Walker Lake is a terminal lake in west-central Nevada with almost all outflow occurring through evaporation. Diversions from Walker River since the early 1900s have contributed to a substantial reduction in flow entering Walker Lake. As a result, the lake is receding, and salt concentrations have increased to a level in which Oncorhynchus clarkii henshawi (Lahontan Cutthroat trout) are no longer present, and the lake ecosystem is threatened. Consequently, there is a concerted effort to restore the Walker Lake ecosystem and fishery to a level that is more sustainable. However, Walker Lake is interlinked with the lower Walker River and adjacent groundwater system which makes it difficult to understand the full effect of upstream water-management actions on the overall hydrologic system including the lake level, volume, and dissolved-solids concentrations of Walker Lake. To understand the effects of water-management actions on the lower Walker River Basin hydrologic system, a watershed model and groundwater flow model have been developed by the U.S. Geological Survey in cooperation with the Bureau of Reclamation and the National Fish and Wildlife Foundation.
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The watershed model was developed using the precipitation runoff modeling system (PRMS) and the groundwater flow model was constructed using the MODular groundwater FLOW model (MODFLOW) and both were calibrated for the lower Walker River Basin. These models can be incorporated in an integrated Groundwater and Surface-water FLOW (GSFLOW) model of the lower Walker River Basin. Additionally, the MODFLOW model developed for this study is useful for efficiently simulating long-term and large-scale effects of water-management actions on groundwater hydrology, streamflow, and Walker Lake level, volume, and dissolved-solids concentrations.
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The lower Walker River Basin PRMS model (LWR_PRMS) was constructed using a subbasin approach to aid in development and calibration, and simulates a 30-year period from 1978 to 2007 using daily time steps. The LWR_PRMS was used to estimate the distribution of groundwater recharge specified in the MODFLOW model. The highest rates of groundwater recharge occur in the Wassuk Range beneath perennial and ephemeral stream channels, whereas lower rates of recharge occur beneath alluvial fans along mountain fronts. The total groundwater recharge estimated using PRMS was about 25,000 acre-feet per year.
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The lower Walker River Basin MODFLOW (LWR_MF) model simulates an 89-year period using monthly time steps. The LWR_MF was constructed with an initial steady-state simulation to represent dynamic equilibrium conditions from 1908 to 1918 and then a transient simulation representing the period 1919–2007. The model was calibrated using a combination of manual and automated methods of adjusting model parameters to minimize errors between model simulated results and weighted observations of groundwater levels, streamflows, and lake level. Hydrologic conditions simulated with the LWR_MF include the movement and change in storage of groundwater, and the water budgets for Walker River, Walker Lake, and the groundwater system. The LWR_MF computed dissolved-solids concentrations for Walker Lake using simulated lake volume and an assumed constant internal salt mass of 37.2 million tons.
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Effects of potential changes in water management on future conditions (scenarios) of the lower Walker River Basin hydrologic system and Walker Lake from 2011 to 2070 were evaluated. Several water-management scenarios were considered, including a baseline scenario that represents no changes in system management, improved irrigation efficiencies for the Walker River Indian Irrigation Project (WRIIP), a range of increased streamflows entering the lower Walker River Basin, and, the fallowing of fields on the WRIIP.
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For the baseline scenario, it was assumed that streamflow conditions from 1981 to 2010 will be repeated in the future. Results indicate that Walker Lake level and volume continue to decline but at a slower rate as the surface area of the lake becomes smaller and lake evaporation decreases. Dissolved-solids concentrations in Walker Lake continue to increase and increase much more rapidly during periods when minimal flows reach the lake due to a diminished lake volume. Alternatively, in years with high runoff, lake level increases are greater and dissolved-solids decreases are greater, compared with equivalent runoffs experienced during 1981–2010.
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The simulated effects of improving WRIIP efficiencies on Walker River streamflows, Walker Lake inflow, level, and dissolved-solids concentrations, and crop consumptive use, are compared with the baseline reference scenario for a range of irrigation efficiency improvements from 0 to 25 percent over 60 years. Results indicate that water is conserved through a reduction in irrigation-induced groundwater recharge and subsequent groundwater discharge through evapotranspiration. The conserved water mostly goes to increased streamflow to Walker Lake, followed by increased crop consumptive use, then increased evaporation from Weber Reservoir.
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The simulated effects of increased streamflows at Walker River at Wabuska streamgage (10301500) on Walker Lake inflow, level, and dissolved-solids concentrations, and crop consumptive use, are compared with the baseline scenario after 60 years under two different management methods for Weber Reservoir. Results indicate Walker Lake level and dissolved-solids concentrations stabilized with increased irrigation-season streamflow of about 40,000 acre-feet per year at the Walker River at Wabuska streamgage. Walker Lake level increased, and dissolved-solids concentration decreased, with increased flows of 50,000 acre-feet per year or more. After 60 years with additional irrigation-season streamflows of 50,000 acre-feet per year, Walker Lake level increased by about 48 feet, and lake dissolved-solids concentrations decreased by about 3,000 milligrams per liter (mg/L). With 75,000 acre-feet per year of additional streamflow, Walker Lake level increased by 70 feet, and dissolved-solids concentration decreased by 7,600 milligrams per liter.
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The effects of fallowing of Walker River Indian Irrigation Project fields from 2007 to 2010 on Walker Lake inflow, level, and dissolved solids were evaluated. Fallowing resulted in a near doubling of Walker River inflow to Walker Lake during this period, an increase in Walker Lake level of about 1.4 feet, and a decrease in dissolved-solids concentration of about 540 mg/L.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145190","collaboration":"Prepared in cooperation with Bureau of Reclamation and National Fish and Wildlife Foundation","usgsCitation":"Allander, K., Niswonger, R., and Jeton, A.E., 2014, Simulation of the Lower Walker River Basin hydrologic system, west-central Nevada, using PRMS and MODFLOW models: U.S. Geological Survey Scientific Investigations Report 2014-5190, Report: x, 93 p.; 3 Appendices, https://doi.org/10.3133/sir20145190.","productDescription":"Report: x, 93 p.; 3 Appendices","numberOfPages":"108","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-033184","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":296016,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145190.jpg"},{"id":296011,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5190/"},{"id":296012,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5190/pdf/sir2014-5190.pdf","text":"Report","size":"10.7 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":296013,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5190/downloads/sir2014-5190_appendix1.xls","text":"Water-Level Hydrographs","size":"3.4 MB"},{"id":296014,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5190/downloads/sir2014-5190_appendix2.xlsx","text":"Observation-Site Information","size":"23 kB","linkFileType":{"id":3,"text":"xlsx"}},{"id":296015,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5190/downloads/sir2014-5190_appendix3.zip","text":"PRMS and MODFLOW Files and Supporting Utilities","size":"231.8 MB","linkFileType":{"id":3,"text":"xlsx"}}],"country":"United States","state":"Nevada","otherGeospatial":"Lower Walker River","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"546476a1e4b0ba83040c9361","contributors":{"authors":[{"text":"Allander, Kip K.","contributorId":118578,"corporation":false,"usgs":true,"family":"Allander","given":"Kip K.","affiliations":[],"preferred":false,"id":519588,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Niswonger, Richard G. 0000-0001-6397-2403 rniswon@usgs.gov","orcid":"https://orcid.org/0000-0001-6397-2403","contributorId":2833,"corporation":false,"usgs":true,"family":"Niswonger","given":"Richard G.","email":"rniswon@usgs.gov","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":false,"id":525100,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jeton, Anne E.","contributorId":45351,"corporation":false,"usgs":true,"family":"Jeton","given":"Anne","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":525101,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70129723,"text":"70129723 - 2014 - Deformation from the 1989 Loma Prieta earthquake near the southwest margin of the Santa Clara Valley, California","interactions":[],"lastModifiedDate":"2020-12-03T12:50:06.352931","indexId":"70129723","displayToPublicDate":"2014-11-12T03:30:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Deformation from the 1989 Loma Prieta earthquake near the southwest margin of the Santa Clara Valley, California","docAbstract":"Damage to pavement and near-surface utility pipes, caused by the 17 October 1989, Loma Prieta earthquake, provides evidence for ground deformation in a 663 km2 area near the southwest margin of the Santa Clara Valley, California (USA). A total of 1427 damage sites, collected from more than 30 sources, are concentrated in four zones, three of which lie near previously mapped faults. In one of these zones, the channel lining of Los Gatos Creek, a 2-km-long concrete strip trending perpendicular to regional geologic structure, was broken by thrusts that were concentrated in two belts, each several tens of meters wide, separated by more than 300 m of relatively undeformed concrete.
\nTo gain additional measurement of any permanent ground deformation that accompanied this damage, we compiled and conducted post-earthquake surveys along two 5-km lines of horizontal control and a 15-km level line. Measurements of horizontal distortion indicate approximately 0.1 m shortening in a NE-SW direction across the valley margin, similar to the amount measured in the channel lining. Evaluation of precise leveling by the National Geodetic Survey showed a downwarp, with an amplitude of >0.1 m over a span of >12 km, that resembled regional geodetic models of coseismic deformation. Although the leveling indicates broad, regional warping, abrupt discontinuities characteristic of faulting characterize both the broad-scale distribution of damage and the local deformation of the channel lining. Reverse movement largely along preexisting faults and probably enhanced significantly by warping combined with enhanced ground shaking, produced the documented coseismic ground deformation.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES01095.1","usgsCitation":"Schmidt, K.M., Ellen, S.D., and Peterson, D.M., 2014, Deformation from the 1989 Loma Prieta earthquake near the southwest margin of the Santa Clara Valley, California: Geosphere, v. 10, no. 6, p. 1177-1202, https://doi.org/10.1130/GES01095.1.","productDescription":"26 p.","startPage":"1177","endPage":"1202","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057868","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":472642,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges01095.1","text":"Publisher Index Page"},{"id":380932,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Santa Clara Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.26684570312499,\n 35.639441068973944\n ],\n [\n -119.81689453125,\n 35.639441068973944\n ],\n [\n -119.81689453125,\n 37.23032838760387\n ],\n [\n -122.26684570312499,\n 37.23032838760387\n ],\n [\n -122.26684570312499,\n 35.639441068973944\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"6","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"546476a0e4b0ba83040c9355","contributors":{"authors":[{"text":"Schmidt, Kevin M. 0000-0003-2365-8035 kschmidt@usgs.gov","orcid":"https://orcid.org/0000-0003-2365-8035","contributorId":1985,"corporation":false,"usgs":true,"family":"Schmidt","given":"Kevin","email":"kschmidt@usgs.gov","middleInitial":"M.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":519916,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ellen, Stephen D.","contributorId":107300,"corporation":false,"usgs":true,"family":"Ellen","given":"Stephen","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":519917,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Peterson, David M.","contributorId":11644,"corporation":false,"usgs":true,"family":"Peterson","given":"David","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":519918,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70133045,"text":"70133045 - 2014 - The relative impacts of climate and land-use change on conterminous United States bird species from 2001 to 2075","interactions":[],"lastModifiedDate":"2017-01-23T15:21:04","indexId":"70133045","displayToPublicDate":"2014-11-12T03:15:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"The relative impacts of climate and land-use change on conterminous United States bird species from 2001 to 2075","docAbstract":"Species distribution models often use climate data to assess contemporary and/or future ranges for animal or plant species. Land use and land cover (LULC) data are important predictor variables for determining species range, yet are rarely used when modeling future distributions. In this study, maximum entropy modeling was used to construct species distribution maps for 50 North American bird species to determine relative contributions of climate and LULC for contemporary (2001) and future (2075) time periods. Species presence data were used as a dependent variable, while climate, LULC, and topographic data were used as predictor variables. Results varied by species, but in general, measures of model fit for 2001 indicated significantly poorer fit when either climate or LULC data were excluded from model simulations. Climate covariates provided a higher contribution to 2001 model results than did LULC variables, although both categories of variables strongly contributed. The area deemed to be \"suitable\" for 2001 species presence was strongly affected by the choice of model covariates, with significantly larger ranges predicted when LULC was excluded as a covariate. Changes in species ranges for 2075 indicate much larger overall range changes due to projected climate change than due to projected LULC change. However, the choice of study area impacted results for both current and projected model applications, with truncation of actual species ranges resulting in lower model fit scores and increased difficulty in interpreting covariate impacts on species range. Results indicate species-specific response to climate and LULC variables; however, both climate and LULC variables clearly are important for modeling both contemporary and potential future species ranges.
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along a regulated dryland river","interactions":[],"lastModifiedDate":"2020-12-31T20:52:47.8568","indexId":"70132474","displayToPublicDate":"2014-11-12T03:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3301,"text":"River Research and Applications","active":true,"publicationSubtype":{"id":10}},"title":"Abandoned floodplain plant communities along a regulated dryland river","docAbstract":"Rivers and their floodplains worldwide have changed dramatically over the last century because of regulation by dams, flow diversions and channel stabilization. Floodplains no longer inundated by river flows following dam-induced flood reduction comprise large areas of bottomland habitat, but the effects of abandonment on plant communities are not well understood. Using a hydraulic flow model, geomorphic mapping and field surveys, we addressed the following questions along the Bill Williams River, Arizona: (i) What per cent of the bottomland do abandoned floodplains comprise? and (ii) Are abandoned floodplains quantitatively different from adjacent xeric and riparian surfaces in terms of vegetation composition and surface sediment? We found that nearly 70% of active channel and floodplain area was abandoned following dam installation. Abandoned floodplains along the Bill Williams River tend to be similar to each other yet distinct from neighbouring habitats: they have been altered physically from their historic state, leading to distinct combinations of surface sediments, hydrology and plant communities. Abandoned floodplains may transition to xeric communities over time but are likely to retain some riparian qualities as long as there is access to relatively shallow ground water. With expected increases in water demand and drying climatic conditions in many regions, these surfaces and associated vegetation will continue to be extensive in riparian landscapes worldwide
","language":"English","publisher":"Wiley","usgsCitation":"Reynolds, L.V., Shafroth, P.B., and House, P., 2014, Abandoned floodplain plant communities along a regulated dryland river: River Research and Applications, v. 30, no. 9, p. 1084-1098.","productDescription":"15 p.","startPage":"1084","endPage":"1098","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-051066","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":296008,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":295828,"type":{"id":15,"text":"Index Page"},"url":"https://onlinelibrary.wiley.com/doi/10.1002/rra.2708/abstract"}],"country":"United States","state":"Arizona","otherGeospatial":"Bill Williams River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.8344955444336,\n 34.19362958613085\n ],\n [\n -113.65699768066406,\n 34.19362958613085\n ],\n [\n -113.65699768066406,\n 34.256081384716566\n ],\n [\n -113.8344955444336,\n 34.256081384716566\n ],\n [\n -113.8344955444336,\n 34.19362958613085\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"30","issue":"9","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5464769ee4b0ba83040c9343","contributors":{"authors":[{"text":"Reynolds, L. V.","contributorId":127341,"corporation":false,"usgs":false,"family":"Reynolds","given":"L.","email":"","middleInitial":"V.","affiliations":[{"id":6782,"text":"Biology Department, Colorado State University","active":true,"usgs":false}],"preferred":false,"id":523255,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shafroth, Patrick B. 0000-0002-6064-871X shafrothp@usgs.gov","orcid":"https://orcid.org/0000-0002-6064-871X","contributorId":2000,"corporation":false,"usgs":true,"family":"Shafroth","given":"Patrick","email":"shafrothp@usgs.gov","middleInitial":"B.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":523254,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"House, P. K.","contributorId":127342,"corporation":false,"usgs":false,"family":"House","given":"P. K.","affiliations":[{"id":6783,"text":"Geology, Minerals, Energy, and Geophysics Program, U.S. Geological Survey","active":true,"usgs":false}],"preferred":false,"id":523256,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70134557,"text":"70134557 - 2014 - The Late Cretaceous Middle Fork caldera, its resurgent intrusion, and enduring landscape stability in east-central Alaska","interactions":[],"lastModifiedDate":"2019-02-25T13:22:10","indexId":"70134557","displayToPublicDate":"2014-11-12T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"The Late Cretaceous Middle Fork caldera, its resurgent intrusion, and enduring landscape stability in east-central Alaska","docAbstract":"Dissected caldera structures expose thick intracaldera tuff and, uncommonly, cogenetic shallow plutons, while remnants of correlative outflow tuffs deposited on the pre-eruption ground surface record elements of ancient landscapes. The Middle Fork caldera encompasses a 10 km × 20 km area of rhyolite welded tuff and granite porphyry in east-central Alaska, ∼100 km west of the Yukon border. Intracaldera tuff is at least 850 m thick. The K-feldspar megacrystic granite porphyry is exposed over much of a 7 km × 12 km area having 650 m of relief within the western part of the caldera fill. Sensitive high-resolution ion microprobe with reverse geometry (SHRIMP-RG) analyses of zircon from intracaldera tuff, granite porphyry, and outflow tuff yield U-Pb ages of 70.0 ± 1.2, 69.7 ± 1.2, and 71.1 ± 0.5 Ma (95% confidence), respectively. An aeromagnetic survey indicates that the tuff is reversely magnetized, and, therefore, that the caldera-forming eruption occurred in the C31r geomagnetic polarity chron. The tuff and porphyry have arc geochemical signatures and a limited range in SiO2 of 69 to 72 wt%. Although their phenocrysts differ in size and abundance, similar quartz + K-feldspar + plagioclase + biotite mineralogy, whole-rock geochemistry, and analytically indistinguishable ages indicate that the tuff and porphyry were comagmatic. Resorption of phenocrysts in tuff and porphyry suggests that these magmas formed by thermal rejuvenation of near-solidus or solidified crystal mush. A rare magmatic enclave (54% SiO2, arc geochemical signature) in the porphyry may be similar to parental magma and provides evidence of mafic magma and thermal input.
\n\n
The Middle Fork is a relatively well preserved caldera within a broad region of Paleozoic metamorphic rocks and Mesozoic plutons bounded by northeast-trending faults. In the relatively downdropped and less deeply exhumed crustal blocks, Cretaceous–Early Tertiary silicic volcanic rocks attest to long-term stability of the landscape. Within the Middle Fork caldera, the granite porphyry is interpreted to have been exposed by erosion of thick intracaldera tuff from an asymmetric resurgent dome. The Middle Fork of the North Fork of the Fortymile River incised an arcuate valley into and around the caldera fill on the west and north and may have cut down from within an original caldera moat. The 70 Ma land surface is preserved beneath proximal outflow tuff at the west margin of the caldera structure and beneath welded outflow tuff 16–23 km east-southeast of the caldera in a paleovalley. Within ∼50 km of the Middle Fork caldera are 14 examples of Late Cretaceous (?)–Tertiary felsic volcanic and hypabyssal intrusive rocks that range in area from <1 km2 to ∼100 km2. Rhyolite dome clusters north and northwest of the caldera occupy tectonic basins associated with northeast-trending faults and are relatively little eroded. Lava of a latite complex, 12–19 km northeast of the caldera, apparently flowed into the paleovalley of the Middle Fork of the North Fork of the Fortymile River. To the northwest of the Middle Fork caldera, in the Mount Harper crustal block, mid-Cretaceous plutonic rocks are widely exposed, indicating greater total exhumation. To the southeast of the Middle Fork block, the Mount Veta block has been uplifted sufficiently to expose a ca. 68–66 Ma equigranular granitic pluton. Farther to the southeast, in the Kechumstuk block, the flat-lying outflow tuff remnant in Gold Creek and a regionally extensive high terrace indicate that the landscape there has been little modified since 70 Ma other than entrenchment of tributaries in response to post–2.7 Ma lowering of base level of the Yukon River associated with advance of the Cordilleran ice sheet.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES01037.1","usgsCitation":"Bacon, C.R., Dusel-Bacon, C., Aleinikoff, J.N., and Slack, J.F., 2014, The Late Cretaceous Middle Fork caldera, its resurgent intrusion, and enduring landscape stability in east-central Alaska: Geosphere, v. 10, no. 6, p. 1432-1455, https://doi.org/10.1130/GES01037.1.","productDescription":"24 p.","startPage":"1432","endPage":"1455","numberOfPages":"24","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054534","costCenters":[{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":472644,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges01037.1","text":"Publisher Index Page"},{"id":296440,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -181.494140625,\n 51.01375465718821\n ],\n [\n -181.494140625,\n 71.74643171904148\n ],\n [\n -140.80078125,\n 71.74643171904148\n ],\n [\n -140.80078125,\n 51.01375465718821\n ],\n [\n -181.494140625,\n 51.01375465718821\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"10","issue":"6","noUsgsAuthors":false,"publicationDate":"2014-11-12","publicationStatus":"PW","scienceBaseUri":"548193cae4b0aa6d778520fd","contributors":{"authors":[{"text":"Bacon, Charles R. 0000-0002-2165-5618 cbacon@usgs.gov","orcid":"https://orcid.org/0000-0002-2165-5618","contributorId":2909,"corporation":false,"usgs":true,"family":"Bacon","given":"Charles","email":"cbacon@usgs.gov","middleInitial":"R.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":526166,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dusel-Bacon, Cynthia 0000-0001-8481-739X cdusel@usgs.gov","orcid":"https://orcid.org/0000-0001-8481-739X","contributorId":2797,"corporation":false,"usgs":true,"family":"Dusel-Bacon","given":"Cynthia","email":"cdusel@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":526167,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Aleinikoff, John N. 0000-0003-3494-6841 jaleinikoff@usgs.gov","orcid":"https://orcid.org/0000-0003-3494-6841","contributorId":1478,"corporation":false,"usgs":true,"family":"Aleinikoff","given":"John","email":"jaleinikoff@usgs.gov","middleInitial":"N.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":526168,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Slack, John F. 0000-0001-6600-3130 jfslack@usgs.gov","orcid":"https://orcid.org/0000-0001-6600-3130","contributorId":1032,"corporation":false,"usgs":true,"family":"Slack","given":"John","email":"jfslack@usgs.gov","middleInitial":"F.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":245,"text":"Eastern Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"preferred":true,"id":526169,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70133231,"text":"ds883 - 2014 - USGS Field Activities 12BHM01, 12BHM02, 12BHM03, 12BHM04, and 12BHM05 on the West Florida Shelf, in February, April, May, June, and August 2012","interactions":[],"lastModifiedDate":"2014-11-11T09:24:29","indexId":"ds883","displayToPublicDate":"2014-11-11T10:15:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"883","title":"USGS Field Activities 12BHM01, 12BHM02, 12BHM03, 12BHM04, and 12BHM05 on the West Florida Shelf, in February, April, May, June, and August 2012","docAbstract":"Atmospheric carbon dioxide (CO2) is absorbed by the ocean’s surface where it combines with seawater to form a weak, naturally occurring acid called carbonic acid (H2CO3). Increasing carbon dioxide in the atmosphere results in the absorption of more CO2 by the ocean and, therefore, increases in the acidity of seawater. This process, known as ocean acidification, has the potential to elicit change in ecosystems and organisms by disrupting biological processes. For example, ocean acidification is a problem for marine organisms such as corals, foraminifera, and algae that precipitate calcium carbonate to form their skeletons and shells (Kleypas and others, 2006). The effects are related to corresponding changes in the carbonate saturation state (Ω), where Ω is the ratio of the ion concentration product (Ca2+ x CO32-) to the stoichiometric aragonite solubility product (K*sp) (Langdon and Atkinson, 2005). Because pH and CO32- are strongly interdependent through the inorganic carbon system, the decrease in pH will cause a proportionally greater decrease in CO32-.
\n\n
Globally, ocean acidification is occurring faster than at any time in the last 300 million years (Broeker and others, 1979). Recent evidence indicates that individual oceans are responding at different rates, depending on physical and biological processes. For example in the Arctic Ocean, the rate of saturation state decrease was 2.1 percent per year between 1997 and 2010 (Robbins and others., 2013) in an area as large as Montana, largely because of increases in melt of ice, versus the average rate observed for the Pacific Ocean (0.36 percent per year) (Feely and others, 2012). Unfortunately, comparative data sets over multiyear time frames are often not available because time series baseline carbon information has not been collected in many oceans. Data are needed in subtropical latitudes where carbonate saturation states are already naturally low and fluctuate seasonally. These data will help construct a baseline for the assessment of future changes.
\n\n
As part of the U.S. Geological Survey (USGS) Coastal and Marine Geology Program project \"Response of Florida Shelf Ecosystems to Climate Change\" and in partnership with Kendra Daly, University of South Florida (USF), data on surface ocean carbonate chemistry were collected on five cruises along transects on the shallow inner west Florida shelf and northern Gulf of Mexico in 2012. Data from the 2011 cruises were also published (Robbins and others., 2013). The data collected allows the USGS, National Oceanic and Atmospheric Administration (NOAA), and USF scientists to map variations in ocean chemistry including carbonate saturation states along designated tracks. The USGS also partners with NOAA and the National Aeronautics and Space Administration (NASA) to model air-sea flux as part of a Gulf of Mexico Carbon Synthesis project led by NASA.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds883","usgsCitation":"Robbins, L.L., Knorr, P.O., Daly, K.L., and Barrera, K.E., 2014, USGS Field Activities 12BHM01, 12BHM02, 12BHM03, 12BHM04, and 12BHM05 on the West Florida Shelf, in February, April, May, June, and August 2012: U.S. Geological Survey Data Series 883, HTML Document, https://doi.org/10.3133/ds883.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2012-02-01","temporalEnd":"2012-08-31","ipdsId":"IP-051019","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":295983,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds883.png"},{"id":295960,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0883/"},{"id":295982,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0883/html/ds883_abstract.html","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Florida","otherGeospatial":"West Florida Shelf","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -85.89111328125,\n 27.371767300523047\n ],\n [\n -85.89111328125,\n 30.14512718337613\n ],\n [\n -82.265625,\n 30.14512718337613\n ],\n [\n -82.265625,\n 27.371767300523047\n ],\n [\n -85.89111328125,\n 27.371767300523047\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5463251ee4b0ba83040c6a54","contributors":{"authors":[{"text":"Robbins, Lisa L. 0000-0003-3681-1094 lrobbins@usgs.gov","orcid":"https://orcid.org/0000-0003-3681-1094","contributorId":422,"corporation":false,"usgs":true,"family":"Robbins","given":"Lisa","email":"lrobbins@usgs.gov","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":524923,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Knorr, Paul O. pknorr@usgs.gov","contributorId":3691,"corporation":false,"usgs":true,"family":"Knorr","given":"Paul","email":"pknorr@usgs.gov","middleInitial":"O.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":524925,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Daly, Kendra L.","contributorId":79018,"corporation":false,"usgs":true,"family":"Daly","given":"Kendra","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":524924,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barrera, Kira E. 0000-0002-2807-4795 kbarrera@usgs.gov","orcid":"https://orcid.org/0000-0002-2807-4795","contributorId":4910,"corporation":false,"usgs":true,"family":"Barrera","given":"Kira","email":"kbarrera@usgs.gov","middleInitial":"E.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":524926,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70133281,"text":"ofr20141232 - 2014 - Surface wave site characterization at 27 locations near Boston, Massachusetts, including 2 strong-motion stations","interactions":[],"lastModifiedDate":"2014-11-13T09:45:51","indexId":"ofr20141232","displayToPublicDate":"2014-11-11T09:15:00","publicationYear":"2014","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":"2014-1232","title":"Surface wave site characterization at 27 locations near Boston, Massachusetts, including 2 strong-motion stations","docAbstract":"The geotechnical properties of the soils in and around Boston, Massachusetts, have been extensively studied. This is partly due to the importance of the Boston Blue Clay and the extent of landfill in the Boston area. Although New England is not a region that is typically associated with seismic hazards, there have been several historical earthquakes that have caused significant ground shaking (for example, see Street and Lacroix, 1979; Ebel, 1996; Ebel, 2006). The possibility of strong ground shaking, along with heightened vulnerability from unreinforced masonry buildings, motivates further investigation of seismic hazards throughout New England. Important studies that are pertinent to seismic hazards in New England include source-parameter studies (Somerville and others, 1987; Boore and others, 2010), wave-propagation studies (Frankel, 1991; Viegas and others, 2010), empirical ground-motion prediction equations (GMPE) for computing ground-motion intensity (Tavakoli and Pezeshk, 2005; Atkinson and Boore, 2006), site-response studies (Hayles and others, 2001; Ebel and Kim, 2006), and liquefaction studies (Brankman and Baise, 2008). The shear-wave velocity (VS) profiles collected for this report are pertinent to the GMPE, site response, and liquefaction aspects of seismic hazards in the greater Boston area. Besides the application of these data for the Boston region, the data may be applicable throughout New England, through correlations with geologic units (similar to Ebel and Kim, 2006) or correlations with topographic slope (Wald and Allen, 2007), because few VS measurements are available in stable tectonic regions.
Ebel and Hart (2001) used felt earthquake reports to infer amplification patterns throughout the greater Boston region and noted spatial correspondence with the dominant period and amplification factors obtained from ambient noise (horizontal-to-vertical ratios) by Kummer (1998). Britton (2003) compiled geotechnical borings in the area and produced a microzonation map based on generalized velocity profiles, where the amplifications were computed using Shake (Schnable and others, 1972), along with an assumed input ground motion. The velocities were constrained by only a few local measurements associated with the Central Artery/Tunnel project. The additional VS measurements presented in this report provide a number of benefits. First, these measurements provide improved spatial coverage. Second, the larger sample size provides better constraints on the mean and variance of the VS distribution for each layer, which may be paired with a three-dimensional (3D) model of the stratigraphy to generate one-dimensional (1D) profiles for use in a standard site-response analysis (for example, Britton, 2003). Third, the velocity profiles may also be used, along with a 3D model of the stratigraphy, as input into a 3D simulation of the ground motion to investigate the effects of basin-generated surface waves and the potential focusing of seismic waves.
This report begins with a short review of the geology of the study area and the field methods that we used to estimate the velocity profiles. The raw data, processed data, and the interpreted VS profiles are given in appendix 1. Photographs and descriptions of the sites are provided in appendix 2.
Changes in water temperatures resulting from climate warming can alter the structure and function of aquatic ecosystems. Lake-specific physical characteristics may play a role in mediating individual lake responses to climate. Past mechanistic studies of lake-climate interactions have simulated generic lake classes at large spatial scales or performed detailed analyses of small numbers of real lakes. Understanding the diversity of lake responses to climate change across landscapes requires a hybrid approach that couples site-specific lake characteristics with broad-scale environmental drivers. This study provides a substantial advancement in lake ecosystem modeling by combining open-source tools with freely available continental-scale data to mechanistically model daily temperatures for 2,368 Wisconsin lakes over three decades (1979-2011). The model accurately predicted observed surface layer temperatures (RMSE: 1.74°C) and the presence/absence of stratification (81.1% agreement). Among-lake coherence was strong for surface temperatures and weak for the timing of stratification, suggesting individual lake characteristics mediate some - but not all - ecologically relevant lake responses to climate.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolmodel.2014.07.029","usgsCitation":"Read, J.S., Winslow, L.A., Hansen, G.J., Van Den Hoek, J., Hanson, P.C., Bruce, L.C., and Markfort, C.D., 2014, Simulating 2,368 temperate lakes reveals weak coherence in stratification phenology: Ecological Modelling, v. 291, p. 142-150, https://doi.org/10.1016/j.ecolmodel.2014.07.029.","productDescription":"9 p.","startPage":"142","endPage":"150","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-056409","costCenters":[{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true},{"id":36940,"text":"National Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":472647,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.ecolmodel.2014.07.029","text":"Publisher Index Page"},{"id":296929,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":337361,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7028PN4","text":"Climate warming of Wisconsin lakes can be either amplified or suppressed by trends in water clarity"}],"volume":"291","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54dd2c58e4b08de9379b373c","chorus":{"doi":"10.1016/j.ecolmodel.2014.07.029","url":"http://dx.doi.org/10.1016/j.ecolmodel.2014.07.029","publisher":"Elsevier BV","authors":"Read Jordan S., Winslow Luke A., Hansen Gretchen J.A., Van Den Hoek Jamon, Hanson Paul C., Bruce Louise C., Markfort Corey D.","journalName":"Ecological Modelling","publicationDate":"11/2014","auditedOn":"11/1/2014","publiclyAccessibleDate":"8/5/2014"},"contributors":{"authors":[{"text":"Read, Jordan S. 0000-0002-3888-6631 jread@usgs.gov","orcid":"https://orcid.org/0000-0002-3888-6631","contributorId":4453,"corporation":false,"usgs":true,"family":"Read","given":"Jordan","email":"jread@usgs.gov","middleInitial":"S.","affiliations":[{"id":160,"text":"Center for Integrated Data Analytics","active":false,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":5054,"text":"Office of Water Information","active":true,"usgs":true}],"preferred":true,"id":537269,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Winslow, Luke A. 0000-0002-8602-5510 lwinslow@usgs.gov","orcid":"https://orcid.org/0000-0002-8602-5510","contributorId":5919,"corporation":false,"usgs":true,"family":"Winslow","given":"Luke","email":"lwinslow@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":false,"id":537270,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hansen, Gretchen J. A.","contributorId":131099,"corporation":false,"usgs":false,"family":"Hansen","given":"Gretchen","email":"","middleInitial":"J. A.","affiliations":[{"id":7242,"text":"Wisconsin Department of Natural Resources, Madison, WI, USA","active":true,"usgs":false}],"preferred":false,"id":537271,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Van Den Hoek, Jamon","contributorId":127555,"corporation":false,"usgs":false,"family":"Van Den Hoek","given":"Jamon","email":"","affiliations":[{"id":7049,"text":"NASA Goddard Space Flight Center","active":true,"usgs":false}],"preferred":false,"id":537272,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hanson, Paul C.","contributorId":35634,"corporation":false,"usgs":false,"family":"Hanson","given":"Paul","email":"","middleInitial":"C.","affiliations":[{"id":12951,"text":"Center for Limnology, University of Wisconsin Madison","active":true,"usgs":false}],"preferred":false,"id":537273,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bruce, Louise C.","contributorId":131100,"corporation":false,"usgs":false,"family":"Bruce","given":"Louise","email":"","middleInitial":"C.","affiliations":[{"id":7243,"text":"School of Earth & Environment, The University of Western Australia, Perth, Australia","active":true,"usgs":false}],"preferred":false,"id":537274,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Markfort, Corey D.","contributorId":131098,"corporation":false,"usgs":false,"family":"Markfort","given":"Corey","email":"","middleInitial":"D.","affiliations":[{"id":7241,"text":"IIHR-Hydroscience and Engineering, Department of Civil and Environmental Engineering, The University of Iowa","active":true,"usgs":false}],"preferred":false,"id":537275,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70133363,"text":"70133363 - 2014 - Termini of calving glaciers as self-organized critical systems","interactions":[],"lastModifiedDate":"2021-02-04T18:07:11.514468","indexId":"70133363","displayToPublicDate":"2014-11-10T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2845,"text":"Nature Geoscience","active":true,"publicationSubtype":{"id":10}},"title":"Termini of calving glaciers as self-organized critical systems","docAbstract":"Over the next century, one of the largest contributions to sea level rise will come from ice sheets and glaciers calving ice into the ocean1. Factors controlling the rapid and nonlinear variations in calving fluxes are poorly understood, and therefore difficult to include in prognostic climate-forced land-ice models. Here we analyse globally distributed calving data sets from Svalbard, Alaska (USA), Greenland and Antarctica in combination with simulations from a first-principles, particle-based numerical calving model to investigate the size and inter-event time of calving events. We find that calving events triggered by the brittle fracture of glacier ice are governed by the same power-law distributions as avalanches in the canonical Abelian sandpile model2. This similarity suggests that calving termini behave as self-organized critical systems that readily flip between states of sub-critical advance and super-critical retreat in response to changes in climate and geometric conditions. Observations of sudden ice-shelf collapse and tidewater glacier retreat in response to gradual warming of their environment3 are consistent with a system fluctuating around its critical point in response to changing external forcing. We propose that self-organized criticality provides a yet unexplored framework for investigations into calving and projections of sea level rise.
","language":"English","publisher":"Nature","doi":"10.1038/ngeo2290","usgsCitation":"Astrom, J., Vallot, D., Schafer, M., Welty, E., O’Neel, S., Bartholomaus, T., Liu, Y., Riikila, T., Zwinger, T., Timonen, J., and Moore, J.N., 2014, Termini of calving glaciers as self-organized critical systems: Nature Geoscience, v. 7, p. 874-878, https://doi.org/10.1038/ngeo2290.","productDescription":"5 p.","startPage":"874","endPage":"878","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-058378","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":296131,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"7","noUsgsAuthors":false,"publicationDate":"2014-11-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Astrom, J.","contributorId":127397,"corporation":false,"usgs":false,"family":"Astrom","given":"J.","email":"","affiliations":[{"id":6937,"text":"CSC – IT Centre for Science, P.O. Box 405, 02101, Espoo, Finland","active":true,"usgs":false}],"preferred":false,"id":525016,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Vallot, D.","contributorId":127398,"corporation":false,"usgs":false,"family":"Vallot","given":"D.","email":"","affiliations":[{"id":6938,"text":"Department of Earth Science, Uppsala University, Villavägen 16, Uppsala, 75236, Sweden","active":true,"usgs":false}],"preferred":false,"id":525017,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schafer, M.","contributorId":127399,"corporation":false,"usgs":false,"family":"Schafer","given":"M.","email":"","affiliations":[{"id":6939,"text":"Arctic Centre, University of Lapland, PL122, 96100 Rovaniemi, Finland","active":true,"usgs":false}],"preferred":false,"id":525018,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Welty, E.","contributorId":56464,"corporation":false,"usgs":true,"family":"Welty","given":"E.","email":"","affiliations":[],"preferred":false,"id":525019,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"O’Neel, Shad 0000-0002-9185-0144 soneel@usgs.gov","orcid":"https://orcid.org/0000-0002-9185-0144","contributorId":166740,"corporation":false,"usgs":true,"family":"O’Neel","given":"Shad","email":"soneel@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":107,"text":"Alaska Climate Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true}],"preferred":true,"id":525015,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bartholomaus, T.C.","contributorId":94569,"corporation":false,"usgs":true,"family":"Bartholomaus","given":"T.C.","affiliations":[],"preferred":false,"id":525020,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Liu, Y.","contributorId":127400,"corporation":false,"usgs":false,"family":"Liu","given":"Y.","email":"","affiliations":[{"id":6940,"text":"State Key Laboratory of Earth Surface Processes and Resource Ecology, College of Global Change and Earth System Science, Beijing Normal University, Beijing, China","active":true,"usgs":false}],"preferred":false,"id":525021,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Riikila, T.","contributorId":127401,"corporation":false,"usgs":false,"family":"Riikila","given":"T.","email":"","affiliations":[{"id":6941,"text":"Department of Physics and Nanoscience Center, University of Jyväskylä, P.O. Box 35, 40014, Jyväskylä, Finland","active":true,"usgs":false}],"preferred":false,"id":525022,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Zwinger, T.","contributorId":82612,"corporation":false,"usgs":true,"family":"Zwinger","given":"T.","email":"","affiliations":[],"preferred":false,"id":525024,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Timonen, J.","contributorId":248787,"corporation":false,"usgs":false,"family":"Timonen","given":"J.","email":"","affiliations":[],"preferred":false,"id":809840,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Moore, Johnnie N.","contributorId":13668,"corporation":false,"usgs":true,"family":"Moore","given":"Johnnie","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":525023,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70173943,"text":"70173943 - 2014 - The birth and death of transverse aeolian ridges on Mars","interactions":[],"lastModifiedDate":"2021-04-22T20:39:56.481975","indexId":"70173943","displayToPublicDate":"2014-11-08T14:30:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2317,"text":"Journal of Geophysical Research E: Planets","active":true,"publicationSubtype":{"id":10}},"title":"The birth and death of transverse aeolian ridges on Mars","docAbstract":"Transverse aeolian ridges (TARs) are small bright windblown deposits found throughout the Martian tropics that stand a few meters tall and are spaced a few tens of meters apart. The origin of these features remains mysterious more than 20 years after their discovery on Mars. This paper presents a new hypothesis, that some of the TARs could be indurated dust deposits emplaced millions of years ago during periods of higher axial obliquity. It suggests that these TARs are primary depositional bed forms that accumulated in place from dust carried by the winds in suspension, perhaps in a manner comparable to antidunes on Earth, and were subsequently indurated and eroded to their current states by eons of sandblasting. It points out examples of modern dust drifts and dune‐like features that appear to have been recently formed by dust accumulating directly onto the surface from atmospheric suspension. It shows how these pristine dust deposits could evolve to explain the range of morphologies of the TARs. Finally, it explains how the known properties of many TARs are consistent with this hypothesis, including their composition, thermal behavior, and distribution.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2014JE004633","usgsCitation":"Geissler, P.E., 2014, The birth and death of transverse aeolian ridges on Mars: Journal of Geophysical Research E: Planets, v. 119, no. 12, p. 2583-2599, https://doi.org/10.1002/2014JE004633.","productDescription":"16 p.","startPage":"2583","endPage":"2599","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-054232","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":472648,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2014je004633","text":"Publisher Index Page"},{"id":323959,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Mars","volume":"119","issue":"12","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2014-12-11","publicationStatus":"PW","scienceBaseUri":"576913ece4b07657d19ff293","contributors":{"authors":[{"text":"Geissler, Paul E. pgeissler@usgs.gov","contributorId":2811,"corporation":false,"usgs":true,"family":"Geissler","given":"Paul","email":"pgeissler@usgs.gov","middleInitial":"E.","affiliations":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"preferred":true,"id":639653,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70131482,"text":"70131482 - 2014 - Practical limitations on the use of diurnal temperature signals to quantify groundwater upwelling","interactions":[],"lastModifiedDate":"2018-09-18T16:25:14","indexId":"70131482","displayToPublicDate":"2014-11-07T17:15:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2342,"text":"Journal of Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Practical limitations on the use of diurnal temperature signals to quantify groundwater upwelling","docAbstract":"Groundwater upwelling to streams creates unique habitat by influencing stream water quality and temperature; upwelling zones also serve as vectors for contamination when groundwater is degraded. Temperature time series data acquired along vertical profiles in the streambed have been applied to simple analytical models to determine rates of vertical fluid flux. These models are based on the downward propagation characteristics (amplitude attenuation and phase-lag) of the surface diurnal signal. Despite the popularity of these models, there are few published characterizations of moderate-to-strong upwelling. We attribute this limitation to the thermodynamics of upwelling, under which the downward conductive signal transport from the streambed interface occurs opposite the upward advective fluid flux. Governing equations describing the advection–diffusion of heat within the streambed predict that under upwelling conditions, signal amplitude attenuation will increase, but, counterintuitively, phase-lag will decrease. Therefore the extinction (measurable) depth of the diurnal signal is very shallow, but phase lag is also short, yielding low signal to noise ratio and poor model sensitivity. Conversely, amplitude attenuation over similar sensor spacing is strong, yielding greater potential model sensitivity. Here we present streambed thermal time series over a range of moderate to strong upwelling sites in the Quashnet River, Cape Cod, Massachusetts. The predicted inverse relationship between phase-lag and rate of upwelling was observed in the field data over a range of conditions, but the observed phase-lags were consistently shorter than predicted. Analytical solutions for fluid flux based on signal amplitude attenuation return results consistent with numerical models and physical seepage meters, but the phase-lag analytical model results are generally unreasonable. Through numerical modeling we explore reasons why phase-lag may have been over-predicted by the analytical models, and develop guiding relations of diurnal temperature signal extinction depth based on stream diurnal signal amplitude, upwelling magnitude, and streambed thermal properties that will be useful in designing future experiments.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jhydrol.2014.09.030","usgsCitation":"Briggs, M.A., Lautz, L.K., Buckley, S.F., and Lane, J.W., 2014, Practical limitations on the use of diurnal temperature signals to quantify groundwater upwelling: Journal of Hydrology, v. 519, no. B, p. 1739-1751, https://doi.org/10.1016/j.jhydrol.2014.09.030.","productDescription":"13 p.","startPage":"1739","endPage":"1751","numberOfPages":"13","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057864","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":295951,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":295952,"type":{"id":15,"text":"Index Page"},"url":"https://www.sciencedirect.com/science/article/pii/S0022169414007124"}],"volume":"519","issue":"B","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"545ddf17e4b0ba8303f8b62a","contributors":{"authors":[{"text":"Briggs, Martin A. 0000-0003-3206-4132 mbriggs@usgs.gov","orcid":"https://orcid.org/0000-0003-3206-4132","contributorId":4114,"corporation":false,"usgs":true,"family":"Briggs","given":"Martin","email":"mbriggs@usgs.gov","middleInitial":"A.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":521241,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Lautz, Laura K.","contributorId":124523,"corporation":false,"usgs":false,"family":"Lautz","given":"Laura","email":"","middleInitial":"K.","affiliations":[{"id":5082,"text":"Syracuse University","active":true,"usgs":false}],"preferred":false,"id":521242,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Buckley, Sean F. sbuckley@usgs.gov","contributorId":3910,"corporation":false,"usgs":true,"family":"Buckley","given":"Sean","email":"sbuckley@usgs.gov","middleInitial":"F.","affiliations":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"preferred":true,"id":521243,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lane, John W. Jr. jwlane@usgs.gov","contributorId":1738,"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}],"preferred":false,"id":521244,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70131483,"text":"70131483 - 2014 - On the downscaling of actual evapotranspiration maps based on combination of MODIS and landsat-based actual evapotranspiration estimates","interactions":[],"lastModifiedDate":"2017-01-18T11:27:04","indexId":"70131483","displayToPublicDate":"2014-11-07T17:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"On the downscaling of actual evapotranspiration maps based on combination of MODIS and landsat-based actual evapotranspiration estimates","docAbstract":"Downscaling is one of the important ways of utilizing the combined benefits of the high temporal resolution of Moderate Resolution Imaging Spectroradiometer (MODIS) images and fine spatial resolution of Landsat images. We have evaluated the output regression with intercept method and developed the Linear with Zero Intercept (LinZI) method for downscaling MODIS-based monthly actual evapotranspiration (AET) maps to the Landsat-scale monthly AET maps for the Colorado River Basin for 2010. We used the 8-day MODIS land surface temperature product (MOD11A2) and 328 cloud-free Landsat images for computing AET maps and downscaling. The regression with intercept method does have limitations in downscaling if the slope and intercept are computed over a large area. A good agreement was obtained between downscaled monthly AET using the LinZI method and the eddy covariance measurements from seven flux sites within the Colorado River Basin. The mean bias ranged from −16 mm (underestimation) to 22 mm (overestimation) per month, and the coefficient of determination varied from 0.52 to 0.88. Some discrepancies between measured and downscaled monthly AET at two flux sites were found to be due to the prevailing flux footprint. A reasonable comparison was also obtained between downscaled monthly AET using LinZI method and the gridded FLUXNET dataset. The downscaled monthly AET nicely captured the temporal variation in sampled land cover classes. The proposed LinZI method can be used at finer temporal resolution (such as 8 days) with further evaluation. The proposed downscaling method will be very useful in advancing the application of remotely sensed images in water resources planning and management.
","language":"English","publisher":"MDPI","doi":"10.3390/rs61110483","usgsCitation":"Singh, R.K., Senay, G.B., Velpuri, N.M., Bohms, S., and Verdin, J.P., 2014, On the downscaling of actual evapotranspiration maps based on combination of MODIS and landsat-based actual evapotranspiration estimates: Remote Sensing, v. 6, no. 11, p. 10483-10509, https://doi.org/10.3390/rs61110483.","productDescription":"27 p.","startPage":"10483","endPage":"10509","numberOfPages":"27","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057248","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":472650,"rank":3,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs61110483","text":"Publisher Index Page"},{"id":295950,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":295953,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://www.mdpi.com/2072-4292/6/11/10483"}],"volume":"6","issue":"11","noUsgsAuthors":false,"publicationDate":"2014-10-30","publicationStatus":"PW","scienceBaseUri":"545ddf17e4b0ba8303f8b625","contributors":{"authors":[{"text":"Singh, Ramesh K. 0000-0002-8164-3483 rsingh@usgs.gov","orcid":"https://orcid.org/0000-0002-8164-3483","contributorId":3895,"corporation":false,"usgs":true,"family":"Singh","given":"Ramesh","email":"rsingh@usgs.gov","middleInitial":"K.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":521245,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Senay, Gabriel B. 0000-0002-8810-8539 senay@usgs.gov","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":3114,"corporation":false,"usgs":true,"family":"Senay","given":"Gabriel","email":"senay@usgs.gov","middleInitial":"B.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":521246,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Velpuri, Naga Manohar 0000-0002-6370-1926 nvelpuri@usgs.gov","orcid":"https://orcid.org/0000-0002-6370-1926","contributorId":4441,"corporation":false,"usgs":true,"family":"Velpuri","given":"Naga","email":"nvelpuri@usgs.gov","middleInitial":"Manohar","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":521247,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bohms, Stefanie 0000-0002-2979-4655 sbohms@usgs.gov","orcid":"https://orcid.org/0000-0002-2979-4655","contributorId":3148,"corporation":false,"usgs":true,"family":"Bohms","given":"Stefanie","email":"sbohms@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":521248,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Verdin, James P. 0000-0003-0238-9657 verdin@usgs.gov","orcid":"https://orcid.org/0000-0003-0238-9657","contributorId":720,"corporation":false,"usgs":true,"family":"Verdin","given":"James","email":"verdin@usgs.gov","middleInitial":"P.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":521249,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70129577,"text":"fs20143106 - 2014 - The 3D Elevation Program: summary for Kansas","interactions":[],"lastModifiedDate":"2016-08-17T15:20:05","indexId":"fs20143106","displayToPublicDate":"2014-11-07T16:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-3106","title":"The 3D Elevation Program: summary for Kansas","docAbstract":"Elevation data are essential to a broad range of applications, including forest resources management, wildlife and habitat management, national security, recreation, and many others. For the State of Kansas, elevation data are critical for agriculture and precision farming, natural resources conservation, flood risk management, infrastructure and construction management, geologic resource assessment and hazard mitigation, and other business uses. Today, high-density light detection and ranging (lidar) data are the primary sources for deriving elevation models and other datasets. Federal, State, Tribal, and local agencies work in partnership to (1) replace data that are older and of lower quality and (2) provide coverage where publicly accessible data do not exist. A joint goal of State and Federal partners is to acquire consistent, statewide coverage to support existing and emerging applications enabled by lidar data.
\nThe National Enhanced Elevation Assessment evaluated multiple elevation data acquisition options to determine the optimal data quality and data replacement cycle relative to cost to meet the identified requirements of the user community. The evaluation demonstrated that lidar acquisition at quality level 2 for the conterminous United States and quality level 5 interferometric synthetic aperture radar (ifsar) data for Alaska with a 6- to 10-year acquisition cycle provided the highest benefit/cost ratios. The 3D Elevation Program (3DEP) initiative selected an 8-year acquisition cycle for the respective quality levels. 3DEP, managed by the U.S. Geological Survey, the Office of Management and Budget Circular A–16 lead agency for terrestrial elevation data, responds to the growing need for high-quality topographic data and a wide range of other 3D representations of the Nation’s natural and constructed features.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20143106","usgsCitation":"Carswell, W., 2014, The 3D Elevation Program: summary for Kansas: U.S. Geological Survey Fact Sheet 2014-3106, 2 p., https://doi.org/10.3133/fs20143106.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-059303","costCenters":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"links":[{"id":295947,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20143106.jpg"},{"id":295945,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2014/3106/"},{"id":295946,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2014/3106/pdf/fs2014-3106.pdf","text":"Report","size":"285 KB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"country":"United 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William J. Jr. carswell@usgs.gov","contributorId":1787,"corporation":false,"usgs":true,"family":"Carswell","given":"William J.","suffix":"Jr.","email":"carswell@usgs.gov","affiliations":[{"id":423,"text":"National Geospatial Program","active":true,"usgs":true}],"preferred":false,"id":519897,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70128252,"text":"sir20145193 - 2014 - An initial abstraction and constant loss model, and methods for estimating unit hydrographs, peak streamflows, and flood volumes for urban basins in Missouri","interactions":[],"lastModifiedDate":"2014-11-07T13:13:55","indexId":"sir20145193","displayToPublicDate":"2014-11-07T11:00:00","publicationYear":"2014","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":"2014-5193","title":"An initial abstraction and constant loss model, and methods for estimating unit hydrographs, peak streamflows, and flood volumes for urban basins in Missouri","docAbstract":"Streamflow data, basin characteristics, and rainfall data from 39 streamflow-gaging stations for urban areas in and adjacent to Missouri were used by the U.S. Geological Survey in cooperation with the Metropolitan Sewer District of St. Louis to develop an initial abstraction and constant loss model (a time-distributed basin-loss model) and a gamma unit hydrograph (GUH) for urban areas in Missouri. Study-specific methods to determine peak streamflow and flood volume for a given rainfall event also were developed.
\n\n
Distinct basin characteristics were evaluated and selected for use on the basis of their theoretical relation to flow, results from previous studies, and the ability to reliably measure the basin characteristic using digital datasets and geographic information system (GIS) technology. The key basin characteristics determined or computed for each of the 39 basins upstream from the streamflow-gaging stations were drainage area, percent impervious area, main-channel slope based on the 10- and 85-percent length method, percentage of the basin area in storage (lakes, ponds, reservoirs, wetlands), the composite Natural Resources Conservation Service curve number estimated from a combination of the soil type data and land-use characteristics, and the streamflow variability index developed for the recently completed study of low-flow regression in Missouri.
\n\n
Characteristics of spatial and temporal rainfall distribution came from the next generation weather radar (NEXRAD) network. Procedures were developed for this study to convert the variable radar sweep rate into a 5-minute total rainfall hyetograph using data from the radar bin at the centroid of a given basin. Additional characteristics determined for each storm on the basin included the 5-day and 14-day antecedent rainfall, estimated from the mean of daily rainfall values from various rain gages in the area.
\n\n
The database of observed rainfall and runoff events for the 39 basins upstream from the streamflow-gaging stations was analyzed to compute the optimal storm-specific initial abstraction and constant loss values, as well as the time to peak, peak streamflow, and shape factor values of the GUH. The optimal storm-specific values were used to develop a regional regression equation for initial abstraction; conversely, the constant loss was estimated not by regression but from either a generalized or specific regional mean value. The optimal storm-specific values of GUH time to peak, GUH peak streamflow, and GUH shape factor were used to develop regression equations for the GUH.
\n\n
The regression equations for the GUH initially were tested alone, and then were combined with the appropriate regional regression equation for initial abstraction and both the generalized regional and specific regional mean constant loss values. For the GUH regression equations, the interquartile range was substantially smaller than the range spanned by the minimum and maximum values, which indicates most of the errors have much smaller variation, and the minimum and maximum values may be extreme outliers. The central tendency of the regressed errors for peak streamflow and runoff hydrograph volume were both approximately zero, which implies a generally unbiased estimation of these values. The mean and median of the regressed errors for time to peak streamflow were both small but greater than zero, which implies the GUH regression equations create a hydrograph that has a peak that is later in time than observed. Specifically, the regressed times indicate an offset of about 10 minutes, on average, from observed. The mean and median of the regressed errors for widths of the runoff hydrograph at 50 and 75 percent were less than zero, which implies the GUH tends to slightly underestimate these widths compared to the observed.
\n\n
The appropriate regional initial abstraction regression equation was combined with both the generalized and the specific regional mean constant loss values and the GUH regression equations. Both the generalized regional mean constant loss and specific regional mean constant loss forms of the basin-loss model worked equally well to model the observed runoff hydrograph based on the error analysis, and neither model seems to make a consistently better approximation. Both initial abstraction and constant loss models combined with the GUH regression equations were further validated using several storms available after the start of the project in early 2011 with similar but consistently higher error results. If these methods are used in an urban area in Missouri other than those examined in this study, advice to the user is given to consider using the generalized regional mean values. If these methods are used in an urban area that is a subbasin of one of the basins in this study, advice to the user is given to consider using the specific regional mean values.
\n\n
The rainfall-runoff pairs from the storm-specific GUH analysis were further analyzed against various basin and rainfall characteristics to develop equations to estimate the peak streamflow and flood volume based on a quantity of rainfall on the basin.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145193","collaboration":"Prepared in cooperation with the Metropolitan Sewer District of St. Louis","usgsCitation":"Huizinga, R.J., 2014, An initial abstraction and constant loss model, and methods for estimating unit hydrographs, peak streamflows, and flood volumes for urban basins in Missouri: U.S. Geological Survey Scientific Investigations Report 2014-5193, Report: x, 59 p.; Downloads Directory, https://doi.org/10.3133/sir20145193.","productDescription":"Report: x, 59 p.; Downloads Directory","numberOfPages":"74","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057930","costCenters":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true}],"links":[{"id":295937,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145193.jpg"},{"id":295934,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5193/"},{"id":295935,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5193/pdf/sir2014-5193.pdf"},{"id":295936,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2014/5193/downloads/"}],"country":"United States","state":"Missouri","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"545ddf16e4b0ba8303f8b61f","contributors":{"authors":[{"text":"Huizinga, Richard J. 0000-0002-2940-2324 huizinga@usgs.gov","orcid":"https://orcid.org/0000-0002-2940-2324","contributorId":2089,"corporation":false,"usgs":true,"family":"Huizinga","given":"Richard","email":"huizinga@usgs.gov","middleInitial":"J.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":519683,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70114464,"text":"70114464 - 2014 - Using multiple data sets to populate probabilistic volcanic event trees","interactions":[],"lastModifiedDate":"2016-06-28T16:29:33","indexId":"70114464","displayToPublicDate":"2014-11-07T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":5,"text":"Book chapter"},"publicationSubtype":{"id":24,"text":"Book Chapter"},"title":"Using multiple data sets to populate probabilistic volcanic event trees","docAbstract":"The key parameters one needs to forecast outcomes of volcanic unrest are hidden kilometers beneath the Earth’s surface, and volcanic systems are so complex that there will invariably be stochastic elements in the evolution of any unrest. Fortunately, there is sufficient regularity in behaviour that some, perhaps many, eruptions can be forecast with enough certainty for populations to be evacuated and kept safe. Volcanologists charged with forecasting eruptions must try to understand each volcanic system well enough that unrest can be interpreted in terms of pre-eruptive process, but must simultaneously recognize and convey uncertainties in their assessment. We have found that use of event trees helps to focus discussion, integrate data from multiple sources, reach consensus among scientists about both pre-eruptive process and uncertainties and, in some cases, to explain all of this to officials. Figure 1 shows a generic volcanic event tree from Newhall and Hoblitt (2002) that can be modified as needed for each specific volcano. This paper reviews how we and our colleagues have used such trees during a number of volcanic crises worldwide, for rapid hazard assessments in situations in which more formal expert elicitations could not be conducted. We describe how Multiple Data Sets can be used to estimate probabilities at each node and branch. We also present case histories of probability estimation during crises, how the estimates were used by public officials, and some suggestions for future improvements.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"Volcanic Hazards, Risks and Disasters","language":"English","publisher":"Elsevier","doi":"10.1016/B978-0-12-396453-3.00008-3","usgsCitation":"Newhall, C.G., and Pallister, J.S., 2014, Using multiple data sets to populate probabilistic volcanic event trees, chap. of Volcanic Hazards, Risks and Disasters, p. 203-232, https://doi.org/10.1016/B978-0-12-396453-3.00008-3.","productDescription":"30 p.","startPage":"203","endPage":"232","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-055823","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":324570,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57739fb8e4b07657d1a90da1","contributors":{"authors":[{"text":"Newhall, C. G.","contributorId":93056,"corporation":false,"usgs":true,"family":"Newhall","given":"C.","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":519002,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pallister, John S. 0000-0002-2041-2147 jpallist@usgs.gov","orcid":"https://orcid.org/0000-0002-2041-2147","contributorId":2024,"corporation":false,"usgs":true,"family":"Pallister","given":"John","email":"jpallist@usgs.gov","middleInitial":"S.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":519001,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70118093,"text":"ds862 - 2014 - USGS Arctic Ocean Carbon Cruise 2012: Field Activity L-01-12-AR to collect carbon data in the Arctic Ocean, August-September 2012","interactions":[],"lastModifiedDate":"2014-11-07T13:27:04","indexId":"ds862","displayToPublicDate":"2014-11-06T16:30:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"862","title":"USGS Arctic Ocean Carbon Cruise 2012: Field Activity L-01-12-AR to collect carbon data in the Arctic Ocean, August-September 2012","docAbstract":"From August 25 to September 27, 2012, the United States Coast Guard Cutter (USCGC) Healy was part of an Extended Continental Shelf Project to determine the limits of the extended continental shelf in the Arctic. On a non-interference basis, a USGS ocean acidification team participated on the cruise to collect baseline water data in the Arctic. The collection of data extended from coastal waters near Barrow, Alaska, to 83°2'N., -175°36'W., and southward back to coastal waters near Barrow and on to Dutch Harbor, Alaska. As a consequence, a number of hypotheses were tested and questions asked associated with ocean acidification, including:
\n\n
\n
During the cruise, underway continuous and discrete water samples were collected, and discrete water samples were collected at stations to document the carbonate chemistry of the Arctic waters and quantify the saturation state of seawater with respect to calcium carbonate. These data are critical for providing baseline information in areas where no data have existed prior and will also be used to test existing models and predict future trends.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds862","usgsCitation":"Robbins, L.L., Wynn, J., Knorr, P.O., Onac, B., Lisle, J.T., McMullen, K.Y., Yates, K.K., Byrne, R., and Liu, X., 2014, USGS Arctic Ocean Carbon Cruise 2012: Field Activity L-01-12-AR to collect carbon data in the Arctic Ocean, August-September 2012: U.S. Geological Survey Data Series 862, HTML Document, https://doi.org/10.3133/ds862.","productDescription":"HTML Document","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2012-08-01","temporalEnd":"2012-09-30","ipdsId":"IP-051020","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":295933,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds862.jpg"},{"id":295931,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0862/"},{"id":295932,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0862/ds862_abstract.html"}],"country":"United States","otherGeospatial":"Arctic Ocean","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"545c8da2e4b0ba8303f703c0","contributors":{"authors":[{"text":"Robbins, Lisa L. 0000-0003-3681-1094 lrobbins@usgs.gov","orcid":"https://orcid.org/0000-0003-3681-1094","contributorId":422,"corporation":false,"usgs":true,"family":"Robbins","given":"Lisa","email":"lrobbins@usgs.gov","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":519133,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wynn, Jonathan","contributorId":9943,"corporation":false,"usgs":false,"family":"Wynn","given":"Jonathan","affiliations":[],"preferred":false,"id":524457,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Knorr, Paul O. pknorr@usgs.gov","contributorId":3691,"corporation":false,"usgs":true,"family":"Knorr","given":"Paul","email":"pknorr@usgs.gov","middleInitial":"O.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":524458,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Onac, Bogdan","contributorId":127356,"corporation":false,"usgs":false,"family":"Onac","given":"Bogdan","affiliations":[],"preferred":false,"id":524459,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lisle, John T. 0000-0002-5447-2092 jlisle@usgs.gov","orcid":"https://orcid.org/0000-0002-5447-2092","contributorId":2944,"corporation":false,"usgs":true,"family":"Lisle","given":"John","email":"jlisle@usgs.gov","middleInitial":"T.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":524460,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McMullen, Katherine Y. kmcmullen@usgs.gov","contributorId":2148,"corporation":false,"usgs":true,"family":"McMullen","given":"Katherine","email":"kmcmullen@usgs.gov","middleInitial":"Y.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":524461,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Yates, Kimberly K. 0000-0001-8764-0358 kyates@usgs.gov","orcid":"https://orcid.org/0000-0001-8764-0358","contributorId":420,"corporation":false,"usgs":true,"family":"Yates","given":"Kimberly","email":"kyates@usgs.gov","middleInitial":"K.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":524462,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Byrne, Robert H.","contributorId":83260,"corporation":false,"usgs":true,"family":"Byrne","given":"Robert H.","affiliations":[],"preferred":false,"id":524463,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Liu, Xuewu","contributorId":87676,"corporation":false,"usgs":true,"family":"Liu","given":"Xuewu","email":"","affiliations":[],"preferred":false,"id":524464,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":70120966,"text":"ofr20141025B - 2014 - Earthquake catalog for estimation of maximum earthquake magnitude, Central and Eastern United States: Part B, historical earthquakes","interactions":[],"lastModifiedDate":"2014-11-14T11:42:22","indexId":"ofr20141025B","displayToPublicDate":"2014-11-06T14:00:00","publicationYear":"2014","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":"2014-1025","chapter":"B","title":"Earthquake catalog for estimation of maximum earthquake magnitude, Central and Eastern United States: Part B, historical earthquakes","docAbstract":"Computation of probabilistic earthquake hazard requires an estimate of Mmax: the moment magnitude of the largest earthquake that is thought to be possible within a specified geographic region. The region specified in this report is the Central and Eastern United States and adjacent Canada. Parts A and B of this report describe the construction of a global catalog of moderate to large earthquakes that occurred worldwide in tectonic analogs of the Central and Eastern United States. Examination of histograms of the magnitudes of these earthquakes allows estimation of Central and Eastern United States Mmax. The catalog and Mmax estimates derived from it are used in the 2014 edition of the U.S. Geological Survey national seismic-hazard maps. Part A deals with prehistoric earthquakes, and this part deals with historical events.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141025B","usgsCitation":"Wheeler, R.L., 2014, Earthquake catalog for estimation of maximum earthquake magnitude, Central and Eastern United States: Part B, historical earthquakes: U.S. Geological Survey Open-File Report 2014-1025, Report: iii, 30 p.; 1 Table, https://doi.org/10.3133/ofr20141025B.","productDescription":"Report: iii, 30 p.; 1 Table","numberOfPages":"33","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-057626","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":295927,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141025B.jpg"},{"id":295774,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1025/b/"},{"id":295925,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1025/b/pdf/ofr2014-1025b.pdf","size":"617 kB","linkFileType":{"id":1,"text":"pdf"}},{"id":295926,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2014/1025/b/downloads/table8.xlsx","text":"Table 8","size":"54.9 kB","linkFileType":{"id":3,"text":"xlsx"}}],"country":"United States","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"545c8d9ae4b0ba8303f70367","contributors":{"authors":[{"text":"Wheeler, Russell L. wheeler@usgs.gov","contributorId":858,"corporation":false,"usgs":true,"family":"Wheeler","given":"Russell","email":"wheeler@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":false,"id":522761,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70129027,"text":"sim3314 - 2014 - Geologic map of the west-central Buffalo National River region, northern Arkansas","interactions":[],"lastModifiedDate":"2014-11-06T13:08:05","indexId":"sim3314","displayToPublicDate":"2014-11-06T13:45:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3314","title":"Geologic map of the west-central Buffalo National River region, northern Arkansas","docAbstract":"This map summarizes the geology of the west-central Buffalo National River region in the Ozark Plateaus region of northern Arkansas. Geologically, the region lies on the southern flank of the Ozark dome, an uplift that exposes oldest rocks at its center in Missouri. Physiographically, the map area spans the Springfield Plateau, a topographic surface generally held up by Mississippian cherty limestone and the higher Boston Mountains to the south, held up by Pennsylvanian rocks. The Buffalo River flows eastward through the map area, enhancing bedrock erosion of an approximately 1,600-ft- (490-m-) thick sequence of Ordovician, Mississippian, and Pennsylvanian carbonate and clastic sedimentary rocks that have been mildly deformed by a series of faults and folds. Quaternary surficial units are present as alluvial deposits along major streams, including a series of terrace deposits from the Buffalo River, as well as colluvium and landslide deposits mantling bedrock on hillslopes.
\n\n
This report provides a geologic map database of the map area that improves understanding of the regional geologic framework and its influence on the regional groundwater flow system. Furthermore, additional edits were made to the Ponca and Jasper quadrangles in the following ways: new control points on important contacts were obtained using modern GPS; recent higher resolution elevation data allowed further control on placement of contacts; some new contacts were added, in particular the contact separating the upper and lower Everton Formation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3314","usgsCitation":"Hudson, M., and Turner, K.J., 2014, Geologic map of the west-central Buffalo National River region, northern Arkansas: U.S. Geological Survey Scientific Investigations Map 3314, 2 Plates: 58.0 x 51.5 inches and 58.0 x 29.0 inches; Downloads Directory, https://doi.org/10.3133/sim3314.","productDescription":"2 Plates: 58.0 x 51.5 inches and 58.0 x 29.0 inches; Downloads Directory","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-045630","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":295923,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim3314.jpg"},{"id":295891,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3314/"},{"id":295920,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3314/pdf/SIM3314_west_sheet1.pdf","text":"Map Sheet 1 (West)","size":"71.1 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":295921,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3314/pdf/SIM3314_east_sheet2.pdf","text":"Map Sheet 2 (East)","size":"46.5","linkFileType":{"id":1,"text":"pdf"}},{"id":295922,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sim/3314/downloads/","text":"Downloads Directory"}],"scale":"24000","projection":"Universal Transverse Mercator projection","datum":"North American Datum of 1927","country":"United States","state":"Arkansas","otherGeospatial":"Buffalo National River","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"545c8d9ee4b0ba8303f7037e","contributors":{"authors":[{"text":"Hudson, Mark R. 0000-0003-0338-6079 mhudson@usgs.gov","orcid":"https://orcid.org/0000-0003-0338-6079","contributorId":1236,"corporation":false,"usgs":true,"family":"Hudson","given":"Mark R.","email":"mhudson@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":524264,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Turner, Kenzie J. 0000-0002-4940-3981 kturner@usgs.gov","orcid":"https://orcid.org/0000-0002-4940-3981","contributorId":496,"corporation":false,"usgs":true,"family":"Turner","given":"Kenzie","email":"kturner@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":524265,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70131570,"text":"ofr20141225 - 2014 - Ecological implications of Laurel Wilt infestation on Everglades Tree Islands, southern Florida","interactions":[],"lastModifiedDate":"2016-04-19T11:34:56","indexId":"ofr20141225","displayToPublicDate":"2014-11-06T09:30:00","publicationYear":"2014","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":"2014-1225","title":"Ecological implications of Laurel Wilt infestation on Everglades Tree Islands, southern Florida","docAbstract":"There is a long history of introduced pests attacking native forest trees in the United States (Liebhold and others, 1995; Aukema and others, 2010). Well-known examples include chestnut blight that decimated the American chestnut (Castanea dentata), an extremely important tree in the eastern United States, both as a food source for wildlife and humans and for the wood; Dutch elm disease that attacks native elms (Ulmus spp.), including those commonly planted as shade trees along city streets; and the balsam wooly adelgid (Adelges piceae), an insect that is destroying Fraser firs (Abies fraseri) in higher elevations of Great Smoky Mountains National Park. Laurel wilt, a fungal disease transmitted by the redbay ambrosia beetle (Xyleborus glabratus), is a 21st-century example of an introduced forest pest that attacks native tree species in the laurel family (Lauraceae) (Mayfield, 2007; Hulcr and Dunn, 2011).
The introduction of laurel wilt disease has been traced to the arrival of an Asian ambrosia beetle (Xyleborus glabratus) at Port Wentworth, Georgia, near Savannah, in 2002, apparently accidently introduced in wooden shipping material (Mayfield, 2007). Within the next 2 years, it was determined that the non-native wood-boring insect was the vector of an undescribed species of fungus, responsible for killing large numbers of red bay (Persea borbonia) trees in the surrounding area. Dispersing female redbay ambrosia beetles drill into live trees and create tunnels in the wood. They carry with them fungal spores in specialized organs called mycangia at the base of each mandible and sow the spores in the tunnels they excavate. The fungus, since named Raffaelea lauricola (Harrington and others, 2008), is the food source for adults and larvae. The introduction of Raffaelea lauricola causes the host plant to react in such a way as to block the vascular tissue, resulting in loss of water conduction, wilt, and death (Kendra and others, 2013).
Although first seen in red bay, laurel wilt disease also kills other native trees that are members of the laurel family, including swamp bay (Persea palustris), silk bay (Persea borbonia var. humilis), and sassafras (Sassafras albidum), as well as the economically important cultivated avocado (Persea americana) (Fraedrich and others, 2008). This paper is concerned primarily with swamp bay, an important component of Everglades tree islands.
The spread of the redbay ambrosia beetle and its fungal symbiont has been very rapid, exceeding model predictions (Koch and Smith, 2008); by 2011, laurel wilt disease was found from the southern coastal plain of North Carolina to southern peninsular Florida. The first redbay ambrosia beetle was trapped in Miami-Dade County in March 2010, and laurel wilt disease was discovered in swamp bays in February 2011 and in commercial avocado groves about a year later (Kendra and others, 2013). By 2013, laurel wilt disease was seen in swamp bays throughout the southern Everglades in Everglades National Park, Big Cypress National Preserve, and Water Conservation Areas (WCAs) 3A and 3B (Rodgers and others, 2014).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141225","usgsCitation":"Snyder, J.R., 2014, Ecological implications of Laurel Wilt infestation on Everglades Tree Islands, southern Florida: U.S. Geological Survey Open-File Report 2014-1225, iv, 18 p., https://doi.org/10.3133/ofr20141225.","productDescription":"iv, 18 p.","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-056042","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":295912,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141225.JPG"},{"id":295892,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2014/1225/"},{"id":295911,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1225/pdf/ofr2014-1225.pdf"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades National 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Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":524266,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70121112,"text":"fs20143078 - 2014 - The rare-earth elements: Vital to modern technologies and lifestyles","interactions":[],"lastModifiedDate":"2017-04-21T13:53:18","indexId":"fs20143078","displayToPublicDate":"2014-11-06T09:15:00","publicationYear":"2014","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-3078","title":"The rare-earth elements: Vital to modern technologies and lifestyles","docAbstract":"Until recently, the rare-earth elements (REEs) were familiar to a relatively small number of people, such as chemists, geologists, specialized materials scientists, and engineers. In the 21st century, the REEs have gained visibility through many media outlets because of (1) the public has recognized the critical, specialized properties that REEs contribute to modern technology, as well as (2) China's dominance in production and supply of the REEs and (3) international dependence on China for the majority of the world's REE supply.
Since the late 1990s, China has provided 85–95 percent of the world’s REEs. In 2010, China announced their intention to reduce REE exports. During this timeframe, REE use increased substantially. REEs are used as components in high technology devices, including smart phones, digital cameras, computer hard disks, fluorescent and light-emitting-diode (LED) lights, flat screen televisions, computer monitors, and electronic displays. Large quantities of some REEs are used in clean energy and defense technologies. Because of the many important uses of REEs, nations dependent on new technologies, such as Japan, the United States, and members of the European Union, reacted with great concern to China’s intent to reduce its REE exports. Consequently, exploration activities intent on discovering economic deposits of REEs and bringing them into production have increased.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20143078","collaboration":"USGS Mineral Resources Program","usgsCitation":"Van Gosen, B.S., Verplanck, P.L., Long, K.R., Gambogi, J., and Seal, R., 2014, The rare-earth elements: Vital to modern technologies and lifestyles: U.S. Geological Survey Fact Sheet 2014-3078, 4 p., https://doi.org/10.3133/fs20143078.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-051526","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":295910,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20143078.jpg"},{"id":295909,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2014/3078/pdf/fs2014-3078.pdf"},{"id":295908,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2014/3078/"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"545c8da2e4b0ba8303f703b7","contributors":{"authors":[{"text":"Van Gosen, Bradley S. 0000-0003-4214-3811 bvangose@usgs.gov","orcid":"https://orcid.org/0000-0003-4214-3811","contributorId":1174,"corporation":false,"usgs":true,"family":"Van Gosen","given":"Bradley","email":"bvangose@usgs.gov","middleInitial":"S.","affiliations":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true},{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":519244,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Verplanck, Philip L. 0000-0002-3653-6419 plv@usgs.gov","orcid":"https://orcid.org/0000-0002-3653-6419","contributorId":728,"corporation":false,"usgs":true,"family":"Verplanck","given":"Philip","email":"plv@usgs.gov","middleInitial":"L.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":524284,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Long, Keith R. 0000-0002-6457-2820 klong@usgs.gov","orcid":"https://orcid.org/0000-0002-6457-2820","contributorId":2279,"corporation":false,"usgs":true,"family":"Long","given":"Keith","email":"klong@usgs.gov","middleInitial":"R.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":524285,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gambogi, Joseph 0000-0002-5719-2280 jgambogi@usgs.gov","orcid":"https://orcid.org/0000-0002-5719-2280","contributorId":4424,"corporation":false,"usgs":true,"family":"Gambogi","given":"Joseph","email":"jgambogi@usgs.gov","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":false,"id":524286,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Seal, Robert R. II 0000-0003-0901-2529 rseal@usgs.gov","orcid":"https://orcid.org/0000-0003-0901-2529","contributorId":397,"corporation":false,"usgs":true,"family":"Seal","given":"Robert R.","suffix":"II","email":"rseal@usgs.gov","affiliations":[],"preferred":false,"id":524287,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70156257,"text":"70156257 - 2014 - Using ecological indicators and a decision support system for integrated ecological assessment at two national park units in the Mid-Atlantic region, U.S.A.","interactions":[],"lastModifiedDate":"2022-11-10T16:32:18.700862","indexId":"70156257","displayToPublicDate":"2014-11-05T00:00:00","publicationYear":"2014","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1547,"text":"Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Using ecological indicators and a decision support system for integrated ecological assessment at two national park units in the Mid-Atlantic region, U.S.A.","docAbstract":"We implemented an integrated ecological assessment using a GIS-based decision support system model for Upper Delaware Scenic and Recreational River (UPDE) and Delaware Water Gap National Recreation Area (DEWA)—national park units with the mid-Atlantic region of the United States. Our assessment examined a variety of aquatic and terrestrial indicators of ecosystem components that reflect the parks’ conservation purpose and reference condition. Our assessment compared these indicators to ecological thresholds to determine the condition of park watersheds. Selected indicators included chemical and physical measures of water quality, biologic indicators of water quality, and landscape condition measures. For the chemical and physical measures of water quality, we used a water quality index and each of its nine components to assess the condition of water quality in each watershed. For biologic measures of water quality, we used the Ephemeroptera, Plecoptera, Trichoptera aquatic macroinvertebrate index and, secondarily, the Hilsenhoff aquatic macroinvertebrate index. Finally, for the landscape condition measures of our model, we used percent forest and percent impervious surface. Based on our overall assessment, UPDE and DEWA watersheds had an ecological assessment score of 0.433 on a −1 to 1 fuzzy logic scale. This score indicates that, in general, the natural resource condition within watersheds at these parks is healthy or ecologically unimpaired; however, we had only partial data for many of our indicators. Our model is iterative and new data may be incorporated as they become available. These natural parks are located within a rapidly urbanizing landscape—we recommend that natural resource managers remain vigilant to surrounding land uses that may adversely affect natural resources within the parks.
","language":"English","publisher":"Springer","doi":"10.1007/s00267-014-0391-y","usgsCitation":"Mahan, C.G., Young, J.A., Miller, B., and Saunders, M.C., 2014, Using ecological indicators and a decision support system for integrated ecological assessment at two national park units in the Mid-Atlantic region, U.S.A.: Environmental Management, v. 55, no. 2, p. 508-522, https://doi.org/10.1007/s00267-014-0391-y.","productDescription":"14 p.","startPage":"508","endPage":"522","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-061210","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":472651,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s00267-014-0391-y","text":"Publisher Index Page"},{"id":306857,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Jersey, New York, 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Bruce","contributorId":146583,"corporation":false,"usgs":false,"family":"Miller","given":"Bruce","email":"","affiliations":[{"id":6945,"text":"private 3721 2nd Avenue, Salt Lake City","active":true,"usgs":false}],"preferred":false,"id":568353,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Saunders, Michael C.","contributorId":146584,"corporation":false,"usgs":false,"family":"Saunders","given":"Michael","email":"","middleInitial":"C.","affiliations":[{"id":16724,"text":"Penn Sate University","active":true,"usgs":false}],"preferred":false,"id":568354,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70074082,"text":"sir20105090P - 2014 - Porphyry copper assessment of East and Southeast Asia: Philippines, Taiwan (Republic of China), Republic of Korea (South Korea), and Japan","interactions":[{"subject":{"id":70074082,"text":"sir20105090P - 2014 - Porphyry copper assessment of East and Southeast Asia: Philippines, Taiwan (Republic of China), Republic of Korea (South Korea), and Japan","indexId":"sir20105090P","publicationYear":"2014","noYear":false,"chapter":"P","title":"Porphyry copper assessment of East and Southeast Asia: Philippines, Taiwan (Republic of China), Republic of Korea (South Korea), and Japan"},"predicate":"IS_PART_OF","object":{"id":70040436,"text":"sir20105090 - 2010 - Global mineral resource assessment","indexId":"sir20105090","publicationYear":"2010","noYear":false,"title":"Global mineral resource assessment"},"id":1}],"isPartOf":{"id":70040436,"text":"sir20105090 - 2010 - Global mineral resource assessment","indexId":"sir20105090","publicationYear":"2010","noYear":false,"title":"Global mineral resource assessment"},"lastModifiedDate":"2020-07-01T19:22:00.184549","indexId":"sir20105090P","displayToPublicDate":"2014-11-04T14:30:00","publicationYear":"2014","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":"2010-5090","chapter":"P","title":"Porphyry copper assessment of East and Southeast Asia: Philippines, Taiwan (Republic of China), Republic of Korea (South Korea), and Japan","docAbstract":"The U.S. Geological Survey collaborated with member countries of the Coordinating Committee for Geoscience Programmes in East and Southeast Asia (CCOP) on an assessment of the porphyry copper resources of East and Southeast Asia as part of a global mineral resource assessment. The assessment covers the Philippines in Southeast Asia, and the Republic of Korea (South Korea), Taiwan (Province of China), and Japan in East Asia. The Philippines host world class porphyry copper deposits, such as the Tampakan and Atlas deposits. No porphyry copper deposits have been discovered in the Republic of Korea (South Korea), Taiwan (Province of China), or Japan.
\nThirteen geographic areas were delineated as tracts that are permissive for porphyry copper deposits in the assessed area. Individual tracts range from about 3,000 to 100,000 square kilometers in area. Permissive tracts are delineated on the basis of mapped distributions of igneous rocks of specific age ranges that define subduction-related magmatic arcs or magmatic belts that might contain porphyry copper deposits. Most of these magmatic arcs are subduction related, although some porphyry deposits and prospects are present in back-arc or poorly understood tectonic settings. Maps at various scales were used in the compilation; however, the final tract boundaries are intended for use at a scale of 1:1,000,000.
\nNumbers of undiscovered deposits were estimated at different levels of confidence for 10 permissive tracts in the Philippines including one area that extends to eastern Taiwan (Republic of China); permissive tracts in South Korea and Japan are discussed qualitatively. Estimates of numbers of undiscovered deposits were combined with grade and tonnage models using Monte Carlo simulation to estimate amounts of undiscovered resources. Grades and tonnages of known porphyry copper deposits in the study area were compared with global grade and tonnage models to determine the appropriate model for simulation of undiscovered resources. Most of the known deposits are best described as copper-gold subtypes of porphyry copper deposits. For some permissive tracts, a general porphyry copper-gold-molybdenum model was used.
\nThirty-eight porphyry copper deposits are known in the Philippines; the mean number of undiscovered deposits was estimated to be 28. Mean (arithmetic) resources that could be associated with the undiscovered deposits are 90 million metric tons of copper and 5,800 metric tons of gold, as well as byproduct molybdenum and silver. Additional resources that could be discovered in extensions to known deposits were not evaluated. Assessment results, presented in tables and graphs, indicate expected amounts of total contained metal and mineralized rock in undiscovered deposits at different quantile levels, as well as the arithmetic mean for each tract.
\nThe Philippines have a long history of porphyry exploration cycles and mine development, interrupted at times by political and social unrest, environmental concerns, and natural disasters. Changes in mining laws within the region and the recent high price of gold on the world market have prompted renewed interest in porphyry copper deposits in the region. South Korea and Japan have been thoroughly explored for many types of mineral deposits. Available data suggest that the permissive rocks in South Korea typically are too deeply eroded to preserve porphyry copper deposits. Porphyry copper systems may be present in Japan, but are likely to lie at depths greater than the 1 kilometer from the surface protocol adopted for this study.
\nDescriptions of the geologic basis for delineating each tract, the data used, the geologic criteria and rationale for the assessment, and results of the assessment are included in appendixes along with the description of a geographic information system (GIS) that includes tract boundaries, known porphyry copper deposits and significant prospects, and assessment results.
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As part of the American Recovery and Reinvestment Act (ARRA) of 2009, the U.S. Geological Survey was awarded funding for high-precision airborne lidar (light detection and ranging) data collection at several volcanoes in the Cascade Range. Data collection was arranged by the Oregon Lidar Consortium, administered by the Oregon Department of Geology and Mineral Industries (DOGAMI). The Oregon Lidar Consortium contracted with Watershed Sciences, Inc., to collect 1,220 square km of high-precision airborne lidar data. These data provide a digital map of the ground surface beneath forest cover with horizontal resolution of 1 m (average of 1.82 ground laser returns per square meter) and estimated vertical accuracy of ±4 centimeters (1 sigma), and horizontal accuracies of ±1.5 centimeters. These data will contribute to monitoring and description of natural hazards, the study of regional geology and volcanic landforms, and analysis of landscape modification during and after the next volcanic eruption at Mount Shasta.
Survey Bounding Coordinates:
Coastal wetlands play a unique role in extreme hurricane events. The impact of wetlands on storm surge depends on multiple factors including vegetation, landscape, and storm characteristics. The Delft3D model, in which vegetation effects on flow and turbulence are explicitly incorporated, was applied to the semi-enclosed Breton Sound (BS) estuary in coastal Louisiana to investigate the wetland impact. Guided by extensive field observations, a series of numerical experiments were conducted based on variations of actual vegetation properties and storm parameters from Hurricane Isaac in 2012. Both the vegetation-induced maximum surge reduction (MSR) and maximum surge reduction rate (MSRR) increased with stem height and stem density, and were more sensitive to stem height. The MSR and MSRR decreased significantly with increasing wind intensity. The MSRR was the highest with a fast-moving weak storm. It was also found that the MSRR varied proportionally to the expression involving the maximum bulk velocity and surge over the area of interest, and was more dependent on the maximum bulk surge. Both MSR and MSRR appeared to increase when the area of interest decreased from the whole BS estuary to the upper estuary. Within the range of the numerical experiments, the maximum simulated MSR and MSRR over the upper estuary were 0.7 m and 37%, respectively.
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