regression coefficients from temporal analysis of 117 streamgages in northeastern Illinois and adjacent states, as a function of annual exceedance probability"},{"id":386856,"rank":7,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2016/5050/sir20165050_table_04.csv","text":"Table 4","size":"9.96 kB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2016–5050 Table 4","linkHelpText":"— Segment information for 181 U.S. Geological Survey streamgages used in this study, northeastern Illinois and adjacent states"},{"id":386855,"rank":6,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2016/5050/sir20165050_table_03.csv","text":"Table 3","size":"7.02 kB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2016–5050 Table 3","linkHelpText":"— Spatially averaged basin characteristics considered for developing spatial regression equations in this study in northeastern Illinois"},{"id":386854,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2016/5050/sir20165050_table_02.csv","text":"Table 2","size":"104 kB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2016–5050 Table 2","linkHelpText":"— Estimated peak discharge quantiles for 181 streamgages in northeastern Illinois and adjacent states, at selected exceedance probabilities"},{"id":386853,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2016/5050/sir20165050_table_01.csv","text":"Table 1","size":"29.2 kB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2016–5050 Table 1","linkHelpText":"— U.S. Geological Survey streamgages used in this study in northeastern Illinois and adjacent states"},{"id":386852,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5050/sir20165050.pdf","text":"Report","size":"6.28 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5050"},{"id":324328,"rank":1,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2016/5050/sir20165050_Links_To_Files.html","text":"Annual maximum peak discharge and associated urban fraction and precipitation values by streamgage","size":"29 kB","linkFileType":{"id":5,"text":"html"},"description":"SIR 2016–5050 Supplemental Graphs and Tables"},{"id":386861,"rank":12,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2016/5050/sir20165050_tables.xlsx","text":"Tables 1 through 4, 6, 8 and 13 and Table 1–1","size":"673 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016–5050 Tables"},{"id":386860,"rank":11,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2016/5050/sir20165050_appendix_table_1.1.csv","text":"Table 1.1","size":"7.58 kB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2016–5050 Table 1.1","linkHelpText":"— Skew statistics at streamgages used in the development of the regional skew model in this study in northeastern Illinois"},{"id":386857,"rank":8,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/sir/2016/5050/sir20165050_table_06.csv","text":"Table 6","size":"345 kB","linkFileType":{"id":7,"text":"csv"},"description":"SIR 2016–5050 Table 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]\n}","edition":"Version 1.0: June 2016; Version 2.0: November 2017; Version 3.0: June 2021","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
405 North Goodwin Avenue
Urbana, IL 61801
Anthropogenic desertification is a problem that plagues drylands globally; however, the factors which maintain degraded states are often unclear. In Canyonlands National Park on the Colorado Plateau of southeastern Utah, many degraded grasslands have not recovered structure and function >40 yr after release from livestock grazing pressure, necessitating active restoration. We hypothesized that multiple factors contribute to the persistent degraded state, including lack of seed availability, surficial soil-hydrological properties, and high levels of spatial connectivity (lack of perennial vegetation and other surface structure to retain water, litter, seed, and sediment). In combination with seeding and surface raking treatments, we tested the effect of small barrier structures (“ConMods”) designed to disrupt the loss of litter, seed and sediment in degraded soil patches within the park. Grass establishment was highest when all treatments (structures, seed addition, and soil disturbance) were combined, but only in the second year after installation, following favorable climatic conditions. We suggest that multiple limiting factors were ameliorated by treatments, including seed limitation and microsite availability, seed removal by harvester ants, and stressful abiotic conditions. Higher densities of grass seedlings on the north and east sides of barrier structures following the summer months suggest that structures may have functioned as artificial “nurse-plants”, sheltering seedlings from wind and radiation as well as accumulating wind-blown resources. Barrier structures increased the establishment of both native perennial grasses and exotic annuals, although there were species-specific differences in mortality related to spatial distribution of seedlings within barrier structures. The unique success of all treatments combined, and even then only under favorable climatic conditions and in certain soil patches, highlights that restoration success (and potentially, natural regeneration) often is contingent on many interacting factors.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.1354","usgsCitation":"Fick, S., Decker, C.E., Duniway, M.C., and Miller, M.E., 2016, Small-scale barriers mitigate desertification processes and enhance plant recruitment in a degraded semiarid grassland: Ecosphere, v. 7, no. 6, e01354; 16 p., https://doi.org/10.1002/ecs2.1354.","productDescription":"e01354; 16 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069023","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":470829,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.1354","text":"Publisher Index Page"},{"id":324488,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"Needles District of Canyonlands National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -109.7,\n 38.1\n ],\n [\n -109.7,\n 38.2\n ],\n [\n -109.8,\n 38.2\n ],\n [\n -109.8,\n 38.1\n ],\n [\n -109.7,\n 38.1\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","issue":"6","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-24","publicationStatus":"PW","scienceBaseUri":"57724022e4b07657d1a793a3","contributors":{"authors":[{"text":"Fick, Stephen E.","contributorId":172490,"corporation":false,"usgs":false,"family":"Fick","given":"Stephen E.","affiliations":[{"id":27054,"text":"Department of Plant Sciences, University of California, Davis, CA, 95616 USA. E-mail: sfick@ucdavis.edu","active":true,"usgs":false}],"preferred":false,"id":640945,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Decker, Cheryl E.","contributorId":86051,"corporation":false,"usgs":false,"family":"Decker","given":"Cheryl","email":"","middleInitial":"E.","affiliations":[{"id":6959,"text":"National Park Service Southeast Utah Group","active":true,"usgs":false}],"preferred":false,"id":640946,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Duniway, Michael C. 0000-0002-9643-2785 mduniway@usgs.gov","orcid":"https://orcid.org/0000-0002-9643-2785","contributorId":4212,"corporation":false,"usgs":true,"family":"Duniway","given":"Michael","email":"mduniway@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":640947,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miller, Mark E.","contributorId":91580,"corporation":false,"usgs":false,"family":"Miller","given":"Mark","email":"","middleInitial":"E.","affiliations":[{"id":6959,"text":"National Park Service Southeast Utah Group","active":true,"usgs":false}],"preferred":false,"id":640948,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70171552,"text":"sir20165080 - 2016 - Groundwater-flow model for the Wood River Valley aquifer system, south-central Idaho","interactions":[],"lastModifiedDate":"2016-08-22T09:04:33","indexId":"sir20165080","displayToPublicDate":"2016-06-27T17:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-5080","title":"Groundwater-flow model for the Wood River Valley aquifer system, south-central Idaho","docAbstract":"A three-dimensional numerical model of groundwater flow was developed for the Wood River Valley (WRV) aquifer system, Idaho, to evaluate groundwater and surface-water availability at the regional scale. This mountain valley is located in Blaine County and has a drainage area of about 2,300 square kilometers (888 square miles). The model described in this report can serve as a tool for water-rights administration and water-resource management and planning. The model was completed with support from the Idaho Department of Water Resources, and is part of an ongoing U.S. Geological Survey effort to characterize the groundwater resources of the WRV. A highly reproducible approach was taken for constructing the WRV groundwater-flow model. The collection of datasets, source code, and processing instructions used to construct and analyze the model was distributed as an R statistical-computing and graphics package.
\nFlow in the WRV aquifer was simulated using the MODFLOW-USG groundwater flow model. The transient flow model simulates groundwater flow between 1995 and 2010. The model uses a 100-meter (328-feet) uniform grid spacing with 54,922 active model cells distributed over three model layers. A confining unit in the south-central part of the Bellevue fan necessitated the use of a multi-layer model. Specified-flow boundaries were used to simulate the groundwater inflows from each of the major tributary basins (also known as tributary basin underflow) and the areal recharge of precipitation and applied irrigation. Head‑dependent flow boundaries were used to simulate the stream-aquifer flow exchange in river reaches and the groundwater discharge at the outlet boundaries of Stanton Crossing and Silver Creek. The model was calibrated by adjusting aquifer hydraulic properties to match simulated and measured water levels and stream-aquifer flow exchange, using the parameter-estimation program PEST. The model reasonably simulated the measured water-table elevation, orientation, and gradients. Stream-aquifer flow exchange along river reaches also was reasonably simulated by the model.
\nInflow into the WRV aquifer system originates from three sources (from largest to smallest):
\nOutflow from the WRV aquifer system originates from five sources (from largest to smallest):
\nTemporal changes in aquifer storage are most affected by areal recharge and groundwater pumping, and also contribute to changes in streamflow gains.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165080","collaboration":"Prepared in cooperation with the Idaho Department of Water Resources","usgsCitation":"Fisher, J.C., Bartolino, J.R., Wylie, A.H., Sukow, Jennifer, and McVay, Michael, 2016, Groundwater-flow model of the Wood River Valley aquifer system, south-central Idaho: U.S. Geological Survey Scientific Investigations Report 2016–5080, 71 p., https://dx.doi.org/10.3133/sir20165080.","productDescription":"Report: viii, 71 p.; Appendixes A-H; Model Archive; Data Repository","numberOfPages":"84","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-039541","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":324425,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5080/sir20165080_appendixE.pdf","text":"Appendix E","size":"6.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5080 Appendix E","linkHelpText":"Tributary Basin Underflow into the Wood River Valley Aquifer System, South-Central Idaho"},{"id":324424,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5080/sir20165080_appendixD.pdf","text":"Appendix D","size":"11 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5080 Appendix D","linkHelpText":"Uncalibrated Groundwater-Flow Model for the Wood River Valley Aquifer System, South-Central Idaho"},{"id":324426,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5080/sir20165080_appendixF.pdf","text":"Appendix F","size":"8.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5080 Appendix F","linkHelpText":"Natural Groundwater Recharge and Discharge in the Wood River Valley Aquifer System, South-Central Idaho"},{"id":324428,"rank":10,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5080/sir20165080_appendixH.pdf","text":"Appendix H","size":"9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5080 Appendix H","linkHelpText":"Calibration of the Wood River Valley Groundwater Flow Model"},{"id":324427,"rank":9,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5080/sir20165080_appendixG.pdf","text":"Appendix G","size":"15 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5080 Appendix G","linkHelpText":"Incidental Groundwater Recharge and Pumping Demand in the Wood River Valley Aquifer System, South-Central Idaho"},{"id":324430,"rank":12,"type":{"id":7,"text":"Companion Files"},"url":"https://github.com/USGS-R/wrv","text":"R-package repository"},{"id":324423,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5080/sir20165080_appendixC.pdf","text":"Appendix C","size":"6.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5080 Appendix C","linkHelpText":"Creating Datasets for the R-Package ‘wrv’"},{"id":324429,"rank":11,"type":{"id":7,"text":"Companion Files"},"url":"https://dx.doi.org/10.5066/F7C827DT","text":"Model Archive"},{"id":324419,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5080/coverthb.jpg"},{"id":324420,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5080/sir20165080.pdf","text":"Report","size":"10 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5080 Report PDF"},{"id":324421,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5080/sir20165080_appendixA.pdf","text":"Appendix A","size":"2.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5080 Appendix A","linkHelpText":"An Introduction to the R-Package ‘wrv’"},{"id":324422,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5080/sir20165080_appendixB.pdf","text":"Appendix B","size":"525 KB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5080 Appendix B","linkHelpText":"Manual for Functions and Datasets in the R-Package ‘wrv’"}],"country":"United States","state":"Idaho","otherGeospatial":"Wood River Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.47753906249999,\n 43.30119623257966\n ],\n [\n -114.47753906249999,\n 43.82065657651685\n ],\n [\n -114.04083251953124,\n 43.82065657651685\n ],\n [\n -114.04083251953124,\n 43.30119623257966\n ],\n [\n -114.47753906249999,\n 43.30119623257966\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702
http://id.water.usgs.gov
Interactions and feedbacks between abundant surface waters and permafrost fundamentally shape lowland Arctic landscapes. Sublake permafrost is maintained when the maximum ice thickness (MIT) exceeds lake depth and mean annual bed temperatures (MABTs) remain below freezing. However, declining MIT since the 1970s is likely causing talik development below shallow lakes. Here we show high-temperature sensitivity to winter ice growth at the water-sediment interface of shallow lakes based on year-round lake sensor data. Empirical model experiments suggest that shallow (1 m depth) lakes have warmed substantially over the last 30 years (2.4°C), with MABT above freezing 5 of the last 7 years. This is in comparison to slower rates of warming in deeper (3 m) lakes (0.9°C), with already well-developed taliks. Our findings indicate that permafrost below shallow lakes has already begun crossing a critical thawing threshold approximately 70 years prior to predicted terrestrial permafrost thaw in northern Alaska.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2016GL068506","usgsCitation":"Arp, C.D., Jones, B.M., Grosse, G., Bondurant, A.C., Romanovksy, V.E., Hinkel, K.M., and Parsekian, A.D., 2016, Threshold sensitivity of shallow Arctic lakes and sublake permafrost to changing winter climate: Geophysical Research Letters, v. 43, no. 12, p. 6358-6365, https://doi.org/10.1002/2016GL068506.","productDescription":"8 p.","startPage":"6358","endPage":"6365","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-073772","costCenters":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"links":[{"id":470830,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016gl068506","text":"Publisher Index Page"},{"id":324491,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Teshekpuk Lake, Umiat Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -150,\n 69\n ],\n [\n -150,\n 72\n ],\n [\n -158,\n 72\n ],\n [\n -158,\n 69\n ],\n [\n -150,\n 69\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"43","issue":"12","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-24","publicationStatus":"PW","scienceBaseUri":"57724023e4b07657d1a793b8","chorus":{"doi":"10.1002/2016gl068506","url":"http://dx.doi.org/10.1002/2016gl068506","publisher":"Wiley-Blackwell","authors":"Arp Christopher D., Jones Benjamin M., Grosse Guido, Bondurant Allen C., Romanovsky Vladimir E., Hinkel Kenneth M., Parsekian Andrew D.","journalName":"Geophysical Research Letters","publicationDate":"6/24/2016","publiclyAccessibleDate":"6/24/2016"},"contributors":{"authors":[{"text":"Arp, Christopher D.","contributorId":17330,"corporation":false,"usgs":false,"family":"Arp","given":"Christopher","email":"","middleInitial":"D.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":640934,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, Benjamin M. 0000-0002-1517-4711 bjones@usgs.gov","orcid":"https://orcid.org/0000-0002-1517-4711","contributorId":2286,"corporation":false,"usgs":true,"family":"Jones","given":"Benjamin","email":"bjones@usgs.gov","middleInitial":"M.","affiliations":[{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":640933,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grosse, Guido","contributorId":146182,"corporation":false,"usgs":false,"family":"Grosse","given":"Guido","email":"","affiliations":[{"id":12916,"text":"Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Potsdam, Germany","active":true,"usgs":false}],"preferred":false,"id":640935,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bondurant, Allen C.","contributorId":172493,"corporation":false,"usgs":false,"family":"Bondurant","given":"Allen","email":"","middleInitial":"C.","affiliations":[{"id":6695,"text":"UAF","active":true,"usgs":false}],"preferred":false,"id":640936,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Romanovksy, Vladimir E.","contributorId":172494,"corporation":false,"usgs":false,"family":"Romanovksy","given":"Vladimir","email":"","middleInitial":"E.","affiliations":[{"id":6695,"text":"UAF","active":true,"usgs":false}],"preferred":false,"id":640937,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hinkel, Kenneth M.","contributorId":15405,"corporation":false,"usgs":true,"family":"Hinkel","given":"Kenneth","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":640938,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Parsekian, Andrew D.","contributorId":23829,"corporation":false,"usgs":false,"family":"Parsekian","given":"Andrew","email":"","middleInitial":"D.","affiliations":[{"id":17842,"text":"University of Wyoming, Laramie","active":true,"usgs":false}],"preferred":false,"id":640939,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70171556,"text":"sir20165079 - 2016 - A spatially explicit suspended-sediment load model for western Oregon","interactions":[],"lastModifiedDate":"2016-07-20T09:48:24","indexId":"sir20165079","displayToPublicDate":"2016-06-27T16:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-5079","title":"A spatially explicit suspended-sediment load model for western Oregon","docAbstract":"We calibrated the watershed model SPARROW (Spatially Referenced Regressions on Watershed attributes) to give estimates of suspended-sediment loads for western Oregon and parts of northwestern California. Estimates of suspended-sediment loads were derived from a nonlinear least squares regression that related explanatory variables representing landscape and transport conditions to measured suspended-sediment loads at 68 measurement stations. The model gives estimates of model coefficients and their uncertainty within a spatial framework defined by the National Hydrography Dataset Plus hydrologic network. The resulting model explained 64 percent of the variability in suspended-sediment yield and had a root mean squared error value of 0.737. The predictor variables selected for the final model were (1) generalized lithologic province, (2) mean annual precipitation, and (3) burned area (by recent wildfire). Other landscape characteristics also were considered, but they were not significant predictors of sediment transport, were strongly correlated with another predictor variable, or were not as significant as the predictors selected for the final model.
\nThe northern Oregon coastal drainages had the highest predicted suspended sediment yields (median yield 475 kilograms per hectare per year) and the Klamath River Basin had the lowest (median yield 53 kilograms per hectare per year). Quaternary deposits were, on average, the largest contributor to incremental suspended-sediment yield even though this lithologic province only makes up 17 percent of the modeling domain. Coast Range sedimentary rocks and Coast Range volcanic rocks had high suspended-sediment yields whereas, in addition to the Klamath terrane, the Western Cascade and High Cascade lithologic provinces had low suspended-sediment yields. Precipitation and the area affected by recent wildfire both positively correlated with suspended-sediment load.
\nSuspended-sediment transport rates predicted by this SPARROW model are less than historical (1956–73) and long‑term (thousands of years) geological rates. This difference likely results, in part, from biases in the data underlying the SPARROW model, probably resulting in predicted suspended-sediment estimates that underestimate actual transport rates. However, the differences also likely owe to natural and human-caused variation in suspended-sediment yields as they respond to changes in climate, vegetation, fire frequency, and land use. In particular, decreases in mean annual suspended-sediment yields within the Umpqua River Basin since 1956–73 may owe to less intense forest harvest, passage of the Oregon Forest Practices Act of 1971, and increased emphasis in habitat protection in recent decades. Such sensitivity may have implications for the spatial and temporal distributions of aquatic and riparian habitats.
\nKnowledge of the regionally important patterns and factors in suspended-sediment sources and transport could support broad-scale, water-quality management objectives and priorities. Because of biases and limitations of this model, however, these results are most applicable for general comparisons and for broad areas such as large watersheds. For example, despite having similar area, precipitation, and land-use, the Umpqua River Basin generates 68 percent more suspended sediment than the Rogue River Basin, chiefly because of the large area of Coast Range sedimentary province in the Umpqua River Basin. By contrast, the Rogue River Basin contains a much larger area of Klamath terrane rocks, which produce significantly less suspended load, although recent fire disturbance (in 2002) has apparently elevated suspended sediment yields in the tributary Illinois River watershed. Fine-scaled analysis, however, will require more intensive, locally focused measurements.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165079","usgsCitation":"Wise, D.R., and O’Connor, J.E., 2016, A spatially explicit suspended-sediment load model for western Oregon: U.S. Geological Survey Scientific Investigations Report 2016–5079, 25 p., https://dx.doi.org/10.3133/sir20165079.","productDescription":"Report: v, 25 p.; Appendix A; Companion File","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-064150","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":324455,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5079/coverthb.jpg"},{"id":324458,"rank":4,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2016/5079/sir20165079_NHDV2_predict_data.txt","text":"Mean annual suspended loads estimated by the SPARROW model","size":"1 MB","linkFileType":{"id":2,"text":"txt"}},{"id":324456,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5079/sir20165079.pdf","text":"Report","size":"18 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5079 Report PDF"},{"id":324457,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5079/sir20165079_appendixa.xlsx","text":"Appendix A ","size":"23 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2016-5079 Appendix A","linkHelpText":"Summary of Calibration Data for the Suspended Sediment Sparrow Model Developed for Western Oregon and Northwestern California"}],"contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
http://or.water.usgs.gov
The U.S. Geological Survey, in cooperation with the Idaho Transportation Department, updated regional regression equations to estimate peak-flow statistics at ungaged sites on Idaho streams using recent streamflow (flow) data and new statistical techniques. Peak-flow statistics with 80-, 67-, 50-, 43-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities (1.25-, 1.50-, 2.00-, 2.33-, 5.00-, 10.0-, 25.0-, 50.0-, 100-, 200-, and 500-year recurrence intervals, respectively) were estimated for 192 streamgages in Idaho and bordering States with at least 10 years of annual peak-flow record through water year 2013. The streamgages were selected from drainage basins with little or no flow diversion or regulation. The peak-flow statistics were estimated by fitting a log-Pearson type III distribution to records of annual peak flows and applying two additional statistical methods: (1) the Expected Moments Algorithm to help describe uncertainty in annual peak flows and to better represent missing and historical record; and (2) the generalized Multiple Grubbs Beck Test to screen out potentially influential low outliers and to better fit the upper end of the peak-flow distribution. Additionally, a new regional skew was estimated for the Pacific Northwest and used to weight at-station skew at most streamgages. The streamgages were grouped into six regions (numbered 1_2, 3, 4, 5, 6_8, and 7, to maintain consistency in region numbering with a previous study), and the estimated peak-flow statistics were related to basin and climatic characteristics to develop regional regression equations using a generalized least squares procedure. Four out of 24 evaluated basin and climatic characteristics were selected for use in the final regional peak-flow regression equations.
Overall, the standard error of prediction for the regional peak-flow regression equations ranged from 22 to 132 percent. Among all regions, regression model fit was best for region 4 in west-central Idaho (average standard error of prediction=46.4 percent; pseudo-R2>92 percent) and region 5 in central Idaho (average standard error of prediction=30.3 percent; pseudo-R2>95 percent). Regression model fit was poor for region 7 in southern Idaho (average standard error of prediction=103 percent; pseudo-R2<78 percent) compared to other regions because few streamgages in region 7 met the criteria for inclusion in the study, and the region’s semi-arid climate and associated variability in precipitation patterns causes substantial variability in peak flows.
A drainage area ratio-adjustment method, using ratio exponents estimated using generalized least-squares regression, was presented as an alternative to the regional regression equations if peak-flow estimates are desired at an ungaged site that is close to a streamgage selected for inclusion in this study. The alternative drainage area ratio-adjustment method is appropriate for use when the drainage area ratio between the ungaged and gaged sites is between 0.5 and 1.5.
The updated regional peak-flow regression equations had lower total error (standard error of prediction) than all regression equations presented in a 1982 study and in four of six regions presented in 2002 and 2003 studies in Idaho. A more extensive streamgage screening process used in the current study resulted in fewer streamgages used in the current study than in the 1982, 2002, and 2003 studies. Fewer streamgages used and the selection of different explanatory variables were likely causes of increased error in some regions compared to previous studies, but overall, regional peak‑flow regression model fit was generally improved for Idaho. The revised statistical procedures and increased streamgage screening applied in the current study most likely resulted in a more accurate representation of natural peak-flow conditions.
The updated, regional peak-flow regression equations will be integrated in the U.S. Geological Survey StreamStats program to allow users to estimate basin and climatic characteristics and peak-flow statistics at ungaged locations of interest. StreamStats estimates peak-flow statistics with quantifiable certainty only when used at sites with basin and climatic characteristics within the range of input variables used to develop the regional regression equations. Both the regional regression equations and StreamStats should be used to estimate peak-flow statistics only in naturally flowing, relatively unregulated streams without substantial local influences to flow, such as large seeps, springs, or other groundwater-surface water interactions that are not widespread or characteristic of the respective region.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165083","collaboration":"Prepared in cooperation with Idaho Transportation Department","usgsCitation":"Wood, M.S., Fosness, R.L., Skinner, K.D., and Veilleux, A.G., 2016, Estimating peak-flow frequency statistics for selected gaged and ungaged sites in naturally flowing streams and rivers in Idaho (ver. 1.1, April 2017): U.S. Geological Survey Scientific Investigations Report 2016–5083, 56 p., https://doi.org/10.3133/sir20165083.","productDescription":"Report: vi, 56 p.; Appendix A","numberOfPages":"66","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-046287","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":324444,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5083/sir20165083.pdf","text":"Report","size":"5.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5083 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\"}}]}","edition":"Version 1.0: Originally posted June 27, 2016; Version 1.1: April 26, 2017","contact":"Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702
https://id.water.usgs.gov
Groundwater is the source of drinking water for ∼1.4 million people in the Coastal Plain Province of Maryland (USA). In addition, groundwater is essential for commercial, industrial, and agricultural uses. Approximately 0.757 × 109 L d–1 (200 million gallons/d) were withdrawn in 2010. As a result of decades of withdrawals from the coastal plain confined aquifers, groundwater levels have declined by as much as 70 m (230 ft) from estimated prepumping levels. Other issues posing challenges to long-term groundwater sustainability include degraded water quality from both man-made and natural sources, reduced stream base flow, land subsidence, and changing recharge patterns (drought) caused by climate change. In Maryland, groundwater supply is managed primarily by the Maryland Department of the Environment, which seeks to balance reasonable use of the resource with long-term sustainability. The chief goal of groundwater management in Maryland is to ensure safe and adequate supplies for all current and future users through the implementation of appropriate usage, planning, and conservation policies. To assist in that effort, the geographic information system (GIS)–based Maryland Coastal Plain Aquifer Information System was developed as a tool to help water managers access and visualize groundwater data for use in the evaluation of groundwater allocation and use permits. The system, contained within an ESRI ArcMap desktop environment, includes both interpreted and basic data for 16 aquifers and 14 confining units. Data map layers include aquifer and confining unit layer surfaces, aquifer extents, borehole information, hydraulic properties, time-series groundwater-level data, well records, and geophysical and lithologic logs. The aquifer and confining unit layer surfaces were generated specifically for the GIS system. The system also contains select groundwater-quality data and map layers that quantify groundwater and surface-water withdrawals. The aquifer information system can serve as a pre- and postprocessing environment for groundwater-flow models for use in water-supply planning, development, and management. The system also can be expanded to include features that evaluate constraints to groundwater development, such as insufficient available drawdown, degraded groundwater quality, insufficient aquifer yields, and well-field interference. Ultimately, the aquifer information system is intended to function as an interactive Web-based utility that provides a broad array of information related to groundwater resources in Maryland’s coastal plain to a wide-ranging audience, including well drillers, consultants, academia, and the general public.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/2016.2520(15)","usgsCitation":"Andreasen, D., Nardi, M.R., Staley, A., Achmad, G., and Grace, J.W., 2016, The Maryland Coastal Plain Aquifer Information System: A GIS-based tool for assessing groundwater resources: Special Paper of the Geological Society of America, v. 520, p. 159-170, https://doi.org/10.1130/2016.2520(15).","productDescription":"12 p.","startPage":"159","endPage":"170","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068540","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"links":[{"id":324417,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"520","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57724023e4b07657d1a793b0","contributors":{"authors":[{"text":"Andreasen, David C.","contributorId":59003,"corporation":false,"usgs":true,"family":"Andreasen","given":"David C.","affiliations":[],"preferred":false,"id":640806,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nardi, Mark R. 0000-0002-7310-8050 mrnardi@usgs.gov","orcid":"https://orcid.org/0000-0002-7310-8050","contributorId":1859,"corporation":false,"usgs":true,"family":"Nardi","given":"Mark","email":"mrnardi@usgs.gov","middleInitial":"R.","affiliations":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":640805,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Staley, Andrew W.","contributorId":43319,"corporation":false,"usgs":true,"family":"Staley","given":"Andrew W.","affiliations":[],"preferred":false,"id":640807,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Achmad, Grufron","contributorId":172464,"corporation":false,"usgs":false,"family":"Achmad","given":"Grufron","email":"","affiliations":[{"id":25435,"text":"Maryland Geological Survey","active":true,"usgs":false}],"preferred":false,"id":640808,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Grace, John W.","contributorId":172465,"corporation":false,"usgs":false,"family":"Grace","given":"John","email":"","middleInitial":"W.","affiliations":[{"id":27050,"text":"Maryland Department of the Environment","active":true,"usgs":false}],"preferred":false,"id":640809,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70174059,"text":"70174059 - 2016 - Pre/post-closure assessment of groundwater pharmaceutical fate in a wastewater‑facility-impacted stream reach","interactions":[],"lastModifiedDate":"2018-08-09T12:08:00","indexId":"70174059","displayToPublicDate":"2016-06-27T12:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"Pre/post-closure assessment of groundwater pharmaceutical fate in a wastewater‑facility-impacted stream reach","docAbstract":"Pharmaceutical contamination of contiguous groundwater is a substantial concern in wastewater-impacted streams, due to ubiquity in effluent, high aqueous mobility, designed bioactivity, and to effluent-driven hydraulic gradients. Wastewater treatment facility (WWTF) closures are rare environmental remediation events; offering unique insights into contaminant persistence, long-term wastewater impacts, and ecosystem recovery processes. The USGS conducted a combined pre/post-closure groundwater assessment adjacent to an effluent-impacted reach of Fourmile Creek, Ankeny, Iowa, USA. Higher surface-water concentrations, consistent surface-water to groundwater concentration gradients, and sustained groundwater detections tens of meters from the stream bank demonstrated the importance of WWTF effluent as the source of groundwater pharmaceuticals as well as the persistence of these contaminants under effluent-driven, pre-closure conditions. The number of analytes (110 total) detected in surface water decreased from 69 prior to closure down to 8 in the first post-closure sampling event approximately 30 d later, with a corresponding 2 order of magnitude decrease in the cumulative concentration of detected analytes. Post-closure cumulative concentrations of detected analytes were approximately 5 times higher in proximal groundwater than in surface water. About 40% of the 21 contaminants detected in a downstream groundwater transect immediately before WWTF closure exhibited rapid attenuation with estimated half-lives on the order of a few days; however, a comparable number exhibited no consistent attenuation during the year-long post-closure assessment. The results demonstrate the potential for effluent-impacted shallow groundwater systems to accumulate pharmaceutical contaminants and serve as long-term residual sources, further increasing the risk of adverse ecological effects in groundwater and the near-stream ecosystem.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.scitotenv.2016.06.104","usgsCitation":"Bradley, P.M., Barber, L.B., Clark, J.M., Duris, J.W., Foreman, W., Furlong, E.T., Givens, C.E., Hubbard, L.E., Hutchinson, K.J., Journey, C.A., Keefe, S.H., and Kolpin, D.W., 2016, Pre/post-closure assessment of groundwater pharmaceutical fate in a wastewater‑facility-impacted stream reach: Science of the Total Environment, v. 568, p. 916-925, https://doi.org/10.1016/j.scitotenv.2016.06.104.","productDescription":"10 p.","startPage":"916","endPage":"925","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069485","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":470833,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2016.06.104","text":"Publisher Index Page"},{"id":324408,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Iowa","county":"Ankeny","otherGeospatial":"Fourmile Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.61347198486328,\n 41.761196772309965\n ],\n [\n -93.61347198486328,\n 41.79172868968446\n ],\n [\n -93.5866928100586,\n 41.79172868968446\n ],\n [\n -93.5866928100586,\n 41.761196772309965\n ],\n [\n -93.61347198486328,\n 41.761196772309965\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"568","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57724022e4b07657d1a7939b","chorus":{"doi":"10.1016/j.scitotenv.2016.06.104","url":"http://dx.doi.org/10.1016/j.scitotenv.2016.06.104","publisher":"Elsevier BV","authors":"Bradley Paul M., Barber Larry B., Clark Jimmy M., Duris Joseph W., Foreman William T., Furlong Edward T., Givens Carrie E., Hubbard Laura E., Hutchinson Kasey J., Journey Celeste A., Keefe Steffanie H., Kolpin Dana W.","journalName":"Science of The Total Environment","publicationDate":"10/2016"},"contributors":{"authors":[{"text":"Bradley, Paul M. 0000-0001-7522-8606 pbradley@usgs.gov","orcid":"https://orcid.org/0000-0001-7522-8606","contributorId":361,"corporation":false,"usgs":true,"family":"Bradley","given":"Paul","email":"pbradley@usgs.gov","middleInitial":"M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":640743,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barber, Larry B. 0000-0002-0561-0831 lbbarber@usgs.gov","orcid":"https://orcid.org/0000-0002-0561-0831","contributorId":921,"corporation":false,"usgs":true,"family":"Barber","given":"Larry","email":"lbbarber@usgs.gov","middleInitial":"B.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":640744,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clark, Jimmy M. 0000-0002-3138-5738 jmclark@usgs.gov","orcid":"https://orcid.org/0000-0002-3138-5738","contributorId":4773,"corporation":false,"usgs":true,"family":"Clark","given":"Jimmy","email":"jmclark@usgs.gov","middleInitial":"M.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":true,"id":640745,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Duris, Joseph W. 0000-0002-8669-8109 jwduris@usgs.gov","orcid":"https://orcid.org/0000-0002-8669-8109","contributorId":172426,"corporation":false,"usgs":true,"family":"Duris","given":"Joseph","email":"jwduris@usgs.gov","middleInitial":"W.","affiliations":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true},{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":false,"id":640746,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Foreman, William T. 0000-0002-2530-3310 wforeman@usgs.gov","orcid":"https://orcid.org/0000-0002-2530-3310","contributorId":169108,"corporation":false,"usgs":true,"family":"Foreman","given":"William T. 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