Oxygen, hydrogen, sulfur, and carbon isotopes have been analyzed in the Pea Ridge magnetite-apatite deposit, the largest historic producer among the known iron deposits in the southeast Missouri portion of the 1.5 to 1.3 Ga eastern granite-rhyolite province. The data were collected to investigate the sources of ore fluids, conditions of ore formation, and provenance of sulfur, and to improve the general understanding of the copper, gold, and rare earth element potential of iron deposits regionally. The δ18O values of Pea Ridge magnetite are 1.9 to 4.0‰, consistent with a model in which some magnetite crystallized from a melt and other magnetite—perhaps the majority—precipitated from an aqueous fluid of magmatic origin. The δ18O values of quartz, apatite, actinolite, K-feldspar, sulfates, and calcite are significantly higher, enough so as to indicate growth or equilibration under cooler conditions than magnetite and/or in the presence of a fluid that was not entirely magmatic. A variety of observations, including stable isotope observations, implicate a second fluid that may ultimately have been meteoric in origin and may have been modified by isotopic exchange with rocks or by evaporation during storage in lakes.
Sulfur isotope analyses of sulfides from Pea Ridge and seven other mineral deposits in the region reveal two distinct populations that average 3 and 13‰. Two sulfur sources are implied. One was probably igneous melts or rocks belonging to the mafic- to intermediate-composition volcanic suite that is present at or near most of the iron deposits; the other was either melts or volcanic rocks that had degassed very extensively, or else volcanic lakes that had trapped rising magmatic gases. The higher δ34S values correspond to deposits or prospects where copper is noteworthy—the Central Dome portion of the Boss deposit, the Bourbon deposit, and the Vilander prospective area. The correspondence suggests that (1) sulfur either limited the deposition of copper or was cotransported with copper, and (2) sulfur isotope analysis may be useful in evaluating southeast Missouri iron deposits for copper and possibly for gold.
","language":"English","publisher":"Society of Economic Geologists","doi":"10.2113/econgeo.111.8.2017","usgsCitation":"Johnson, C.A., Day, W.C., and Rye, R.O., 2016, Oxygen, hydrogen, sulfur, and carbon isotopes in the Pea Ridge magnetite-apatite deposit, southeast Missouri, and sulfur isotope comparisons to other iron deposits in the region: Economic Geology, v. 111, no. 8, p. 2017-2032, https://doi.org/10.2113/econgeo.111.8.2017.","productDescription":"16 p.","startPage":"2017","endPage":"2032","ipdsId":"IP-069800","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":331639,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri","volume":"111","issue":"8","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-16","publicationStatus":"PW","scienceBaseUri":"58492df2e4b06d80b7b093a0","contributors":{"authors":[{"text":"Johnson, Craig A. 0000-0002-1334-2996 cjohnso@usgs.gov","orcid":"https://orcid.org/0000-0002-1334-2996","contributorId":909,"corporation":false,"usgs":true,"family":"Johnson","given":"Craig","email":"cjohnso@usgs.gov","middleInitial":"A.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":655118,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Day, Warren C. 0000-0002-9278-2120 wday@usgs.gov","orcid":"https://orcid.org/0000-0002-9278-2120","contributorId":1308,"corporation":false,"usgs":true,"family":"Day","given":"Warren","email":"wday@usgs.gov","middleInitial":"C.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":655119,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rye, Robert O. rrye@usgs.gov","contributorId":1486,"corporation":false,"usgs":true,"family":"Rye","given":"Robert","email":"rrye@usgs.gov","middleInitial":"O.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":655120,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70185064,"text":"70185064 - 2016 - Modeling the effects of tile drain placement on the hydrologic function of farmed prairie wetlands","interactions":[],"lastModifiedDate":"2017-03-14T11:39:36","indexId":"70185064","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Modeling the effects of tile drain placement on the hydrologic function of farmed prairie wetlands","docAbstract":"The early 2000s saw large increases in agricultural tile drainage in the eastern Dakotas of North America. Agricultural practices that drain wetlands directly are sometimes limited by wetland protection programs. Little is known about the impacts of tile drainage beyond the delineated boundaries of wetlands in upland catchments that may be in agricultural production. A series of experiments were conducted using the well-published model WETLANDSCAPE that revealed the potential for wetlands to have significantly shortened surface water inundation periods and lower mean depths when tile is placed in certain locations beyond the wetland boundary. Under the soil conditions found in agricultural areas of South Dakota in North America, wetland hydroperiod was found to be more sensitive to the depth that drain tile is installed relative to the bottom of the wetland basin than to distance-based setbacks. Because tile drainage can change the hydrologic conditions of wetlands, even when deployed in upland catchments, tile drainage plans should be evaluated more closely for the potential impacts they might have on the ecological services that these wetlands currently provide. Future research should investigate further how drainage impacts are affected by climate variability and change.
","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12471","usgsCitation":"Werner, B., Tracy, J., Johnson, W.C., Voldseth, R.A., Guntenspergen, G.R., and Millett, B., 2016, Modeling the effects of tile drain placement on the hydrologic function of farmed prairie wetlands: Journal of the American Water Resources Association, v. 52, no. 6, p. 1482-1492, https://doi.org/10.1111/1752-1688.12471.","productDescription":"11 p.","startPage":"1482","endPage":"1492","ipdsId":"IP-067298","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":488561,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://digitalcommons.unl.edu/usgsstaffpub/1156","text":"External Repository"},{"id":337490,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"52","issue":"6","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-29","publicationStatus":"PW","scienceBaseUri":"58c90124e4b0849ce97abcc1","contributors":{"authors":[{"text":"Werner, Brett","contributorId":189217,"corporation":false,"usgs":false,"family":"Werner","given":"Brett","email":"","affiliations":[],"preferred":false,"id":684132,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Tracy, John","contributorId":189218,"corporation":false,"usgs":false,"family":"Tracy","given":"John","email":"","affiliations":[],"preferred":false,"id":684133,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, W. 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In response to California’s extreme natural hydroclimatic variability, complex water-management systems have been developed, even as the Delta’s natural ecosystems have been largely devastated. Climate change is projected to challenge these management and ecological systems in different ways that are characterized by different levels of uncertainty. For example, there is high certainty that climate will warm by about 2°C more (than late-20th-century averages) by mid-century and about 4°C by end of century, if greenhouse-gas emissions continue their current rates of acceleration. Future precipitation changes are much less certain, with as many climate models projecting wetter conditions as drier. However, the same projections agree that precipitation will be more intense when storms do arrive, even as more dry days will separate storms. Warmer temperatures will likely enhance evaporative demands and raise water temperatures. Consequently, climate change is projected to yield both more extreme flood risks and greater drought risks. Sea level rise (SLR) during the 20th century was about 22cm, and is projected to increase by at least 3-fold this century. SLR together with land subsidence threatens the Delta with greater vulnerabilities to inundation and salinity intrusion. Effects on the Delta ecosystem that are traceable to warming include SLR, reduced snowpack, earlier snowmelt and larger storm-driven streamflows, warmer and longer summers, warmer summer water temperatures, and water-quality changes. These changes and their uncertainties will challenge the operations of water projects and uses throughout the Delta’s watershed and delivery areas. Although the effects of climate change on Delta ecosystems may be profound, the end results are difficult to predict, except that native species will fare worse than invaders. Successful preparation for the coming changes will require greater integration of monitoring, modeling, and decision making across time, variables, and space than has been historically normal.
","language":"English","publisher":"University of California","doi":"10.15447/sfews.2016v14iss3art5","usgsCitation":"Dettinger, M.D., Anderson, J., Anderson, M.L., Brown, L.R., Cayan, D., and Maurer, E., 2016, Climate change and the Delta: San Francisco Estuary and Watershed Science, v. 14, no. 3, p. 1-26, https://doi.org/10.15447/sfews.2016v14iss3art5.","productDescription":"Article 5; 26 p.","startPage":"1","endPage":"26","ipdsId":"IP-077659","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":552,"text":"San Francisco Bay-Delta","active":false,"usgs":true}],"links":[{"id":470395,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.15447/sfews.2016v14iss3art5","text":"Publisher Index Page"},{"id":334064,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"14","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-09","publicationStatus":"PW","scienceBaseUri":"588b1977e4b0ad67323f97e2","contributors":{"authors":[{"text":"Dettinger, Michael D. 0000-0002-7509-7332 mddettin@usgs.gov","orcid":"https://orcid.org/0000-0002-7509-7332","contributorId":149896,"corporation":false,"usgs":true,"family":"Dettinger","given":"Michael","email":"mddettin@usgs.gov","middleInitial":"D.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":660928,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Jamie","contributorId":178769,"corporation":false,"usgs":false,"family":"Anderson","given":"Jamie","email":"","affiliations":[],"preferred":false,"id":660929,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, Michael L.","contributorId":149932,"corporation":false,"usgs":false,"family":"Anderson","given":"Michael","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":660930,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Brown, Larry R. 0000-0001-6702-4531 lrbrown@usgs.gov","orcid":"https://orcid.org/0000-0001-6702-4531","contributorId":1717,"corporation":false,"usgs":true,"family":"Brown","given":"Larry","email":"lrbrown@usgs.gov","middleInitial":"R.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":660931,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cayan, Daniel drcayan@usgs.gov","contributorId":149912,"corporation":false,"usgs":true,"family":"Cayan","given":"Daniel","email":"drcayan@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":660932,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Maurer, Edwin P.","contributorId":13129,"corporation":false,"usgs":true,"family":"Maurer","given":"Edwin P.","affiliations":[],"preferred":false,"id":660933,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70178875,"text":"70178875 - 2016 - Cryovolcanism on Ceres","interactions":[],"lastModifiedDate":"2016-12-12T11:43:14","indexId":"70178875","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3338,"text":"Science","active":true,"publicationSubtype":{"id":10}},"title":"Cryovolcanism on Ceres","docAbstract":"Volcanic edifices are abundant on rocky bodies of the inner solar system. In the cold outer solar system, volcanism can occur on solid bodies with a water-ice shell, but derived cryovolcanic constructs have proved elusive. We report the discovery using Dawn Framing Camera images of a landform on dwarf planet Ceres, which we argue represents a viscous cryovolcanic dome. Parent material of the cryomagma is a mixture of secondary minerals, including salts and water ice. Absolute model ages from impact craters reveal that extrusion of the dome has occurred recently. Ceres’ evolution must have been able to sustain recent interior activity and associated surface expressions. We propose salts with low eutectic temperatures and thermal conductivities as key drivers for Ceres’ long-term internal evolution.","language":"English","publisher":"American Association for the Advancement of Science","doi":"10.1126/science.aaf4286","usgsCitation":"Ruesch, O., Platz, T., Schenk, P., McFadden, L., Castillo-Rogez, J.C., Quick, L.C., Byrne, S., Preusker, F., O'Brien, D., Schmedemann, N., Williams, D., Li, J., Bland, M.T., Hiesinger, H., Kneissl, T., Neesemann, A., Schaefer, M., Pasckert, J.H., Schmidt, B., Buczkowski, D., Sykes, M.V., Nathues, A., Roatsch, T., Hoffman, M., Raymond, C., and Russell, C., 2016, Cryovolcanism on Ceres: Science, v. 353, no. 6303, https://doi.org/10.1126/science.aaf4286.","ipdsId":"IP-073646","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":462017,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://zenodo.org/record/1231277","text":"Publisher Index Page"},{"id":331910,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"353","issue":"6303","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"584fc563e4b00645734c539f","contributors":{"authors":[{"text":"Ruesch, O.","contributorId":177366,"corporation":false,"usgs":false,"family":"Ruesch","given":"O.","email":"","affiliations":[],"preferred":false,"id":655537,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Platz, T.","contributorId":177362,"corporation":false,"usgs":false,"family":"Platz","given":"T.","affiliations":[],"preferred":false,"id":655538,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schenk, P.","contributorId":105484,"corporation":false,"usgs":true,"family":"Schenk","given":"P.","affiliations":[],"preferred":false,"id":655539,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McFadden, L.A.","contributorId":35511,"corporation":false,"usgs":true,"family":"McFadden","given":"L.A.","email":"","affiliations":[],"preferred":false,"id":655540,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Castillo-Rogez, J. 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H.","contributorId":177382,"corporation":false,"usgs":false,"family":"Pasckert","given":"J.","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":655553,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Schmidt, B.E.","contributorId":177354,"corporation":false,"usgs":false,"family":"Schmidt","given":"B.E.","email":"","affiliations":[{"id":27526,"text":"Georgia Institute of Technology","active":true,"usgs":false}],"preferred":false,"id":655554,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Buczkowski, D.L.","contributorId":66512,"corporation":false,"usgs":true,"family":"Buczkowski","given":"D.L.","email":"","affiliations":[],"preferred":false,"id":655555,"contributorType":{"id":1,"text":"Authors"},"rank":20},{"text":"Sykes, M. V.","contributorId":177363,"corporation":false,"usgs":false,"family":"Sykes","given":"M.","email":"","middleInitial":"V.","affiliations":[],"preferred":false,"id":655556,"contributorType":{"id":1,"text":"Authors"},"rank":21},{"text":"Nathues, A.","contributorId":24145,"corporation":false,"usgs":true,"family":"Nathues","given":"A.","affiliations":[],"preferred":false,"id":655557,"contributorType":{"id":1,"text":"Authors"},"rank":22},{"text":"Roatsch, T.","contributorId":18933,"corporation":false,"usgs":true,"family":"Roatsch","given":"T.","email":"","affiliations":[],"preferred":false,"id":655558,"contributorType":{"id":1,"text":"Authors"},"rank":23},{"text":"Hoffman, M.","contributorId":73163,"corporation":false,"usgs":false,"family":"Hoffman","given":"M.","email":"","affiliations":[],"preferred":false,"id":655559,"contributorType":{"id":1,"text":"Authors"},"rank":24},{"text":"Raymond, C.A.","contributorId":50301,"corporation":false,"usgs":false,"family":"Raymond","given":"C.A.","email":"","affiliations":[{"id":18954,"text":"Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA","active":true,"usgs":false}],"preferred":false,"id":655560,"contributorType":{"id":1,"text":"Authors"},"rank":25},{"text":"Russell, C.T.","contributorId":32275,"corporation":false,"usgs":false,"family":"Russell","given":"C.T.","email":"","affiliations":[{"id":33607,"text":"University of California Los Angeles","active":true,"usgs":false}],"preferred":false,"id":655561,"contributorType":{"id":1,"text":"Authors"},"rank":26}]}} ,{"id":70184979,"text":"70184979 - 2016 - 3-D P- and S-wave velocity structure and low-frequency earthquake locations in the Parkfield, California region","interactions":[],"lastModifiedDate":"2017-03-14T15:44:12","indexId":"70184979","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1803,"text":"Geophysical Journal International","active":true,"publicationSubtype":{"id":10}},"title":"3-D P- and S-wave velocity structure and low-frequency earthquake locations in the Parkfield, California region","docAbstract":"To refine the 3-D seismic velocity model in the greater Parkfield, California region, a new data set including regular earthquakes, shots, quarry blasts and low-frequency earthquakes (LFEs) was assembled. Hundreds of traces of each LFE family at two temporary arrays were stacked with time–frequency domain phase weighted stacking method to improve signal-to-noise ratio. We extend our model resolution to lower crustal depth with LFE data. Our result images not only previously identified features but also low velocity zones (LVZs) in the area around the LFEs and the lower crust beneath the southern Rinconada Fault. The former LVZ is consistent with high fluid pressure that can account for several aspects of LFE behaviour. The latter LVZ is consistent with a high conductivity zone in magnetotelluric studies. A new Vs model was developed with S picks that were obtained with a new autopicker. At shallow depth, the low Vs areas underlie the strongest shaking areas in the 2004 Parkfield earthquake. We relocate LFE families and analyse the location uncertainties with the NonLinLoc and tomoDD codes. The two methods yield similar results.
","language":"English","publisher":"Oxford University Press","doi":"10.1093/gji/ggw217","usgsCitation":"Zeng, X., Thurber, C.H., Shelly, D.R., Harrington, R., Cochran, E.S., Bennington, N.L., Peterson, D., Guo, B., and McClement, K., 2016, 3-D P- and S-wave velocity structure and low-frequency earthquake locations in the Parkfield, California region: Geophysical Journal International, v. 206, no. 3, p. 1574-1585, https://doi.org/10.1093/gji/ggw217.","productDescription":"12 p.","startPage":"1574","endPage":"1585","ipdsId":"IP-070431","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":470385,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/gji/ggw217","text":"Publisher Index Page"},{"id":337540,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Parkfield","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.5,\n 35\n ],\n [\n -119,\n 35\n ],\n [\n -119,\n 37\n ],\n [\n -121.5,\n 37\n ],\n [\n -121.5,\n 35\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"206","issue":"3","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-06-14","publicationStatus":"PW","scienceBaseUri":"58c90125e4b0849ce97abcc9","contributors":{"authors":[{"text":"Zeng, Xiangfang","contributorId":177477,"corporation":false,"usgs":false,"family":"Zeng","given":"Xiangfang","email":"","affiliations":[],"preferred":false,"id":683807,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Thurber, Clifford H. 0000-0002-4940-4618","orcid":"https://orcid.org/0000-0002-4940-4618","contributorId":73184,"corporation":false,"usgs":false,"family":"Thurber","given":"Clifford","email":"","middleInitial":"H.","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":683808,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shelly, David R. dshelly@usgs.gov","contributorId":2978,"corporation":false,"usgs":true,"family":"Shelly","given":"David","email":"dshelly@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":683806,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Harrington, Rebecca M.","contributorId":71089,"corporation":false,"usgs":true,"family":"Harrington","given":"Rebecca M.","affiliations":[],"preferred":false,"id":683809,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Cochran, Elizabeth S. 0000-0003-2485-4484 ecochran@usgs.gov","orcid":"https://orcid.org/0000-0003-2485-4484","contributorId":2025,"corporation":false,"usgs":true,"family":"Cochran","given":"Elizabeth","email":"ecochran@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":683810,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bennington, Ninfa L.","contributorId":172950,"corporation":false,"usgs":false,"family":"Bennington","given":"Ninfa","email":"","middleInitial":"L.","affiliations":[{"id":16925,"text":"University of Wisconsin-Madison","active":true,"usgs":false}],"preferred":false,"id":684308,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Peterson, Dana","contributorId":189268,"corporation":false,"usgs":false,"family":"Peterson","given":"Dana","affiliations":[],"preferred":false,"id":684309,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Guo, Bin","contributorId":189269,"corporation":false,"usgs":false,"family":"Guo","given":"Bin","email":"","affiliations":[],"preferred":false,"id":684310,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"McClement, Kara","contributorId":189270,"corporation":false,"usgs":false,"family":"McClement","given":"Kara","email":"","affiliations":[],"preferred":false,"id":684311,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70179443,"text":"70179443 - 2016 - Modeling and simulation of storm surge on Staten Island to understand inundation mitigation strategies","interactions":[],"lastModifiedDate":"2017-01-03T11:32:41","indexId":"70179443","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2220,"text":"Journal of Coastal Research","active":true,"publicationSubtype":{"id":10}},"title":"Modeling and simulation of storm surge on Staten Island to understand inundation mitigation strategies","docAbstract":"Hurricane Sandy made landfall on October 29, 2012, near Brigantine, New Jersey, and had a transformative impact on Staten Island and the New York Metropolitan area. Of the 43 New York City fatalities, 23 occurred on Staten Island. The borough, with a population of approximately 500,000, experienced some of the most devastating impacts of the storm. Since Hurricane Sandy, protective dunes have been constructed on the southeast shore of Staten Island. ADCIRC+SWAN model simulations run on The City University of New York's Cray XE6M, housed at the College of Staten Island, using updated topographic data show that the coast of Staten Island is still susceptible to tidal surge similar to those generated by Hurricane Sandy. Sandy hindcast simulations of storm surges focusing on Staten Island are in good agreement with observed storm tide measurements. Model results calculated from fine-scaled and coarse-scaled computational grids demonstrate that finer grids better resolve small differences in the topography of critical hydraulic control structures, which affect storm surge inundation levels. The storm surge simulations, based on post-storm topography obtained from high-resolution lidar, provide much-needed information to understand Staten Island's changing vulnerability to storm surge inundation. The results of fine-scale storm surge simulations can be used to inform efforts to improve resiliency to future storms. For example, protective barriers contain planned gaps in the dunes to provide for beach access that may inadvertently increase the vulnerability of the area.
","language":"English","publisher":"Coastal Education and Research Foundation","doi":"10.2112/SI76-013","usgsCitation":"Kress, M.E., Benimoff, A.I., Fritz, W.J., Thatcher, C.A., Blanton, B.O., and Dzedzits, E., 2016, Modeling and simulation of storm surge on Staten Island to understand inundation mitigation strategies: Journal of Coastal Research, v. Special Issue 76, p. 149-161, https://doi.org/10.2112/SI76-013.","productDescription":"13 p.","startPage":"149","endPage":"161","ipdsId":"IP-062638","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"links":[{"id":462021,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.17615/7b0p-2a36","text":"External Repository"},{"id":332735,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Staten Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.13625717163086,\n 40.52593506631396\n ],\n [\n -74.04544830322264,\n 40.605090749765786\n ],\n [\n -74.06364440917969,\n 40.61890405098613\n ],\n [\n -74.1525650024414,\n 40.53806878053114\n ],\n [\n -74.13625717163086,\n 40.52593506631396\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"Special Issue 76","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"586cc695e4b0f5ce109fa94f","contributors":{"authors":[{"text":"Kress, Michael E.","contributorId":177814,"corporation":false,"usgs":false,"family":"Kress","given":"Michael","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":657220,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Benimoff, Alan I.","contributorId":177815,"corporation":false,"usgs":false,"family":"Benimoff","given":"Alan","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":657221,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fritz, William J.","contributorId":177816,"corporation":false,"usgs":false,"family":"Fritz","given":"William","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":657222,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thatcher, Cindy A. 0000-0003-0331-071X thatcherc@usgs.gov","orcid":"https://orcid.org/0000-0003-0331-071X","contributorId":2868,"corporation":false,"usgs":true,"family":"Thatcher","given":"Cindy","email":"thatcherc@usgs.gov","middleInitial":"A.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":423,"text":"National Geospatial Program","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"preferred":false,"id":657223,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Blanton, Brian O.","contributorId":177817,"corporation":false,"usgs":false,"family":"Blanton","given":"Brian","email":"","middleInitial":"O.","affiliations":[],"preferred":false,"id":657224,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dzedzits, Eugene","contributorId":177818,"corporation":false,"usgs":false,"family":"Dzedzits","given":"Eugene","email":"","affiliations":[],"preferred":false,"id":657225,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70179123,"text":"70179123 - 2016 - Case study: 2016 Natural glide and wet slab avalanche cycle, Going-to-the-Sun Road, Glacier National Park, Montana, USA","interactions":[],"lastModifiedDate":"2017-01-12T13:53:11","indexId":"70179123","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Case study: 2016 Natural glide and wet slab avalanche cycle, Going-to-the-Sun Road, Glacier National Park, Montana, USA","docAbstract":"The Going-to-the-Sun Road (GTSR) is the premier tourist attraction in Glacier\nNational Park, Montana. The GTSR also traverses through and under 40 avalanche paths which\npose a hazard to National Park Service (NPS) road crews during the annual spring snow plowing\noperation. Through a joint collaboration between the NPS and the U.S. Geological Survey\n(USGS), a forecasting program primarily dealing with wet snow avalanche problems serves to\naid worker safety. The objective of this case study is to examine the meteorological metrics and\nsnowpack characteristics leading up to a noteworthy wet slab and glide avalanche cycle that occurred\n16-22 April, 2016 during a period of unseasonably warm and sunny weather. Continuous\nabove freezing temperatures at upper elevations with daily maximum values reaching 10-15° C\npersisted for four days. The nearby Flattop Mountain SNOTEL station reported a steady loss of\nSWE of approximately 1.25 cm/day. River height and discharge on the Middle Fork of the Flathead\nRiver (app. 20-35 km away from starting zones) increased from 1.26 m and 139.60 m3/s\n(4930 cfs), respectively, on April 18 to 1.69 m and 267.59 m3/s (9450 cfs) on April 22. The ensuing\navalanche cycle began with three small glide avalanches on 17 April and culminated in three\nlarge wet slab avalanches that released on wet, basal facets. These wet slabs were triggered by\nglide avalanches releasing above and cascading over cliffs. Four of these avalanches crossed\nplowed sections of the road, resulting in a three day delay in plowing operations. Finally, this\nspecific case was compared to previous statistical models for wet snow avalanches in this transportation\ncorridor. Out of 12 avalanche days, the model correctly predicted six of those days as\navalanche days. This case study allowed for a greater understanding of a wet slab and glide avalanche\ncycle that occurred during a prolonged spring warming event and can serve as a reference\nfor future similar cycles.","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Proceedings of the International Snow Science Workshop","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"International Snow Science Workshop","conferenceDate":"October 3-7, 2016","conferenceLocation":"Breckenridge, CO","language":"English","publisher":"International Snow Science Workshop","usgsCitation":"Hutchinson, J., Peitzsch, E.H., and Clark, A., 2016, Case study: 2016 Natural glide and wet slab avalanche cycle, Going-to-the-Sun Road, Glacier National Park, Montana, USA, in Proceedings of the International Snow Science Workshop, Breckenridge, CO, October 3-7, 2016, p. 66-73.","productDescription":"8 p.","startPage":"66","endPage":"73","ipdsId":"IP-079047","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":333112,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5878a48ce4b04df303d9580c","contributors":{"authors":[{"text":"Hutchinson, Jacob","contributorId":177528,"corporation":false,"usgs":false,"family":"Hutchinson","given":"Jacob","email":"","affiliations":[],"preferred":false,"id":656098,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Peitzsch, Erich H. 0000-0001-7624-0455 epeitzsch@usgs.gov","orcid":"https://orcid.org/0000-0001-7624-0455","contributorId":3786,"corporation":false,"usgs":true,"family":"Peitzsch","given":"Erich","email":"epeitzsch@usgs.gov","middleInitial":"H.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":656097,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clark, Adam 0000-0002-8863-1434 amclark@usgs.gov","orcid":"https://orcid.org/0000-0002-8863-1434","contributorId":177529,"corporation":false,"usgs":true,"family":"Clark","given":"Adam","email":"amclark@usgs.gov","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":656099,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70182236,"text":"70182236 - 2016 - The relative contributions of disease and insects in the decline of a long-lived tree: a stochastic demographic model of whitebark pine (Pinus albicaulis)","interactions":[],"lastModifiedDate":"2017-02-22T16:01:15","indexId":"70182236","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1687,"text":"Forest Ecology and Management","active":true,"publicationSubtype":{"id":10}},"title":"The relative contributions of disease and insects in the decline of a long-lived tree: a stochastic demographic model of whitebark pine (Pinus albicaulis)","docAbstract":"Pathogens and insect pests have become increasingly important drivers of tree mortality in forested ecosystems. Unfortunately, understanding the relative contributions of multiple mortality agents to the population decline of trees is difficult, because it requires frequent measures of tree survival, growth, and recruitment, as well as the incidence of mortality agents. We present a population model of whitebark pine (Pinus albicaulis), a high-elevation tree undergoing rapid decline in western North America. The loss of whitebark pine is thought to be primarily due to an invasive pathogen (white pine blister rust; Cronartium ribicola) and a native insect (mountain pine beetle; Dendroctonus ponderosae). We utilized seven plots in Crater Lake National Park (Oregon, USA) where 1220 trees were surveyed for health and the presence of blister rust and beetle activity annually from 2003–2014, except 2008. We constructed size-based projection matrices for nine years and calculated the deterministic growth rate (λ) using an average matrix and the stochastic growth rate (λs) by simulation for whitebark pine in our study population. We then assessed the roles of blister rust and beetles by calculating λ and λsusing matrices in which we removed trees with blister rust and, separately, trees with beetles. We also conducted life-table response experiments (LTRE) to determine which demographic changes contributed most to differences in λ between ambient conditions and the two other scenarios. The model suggests that whitebark pine in our plots are currently declining 1.1% per year (λ = 0.9888, λs = 0.9899). Removing blister rust from the models resulted in almost no increase in growth (λ = 0.9916, λs = 0.9930), while removing beetles resulted in a larger increase in growth (λ = 1.0028, λs = 1.0045). The LTRE demonstrated that reductions in stasis of the three largest size classes due to beetles contributed most to the smaller λ in the ambient condition. Our work demonstrates a method for assessing the relative effects of different mortality agents on declining tree populations, and it shows that the effects of insects and pathogens can be markedly different from one another. In our study, beetle activity significantly reduced tree population growth while a pathogen had minimal effect, thus management actions to stabilize our study population will likely need to include reducing beetle activity.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.foreco.2016.09.022","usgsCitation":"Jules, E., Jackson, J.I., van Mantgem, P.J., Beck, J.S., Murray, M.P., and Sahara, E.A., 2016, The relative contributions of disease and insects in the decline of a long-lived tree: a stochastic demographic model of whitebark pine (Pinus albicaulis): Forest Ecology and Management, v. 381, p. 144-156, https://doi.org/10.1016/j.foreco.2016.09.022.","productDescription":"13 p.","startPage":"144","endPage":"156","ipdsId":"IP-075247","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":470354,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.foreco.2016.09.022","text":"Publisher Index Page"},{"id":336015,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"381","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58aeb13be4b01ccd54f9ee18","chorus":{"doi":"10.1016/j.foreco.2016.09.022","url":"http://dx.doi.org/10.1016/j.foreco.2016.09.022","publisher":"Elsevier BV","authors":"Jules Erik S., Jackson Jenell I., van Mantgem Phillip J., Beck Jennifer S., Murray Michael P., Sahara E. April","journalName":"Forest Ecology and Management","publicationDate":"12/2016"},"contributors":{"authors":[{"text":"Jules, Erik S","contributorId":181945,"corporation":false,"usgs":false,"family":"Jules","given":"Erik S","affiliations":[],"preferred":false,"id":670110,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jackson, Jenell I.","contributorId":181946,"corporation":false,"usgs":false,"family":"Jackson","given":"Jenell","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":670111,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"van Mantgem, Phillip J. 0000-0002-3068-9422 pvanmantgem@usgs.gov","orcid":"https://orcid.org/0000-0002-3068-9422","contributorId":2838,"corporation":false,"usgs":true,"family":"van Mantgem","given":"Phillip","email":"pvanmantgem@usgs.gov","middleInitial":"J.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":670109,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Beck, Jennifer S.","contributorId":181947,"corporation":false,"usgs":false,"family":"Beck","given":"Jennifer","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":670112,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Murray, Michael P.","contributorId":181948,"corporation":false,"usgs":false,"family":"Murray","given":"Michael","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":670113,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sahara, E. April","contributorId":181949,"corporation":false,"usgs":false,"family":"Sahara","given":"E.","email":"","middleInitial":"April","affiliations":[],"preferred":false,"id":670114,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70184994,"text":"70184994 - 2016 - Temporal and spatial trends in nutrient and sediment loading to Lake Tahoe, California-Nevada, USA","interactions":[],"lastModifiedDate":"2017-03-13T12:56:10","indexId":"70184994","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Temporal and spatial trends in nutrient and sediment loading to Lake Tahoe, California-Nevada, USA","docAbstract":"Since 1980, the Lake Tahoe Interagency Monitoring Program (LTIMP) has provided stream-discharge and water quality data—nitrogen (N), phosphorus (P), and suspended sediment—at more than 20 stations in Lake Tahoe Basin streams. To characterize the temporal and spatial patterns in nutrient and sediment loading to the lake, and improve the usefulness of the program and the existing database, we have (1) identified and corrected for sources of bias in the water quality database; (2) generated synthetic datasets for sediments and nutrients, and resampled to compare the accuracy and precision of different load calculation models; (3) using the best models, recalculated total annual loads over the period of record; (4) regressed total loads against total annual and annual maximum daily discharge, and tested for time trends in the residuals; (5) compared loads for different forms of N and P; and (6) tested constituent loads against land use-land cover (LULC) variables using multiple regression. The results show (1) N and P loads are dominated by organic N and particulate P; (2) there are significant long-term downward trends in some constituent loads of some streams; and (3) anthropogenic impervious surface is the most important LULC variable influencing water quality in basin streams. Many of our recommendations for changes in water quality monitoring and load calculation methods have been adopted by the LTIMP.
","language":"English","publisher":"Wiley","doi":"10.1111/1752-1688.12461","usgsCitation":"Coats, R., Lewis, J., Alvarez, N., and Arneson, P., 2016, Temporal and spatial trends in nutrient and sediment loading to Lake Tahoe, California-Nevada, USA: Journal of the American Water Resources Association, v. 52, no. 6, p. 1347-1365, https://doi.org/10.1111/1752-1688.12461.","productDescription":"19 p.","startPage":"1347","endPage":"1365","ipdsId":"IP-075203","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":337429,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Nevada","otherGeospatial":"Lake Tahoe","volume":"52","issue":"6","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2016-10-04","publicationStatus":"PW","scienceBaseUri":"58c7af9ce4b0849ce9795e7c","contributors":{"authors":[{"text":"Coats, Robert","contributorId":108007,"corporation":false,"usgs":true,"family":"Coats","given":"Robert","affiliations":[],"preferred":false,"id":683865,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lewis, Jack","contributorId":189105,"corporation":false,"usgs":false,"family":"Lewis","given":"Jack","email":"","affiliations":[],"preferred":false,"id":683866,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Alvarez, Nancy L. nalvarez@usgs.gov","contributorId":4570,"corporation":false,"usgs":true,"family":"Alvarez","given":"Nancy L.","email":"nalvarez@usgs.gov","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":683864,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Arneson, Patricia","contributorId":189106,"corporation":false,"usgs":false,"family":"Arneson","given":"Patricia","email":"","affiliations":[],"preferred":false,"id":683867,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70185043,"text":"70185043 - 2016 - Application of frequency- and time-domain electromagnetic surveys to characterize hydrostratigraphy and landfill construction at the Amargosa Desert Research Site, Beatty, Nevada","interactions":[],"lastModifiedDate":"2018-08-06T12:35:04","indexId":"70185043","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Application of frequency- and time-domain electromagnetic surveys to characterize hydrostratigraphy and landfill construction at the Amargosa Desert Research Site, Beatty, Nevada","docAbstract":"In 2014 and 2015, the U.S. Geological Survey (USGS), conducted frequency-domain electromagnetic (FDEM) surveys at the USGS Amargosa Desert Research Site (ADRS), approximately 17 kilometers (km) south of Beatty, Nevada. The FDEM surveys were conducted within and adjacent to a closed low-level radioactive waste disposal site located at the ADRS. FDEM surveys were conducted on a grid of north-south and east-west profiles to assess the locations and boundaries of historically recorded waste-disposal trenches. In 2015, the USGS conducted time-domain (TDEM) soundings along a profile adjacent to the disposal site (landfill) in cooperation with the U.S. Environmental Protection Agency (USEPA), to assess the thickness and characteristics of the underlying deep unsaturated zone, and the hydrostratigraphy of the underlying saturated zone.
FDEM survey results indicate the general location and extent of the waste-disposal trenches and reveal potential differences in material properties and the type and concentration of waste in several areas of the landfill. The TDEM surveys provide information on the underlying hydrostratigraphy and characteristics of the unsaturated zone that inform the site conceptual model and support an improved understanding of the hydrostratigraphic framework. Additional work is needed to interpret the TDEM results in the context of the local and regional structural geology.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkSubtype":{"id":12,"text":"Conference publication"},"language":"English","publisher":"Society of Exploration Geophysicists","publisherLocation":"Symposium on the application of geophysics to engineering and environmental problems 2016","doi":"10.4133/SAGEEP.29-024","usgsCitation":"White, E.A., Day-Lewis, F.D., Johnson, C.D., and Lane, J.W., 2016, Application of frequency- and time-domain electromagnetic surveys to characterize hydrostratigraphy and landfill construction at the Amargosa Desert Research Site, Beatty, Nevada, p. 119-125, https://doi.org/10.4133/SAGEEP.29-024.","productDescription":"7 p.","startPage":"119","endPage":"125","ipdsId":"IP-073130","costCenters":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":337694,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Nevada","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-03-24","publicationStatus":"PW","scienceBaseUri":"58cba41ae4b0849ce97dc73a","contributors":{"authors":[{"text":"White, Eric A. 0000-0002-7782-146X eawhite@usgs.gov","orcid":"https://orcid.org/0000-0002-7782-146X","contributorId":1737,"corporation":false,"usgs":false,"family":"White","given":"Eric","email":"eawhite@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":684055,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Day-Lewis, Frederick D. 0000-0003-3526-886X daylewis@usgs.gov","orcid":"https://orcid.org/0000-0003-3526-886X","contributorId":1672,"corporation":false,"usgs":true,"family":"Day-Lewis","given":"Frederick","email":"daylewis@usgs.gov","middleInitial":"D.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":true,"id":684057,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Carole D. 0000-0001-6941-1578 cjohnson@usgs.gov","orcid":"https://orcid.org/0000-0001-6941-1578","contributorId":1891,"corporation":false,"usgs":true,"family":"Johnson","given":"Carole","email":"cjohnson@usgs.gov","middleInitial":"D.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":684058,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lane, John W. Jr. 0000-0002-3558-243X jwlane@usgs.gov","orcid":"https://orcid.org/0000-0002-3558-243X","contributorId":189168,"corporation":false,"usgs":true,"family":"Lane","given":"John","suffix":"Jr.","email":"jwlane@usgs.gov","middleInitial":"W.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true}],"preferred":false,"id":684056,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70175667,"text":"70175667 - 2016 - An experimental study of the role of subsurface plumbing on geothermal discharge","interactions":[],"lastModifiedDate":"2016-12-30T09:50:21","indexId":"70175667","displayToPublicDate":"2016-12-01T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1757,"text":"Geochemistry, Geophysics, Geosystems","active":true,"publicationSubtype":{"id":10}},"title":"An experimental study of the role of subsurface plumbing on geothermal discharge","docAbstract":"In order to better understand the diverse discharge styles and eruption intervals observed at geothermal features, we performed three series of laboratory experiments with differing plumbing geometries. A single, straight conduit that connects a hot water bath (flask) to a vent (funnel) can originate geyser-like periodic eruptions, continuous discharge like a boiling spring, and fumarole-like steam discharge, depending on the conduit length and radius. The balance between the heat loss from the conduit walls and the heat supplied from the bottom determines whether and where water can condense which in turn controls discharge style. Next, we connected the conduit to a cold water reservoir through a branch, simulating the inflow from an external water source. Colder water located at a higher elevation than a branching point can flow into the conduit to stop the boiling in the flask, controlling the periodicity of the eruption. When an additional branch is connected to a second cold water reservoir, the two cold reservoirs can interact. Our experiments show that branching allows new processes to occur, such as recharge of colder water and escape of steam from side channels, leading to greater variation in discharge styles and eruption intervals. This model is consistent with the fact that eruption duration is not controlled by emptying reservoirs. We show how differences in plumbing geometries can explain various discharge styles and eruption intervals observed in El Tatio, Chile, and Yellowstone, USA.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2016GC006472","usgsCitation":"Namiki, A., Ueno, Y., Hurwitz, S., Manga, M., Munoz-Saez, C., and Murphy, F., 2016, An experimental study of the role of subsurface plumbing on geothermal discharge: Geochemistry, Geophysics, Geosystems, v. 17, no. 9, p. 3691-3716, https://doi.org/10.1002/2016GC006472.","productDescription":"26 p.","startPage":"3691","endPage":"3716","ipdsId":"IP-078999","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":470394,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://www.osti.gov/biblio/1480735","text":"Publisher Index Page"},{"id":332596,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"17","issue":"9","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-09-15","publicationStatus":"PW","scienceBaseUri":"5864dd4ee4b0cd2dabe7c1cd","contributors":{"authors":[{"text":"Namiki, Atsuko","contributorId":131170,"corporation":false,"usgs":false,"family":"Namiki","given":"Atsuko","email":"","affiliations":[{"id":7267,"text":"University of Tokyo","active":true,"usgs":false}],"preferred":false,"id":645983,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ueno, Yoshinori","contributorId":173811,"corporation":false,"usgs":false,"family":"Ueno","given":"Yoshinori","email":"","affiliations":[{"id":27300,"text":"Hiroshima University","active":true,"usgs":false}],"preferred":false,"id":645984,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hurwitz, Shaul 0000-0001-5142-6886 shaulh@usgs.gov","orcid":"https://orcid.org/0000-0001-5142-6886","contributorId":2169,"corporation":false,"usgs":true,"family":"Hurwitz","given":"Shaul","email":"shaulh@usgs.gov","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":645982,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Manga, Michael","contributorId":84679,"corporation":false,"usgs":true,"family":"Manga","given":"Michael","affiliations":[],"preferred":false,"id":645985,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Munoz-Saez, Carolina","contributorId":131167,"corporation":false,"usgs":false,"family":"Munoz-Saez","given":"Carolina","affiliations":[{"id":7102,"text":"University of California, Berkeley, Dept. of Civil & Envir. Engineering","active":true,"usgs":false}],"preferred":false,"id":645986,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Murphy, Fred fmurphy@usgs.gov","contributorId":4572,"corporation":false,"usgs":true,"family":"Murphy","given":"Fred","email":"fmurphy@usgs.gov","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":645987,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70178055,"text":"ofr20161185 - 2016 - Mountain goat abundance and population trends in the Olympic Mountains, northwestern Washington, 2016","interactions":[],"lastModifiedDate":"2017-11-22T15:52:53","indexId":"ofr20161185","displayToPublicDate":"2016-11-30T12:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-1185","title":"Mountain goat abundance and population trends in the Olympic Mountains, northwestern Washington, 2016","docAbstract":"We estimated abundance and trends of non-native mountain goats (Oreamnos americanus) in the Olympic Mountains of northwestern Washington, based on aerial surveys conducted during July 13–24, 2016. The surveys produced the seventh population estimate since the first formal aerial surveys were conducted in 1983. This was the second population estimate since we adjusted survey area boundaries and adopted new estimation procedures in 2011. Before 2011, surveys encompassed all areas free of glacial ice at elevations above 1,520 meters (m), but in 2011 we expanded survey unit boundaries to include suitable mountain goat habitats at elevations between 1,425 and 1,520 m. In 2011, we also began applying a sightability correction model allowing us to estimate undercounting bias associated with aerial surveys and to adjust survey results accordingly. The 2016 surveys were carried out by National Park Service (NPS) personnel in Olympic National Park and by Washington Department of Fish and Wildlife (WDFW) biologists in Olympic National Forest and in the southeastern part of Olympic National Park. We surveyed a total of 59 survey units, comprising 55 percent of the 60,218-hectare survey area. We estimated a mountain goat population of 623 ±43 (standard error, SE). Based on this level of estimation uncertainty, the 95-percent confidence interval ranged from 561 to 741 mountain goats at the time of the survey.
We examined the rate of increase of the mountain goat population by comparing the current population estimate to previous estimates from 2004 and 2011. Because aerial survey boundaries changed between 2004 and 2016, we recomputed population estimates for 2011 and 2016 surveys based on the revised survey boundaries as well as the previously defined boundaries so that estimates were directly comparable across years. Additionally, because the Mount Washington survey unit was not surveyed in 2011, we used results from an independent survey of the Mount Washington unit conducted by WDFW biologists in 2012 and combined it with the 2011 survey results to produce a complete survey conducted over 2 years. The revised estimates of mountain goat abundance occurring at elevations above 1,520 m were 230 ±19 (SE) in 2004, 350 ±41 (SE) in 2011, and 584 ±39 (SE) in 2016. The difference between the overall 2016 population estimate (623 ±43 [SE]) and the smaller estimate (584 ±39 [SE]) reflected the number of mountain goats counted in the expanded survey areas added in 2011. Based on comparisons within the standardized survey boundary, the mountain goat population in the Olympic Mountains increased at an average finite rate of 6 percent annually from 2004 to 2011, 11 percent annually from 2011 to 2016, and 8 percent annually over the combined period. We caution that the population may have been underestimated in 2011 because of record heavy snows persisting into the survey season. Therefore, the rate of population increase from 2011 and 2016 may be overestimated. The rate of increase measured over the combined period (2004–16) may be more representative of the recent population growth. We conclude that the abundance of mountain goats has increased for more than a decade, and if the recent average rate of population growth were sustained, the population would increase by 45 percent over the next 5 years.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161185","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Jenkins, K.J., Happe, P.J., Beime, K.F., and Baccus, W.T., 2016, Mountain goat abundance and population trends in the Olympic Mountains, northwestern Washington, 2016: U.S. Geological Survey Open-File Report 2016–1185, 21 p., https://doi.org/10.3133/ofr20161185.","productDescription":"iv, 21 p.","onlineOnly":"Y","ipdsId":"IP-080401","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":331287,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1185/coverthb.jpg"},{"id":331288,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1185/ofr20161185.pdf","text":"Report","size":"1.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1185 Report PDF"}],"country":"United States","state":"Washington","otherGeospatial":"Olympic Mountains, Olympic National Forest, Olympic National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123,\n 48\n ],\n [\n -123,\n 47.5\n ],\n [\n -124,\n 47.5\n ],\n [\n -124,\n 48\n ],\n [\n -123,\n 48\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Forest and Rangeland Ecosystem Science Center
U.S. Geological Survey
777 NW 9th St., Suite 400
Corvallis, Oregon 97330
http://fresc.usgs.gov/
Although current assessments of shark population trends involve both fishery-independent and fishery-dependent data, the latter are generally limited to commercial landings that may neglect nearshore coastal habitats. Texas has supported the longest organized land-based recreational shark fishery in the United States, yet no studies have used this “non-traditional” data source to characterize the catch composition or trends in this multidecadal fishery. We analyzed catch records from two distinct periods straddling heavy commercial exploitation of sharks in the Gulf of Mexico (historical period = 1973–1986; modern period = 2008–2015) to highlight and make available the current status and historical trends in Texas’ land-based shark fishery. Catch records describing large coastal species (>1,800 mm stretched total length [STL]) were examined using multivariate techniques to assess catch seasonality and potential temporal shifts in species composition. These fishery-dependent data revealed consistent seasonality that was independent of the data set examined, although distinct shark assemblages were evident between the two periods. Similarity percentage analysis suggested decreased contributions of Lemon Shark Negaprion brevirostris over time and a general shift toward the dominance of Bull Shark Carcharhinus leucas and Blacktip Shark C. limbatus. Comparisons of mean STL for species captured in historical and modern periods further identified significant decreases for both Bull Sharks and Lemon Sharks. Size structure analysis showed a distinct paucity of landed individuals over 2,000 mm STL in recent years. Although inherent biases in reporting and potential gear-related inconsistencies undoubtedly influenced this fishery-dependent data set, the patterns in our findings documented potential declines in the size and occurrence of select large coastal shark species off Texas, consistent with declines reported in the Gulf of Mexico. Future management efforts should consider the use of non-traditional fishery-dependent data sources, such as land-based records, as data streams in stock assessments.
","language":"English","publisher":"American Fisheries Society","doi":"10.1080/19425120.2016.1227404","usgsCitation":"Ajemian, M.J., Jose, P.D., Froeschke, J.T., Wildhaber, M.L., and Stunz, G., 2016, Was everything bigger in Texas? Characterization and trends of a land-based recreational shark fishery: Marine and Coastal Fisheries: Dynamics, Management, and Ecosystem Science, v. 8, no. 1, p. 553-566, https://doi.org/10.1080/19425120.2016.1227404.","productDescription":"14 p.","startPage":"553","endPage":"566","ipdsId":"IP-070564","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":470400,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/19425120.2016.1227404","text":"Publisher Index Page"},{"id":331354,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Texas","otherGeospatial":"Padre Island National Seashore","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.2894287109375,\n 27.649472352561876\n ],\n [\n -97.196044921875,\n 27.620273282414246\n ],\n [\n -97.2015380859375,\n 27.518015241965667\n ],\n [\n -97.22900390625,\n 27.366889032381295\n ],\n [\n -97.2454833984375,\n 27.205785724383325\n ],\n [\n -97.23999023437499,\n 26.838776064165863\n ],\n [\n -97.2125244140625,\n 26.711266913515747\n ],\n [\n -97.22900390625,\n 26.598351182358293\n ],\n [\n -97.2894287109375,\n 26.5737895138798\n ],\n [\n -97.3828125,\n 26.5737895138798\n ],\n [\n -97.57507324218749,\n 26.62781822639305\n ],\n [\n -97.62451171875,\n 26.735799020431674\n ],\n [\n -97.62451171875,\n 26.877980817017615\n ],\n [\n -97.5860595703125,\n 27.108033801463115\n ],\n [\n -97.58056640625,\n 27.23997867180821\n ],\n [\n -97.5640869140625,\n 27.430289738862594\n ],\n [\n -97.525634765625,\n 27.537500308359462\n ],\n [\n -97.46520996093749,\n 27.6251403350933\n ],\n [\n -97.3828125,\n 27.6543381066919\n ],\n [\n -97.2894287109375,\n 27.649472352561876\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"1","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-10","publicationStatus":"PW","scienceBaseUri":"583ff348e4b04fc80e43724e","contributors":{"authors":[{"text":"Ajemian, Matthew J.","contributorId":177080,"corporation":false,"usgs":false,"family":"Ajemian","given":"Matthew","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":654534,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jose, Philip D.","contributorId":177082,"corporation":false,"usgs":false,"family":"Jose","given":"Philip","email":"","middleInitial":"D.","affiliations":[{"id":6747,"text":"Texas A&M University","active":true,"usgs":false}],"preferred":false,"id":654535,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Froeschke, John T.","contributorId":101794,"corporation":false,"usgs":true,"family":"Froeschke","given":"John","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":654536,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Wildhaber, Mark L. 0000-0002-6538-9083 mwildhaber@usgs.gov","orcid":"https://orcid.org/0000-0002-6538-9083","contributorId":1386,"corporation":false,"usgs":true,"family":"Wildhaber","given":"Mark","email":"mwildhaber@usgs.gov","middleInitial":"L.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":654537,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Stunz, Gregory W.","contributorId":51006,"corporation":false,"usgs":true,"family":"Stunz","given":"Gregory W.","affiliations":[],"preferred":false,"id":654538,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70178563,"text":"70178563 - 2016 - Lidar-based mapping of flood control levees in south Louisiana","interactions":[],"lastModifiedDate":"2022-04-22T14:50:07.222","indexId":"70178563","displayToPublicDate":"2016-11-30T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2068,"text":"International Journal of Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Lidar-based mapping of flood control levees in south Louisiana","docAbstract":"Flood protection in south Louisiana is largely dependent on earthen levees, and in the aftermath of Hurricane Katrina the state’s levee system has received intense scrutiny. Accurate elevation data along the levees are critical to local levee district managers responsible for monitoring and maintaining the extensive system of non-federal levees in coastal Louisiana. In 2012, high resolution airborne lidar data were acquired over levees in Lafourche Parish, Louisiana, and a mobile terrestrial lidar survey was conducted for selected levee segments using a terrestrial lidar scanner mounted on a truck. The mobile terrestrial lidar data were collected to test the feasibility of using this relatively new technology to map flood control levees and to compare the accuracy of the terrestrial and airborne lidar. Metrics assessing levee geometry derived from the two lidar surveys are also presented as an efficient, comprehensive method to quantify levee height and stability. The vertical root mean square error values of the terrestrial lidar and airborne lidar digital-derived digital terrain models were 0.038 m and 0.055 m, respectively. The comparison of levee metrics derived from the airborne and terrestrial lidar-based digital terrain models showed that both types of lidar yielded similar results, indicating that either or both surveying techniques could be used to monitor geomorphic change over time. Because airborne lidar is costly, many parts of the USA and other countries have never been mapped with airborne lidar, and repeat surveys are often not available for change detection studies. Terrestrial lidar provides a practical option for conducting repeat surveys of levees and other terrain features that cover a relatively small area, such as eroding cliffs or stream banks, and dunes.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/01431161.2016.1249304","usgsCitation":"Thatcher, C.A., Lim, S., Palaseanu-Lovejoy, M., Danielson, J.J., and Kimbrow, D.R., 2016, Lidar-based mapping of flood control levees in south Louisiana: International Journal of Remote Sensing, v. 37, no. 24, p. 5708-5725, https://doi.org/10.1080/01431161.2016.1249304.","productDescription":"18 p.","startPage":"5708","endPage":"5725","ipdsId":"IP-055230","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true}],"links":[{"id":331364,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Louisiana","county":"Lafourche Parish","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.56,\n 29.56\n ],\n [\n -90.56,\n 29.65\n ],\n [\n -90.45,\n 29.65\n ],\n [\n -90.45,\n 29.56\n ],\n [\n -90.56,\n 29.56\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"37","issue":"24","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-28","publicationStatus":"PW","scienceBaseUri":"583ff34be4b04fc80e437256","contributors":{"authors":[{"text":"Thatcher, Cindy A. 0000-0003-0331-071X thatcherc@usgs.gov","orcid":"https://orcid.org/0000-0003-0331-071X","contributorId":2868,"corporation":false,"usgs":true,"family":"Thatcher","given":"Cindy","email":"thatcherc@usgs.gov","middleInitial":"A.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":false,"id":654379,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lim, Samsung","contributorId":177043,"corporation":false,"usgs":false,"family":"Lim","given":"Samsung","email":"","affiliations":[],"preferred":false,"id":654380,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Palaseanu-Lovejoy, Monica 0000-0002-3786-5118 mpal@usgs.gov","orcid":"https://orcid.org/0000-0002-3786-5118","contributorId":3639,"corporation":false,"usgs":true,"family":"Palaseanu-Lovejoy","given":"Monica","email":"mpal@usgs.gov","affiliations":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":5061,"text":"National Cooperative Geologic Mapping and Landslide Hazards","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":654381,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Danielson, Jeffrey J. 0000-0003-0907-034X daniels@usgs.gov","orcid":"https://orcid.org/0000-0003-0907-034X","contributorId":3996,"corporation":false,"usgs":true,"family":"Danielson","given":"Jeffrey","email":"daniels@usgs.gov","middleInitial":"J.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":654382,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Kimbrow, Dustin R. dkimbrow@usgs.gov","contributorId":3915,"corporation":false,"usgs":true,"family":"Kimbrow","given":"Dustin","email":"dkimbrow@usgs.gov","middleInitial":"R.","affiliations":[{"id":105,"text":"Alabama Water Science Center","active":true,"usgs":true}],"preferred":true,"id":654383,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70176513,"text":"ofr20161163 - 2016 - Model description and evaluation of the mark-recapture survival model used to parameterize the 2012 status and threats analysis for the Florida manatee (Trichechus manatus latirostris)","interactions":[],"lastModifiedDate":"2016-12-05T09:52:25","indexId":"ofr20161163","displayToPublicDate":"2016-11-30T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-1163","title":"Model description and evaluation of the mark-recapture survival model used to parameterize the 2012 status and threats analysis for the Florida manatee (Trichechus manatus latirostris)","docAbstract":"This report provides supporting details and evidence for the rationale, validity and efficacy of a new mark-recapture model, the Barker Robust Design, to estimate regional manatee survival rates used to parameterize several components of the 2012 version of the Manatee Core Biological Model (CBM) and Threats Analysis (TA). The CBM and TA provide scientific analyses on population viability of the Florida manatee subspecies (Trichechus manatus latirostris) for U.S. Fish and Wildlife Service’s 5-year reviews of the status of the species as listed under the Endangered Species Act. The model evaluation is presented in a standardized reporting framework, modified from the TRACE (TRAnsparent and Comprehensive model Evaluation) protocol first introduced for environmental threat analyses. We identify this new protocol as TRACE-MANATEE SURVIVAL and this model evaluation specifically as TRACE-MANATEE SURVIVAL, Barker RD version 1. The longer-term objectives of the manatee standard reporting format are to (1) communicate to resource managers consistent evaluation information over sequential modeling efforts; (2) build understanding and expertise on the structure and function of the models; (3) document changes in model structures and applications in response to evolving management objectives, new biological and ecological knowledge, and new statistical advances; and (4) provide greater transparency for management and research review.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161163","usgsCitation":"Langtimm, C.A., Kendall, W.L., Beck, C.A., Kochman, H.I., Teague, A.L., Meigs-Friend, Gaia, and Peñaloza, C.L., 2016, Model description and evaluation of the mark-recapture survival model used to parameterize the 2012 status and threats analysis for the Florida manatee (Trichechus manatus latirostris): U.S. Geological Survey Open-File Report 2016–1163, 20 p.,\nhttps://doi.org/10.3133/ofr20161163.","productDescription":"v, 20 p.","onlineOnly":"Y","ipdsId":"IP-065130","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":331034,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1163/coverthb.jpg"},{"id":331035,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1163/ofr20161163.pdf","text":"Report","size":"215 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1163"}],"contact":"Director, Wetland and Aquatic Research Center
U.S. Geological Survey
7920 NW 71st Street
Gainesville, FL 32653
https://www.usgs.gov/centers/wetland-and-aquatic-research-center-warc
","tableOfContents":"During 3 years of study (2010–2012), the western Arctic Ocean was found to have unique aragonite saturation profiles with up to three distinct aragonite undersaturation zones. This complexity is produced as inflow of Atlantic-derived and Pacific-derived water masses mix with Arctic-derived waters, which are further modified by physiochemical and biological processes. The shallowest aragonite undersaturation zone, from the surface to ∼30 m depth is characterized by relatively low alkalinity and other dissolved ions. Besides local influence of biological processes on aragonite undersaturation of shallow coastal waters, the nature of this zone is consistent with dilution by sea-ice melt and invasion of anthropogenic CO2 from the atmosphere. A second undersaturated zone at ∼90–220 m depth (salinity ∼31.8–35.4) occurs within the Arctic Halocline and is characterized by elevated pCO2 and nutrients. The nature of this horizon is consistent with remineralization of organic matter on shallow continental shelves bordering the Canada Basin and the input of the nutrients and CO2 entrained by currents from the Pacific Inlet. Finally, the deepest aragonite undersaturation zone is at greater than 2000 m depth and is controlled by similar processes as deep aragonite saturation horizons in the Atlantic and Pacific Oceans. The comparatively shallow depth of this deepest aragonite saturation horizon in the Arctic is maintained by relatively low temperatures, and stable chemical composition. Understanding the mechanisms controlling the distribution of these aragonite undersaturation zones, and the time scales over which they operate will be crucial to refine predictive models.
","language":"English","publisher":"AGU","doi":"10.1002/2016JC011696","usgsCitation":"Wynn, J., Robbins, L.L., and Anderson, L., 2016, Processes of multibathyal aragonite undersaturation in the Arctic Ocean: Journal of Geophysical Research: Oceans, v. 121, no. 11, p. 8248-8267, https://doi.org/10.1002/2016JC011696.","productDescription":"20 p.","startPage":"8248","endPage":"8267","ipdsId":"IP-059393","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":470402,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016jc011696","text":"Publisher Index Page"},{"id":331298,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Arctic Ocean","volume":"121","issue":"11","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-16","publicationStatus":"PW","scienceBaseUri":"583ea1bee4b0f0dc05ea54df","contributors":{"authors":[{"text":"Wynn, J.G.","contributorId":16215,"corporation":false,"usgs":true,"family":"Wynn","given":"J.G.","email":"","affiliations":[],"preferred":false,"id":654443,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Robbins, L. L.","contributorId":71156,"corporation":false,"usgs":true,"family":"Robbins","given":"L.","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":654444,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, L.G.","contributorId":36727,"corporation":false,"usgs":true,"family":"Anderson","given":"L.G.","email":"","affiliations":[],"preferred":false,"id":654445,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70178491,"text":"ofr20161197 - 2016 - Evaluation of the biological and hydraulic performance of the portable floating fish collector at Cougar Reservoir and Dam, Oregon, September 2015–January 2016","interactions":[],"lastModifiedDate":"2016-12-05T09:53:06","indexId":"ofr20161197","displayToPublicDate":"2016-11-28T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-1197","title":"Evaluation of the biological and hydraulic performance of the portable floating fish collector at Cougar Reservoir and Dam, Oregon, September 2015–January 2016","docAbstract":"The biological and hydraulic performance of a portable floating fish collector (PFFC) located in the cul-de-sac of Cougar Dam and Reservoir, Oregon, was evaluated during 2015–16. The PFFC, first commissioned in May 2014, was modified during winter 2014–15 to address several deficiencies identified during operation and testing in 2014. These modifications included raising the water inflow structures to reduce the depth and volume of inflow to improve the internal hydraulic profiles, and moving the anchors so the PFFC could be positioned closer to the existing reservoir outlet, a water temperature control tower. The PFFC was positioned about 18 meters (m) upstream of the intake of the water temperature control tower and faced into the prevailing water current. Like several floating surface collectors operating in the Pacific Northwest at the time, the PFFC used pumps to draw water and fish over an inclined plane, past dewatering screens, and into a collection area. The portable and experimental nature of the PFFC required a smaller size, shallower entrance (about 2.5-m deep), and smaller inflow rate (72 cubic feet per second [ft3/s] inflow during the Low treatment, 122 ft3/s during the High treatment) than other collectors in the region.
The collection of the target species, juvenile Chinook salmon (Oncorhynchus tshawytscha), during 2015–16 was an order of magnitude larger than in 2014. Subyearling-age Chinook salmon comprised most of the catch (2,616 subyearling compared to 258 yearling) and was greatest during the spring during the High inflow treatment. Bycatch consisted predominantly of cyprinids and centrarchids. Trap mortality (fish found dead in the trap) of juvenile Chinook salmon, at 9.2 percent of the subyearlings and 5.0 percent of yearlings, was about 30 percent of the level in 2014. Fish mortality from handling the live catch was about 1 percent.
Data from fish tagged with passive integrated transponder (PIT) tags and those with acoustic+PIT tags released near the head of the reservoir indicated the catch rates of the PFFC were low. Eight of the 1,497 PIT-tagged fish and 5 of the 534 acoustic+PIT-tagged fish were collected by the PFFC. Fish collection efficiencies—the number collected by the PFFC out of the number detected at the head of the forebay (FCEFB) or in the cul-de-sac (FCECDS)—were 0.002 and 0.003 during the Low treatment and 0.008 and 0.009 during the High treatment. The low FCEs were attributed to the following factors:
The data suggest that the shallow entrance and low inflow rate reduced fish guidance near the PFFC entrance and the hydraulic characteristics resulting from the outflow plumes (and perhaps water entering the temperature control tower) attracted fish to that area. Catch of juvenile Chinook salmon likely would increase if the collector entrance were deepened, the inflow rate were increased, and measures were taken to constrain fish presence to the area upstream of the trap entrance.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161197","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Beeman, J.W., Evans, S.D., Haner, P.V., Hansel, H.C., Hansen, A.C., Hansen, G.S., Hatton, T.W., Kofoot, E.E., and Sprando, J.M., 2016, Evaluation of the biological and hydraulic performance of the portable floating fish collector at Cougar Reservoir and Dam, Oregon, September 2015–January 2016: U.S. Geological Survey Open-File Report 2016–1197, 98 p., https://doi.org/10.3133/ofr20161197.","productDescription":"x, 98 p.","numberOfPages":"112","onlineOnly":"Y","ipdsId":"IP-078812","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":331253,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1197/ofr20161197.pdf","text":"Report","size":"9.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1197"},{"id":331252,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1197/coverthb.jpg"}],"country":"United States","state":"Oregon","otherGeospatial":"Cougar Reservoir and Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.2507095336914,\n 44.065386786862234\n ],\n [\n -122.2507095336914,\n 44.13023159235851\n ],\n [\n -122.20401763916016,\n 44.13023159235851\n ],\n [\n -122.20401763916016,\n 44.065386786862234\n ],\n [\n -122.2507095336914,\n 44.065386786862234\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115
http://wfrc.usgs.gov/
This study produced a geospatial database for use in a decision support system by the Bolivian authorities to investigate further development and investment potentials in sustainable hydropower in Bolivia. The study assessed theoretical hydropower of all 1-kilometer (km) stream segments in the country using multisource satellite data and a hydrologic modeling approach. With the assessment covering the 2 million square kilometer (km2) region influencing Bolivia’s drainage network, the potential hydropower figures are based on theoretical yield assuming that the systems generating the power are 100 percent efficient. There are several factors to consider when determining the real-world or technical power potential of a hydropower system, and these factors can vary depending on local conditions. Since this assessment covers a large area, it was necessary to reduce these variables to the two that can be modeled consistently throughout the region, streamflow or discharge, and elevation drop or head. First, the Shuttle Radar Topography Mission high-resolution 30-meter (m) digital elevation model was used to identify stream segments with greater than 10 km2 of upstream drainage. We applied several preconditioning processes to the 30-m digital elevation model to reduce errors and improve the accuracy of stream delineation and head height estimation. A total of 316,500 1-km stream segments were identified and used in this study to assess the total theoretical hydropower potential of Bolivia. Precipitation observations from a total of 463 stations obtained from the Bolivian Servicio Nacional de Meteorología e Hidrología (Bolivian National Meteorology and Hydrology Service) and the Brazilian Agência Nacional de Águas (Brazilian National Water Agency) were used to validate six different gridded precipitation estimates for Bolivia obtained from various sources. Validation results indicated that gridded precipitation estimates from the Tropical Rainfall Measuring Mission (TRMM) reanalysis product (3B43) had the highest accuracies. The coarse-resolution (25-km) TRMM data were disaggregated to 5-km pixels using climatology information obtained from the Climate Hazards Group Infrared Precipitation with Stations dataset. About a 17-percent bias was observed in the disaggregated TRMM estimates, which was corrected using the station observations. The bias-corrected, disaggregated TRMM precipitation estimate was used to compute stream discharge using a regionalization approach. In regionalization approach, required homogeneous regions for Bolivia were derived from precipitation patterns and topographic characteristics using a k-means clustering approach. Using the discharge and head height estimates for each 1-km stream segment, we computed hydropower potential for 316,490 stream segments within Bolivia and that share borders with Bolivia. The total theoretical hydropower potential (TTHP) of these stream segments was found to be 212 gigawatts (GW). Out of this total, 77.4 GW was within protected areas where hydropower projects cannot be developed; hence, the remaining total theoretical hydropower in Bolivia (outside the protected areas) was estimated as 135 GW. Nearly 1,000 1-km stream segments, however, were within the boundaries of existing hydropower projects. The TTHP of these stream segments was nearly 1.4 GW, so the residual TTHP of the streams in Bolivia was estimated as 133 GW. Care should be exercised to understand and interpret the TTHP identified in this study because all the stream segments identified and assessed in this study cannot be harnessed to their full capacity; furthermore, factors such as required environmental flows, efficiency, economics, and feasibility need to be considered to better identify a more real-world hydropower potential. If environmental flow requirements of 20–40 percent are considered, the total theoretical power available reduces by 60–80 percent. In addition, a 0.72 efficiency factor further reduces the estimation by another 28 percent. This study provides the base theoretical hydropower potential for Bolivia, the next step is to identify optimal hydropower plant locations and factor in the principles to appraise a real-world power potential in Bolivia.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161156","collaboration":"Prepared in cooperation with the CAF – Development Bank of Latin America","usgsCitation":"Velpuri, N.M., Pervez, M.S., and Cushing, W.M., 2016, Hydropower assessment of Bolivia—A multisource satellite data and hydrologic modeling approach: U.S. Geological Survey Open-File Report 2016–1156, 65 p., https://dx.doi.org/10.3133/ofr20161156.","productDescription":"Report: x, 65 p.; Appendixes: 2-4","numberOfPages":"79","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-075626","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":331175,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1156/ofr20161156.pdf","text":"Report","size":"23.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1156"},{"id":331174,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1156/coverthb.jpg"},{"id":331176,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1156/downloads","text":"Appendixes 2–4","description":"OFR 2016–1156 Appendixes 2–4"}],"country":"Bolivia","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-62.84647,-22.03499],[-63.98684,-21.99364],[-64.37702,-22.79809],[-64.96489,-22.07586],[-66.27334,-21.83231],[-67.10667,-22.73592],[-67.82818,-22.87292],[-68.21991,-21.49435],[-68.75717,-20.37266],[-68.44223,-19.40507],[-68.96682,-18.98168],[-69.10025,-18.26013],[-69.59042,-17.58001],[-68.95964,-16.5007],[-69.38976,-15.66013],[-69.16035,-15.32397],[-69.33953,-14.9532],[-68.94889,-14.45364],[-68.92922,-13.60268],[-68.88008,-12.89973],[-68.66508,-12.5613],[-69.52968,-10.95173],[-68.78616,-11.03638],[-68.27125,-11.01452],[-68.04819,-10.71206],[-67.1738,-10.30681],[-66.64691,-9.93133],[-65.33844,-9.76199],[-65.44484,-10.51145],[-65.3219,-10.89587],[-65.40228,-11.56627],[-64.31635,-12.46198],[-63.1965,-12.62703],[-62.80306,-13.00065],[-62.12708,-13.19878],[-61.7132,-13.4892],[-61.08412,-13.47938],[-60.5033,-13.77595],[-60.4592,-14.35401],[-60.26433,-14.64598],[-60.25115,-15.07722],[-60.54297,-15.09391],[-60.15839,-16.25828],[-58.24122,-16.29957],[-58.38806,-16.87711],[-58.2808,-17.27171],[-57.73456,-17.55247],[-57.49837,-18.17419],[-57.67601,-18.96184],[-57.95,-19.4],[-57.8538,-19.97],[-58.16639,-20.1767],[-58.18347,-19.8684],[-59.11504,-19.35691],[-60.04356,-19.34275],[-61.78633,-19.63374],[-62.26596,-20.51373],[-62.29118,-21.05163],[-62.68506,-22.24903],[-62.84647,-22.03499]]]},\"properties\":{\"name\":\"Bolivia\"}}]}","contact":"Director, Earth Resources Observation and Science (EROS) Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
Domestic and foreign renewable energy targets and financial incentives have increased demand for woody biomass and bioenergy in the southeastern United States. This demand is expected to be met through purpose-grown agricultural bioenergy crops, short-rotation tree plantations, thinning and harvest of planted and natural forests, and forest harvest residues. With results from a forest economics model, spatially explicit state-and-transition simulation models, and species–habitat models, we projected change in habitat amount for 16 wildlife species caused by meeting a renewable fuel target and expected demand for wood pellets in North Carolina, USA. We projected changes over 40 years under a baseline ‘business-as-usual’ scenario without bioenergy production and five scenarios with unique feedstock portfolios. Bioenergy demand had potential to influence trends in habitat availability for some species in our study area. We found variation in impacts among species, and no scenario was the ‘best’ or ‘worst’ across all species. Our models projected that shrub-associated species would gain habitat under some scenarios because of increases in the amount of regenerating forests on the landscape, while species restricted to mature forests would lose habitat. Some forest species could also lose habitat from the conversion of forests on marginal soils to purpose-grown feedstocks. The conversion of agricultural lands on marginal soils to purpose-grown feedstocks increased habitat losses for one species with strong associations with pasture, which is being lost to urbanization in our study region. Our results indicate that landscape-scale impacts on wildlife habitat will vary among species and depend upon the bioenergy feedstock portfolio. Therefore, decisions about bioenergy and wildlife will likely involve trade-offs among wildlife species, and the choice of focal species is likely to affect the results of landscape-scale assessments. We offer general principals to consider when crafting lists of focal species for bioenergy impact assessments at the landscape scale.
The hydrogeology and hydrologic characteristics of the Ozark Plateaus aquifer system were characterized as part of ongoing U.S. Geological Survey efforts to assess groundwater availability across the Nation. The need for such a study in the Ozark Plateaus physiographic province (Ozark Plateaus) is highlighted by increasing demand on groundwater resources by the 5.3 million people of the Ozark Plateaus, water-level declines in some areas, and potential impacts of climate change on groundwater availability. The subject study integrates knowledge gained through local investigation within a regional perspective to develop a regional conceptual model of groundwater flow in the Ozark Plateaus aquifer system (Ozark system), a key phase of groundwater availability assessment. The Ozark system extends across much of southern Missouri and northwestern and north-central Arkansas and smaller areas of southeastern Kansas and northeastern Oklahoma. The region is one of the major karst landscapes in the United States, and karst aquifers are predominant in the Ozark system. Groundwater flow is ultimately controlled by aquifer and confining unit lithologies and stratigraphic relations, geologic structure, karst development, and the character of surficial lithologies and regolith mantle. The regolith mantle is a defining element of Ozark Plateaus karst, affecting recharge, karst development, and vulnerability to surface-derived contaminants. Karst development is more advanced—as evidenced by larger springs, hydraulic characteristics, and higher well yields—in the Salem Plateau and in the northern part of the Springfield Plateau (generally north of the Arkansas-Missouri border) as compared with the southern part of the Springfield Plateau in Arkansas, largely due to thinner, less extensive regolith and purer carbonate lithology.
Precipitation is the ultimate source of all water to the Ozark system, and the hydrologic budget for the Ozark system includes inputs from recharge, losing-stream sections, and groundwater inflows and losses of water to gaining-stream sections, groundwater withdrawals, and surface-water and groundwater outflows to neighboring systems. Groundwater recharge, estimated by a soil-water-balance model, represents about 24 percent, or 11 inches, of 43.9 inches annual precipitation. Recharge is spatially variable, being greater in the northern Springfield Plateau and Salem Plateau than in the southern Springfield Plateau (generally south of the Arkansas border) because of differences in regolith mantle extent and thickness and carbonate lithology and hydraulic properties. Increased precipitation and decreased agricultural land use during the period 1951 through 2011 increased recharge by approximately 5 percent. Although all Ozark streams have losing, neutral, and gaining sections, they are dominantly gaining and are a net sink for groundwater with nearly 90 percent of groundwater recharge returned to springs and streams. Groundwater pumping is a small but important loss of water in the Ozark system hydrologic budget; water-level declines and local cones of depression have been observed around pumping centers and strong concerns exist over potential effects on stream and spring flow.
Data indicate that societal needs for freshwater resources in the Ozark Plateaus will continue to increase and will do so in the context of changing climate and hydrology. Groundwater will continue to be an important part of supporting these societal needs and also local ecosystems. The unique character and hydrogeologic variability across the Ozark system will control how the system responds to future stress. Groundwater of the Ozark system in the northern study area is more dynamic, has greater storage and larger flux, and has greater potential for further development than in the part of the study area south of the Arkansas-Missouri border. Further south in Arkansas, a line exists, roughly defined as 5 miles south of the Springfield Plateau-Boston Mountains boundary, beyond which further extensive municipal or commercial development appears unlikely under current economic and resource-need conditions. A small part of the Ozark system groundwater budget is currently drafted for use, leaving an apparently large component available for further development and use—particularly in the northern Springfield Plateau and Salem Plateau; however, the effects of increased pumping on groundwater’s role in maintaining ecosystems and ecosystem services are not quantitatively well understood, and the close relation between groundwater and surface water highlights the importance of further quantitative assessment.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165137","collaboration":"Prepared in cooperation with the Groundwater Resources Program","usgsCitation":"Hays, P.D., Knierim, K.J., Breaker, Brian, Westerman, D.A., and Clark, B.R., 2016, Hydrogeology and hydrologic conditions of the Ozark Plateaus aquifer system: U.S. Geological Survey Scientific Investigations Report 2016–5137, 61 p., https://dx.doi.org/10.3133/sir20165137. \n\n","productDescription":"Report: vii, 61 p.; Appendixes: 1-2","numberOfPages":"73","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-071467","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":331147,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5137/coverthb.jpg"},{"id":331148,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5137/sir20165137.pdf","description":"SIR 2016–5137"},{"id":331149,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2016/5137/downloads","text":"Appendix 1 & 2","description":"SIR 2016–5137 Appendix 1 & 2"}],"country":"United States","state":"Arkansas, Kansas, Missouri, Oklahoma","otherGeospatial":"Ozark Plateaus Aquifer System","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.1263427734375,\n 38.81831117374662\n ],\n [\n -90.3076171875,\n 38.89103282648846\n ],\n [\n -90.4559326171875,\n 38.8225909761771\n ],\n [\n -90.692138671875,\n 38.70694605159386\n ],\n [\n -90.8734130859375,\n 38.556757147352215\n ],\n [\n -91.0546875,\n 38.59970036588819\n ],\n [\n -91.2689208984375,\n 38.66835610151506\n ],\n [\n -91.3897705078125,\n 38.71551876930462\n ],\n [\n -91.571044921875,\n 38.68122173079789\n ],\n [\n -91.7083740234375,\n 38.70265930723801\n ],\n [\n -91.9171142578125,\n 38.65119833229951\n ],\n [\n -92.07092285156249,\n 38.57823196583313\n ],\n [\n -92.197265625,\n 38.586820096127674\n ],\n [\n -92.3345947265625,\n 38.6897975322717\n ],\n [\n -92.4884033203125,\n 38.90813299596705\n ],\n [\n -92.57080078125,\n 38.96368010198575\n ],\n [\n -92.74108886718749,\n 38.98503278695909\n ],\n [\n -92.87841796875,\n 38.997841307500714\n ],\n [\n -92.92236328125,\n 39.091699613104595\n ],\n [\n -92.9058837890625,\n 39.17691709496078\n ],\n [\n -92.8619384765625,\n 39.2407625100131\n ],\n [\n -92.9608154296875,\n 39.317300373271024\n ],\n [\n -93.0926513671875,\n 39.38101803294523\n ],\n [\n -93.2025146484375,\n 39.40224434029275\n ],\n [\n -93.350830078125,\n 39.30454987014581\n ],\n [\n -93.482666015625,\n 39.287545585410435\n ],\n [\n -93.70788574218749,\n 39.223742741391305\n ],\n [\n -93.98803710937499,\n 39.15136267949029\n ],\n [\n -95.2349853515625,\n 38.25112269630296\n ],\n [\n -95.2789306640625,\n 36.45221769643571\n ],\n [\n -95.0152587890625,\n 35.30840140169162\n ],\n [\n -94.19128417968749,\n 35.35321610123823\n ],\n [\n -93.834228515625,\n 35.47409160773029\n ],\n [\n -93.482666015625,\n 35.40696093270201\n ],\n [\n -93.16955566406249,\n 35.25459097465022\n ],\n [\n -93.065185546875,\n 35.15584570226544\n ],\n [\n -92.6641845703125,\n 35.08845057036537\n ],\n [\n -92.55432128906249,\n 34.95349314197422\n ],\n [\n -92.427978515625,\n 34.836349990763864\n ],\n [\n -92.1148681640625,\n 34.8183131456094\n ],\n [\n -90.3515625,\n 35.97800618085566\n ],\n [\n -89.35729980468749,\n 37.01132594307015\n ],\n [\n -89.4561767578125,\n 37.25656608611523\n ],\n [\n -89.4287109375,\n 37.37015718405753\n ],\n [\n -89.46716308593749,\n 37.45741810262938\n ],\n [\n -89.5166015625,\n 37.58811876638322\n ],\n [\n -89.56054687499999,\n 37.71859032558816\n ],\n [\n -89.70886230468749,\n 37.82280243352756\n ],\n [\n -89.8187255859375,\n 37.900865092570065\n ],\n [\n -89.9560546875,\n 37.97451499202459\n ],\n [\n -90.164794921875,\n 38.07836562996712\n ],\n [\n -90.2801513671875,\n 38.14751758025121\n ],\n [\n -90.3680419921875,\n 38.268375880204744\n ],\n [\n -90.32409667968749,\n 38.40194908237822\n ],\n [\n -90.252685546875,\n 38.53097889440024\n ],\n [\n -90.2032470703125,\n 38.62974534092597\n ],\n [\n -90.19775390625,\n 38.70694605159386\n ],\n [\n -90.1263427734375,\n 38.81831117374662\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
401 Hardin Road
Little Rock, AR 72211
There are many types of changes occurring over the Earth's landscapes that can be detected and monitored using Landsat data. Here we focus on monitoring “within-state,” gradual changes in vegetation in contrast with traditional monitoring of “abrupt” land-cover conversions. Gradual changes result from a variety of processes, such as vegetation growth and succession, damage from insects and disease, responses to shifts in climate, and other factors. Despite the prevalence of gradual changes across the landscape, they are largely ignored by the remote sensing community. Gradual changes are best characterized and monitored using time-series analysis, and with the successful launch of Landsat 8 we now have appreciable data continuity that extends the Landsat legacy across the previous 43 years. In this study, we conducted three related analyses: (1) comparison of spectral values acquired by Landsats 7 and 8, separated by eight days, to ensure compatibility for time-series evaluation; (2) tracking of multitemporal signatures for different change processes across Landsat 5, 7, and 8 sensors using anniversary-date imagery; and (3) tracking the same type of processes using all available acquisitions. In this investigation, we found that data representing natural vegetation from Landsats 5, 7, and 8 were comparable and did not indicate a need for major modification prior to use for long-term monitoring. Analyses using anniversary-date imagery can be very effective for assessing long term patterns and trends occurring across the landscape, and are especially good for providing insights regarding trends related to long-term and continuous trends of growth or decline. We found that use of all available data provided a much more comprehensive level of understanding of the trends occurring, providing information about rate, duration, and intra- and inter-annual variability that could not be readily gleaned from the anniversary date analyses. We observed that using all available clear Landsat 5–8 observations with the new Continuous Change Detection and Classification (CCDC) algorithm was very effective for illuminating vegetation trends. There are a number of potential challenges for assessing gradual changes, including atmospheric impacts, algorithm development and visualization of the changes. One of the biggest challenges for studying gradual change will be the lack of appropriate data for validating results and products.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2016.02.060","usgsCitation":"Vogelmann, J., Gallant, A.L., Shi, H., and Zhu, Z., 2016, Perspectives on monitoring gradual change across the continuity of Landsat sensors using time-series data: Remote Sensing of Environment, v. 185, p. 258-270, https://doi.org/10.1016/j.rse.2016.02.060.","productDescription":"13 p.","startPage":"258","endPage":"270","ipdsId":"IP-066052","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":470406,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.rse.2016.02.060","text":"Publisher Index Page"},{"id":341856,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"185","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"592e84b8e4b092b266f10d2c","contributors":{"authors":[{"text":"Vogelmann, James 0000-0002-0804-5823 vogel@usgs.gov","orcid":"https://orcid.org/0000-0002-0804-5823","contributorId":192352,"corporation":false,"usgs":true,"family":"Vogelmann","given":"James","email":"vogel@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":5055,"text":"Land Change Science","active":true,"usgs":true}],"preferred":true,"id":696377,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gallant, Alisa L. 0000-0002-3029-6637 gallant@usgs.gov","orcid":"https://orcid.org/0000-0002-3029-6637","contributorId":2940,"corporation":false,"usgs":true,"family":"Gallant","given":"Alisa","email":"gallant@usgs.gov","middleInitial":"L.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":696378,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shi, Hua 0000-0001-7013-1565 hshi@usgs.gov","orcid":"https://orcid.org/0000-0001-7013-1565","contributorId":646,"corporation":false,"usgs":true,"family":"Shi","given":"Hua","email":"hshi@usgs.gov","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":696379,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zhu, Zhe 0000-0001-8283-6407 zhezhu@usgs.gov","orcid":"https://orcid.org/0000-0001-8283-6407","contributorId":168792,"corporation":false,"usgs":true,"family":"Zhu","given":"Zhe","email":"zhezhu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":696380,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70177790,"text":"sir20165132 - 2016 - Flood-hazard analysis of four headwater streams draining the Argonne National Laboratory property, DuPage County, Illinois","interactions":[],"lastModifiedDate":"2016-11-22T18:06:06","indexId":"sir20165132","displayToPublicDate":"2016-11-22T08:15:00","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":"2016-5132","title":"Flood-hazard analysis of four headwater streams draining the Argonne National Laboratory property, DuPage County, Illinois","docAbstract":"Results of a flood-hazard analysis conducted by the U.S. Geological Survey, in cooperation with the Argonne National Laboratory, for four headwater streams within the Argonne National Laboratory property indicate that the 1-percent and 0.2-percent annual exceedance probability floods would cause multiple roads to be overtopped. Results indicate that most of the effects on the infrastructure would be from flooding of Freund Brook. Flooding on the Northeast and Southeast Drainage Ways would be limited to overtopping of one road crossing for each of those streams. The Northwest Drainage Way would be the least affected with flooding expected to occur in open grass or forested areas.
The Argonne Site Sustainability Plan outlined the development of hydrologic and hydraulic models and the creation of flood-plain maps of the existing site conditions as a first step in addressing resiliency to possible climate change impacts as required by Executive Order 13653 “Preparing the United States for the Impacts of Climate Change.” The Hydrological Simulation Program-FORTRAN is the hydrologic model used in the study, and the Hydrologic Engineering Center‒River Analysis System (HEC–RAS) is the hydraulic model. The model results were verified by comparing simulated water-surface elevations to observed water-surface elevations measured at a network of five crest-stage gages on the four study streams. The comparison between crest-stage gage and simulated elevations resulted in an average absolute difference of 0.06 feet and a maximum difference of 0.19 feet.
In addition to the flood-hazard model development and mapping, a qualitative stream assessment was conducted to evaluate stream channel and substrate conditions in the study reaches. This information can be used to evaluate erosion potential.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165132","collaboration":"Prepared in cooperation with the Argonne National Laboratory","usgsCitation":"Soong, D.T., Murphy, E.A., Straub, T.D., and Zeeb, H.L., 2016, Flood-hazard analysis of four headwater streams draining the Argonne National Laboratory property, DuPage County, Illinois: U.S. Geological Survey Scientific Investigations Report 2016-5132, 57 p., https://dx.doi.org/10.3133/sir20165132.","productDescription":"vii, 57 p.","numberOfPages":"69","onlineOnly":"Y","ipdsId":"IP-075928","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":331075,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5132/sir20165132.pdf","text":"Report","size":"67.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016-5132"},{"id":331074,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5132/coverthb.jpg"}],"country":"United States","state":"Illinois","county":"DuPage County","otherGeospatial":"Sawmill Creek Watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.02177429199219,\n 41.6872711837914\n ],\n [\n -88.02177429199219,\n 41.77873679916478\n ],\n [\n -87.9287338256836,\n 41.77873679916478\n ],\n [\n -87.9287338256836,\n 41.6872711837914\n ],\n [\n -88.02177429199219,\n 41.6872711837914\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Illinois-Iowa Water Science Center
U.S. Geological Survey
405 North Goodwin Avenue
Urbana, Illinois 61801
http://il.water.usgs.gov