Geothermal reservoirs derive their capacity for fluid and heat transport in large part from faults and fractures. Micro-seismicity generated on such faults and fractures can be used to map larger fault structures as well as secondary fractures that add access to hot rock, fluid storage and recharge capacity necessary to have a sustainable geothermal resource. Additionally, inversion of seismic velocities from micro-seismicity permits imaging of regions subject to the combined effects of fracture density, fluid pressure and steam content, among other factors. We relocate 14 years of seismicity (1996-2009) in the Coso geothermal field using differential travel times and simultaneously invert for seismic velocities to improve our knowledge of the subsurface geologic and hydrologic structure. We utilize over 60,000 micro-seismic events using waveform cross-correlation to augment to expansive catalog of P- and S-wave differential travel times recorded at Coso. We further carry out rigorous uncertainty estimation and find that our results are precise to within 10s of meters of relative location error. We find that relocated micro-seismicity outlines prominent, through-going faults in the reservoir in some cases. We also find that a significant portion of seismicity remains diffuse and does not cluster into more sharply defined major structures. The seismic velocity structure reveals heterogeneous distributions of compressional (Vp) and shear (Vs) wave speed, with Vp generally lower in the main field when compared to the east flank and Vs varying more significantly in the shallow portions of the reservoir. The Vp/Vs ratio appears to outline the two main compartments of the reservoir at depths of -0.5 to 1.5 km (relative to sea-level), with a ridge of relatively high Vp/Vs separating the main field from the east flank. In the deeper portion of the reservoir this ridge is less prominent. Our results indicate that high-precision relocations of micro-seismicity can provide useful insight into: 1) prominent structural features, faults and fractures that contribute to the flow of fluid and heat in the reservoir; 2) diffuse seismicity throughout the reservoir representing fractures that likely contribute to the overall permeability, storage and heat exchange capacity of the reservoir, but which are not confined to prominent faults; and 3) seismic velocities that outline the major hydrologic compartments within the Coso geothermal field.
","largerWorkType":{"id":24,"text":"Conference Paper"},"largerWorkTitle":"Proceedings, Thirty-Seventh Workshop on Geothermal Reservoir Engineering","conferenceTitle":"Stanford Geothermal Workshop","conferenceDate":"January 30-February 1, 2012","conferenceLocation":"Stanford, California","language":"English","publisher":"Stanford Geothermal Program","usgsCitation":"Kaven, J.O., Hickman, S.H., and Davatzes, N.C., 2012, Using micro-seismicity and seismic velocities to map subsurface geologic and hydrologic structure within the Coso geothermal field, California, in Proceedings, Thirty-Seventh Workshop on Geothermal Reservoir Engineering, Stanford, California, January 30-February 1, 2012, 8 p.","productDescription":"8 p.","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":308626,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Coso geothermal field","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.89840698242188,\n 35.89516901521329\n ],\n [\n -117.89840698242188,\n 35.943547570924665\n ],\n [\n -117.83111572265625,\n 35.943547570924665\n ],\n [\n -117.83111572265625,\n 35.89516901521329\n ],\n [\n -117.89840698242188,\n 35.89516901521329\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56067042e4b058f706e51976","contributors":{"authors":[{"text":"Kaven, Joern Ole","contributorId":148002,"corporation":false,"usgs":false,"family":"Kaven","given":"Joern","email":"","middleInitial":"Ole","affiliations":[],"preferred":false,"id":573582,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hickman, Stephen H. 0000-0003-2075-9615 hickman@usgs.gov","orcid":"https://orcid.org/0000-0003-2075-9615","contributorId":2705,"corporation":false,"usgs":true,"family":"Hickman","given":"Stephen","email":"hickman@usgs.gov","middleInitial":"H.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":573583,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Davatzes, Nicholas C.","contributorId":138855,"corporation":false,"usgs":false,"family":"Davatzes","given":"Nicholas","email":"","middleInitial":"C.","affiliations":[{"id":12547,"text":"Temple University","active":true,"usgs":false}],"preferred":false,"id":573584,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70178329,"text":"70178329 - 2012 - In situ quantification of spatial and temporal variability of hyporheic exchange in static and mobile gravel-bed rivers","interactions":[],"lastModifiedDate":"2020-11-16T21:12:06.444802","indexId":"70178329","displayToPublicDate":"2012-02-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"displayTitle":"In situ quantification of spatial and temporal variability of hyporheic exchange in static and mobile gravel-bed rivers","title":"In situ quantification of spatial and temporal variability of hyporheic exchange in static and mobile gravel-bed rivers","docAbstract":"Seepage meters modified for use in flowing water were used to directly measure rates of exchange between surface and subsurface water in a gravel‐ and cobble bed river in western Pennsylvania, USA (Allegheny River, Qmean = 190 m3/s) and a sand‐ and gravel‐bed river in Colorado, USA (South Platte River, Qmean = 9·7 m3/s). Study reaches at the Allegheny River were located downstream from a dam. The bed was stable with moss, algae, and river grass present in many locations. Median seepage was + 0·28 m/d and seepage was highly variable among measurement locations. Upward and downward seepage greatly exceeded the median seepage rate, ranging from + 2·26 (upward) to − 3·76 (downward) m/d. At the South Platte River site, substantial local‐scale bed topography as well as mobile bedforms resulted in spatial and temporal variability in seepage greatly in exceedence of the median groundwater discharge rate of 0·24 m/d. Both upward and downward seepage were recorded along every transect across the river with rates ranging from + 2·37 to − 3·40 m/d. Despite a stable bed, which commonly facilitates clogging by fine‐grained or organic sediments, seepage rates at the Allegheny River were not reduced relative to those at the South Platte River. Seepage rate and direction depended primarily on measurement position relative to local‐ and meso‐scale bed topography at both rivers. Hydraulic gradients were small at nearly all seepage‐measurement locations and commonly were not a good indicator of seepage rate or direction. Therefore, measuring hydraulic gradient and hydraulic conductivity at in‐stream piezometers may be misleading if used to determine seepage flux across the sediment‐water interface. Such a method assumes that flow between the well screen and sediment‐water interface is vertical, which appears to be a poor assumption in coarse‐grained hyporheic settings.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.8154","usgsCitation":"Rosenberry, D.O., Klos, P.Z., and Neal, A., 2012, In situ quantification of spatial and temporal variability of hyporheic exchange in static and mobile gravel-bed rivers: Hydrological Processes, v. 26, no. 4, p. 604-612, https://doi.org/10.1002/hyp.8154.","productDescription":"9 p.","startPage":"604","endPage":"612","ipdsId":"IP-025940","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":498897,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/hyp.8154","text":"Publisher Index Page"},{"id":330976,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","otherGeospatial":"Allegheny River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.2828369140625,\n 41.84910468610387\n ],\n [\n -79.43389892578125,\n 41.71187978193456\n ],\n [\n -79.36248779296874,\n 41.64623592868676\n ],\n [\n -79.20318603515625,\n 41.81021999190292\n ],\n [\n -79.2828369140625,\n 41.84910468610387\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"26","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2011-05-18","publicationStatus":"PW","scienceBaseUri":"582adb46e4b0c253bdfff0ba","contributors":{"authors":[{"text":"Rosenberry, Donald O. 0000-0003-0681-5641 rosenber@usgs.gov","orcid":"https://orcid.org/0000-0003-0681-5641","contributorId":1312,"corporation":false,"usgs":true,"family":"Rosenberry","given":"Donald","email":"rosenber@usgs.gov","middleInitial":"O.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":653607,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Klos, P. Zion","contributorId":176826,"corporation":false,"usgs":false,"family":"Klos","given":"P.","email":"","middleInitial":"Zion","affiliations":[],"preferred":false,"id":653609,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Neal, Andrew","contributorId":176825,"corporation":false,"usgs":false,"family":"Neal","given":"Andrew","email":"","affiliations":[],"preferred":false,"id":653608,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70178327,"text":"70178327 - 2012 - Influence of a thin veneer of low-hydraulic-conductivity sediment on modelled exchange between river water and groundwater in response to induced infiltration","interactions":[],"lastModifiedDate":"2021-04-06T12:44:43.709149","indexId":"70178327","displayToPublicDate":"2012-02-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Influence of a thin veneer of low-hydraulic-conductivity sediment on modelled exchange between river water and groundwater in response to induced infiltration","docAbstract":"A thin layer of fine‐grained sediment commonly is deposited at the sediment–water interface of streams and rivers during low‐flow conditions, and may hinder exchange at the sediment–water interface similar to that observed at many riverbank‐filtration (RBF) sites. Results from a numerical groundwater‐flow model indicate that a low‐permeability veneer reduces the contribution of river water to a pumping well in a riparian aquifer to various degrees, depending on simulated hydraulic gradients, hydrogeological properties, and pumping conditions. Seepage of river water is reduced by 5–10% when a 2‐cm thick, low‐permeability veneer is present on the bed surface. Increasing thickness of the low‐permeability layer to 0·1 m has little effect on distribution of seepage or percentage contribution from the river to the pumping well. A three‐orders‐of‐magnitude reduction in hydraulic conductivity of the veneer is required to reduce seepage from the river to the extent typically associated with clogging at RBF sites. This degree of reduction is much larger than field‐measured values that were on the order of a factor of 20–25. Over 90% of seepage occurs within 12 m of the shoreline closest to the pumping well for most simulations. Virtually no seepage occurs through the thalweg near the shoreline opposite the pumping well, although no low‐permeability sediment was simulated for the thalweg. These results are relevant to natural settings that favour formation of a substantial, low‐permeability sediment veneer, as well as central‐pivot irrigation systems, and municipal water supplies where river seepage is induced via pumping wells.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.8153","usgsCitation":"Rosenberry, D.O., and Healy, R.W., 2012, Influence of a thin veneer of low-hydraulic-conductivity sediment on modelled exchange between river water and groundwater in response to induced infiltration: Hydrological Processes, v. 26, no. 4, p. 544-557, https://doi.org/10.1002/hyp.8153.","productDescription":"14 p.","startPage":"544","endPage":"557","ipdsId":"IP-015284","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":384886,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Platte River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.57861328125,\n 39.41922073655956\n ],\n [\n -102.041015625,\n 39.41922073655956\n ],\n [\n -102.041015625,\n 41.104190944576466\n ],\n [\n -105.57861328125,\n 41.104190944576466\n ],\n [\n -105.57861328125,\n 39.41922073655956\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"26","issue":"4","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2011-05-25","publicationStatus":"PW","scienceBaseUri":"582c2ce6e4b0c253be072c0e","contributors":{"authors":[{"text":"Rosenberry, Donald O. 0000-0003-0681-5641 rosenber@usgs.gov","orcid":"https://orcid.org/0000-0003-0681-5641","contributorId":1312,"corporation":false,"usgs":true,"family":"Rosenberry","given":"Donald","email":"rosenber@usgs.gov","middleInitial":"O.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":653601,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Healy, Richard W. 0000-0002-0224-1858 rwhealy@usgs.gov","orcid":"https://orcid.org/0000-0002-0224-1858","contributorId":658,"corporation":false,"usgs":true,"family":"Healy","given":"Richard","email":"rwhealy@usgs.gov","middleInitial":"W.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":653602,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70190451,"text":"70190451 - 2012 - Miocene magmatism in the Bodie Hills volcanic field, California and Nevada: A long-lived eruptive center in the southern segment of the ancestral Cascades arc","interactions":[],"lastModifiedDate":"2017-08-31T16:23:00","indexId":"70190451","displayToPublicDate":"2012-02-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Miocene magmatism in the Bodie Hills volcanic field, California and Nevada: A long-lived eruptive center in the southern segment of the ancestral Cascades arc","docAbstract":"The Middle to Late Miocene Bodie Hills volcanic field is a >700 km2, long-lived (∼9 Ma) but episodic eruptive center in the southern segment of the ancestral Cascades arc north of Mono Lake (California, U.S.). It consists of ∼20 major eruptive units, including 4 trachyandesite stratovolcanoes emplaced along the margins of the field, and numerous, more centrally located silicic trachyandesite to rhyolite flow dome complexes. Bodie Hills volcanism was episodic with two peak periods of eruptive activity: an early period ca. 14.7–12.9 Ma that mostly formed trachyandesite stratovolcanoes and a later period between ca. 9.2 and 8.0 Ma dominated by large trachyandesite-dacite dome fields. A final period of small silicic dome emplacement occurred ca. 6 Ma. Aeromagnetic and gravity data suggest that many of the Miocene volcanoes have shallow plutonic roots that extend to depths ≥1–2 km below the surface, and much of the Bodie Hills may be underlain by low-density plutons presumably related to Miocene volcanism.
Compositions of Bodie Hills volcanic rocks vary from ∼50 to 78 wt% SiO2, although rocks with <55 wt% SiO2 are rare. They form a high-K calc-alkaline series with pronounced negative Ti-P-Nb-Ta anomalies and high Ba/Nb, Ba/Ta, and La/Nb typical of subduction-related continental margin arcs. Most Bodie Hills rocks are porphyritic, commonly containing 15–35 vol% phenocrysts of plagioclase, pyroxene, and hornblende ± biotite. The oldest eruptive units have the most mafic compositions, but volcanic rocks oscillated between mafic and intermediate to felsic compositions through time. Following a 2 Ma hiatus in volcanism, postsubduction rocks of the ca. 3.6–0.1 Ma, bimodal, high-K Aurora volcanic field erupted unconformably onto rocks of the Miocene Bodie Hills volcanic field.
At the latitude of the Bodie Hills, subduction of the Farallon plate is inferred to have ended ca. 10 Ma, evolving to a transform plate margin. However, volcanism in the region continued until 8 Ma without an apparent change in rock composition or style of eruption. Equidimensional, polygenetic volcanoes and the absence of dike swarms suggest a low differential horizontal stress regime throughout the lifespan of the Bodie Hills volcanic field. However, kinematic data for veins and faults in mining districts suggest a change in the stress field from transtensional to extensional approximately coincident with the inferred cessation of subduction.
Numerous hydrothermal systems were operative in the Bodie Hills during the Miocene. Several large systems caused alteration of volcaniclastic rocks in areas as large as 30 km2, but these altered rocks are mostly devoid of economic mineral concentrations. More structurally focused hydrothermal systems formed large epithermal Au-Ag vein deposits in the Bodie and Aurora mining districts. Economically important hydrothermal systems are temporally related to intermediate to silicic composition domes.
Rock types, major and trace element compositions, petrographic characteristics, and volcanic features of the Bodie Hills volcanic field are similar to those of other large Miocene volcanic fields in the southern segment of the ancestral Cascade arc. Relative to other parts of the ancestral arc, especially north of Lake Tahoe in northeastern California, the scarcity of mafic rocks, relatively K-rich calc-alkaline compositions, and abundance of composite dome fields in the Bodie Hills may reflect thicker crust beneath the southern ancestral arc segment. Thicker crust may have inhibited direct ascent and eruption of mafic, mantle-derived magma, instead stalling its ascent in the lower or middle crust, thereby promoting differentiation to silicic compositions and development of porphyritic textures characteristic of the southern ancestral arc segment.
","language":"English","publisher":"The Geological Society of America","doi":"10.1130/GES00674.1","usgsCitation":"John, D.A., du Bray, E.A., Blakely, R.J., Fleck, R.J., Vikre, P.G., Box, S.E., and Moring, B.C., 2012, Miocene magmatism in the Bodie Hills volcanic field, California and Nevada: A long-lived eruptive center in the southern segment of the ancestral Cascades arc: Geosphere, v. 8, no. 1, p. 44-97, https://doi.org/10.1130/GES00674.1.","productDescription":"54 p.","startPage":"44","endPage":"97","ipdsId":"IP-029336","costCenters":[{"id":662,"text":"Western Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":474686,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges00674.1","text":"Publisher Index Page"},{"id":345399,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Nevada","otherGeospatial":"Bodie Hills volcanic field","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -125.24414062499999,\n 36.35052700542763\n ],\n [\n -114.43359375,\n 36.35052700542763\n ],\n [\n -114.43359375,\n 47.42808726171425\n ],\n [\n -125.24414062499999,\n 47.42808726171425\n ],\n [\n -125.24414062499999,\n 36.35052700542763\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59a92040e4b07e1a023ccda5","contributors":{"authors":[{"text":"John, David A. 0000-0001-7977-9106 djohn@usgs.gov","orcid":"https://orcid.org/0000-0001-7977-9106","contributorId":1748,"corporation":false,"usgs":true,"family":"John","given":"David","email":"djohn@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":709226,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"du Bray, Edward A. 0000-0002-4383-8394 edubray@usgs.gov","orcid":"https://orcid.org/0000-0002-4383-8394","contributorId":755,"corporation":false,"usgs":true,"family":"du Bray","given":"Edward","email":"edubray@usgs.gov","middleInitial":"A.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":709227,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Blakely, Richard J. 0000-0003-1701-5236 blakely@usgs.gov","orcid":"https://orcid.org/0000-0003-1701-5236","contributorId":1540,"corporation":false,"usgs":true,"family":"Blakely","given":"Richard","email":"blakely@usgs.gov","middleInitial":"J.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":662,"text":"Western Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":709225,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Fleck, Robert J. 0000-0002-3149-8249 fleck@usgs.gov","orcid":"https://orcid.org/0000-0002-3149-8249","contributorId":1048,"corporation":false,"usgs":true,"family":"Fleck","given":"Robert","email":"fleck@usgs.gov","middleInitial":"J.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":709372,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Vikre, Peter G. 0000-0001-7895-5972 pvikre@usgs.gov","orcid":"https://orcid.org/0000-0001-7895-5972","contributorId":139033,"corporation":false,"usgs":true,"family":"Vikre","given":"Peter","email":"pvikre@usgs.gov","middleInitial":"G.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":662,"text":"Western Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":709229,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Box, Stephen E. 0000-0002-5268-8375 sbox@usgs.gov","orcid":"https://orcid.org/0000-0002-5268-8375","contributorId":1843,"corporation":false,"usgs":true,"family":"Box","given":"Stephen","email":"sbox@usgs.gov","middleInitial":"E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":709230,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Moring, Barry C. 0000-0001-6797-9258 moring@usgs.gov","orcid":"https://orcid.org/0000-0001-6797-9258","contributorId":2794,"corporation":false,"usgs":true,"family":"Moring","given":"Barry","email":"moring@usgs.gov","middleInitial":"C.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":709228,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70193188,"text":"70193188 - 2012 - Using assemblage data in ecological indicators: A comparison and evaluation of commonly available statistical tools","interactions":[],"lastModifiedDate":"2017-12-01T09:59:57","indexId":"70193188","displayToPublicDate":"2012-02-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1456,"text":"Ecological Indicators","active":true,"publicationSubtype":{"id":10}},"title":"Using assemblage data in ecological indicators: A comparison and evaluation of commonly available statistical tools","docAbstract":"Ecological indicators are science-based tools used to assess how human activities have impacted environmental resources. For monitoring and environmental assessment, existing species assemblage data can be used to make these comparisons through time or across sites. An impediment to using assemblage data, however, is that these data are complex and need to be simplified in an ecologically meaningful way. Because multivariate statistics are mathematical relationships, statistical groupings may not make ecological sense and will not have utility as indicators. Our goal was to define a process to select defensible and ecologically interpretable statistical simplifications of assemblage data in which researchers and managers can have confidence. For this, we chose a suite of statistical methods, compared the groupings that resulted from these analyses, identified convergence among groupings, then we interpreted the groupings using species and ecological guilds. When we tested this approach using a statewide stream fish dataset, not all statistical methods worked equally well. For our dataset, logistic regression (Log), detrended correspondence analysis (DCA), cluster analysis (CL), and non-metric multidimensional scaling (NMDS) provided consistent, simplified output. Specifically, the Log, DCA, CL-1, and NMDS-1 groupings were ≥60% similar to each other, overlapped with the fluvial-specialist ecological guild, and contained a common subset of species. Groupings based on number of species (e.g., Log, DCA, CL and NMDS) outperformed groupings based on abundance [e.g., principal components analysis (PCA) and Poisson regression]. Although the specific methods that worked on our test dataset have generality, here we are advocating a process (e.g., identifying convergent groupings with redundant species composition that are ecologically interpretable) rather than the automatic use of any single statistical tool. We summarize this process in step-by-step guidance for the future use of these commonly available ecological and statistical methods in preparing assemblage data for use in ecological indicators.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecolind.2011.06.009","usgsCitation":"Smith, J.M., and Mather, M.E., 2012, Using assemblage data in ecological indicators: A comparison and evaluation of commonly available statistical tools: Ecological Indicators, v. 13, no. 1, p. 253-262, https://doi.org/10.1016/j.ecolind.2011.06.009.","productDescription":"10 p.","startPage":"253","endPage":"262","ipdsId":"IP-008536","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":349610,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"13","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a61059fe4b06e28e9c2556b","contributors":{"authors":[{"text":"Smith, Joseph M.","contributorId":106712,"corporation":false,"usgs":false,"family":"Smith","given":"Joseph","email":"","middleInitial":"M.","affiliations":[{"id":17855,"text":"School of Aquatic and Fishery Sciences, University of Washington, Seattle, WA","active":true,"usgs":false},{"id":6932,"text":"University of Massachusetts, Amherst","active":true,"usgs":false}],"preferred":false,"id":724247,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mather, Martha E. 0000-0003-3027-0215 mather@usgs.gov","orcid":"https://orcid.org/0000-0003-3027-0215","contributorId":2580,"corporation":false,"usgs":true,"family":"Mather","given":"Martha","email":"mather@usgs.gov","middleInitial":"E.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":718143,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70148133,"text":"70148133 - 2012 - Effect of low-head lock and dam structures on migration and spawning of American shad and striped bass in the Cape Fear River, North Carolina","interactions":[],"lastModifiedDate":"2015-06-03T09:59:06","indexId":"70148133","displayToPublicDate":"2012-02-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Effect of low-head lock and dam structures on migration and spawning of American shad and striped bass in the Cape Fear River, North Carolina","docAbstract":"Anadromous fish populations within the Cape Fear River, North Carolina, have declined substantially since the late 1800s. Three low-head lock-and-dam (LD) structures on the river (LD-1–3) contributed to this decline by limiting access to upstream spawning habitat. We used egg sampling and sonic telemetry to examine the effects of the LD structures on migration and spawning activity of American shad Alosa sapidissima and striped bassMorone saxatilis. Egg distribution and stage of development suggested that most of the American shad spawning took place downstream from the lowermost structure, LD-1. The predicted mean density of stage-1 American shad eggs at a water temperature of 21°C was 895 eggs/1,000 m3 (95% credible interval [CI] = 800–994) below LD-1; 147 eggs/1,000 m3 (95% CI = 103–197) below LD-2; and 32 eggs/1,000 m3 (95% CI = 17–49) below the uppermost structure, LD-3. The probability of capturing a stage-1 American shad egg was strongly dependent on water temperature and hour of egg collection. Transmitter detections for 20 sonic-tagged American shad and 20 striped bass in 2008 showed that for both species, the majority of fish moved upstream of LD-1; 35% of American shad and 25% of striped bass migrated upstream of LD-3. Based on passage rates at the three LD structures, American shad would be expected to be most abundant downstream of LD-1 and upstream of LD-3. For striped bass, the river section between LD-2 and LD-3 had the highest egg collections and highest predicted proportion of the run. In combination, these results demonstrate that the locking program provides some access to historical spawning habitat, although further improvements in fish passage could benefit both species.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/00028487.2012.667043","usgsCitation":"Smith, J.A., and Hightower, J.E., 2012, Effect of low-head lock and dam structures on migration and spawning of American shad and striped bass in the Cape Fear River, North Carolina: Transactions of the American Fisheries Society, v. 141, no. 2, p. 402-413, https://doi.org/10.1080/00028487.2012.667043.","productDescription":"12 p.","startPage":"402","endPage":"413","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-028294","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":301001,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Carolina","otherGeospatial":"Cape Fear River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.04388427734375,\n 35.63720889099896\n ],\n [\n -79.1015625,\n 35.61711648382185\n ],\n [\n -79.068603515625,\n 35.538931360333486\n ],\n [\n -79.01641845703125,\n 35.51434313431818\n ],\n [\n -78.83239746093749,\n 35.37561413174875\n ],\n [\n -78.73626708984375,\n 35.303918565311704\n ],\n [\n -78.72116088867188,\n 35.24337596896174\n ],\n [\n -78.74725341796875,\n 35.205233347514536\n ],\n [\n -78.848876953125,\n 35.191766965947394\n ],\n [\n -78.88732910156249,\n 35.146862906756304\n ],\n [\n -78.892822265625,\n 35.073840943666504\n ],\n [\n -78.87222290039062,\n 34.96587351132771\n ],\n [\n -78.804931640625,\n 34.94786508309557\n ],\n [\n -78.82827758789062,\n 34.9163408139391\n ],\n [\n -78.848876953125,\n 34.83296838321102\n ],\n [\n -78.82965087890625,\n 34.742740966060076\n ],\n [\n -78.48358154296875,\n 34.52466147177172\n ],\n [\n -78.34625244140625,\n 34.3955786154917\n ],\n [\n -78.23089599609375,\n 34.32529192442733\n ],\n [\n -78.07708740234375,\n 34.31168124115256\n ],\n [\n -77.991943359375,\n 34.13908837343849\n ],\n [\n -78.0084228515625,\n 33.97297577172598\n ],\n [\n -78.07159423828125,\n 33.90689555128866\n ],\n [\n -77.96722412109374,\n 33.8362013852728\n ],\n [\n -77.89581298828125,\n 34.01168859910852\n ],\n [\n -77.93426513671875,\n 34.28218385709024\n ],\n [\n -78.02490234375,\n 34.36384353883067\n ],\n [\n -78.17047119140625,\n 34.40464357107097\n ],\n [\n -78.277587890625,\n 34.42730166315869\n ],\n [\n -78.42315673828125,\n 34.576690995271974\n ],\n [\n -78.57696533203125,\n 34.67613503380097\n ],\n [\n -78.71978759765625,\n 34.76192255039478\n ],\n [\n -78.78570556640624,\n 34.829586636768205\n ],\n [\n -78.7225341796875,\n 34.95349314197422\n ],\n [\n -78.7774658203125,\n 35.016500995886005\n ],\n [\n -78.80767822265625,\n 35.02099970111467\n ],\n [\n -78.81317138671875,\n 35.133386854253075\n ],\n [\n -78.68133544921875,\n 35.16931803601131\n ],\n [\n -78.64837646484375,\n 35.3308118573182\n ],\n [\n -78.73901367187499,\n 35.42710601280137\n ],\n [\n -78.89007568359375,\n 35.5188142812306\n ],\n [\n -79.04388427734375,\n 35.63720889099896\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"141","issue":"2","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2012-03-12","publicationStatus":"PW","scienceBaseUri":"55702534e4b0d9246a9fd194","contributors":{"authors":[{"text":"Smith, Joseph A.","contributorId":140973,"corporation":false,"usgs":false,"family":"Smith","given":"Joseph","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":548123,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hightower, Joseph E. jhightower@usgs.gov","contributorId":835,"corporation":false,"usgs":true,"family":"Hightower","given":"Joseph","email":"jhightower@usgs.gov","middleInitial":"E.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":547462,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70043304,"text":"70043304 - 2012 - Effects of biotic disturbances on forest carbon cycling in the United States and Canada","interactions":[],"lastModifiedDate":"2018-01-23T10:38:56","indexId":"70043304","displayToPublicDate":"2012-02-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1837,"text":"Global Change Biology","active":true,"publicationSubtype":{"id":10}},"title":"Effects of biotic disturbances on forest carbon cycling in the United States and Canada","docAbstract":"Forest insects and pathogens are major disturbance agents that have affected millions of hectares in North America in recent decades, implying significant impacts to the carbon (C) cycle. Here, we review and synthesize published studies of the effects of biotic disturbances on forest C cycling in the United States and Canada. Primary productivity in stands was reduced, sometimes considerably, immediately following insect or pathogen attack. After repeated growth reductions caused by some insects or pathogens or a single infestation by some bark beetle species, tree mortality occurred, altering productivity and decomposition. In the years following disturbance, primary productivity in some cases increased rapidly as a result of enhanced growth by surviving vegetation, and in other cases increased slowly because of lower forest regrowth. In the decades following tree mortality, decomposition increased as a result of the large amount of dead organic matter. Net ecosystem productivity decreased immediately following attack, with some studies reporting a switch to a C source to the atmosphere, and increased afterward as the forest regrew and dead organic matter decomposed. Large variability in C cycle responses arose from several factors, including type of insect or pathogen, time since disturbance, number of trees affected, and capacity of remaining vegetation to increase growth rates following outbreak. We identified significant knowledge gaps, including limited understanding of carbon cycle impacts among different biotic disturbance types (particularly pathogens), their impacts at landscape and regional scales, and limited capacity to predict disturbance events and their consequences for carbon cycling. We conclude that biotic disturbances can have major impacts on forest C stocks and fluxes and can be large enough to affect regional C cycling. However, additional research is needed to reduce the uncertainties associated with quantifying biotic disturbance effects on the North American C budget.","language":"English","publisher":"Wiley","doi":"10.1111/j.1365-2486.2011.02543.x","usgsCitation":"Vogelmann, J., Allen, C.D., Hicke, J.A., Desai, A.R., Dietze, M.C., Hall, R.J., and Edward H. (Ted) Hogg, 2012, Effects of biotic disturbances on forest carbon cycling in the United States and Canada: Global Change Biology, v. 18, no. 1, p. 7-34, https://doi.org/10.1111/j.1365-2486.2011.02543.x.","productDescription":"27 p.","startPage":"7","endPage":"34","ipdsId":"IP-032156","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":270543,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"18","issue":"1","noUsgsAuthors":false,"publicationDate":"2011-10-27","publicationStatus":"PW","scienceBaseUri":"515d4f65e4b0803bd2eec528","contributors":{"authors":[{"text":"Vogelmann, James E. 0000-0002-0804-5823 vogel@usgs.gov","orcid":"https://orcid.org/0000-0002-0804-5823","contributorId":649,"corporation":false,"usgs":true,"family":"Vogelmann","given":"James E.","email":"vogel@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":473346,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Allen, Craig D. 0000-0002-8777-5989 craig_allen@usgs.gov","orcid":"https://orcid.org/0000-0002-8777-5989","contributorId":2597,"corporation":false,"usgs":true,"family":"Allen","given":"Craig","email":"craig_allen@usgs.gov","middleInitial":"D.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":473347,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hicke, Jeffrey A.","contributorId":87832,"corporation":false,"usgs":true,"family":"Hicke","given":"Jeffrey","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":473352,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Desai, Ankur R. 0000-0002-5226-6041","orcid":"https://orcid.org/0000-0002-5226-6041","contributorId":20622,"corporation":false,"usgs":false,"family":"Desai","given":"Ankur","email":"","middleInitial":"R.","affiliations":[{"id":7122,"text":"University of Wisconsin","active":true,"usgs":false}],"preferred":false,"id":473350,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dietze, Michael C.","contributorId":15908,"corporation":false,"usgs":true,"family":"Dietze","given":"Michael","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":473348,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hall, Ronald J.","contributorId":17504,"corporation":false,"usgs":true,"family":"Hall","given":"Ronald","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":473349,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Edward H. (Ted) Hogg","contributorId":128153,"corporation":true,"usgs":false,"organization":"Edward H. (Ted) Hogg","id":535404,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70156894,"text":"70156894 - 2012 - Long-term creep rates on the Hayward Fault: Evidence for controls on the size and frequency of large earthquakes","interactions":[],"lastModifiedDate":"2022-11-07T17:40:56.947812","indexId":"70156894","displayToPublicDate":"2012-02-01T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Long-term creep rates on the Hayward Fault: Evidence for controls on the size and frequency of large earthquakes","docAbstract":"The Hayward fault (HF) in California exhibits large (Mw 6.5–7.1) earthquakes with short recurrence times (161±65 yr), probably kept short by a 26%–78% aseismic release rate (including postseismic). Its interseismic release rate varies locally over time, as we infer from many decades of surface creep data. Earliest estimates of creep rate, primarily from infrequent surveys of offset cultural features, revealed distinct spatial variation in rates along the fault, but no detectable temporal variation. Since the 1989 Mw 6.9 Loma Prieta earthquake (LPE), monitoring on 32 alinement arrays and 5 creepmeters has greatly improved the spatial and temporal resolution of creep rate. We now identify significant temporal variations, mostly associated with local and regional earthquakes. The largest rate change was a 6‐yr cessation of creep along a 5‐km length near the south end of the HF, attributed to a regional stress drop from the LPE, ending in 1996 with a 2‐cm creep event. North of there near Union City starting in 1991, rates apparently increased by 25% above pre‐LPE levels on a 16‐km‐long reach of the fault. Near Oakland in 2007 an Mw 4.2 earthquake initiated a 1–2 cm creep event extending 10–15 km along the fault. Using new better‐constrained long‐term creep rates, we updated earlier estimates of depth to locking along the HF. The locking depths outline a single, ∼50‐km‐long locked or retarded patch with the potential for an Mw∼6.8 event equaling the 1868 HF earthquake. We propose that this inferred patch regulates the size and frequency of large earthquakes on HF.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120110033","usgsCitation":"Lienkaemper, J.J., McFarland, F.S., Simpson, R.W., Bilham, R.G., Ponce, D.A., Boatwright, J., and Caskey, S., 2012, Long-term creep rates on the Hayward Fault: Evidence for controls on the size and frequency of large earthquakes: Bulletin of the Seismological Society of America, v. 102, no. 1, p. 31-41, https://doi.org/10.1785/0120110033.","productDescription":"11 p.","startPage":"31","endPage":"41","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-027196","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":307782,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Hayward Fault","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.38123406534956,\n 38.00934151742379\n ],\n [\n -122.32149985140742,\n 37.926931149563714\n ],\n [\n -122.25536554311417,\n 37.83600445938727\n ],\n [\n -122.14016384479675,\n 37.721344572141575\n ],\n [\n -121.90549371859511,\n 37.51180141349239\n ],\n [\n -121.83935941030182,\n 37.57607899882744\n ],\n [\n -122.06976280693638,\n 37.812412552098394\n ],\n [\n -122.18069777568618,\n 37.93870972218559\n ],\n [\n -122.35350032316217,\n 38.03959147739795\n ],\n [\n -122.38123406534956,\n 38.00934151742379\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"102","issue":"1","noUsgsAuthors":false,"publicationDate":"2012-02-15","publicationStatus":"PW","scienceBaseUri":"55e6cc35e4b05561fa20a01b","contributors":{"authors":[{"text":"Lienkaemper, James J. 0000-0002-7578-7042 jlienk@usgs.gov","orcid":"https://orcid.org/0000-0002-7578-7042","contributorId":1941,"corporation":false,"usgs":true,"family":"Lienkaemper","given":"James","email":"jlienk@usgs.gov","middleInitial":"J.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":571018,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McFarland, Forrest S.","contributorId":32104,"corporation":false,"usgs":true,"family":"McFarland","given":"Forrest","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":571019,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Simpson, Robert W. simpson@usgs.gov","contributorId":1053,"corporation":false,"usgs":true,"family":"Simpson","given":"Robert","email":"simpson@usgs.gov","middleInitial":"W.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":571020,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bilham, Roger G. 0000-0002-5547-4102","orcid":"https://orcid.org/0000-0002-5547-4102","contributorId":48200,"corporation":false,"usgs":true,"family":"Bilham","given":"Roger","email":"","middleInitial":"G.","affiliations":[],"preferred":true,"id":571021,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Ponce, David A. 0000-0003-4785-7354 ponce@usgs.gov","orcid":"https://orcid.org/0000-0003-4785-7354","contributorId":1049,"corporation":false,"usgs":true,"family":"Ponce","given":"David","email":"ponce@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":571022,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Boatwright, John 0000-0002-6931-5241 boat@usgs.gov","orcid":"https://orcid.org/0000-0002-6931-5241","contributorId":1938,"corporation":false,"usgs":true,"family":"Boatwright","given":"John","email":"boat@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":571023,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Caskey, S. John","contributorId":21483,"corporation":false,"usgs":true,"family":"Caskey","given":"S. John","affiliations":[],"preferred":false,"id":571024,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70007246,"text":"sir20115207 - 2012 - Survey of hydrologic models and hydrologic data needs for tracking flow in the Rio Grande, north-central New Mexico, 2010","interactions":[],"lastModifiedDate":"2012-03-08T17:16:43","indexId":"sir20115207","displayToPublicDate":"2012-01-31T00:00:00","publicationYear":"2012","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":"2011-5207","title":"Survey of hydrologic models and hydrologic data needs for tracking flow in the Rio Grande, north-central New Mexico, 2010","docAbstract":"The six Middle Rio Grande Pueblos have prior and paramount rights to deliveries of water from the Rio Grande for their use. When the pueblos or the Bureau of Indian Affairs Designated Engineer identifies a need for additional flow on the Rio Grande, the Designated Engineer is tasked with deciding the timing and amount of releases of prior and paramount water from storage at El Vado Reservoir to meet the needs of the pueblos. Over the last three decades, numerous models have been developed by Federal, State, and local agencies in New Mexico to simulate, understand, and (or) manage flows in the Middle Rio Grande upstream from Elephant Butte Reservoir. In 2008, the Coalition of Six Middle Rio Grande Basin Pueblos entered into a cooperative agreement with the U.S. Geological Survey to conduct a comprehensive survey of these hydrologic models and their capacity to quantify and track various components of flow. The survey of hydrologic models provided in this report will help water-resource managers at the pueblos, as well as the Designated Engineer, make informed water-resource-management decisions that affect the prior and paramount water use. Analysis of 4 publicly available surface-water models and 13 publicly available groundwater models shows that, although elements from many models can be helpful in tracking flow in the Rio Grande, numerous data gaps and modeling needs indicate that accurate, consistent, and timely tracking of flow on the Rio Grande could be improved. Deficient or poorly constrained hydrologic variables are sources of uncertainty in hydrologic models that can be reduced with the acquisition of more refined data. Data gaps need to be filled to allow hydrologic models to be run on a real-time basis and thus ensure predictable water deliveries to meet needs for irrigation, domestic, stock, and other water uses. Timeliness of flow-data reporting is necessary to facilitate real-time model simulation, but even daily data are sometimes difficult to obtain because the data come from multiple sources. Each surface-water model produces results that could be helpful in quantifying the flow of the Rio Grande, specifically by helping to track water as it moves down the channel of the Rio Grande and by improving the understanding of river hydraulics for the specified reaches. The ability of each surface-water model to track flow on the Rio Grande varies according to the purpose for which each model was designed. The purpose of Upper Rio Grande Water Operations Model (URGWOM) - to simulate water storage and delivery operations in the Rio Grande - is more applicable to tracking flow on the Rio Grande than are any of the other surface-water models surveyed. Specifically, the strengths of URGWOM in relation to modeling flow are the details and attention given to the accounting of Rio Grande flow and San Juan-Chama flow at a daily time step. The most significant difficulty in using any of the surveyed surface-water models for the purpose of predicting the need for requested water releases is that none of the surface-water models surveyed consider water accounting on a real-time basis. Groundwater models that provide detailed simulations of shallow groundwater flow in the vicinity of the Rio Grande can provide large-scale estimates of flow between the Rio Grande and shallow aquifers, which can be an important component of the Rio Grande water budget as a whole. The groundwater models surveyed for this report cannot, however, be expected to provide simulations of flow at time scales of less than the simulated time step (1 month to 1 year in most cases). Of those of the currently used groundwater models, the purpose of model 13 - to simulate the shallow riparian groundwater environment - is the most appropriate for examining local-scale surface-water/groundwater interactions. The basin-scale models, however, are also important in understanding the large-scale water balances between the aquifers and the surface water. In the case of the Upper and Middle Rio Grande Valley, models 6, 10, and 12 are the most accurate and current groundwater models available.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20115207","collaboration":"Prepared in cooperation with the Coalition of Six Middle Rio Grande Basin Pueblos","usgsCitation":"Tillery, A., and Eggleston, J.R., 2012, Survey of hydrologic models and hydrologic data needs for tracking flow in the Rio Grande, north-central New Mexico, 2010: U.S. Geological Survey Scientific Investigations Report 2011-5207, vii, 39 p., https://doi.org/10.3133/sir20115207.","productDescription":"vii, 39 p.","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":116455,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2011_5207.gif"},{"id":115750,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2011/5207/","linkFileType":{"id":5,"text":"html"}}],"scale":"24000","projection":"Universal Transverse Mercator, zone 13","datum":"North American Datum of 1988","country":"United States","state":"Colorado;New Mexico","otherGeospatial":"Rio Grande Basin;Elephant Butte Reservoir","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -105,33 ], [ -105,39 ], [ -109,39 ], [ -109,33 ], [ -105,33 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505ba295e4b08c986b31f7e8","contributors":{"authors":[{"text":"Tillery, Anne","contributorId":16120,"corporation":false,"usgs":true,"family":"Tillery","given":"Anne","affiliations":[],"preferred":false,"id":356177,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Eggleston, Jack R.","contributorId":20011,"corporation":false,"usgs":true,"family":"Eggleston","given":"Jack","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":356178,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70007232,"text":"sir20125015 - 2012 - Preliminary analysis of the hydrologic effects of temporary shutdowns of the Rondout-West Branch Water Tunnel on the groundwater-flow system in Wawarsing, New York","interactions":[],"lastModifiedDate":"2012-03-08T17:16:43","indexId":"sir20125015","displayToPublicDate":"2012-01-31T00:00:00","publicationYear":"2012","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":"2012-5015","title":"Preliminary analysis of the hydrologic effects of temporary shutdowns of the Rondout-West Branch Water Tunnel on the groundwater-flow system in Wawarsing, New York","docAbstract":"Flooding of streets and residential basements, and bacterial contamination of private-supply wells with Escherichia coli (E. coli) are recurring problems in the Rondout Valley near the Town of Wawarsing, Ulster County, New York. Leakage from the Rondout-West Branch (RWB) Water Tunnel and above-normal precipitation have been suspected of causing elevated groundwater levels and basement flooding. The hydrology of a 12-square-mile study area within the Town of Wawarsing was studied during 2008-10. A network of 41 wells (23 unconsolidated-aquifer and 18 bedrock wells) and 2 surface-water sites was used to monitor the hydrologic effects of four RWB Water Tunnel shutdowns. The study area is underlain by a sequence of northeast-trending sedimentary rocks that include limestone, shale, and sandstone. The bedrock contains dissolution features, fractures, and faults. Inflows that ranged from less than 1 to more than 9,000 gallons per minute from the fractured bedrock were documented during construction of the 13.5-foot-diameter RWB Water Tunnel through the sedimentary-rock sequence 710 feet (ft) beneath the study-area valley. Glacial sediments infill the valley above the bedrock sequence and consist of clay, silt, sand, and gravel. The groundwater-flow system in the valley consists of both fractured-rock and unconsolidated aquifers. Water levels in both the bedrock and unconsolidated aquifers respond to variations in seasonal precipitation. During the past 9 years (2002-10), annual precipitation at Central Park, N.Y., has exceeded the 141-year mean. \r\nPotentiometric-surface maps indicate that groundwater in the bedrock flows from the surrounding hills on the east and west sides of the valley toward the center of the valley, and ultimately toward the northeast. On average, water levels in the bedrock aquifer had seasonal differences of 5.3 ft. Analysis of hydrographs of bedrock wells indicates that many of these wells are affected by the RWB Tunnel leakage. Tunnel-leakage influences (water level and temperature changes) in the bedrock aquifer were measured at distances up to 7,000 ft from the RWB Tunnel. Water levels in the bedrock changed as much as 12 ft within 0.5 hour during tunnel shutdowns. Nine of the 10 wells that responded to the shutdowns showed a water-level response of 5 ft or greater. Changes in water levels ranged from 1.5 to 12 ft, with tunnel-leakage influence delay times ranging from 0.5 to 60 hours. Many of the longest tunnel-influence delay times and smallest water-level changes were in wells located closest to the tunnel in shale. Tunnel-influence response of the bedrock aquifer is consistent with its preliminary characterization as an anisotropic aquifer with greater transmissivity along bedding strike than across bedding strike. This tunnel-influence response is also consistent with the likely presence of discrete high-transmissivity networks along fractured limestone beds that have undergone dissolution. A lack of bedrock observation wells in half of the study area hampered a more thorough analysis of the extent of leakage from the RWB Tunnel in the study area. \r\nOn average, water levels in the unconsolidated aquifer had a seasonal difference of 5.0 ft. Some unconsolidated-aquifer wells indicated water-level changes due to tunnel leakage. The locations of unconsolidated-aquifer wells with measurable water-level changes due to tunnel leakage correlated with those in the bedrock. Water levels in the unconsolidated aquifer changed as much as 2.5 ft within 18 hours of tunnel shutdowns, but water-level changes in some unconsolidated-aquifer wells were smaller or nonexistent.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125015","collaboration":"Prepared in cooperation with the New York City Department of Environmental Protection","usgsCitation":"Stumm, F., Chu, A., Como, M.D., and Noll, M.L., 2012, Preliminary analysis of the hydrologic effects of temporary shutdowns of the Rondout-West Branch Water Tunnel on the groundwater-flow system in Wawarsing, New York: U.S. Geological Survey Scientific Investigations Report 2012-5015, vi, 48 p., https://doi.org/10.3133/sir20125015.","productDescription":"vi, 48 p.","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":116387,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5015.gif"},{"id":115713,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5015/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"New York","county":"Ulster","city":"Wawarsing","otherGeospatial":"Rondout Valley;Rondout-west Branch (rwb) Water Tunnel","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a82d1e4b0c8380cd7bc70","contributors":{"authors":[{"text":"Stumm, Frederick 0000-0002-5388-8811 fstumm@usgs.gov","orcid":"https://orcid.org/0000-0002-5388-8811","contributorId":1077,"corporation":false,"usgs":true,"family":"Stumm","given":"Frederick","email":"fstumm@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":356147,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chu, Anthony 0000-0001-8623-2862 achu@usgs.gov","orcid":"https://orcid.org/0000-0001-8623-2862","contributorId":2517,"corporation":false,"usgs":true,"family":"Chu","given":"Anthony","email":"achu@usgs.gov","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":356148,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Como, Michael D. 0000-0002-7911-5390 mcomo@usgs.gov","orcid":"https://orcid.org/0000-0002-7911-5390","contributorId":4651,"corporation":false,"usgs":true,"family":"Como","given":"Michael","email":"mcomo@usgs.gov","middleInitial":"D.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":356149,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Noll, Michael L. 0000-0003-2050-3134 mnoll@usgs.gov","orcid":"https://orcid.org/0000-0003-2050-3134","contributorId":4652,"corporation":false,"usgs":true,"family":"Noll","given":"Michael","email":"mnoll@usgs.gov","middleInitial":"L.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":356150,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70007105,"text":"70007105 - 2012 - A caveat regarding diatom-inferred nitrogen concentrations in oligotrophic lakes","interactions":[],"lastModifiedDate":"2021-01-04T18:07:50.71384","indexId":"70007105","displayToPublicDate":"2012-01-30T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2411,"text":"Journal of Paleolimnology","active":true,"publicationSubtype":{"id":10}},"title":"A caveat regarding diatom-inferred nitrogen concentrations in oligotrophic lakes","docAbstract":"Atmospheric deposition of reactive nitrogen (Nr) has enriched oligotrophic lakes with nitrogen (N) in many regions of the world and elicited dramatic changes in diatom community structure. The lakewater concentrations of nitrate that cause these community changes remain unclear, raising interest in the development of diatom-based transfer functions to infer nitrate. We developed a diatom calibration set using surface sediment samples from 46 high-elevation lakes across the Rocky Mountains of the western US, a region spanning an N deposition gradient from very low to moderate levels (<1 to 3.2 kg Nr ha−1 year−1 in wet deposition). Out of the fourteen measured environmental variables for these 46 lakes, ordination analysis identified that nitrate, specific conductance, total phosphorus, and hypolimnetic water temperature were related to diatom distributions. A transfer function was developed for nitrate and applied to a sedimentary diatom profile from Heart Lake in the central Rockies. The model coefficient of determination (bootstrapping validation) of 0.61 suggested potential for diatom-inferred reconstructions of lakewater nitrate concentrations over time, but a comparison of observed versus diatom-inferred nitrate values revealed the poor performance of this model at low nitrate concentrations. Resource physiology experiments revealed that nitrogen requirements of two key taxa were opposite to nitrate optima defined in the transfer function. Our data set reveals two underlying ecological constraints that impede the development of nitrate transfer functions in oligotrophic lakes: (1) even in lakes with nitrate concentrations below quantification (<1 μg L−1), diatom assemblages were already dominated by species indicative of moderate N enrichment; (2) N-limited oligotrophic lakes switch to P limitation after receiving only modest inputs of reactive N, shifting the controls on diatom species changes along the length of the nitrate gradient. These constraints suggest that quantitative inferences of nitrate from diatom assemblages will likely require experimental approaches.
","language":"English","publisher":"Springer","publisherLocation":"Amsterdam, Netherlands","doi":"10.1007/s10933-011-9576-z","usgsCitation":"Arnett, H.A., Saros, J.E., and Mast, M.A., 2012, A caveat regarding diatom-inferred nitrogen concentrations in oligotrophic lakes: Journal of Paleolimnology, v. 47, no. 2, p. 277-291, https://doi.org/10.1007/s10933-011-9576-z.","productDescription":"15 p.","startPage":"277","endPage":"291","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":204684,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, Idaho, Montana, Utah, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.02636718749999,\n 37.17782559332976\n ],\n [\n -102.41455078125,\n 37.17782559332976\n ],\n [\n -102.41455078125,\n 48.980216985374994\n ],\n [\n -117.02636718749999,\n 48.980216985374994\n ],\n [\n -117.02636718749999,\n 37.17782559332976\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"47","issue":"2","noUsgsAuthors":false,"publicationDate":"2012-01-10","publicationStatus":"PW","scienceBaseUri":"5059e33ce4b0c8380cd45ecc","contributors":{"authors":[{"text":"Arnett, Heather A.","contributorId":74141,"corporation":false,"usgs":true,"family":"Arnett","given":"Heather","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":355826,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Saros, Jasmine E.","contributorId":29958,"corporation":false,"usgs":true,"family":"Saros","given":"Jasmine","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":355825,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mast, M. Alisa 0000-0001-6253-8162 mamast@usgs.gov","orcid":"https://orcid.org/0000-0001-6253-8162","contributorId":827,"corporation":false,"usgs":true,"family":"Mast","given":"M.","email":"mamast@usgs.gov","middleInitial":"Alisa","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":355824,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70007241,"text":"mineral2012 - 2012 - Mineral Commodity Summaries 2012","interactions":[],"lastModifiedDate":"2013-02-04T10:57:03","indexId":"mineral2012","displayToPublicDate":"2012-01-30T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":323,"text":"Mineral Commodity Summaries","code":"MCS","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2012","title":"Mineral Commodity Summaries 2012","docAbstract":"Each chapter of the 2012 edition of the U.S. Geological Survey (USGS) Mineral Commodity Summaries (MCS) includes information on events, trends, and issues for each mineral commodity as well as discussions and tabular presentations on domestic industry structure, Government programs, tariffs, 5-year salient statistics, and world production and resources. The MCS is the earliest comprehensive source of 2011 mineral production data for the world. More than 90 individual minerals and materials are covered by 2-page synopses.
\nFor mineral commodities for which there is a Government stockpile, detailed information concerning the stockpile status is included in the two-page synopsis.
\nAbbreviations and units of measure, and definitions of selected terms used in the report, are in Appendix A and Appendix B, respectively. \"Appendix C—Reserves and Resources\" includes \"Part A—Resource/Reserve Classification for Minerals\" and \"Part B—Sources of Reserves Data.\" A directory of USGS minerals information country specialists and their responsibilities is Appendix D.
\nThe USGS continually strives to improve the value of its publications to users. Constructive comments and suggestions by readers of the MCS 2012 are welcomed.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/mineral2012","isbn":"9781411333499","usgsCitation":"Mineral Commodity Summaries 2012; 2012; MINERAL; 2012; ","productDescription":"191 p.; Appendixes; Individual Commodity Data Sheets; Available Online, Printed, and on CD-ROM","costCenters":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"links":[{"id":115736,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://minerals.usgs.gov/minerals/pubs/mcs/","linkFileType":{"id":5,"text":"html"}},{"id":204589,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/mineral_2012.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a574fe4b0c8380cd6dbc7"} ,{"id":70003956,"text":"70003956 - 2012 - Microhabitat selection by bobcats in the badlands and Black Hills of South Dakota, USA: a comparison of Prairie and forested habitats","interactions":[],"lastModifiedDate":"2013-10-28T14:20:33","indexId":"70003956","displayToPublicDate":"2012-01-28T14:12:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3580,"text":"The Prairie Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Microhabitat selection by bobcats in the badlands and Black Hills of South Dakota, USA: a comparison of Prairie and forested habitats","docAbstract":"An understanding of habitat selection is important for management of wildlife species. Although bobcat (Lynx rufus) resource selection has been addressed in many regions of the United States, little work has been conducted in the Northern Great Plains. From 2006–2008 we captured and radiocollared 20 bobcats in the Badlands (n = 10) and Black Hills (n = 10) regions of South Dakota. During the summers of 2008 and 2009 we collected habitat measurements at 349 (176 Badlands, 176 Black Hills) bobcat locations and 321 (148 Badlands, 173 Black Hills) random sites. Microhabitat characteristics at bobcat use sites varied with region (P < 0.001) and sex of bobcat (P < 0.001). Percent slope, shrub, low cover, medium cover, and total cover were greater (P ≤ 0.017) at bobcat locations in the Black Hills than in the Badlands whereas distance to drainage was greater (P < 0.001) at locations in the Badlands than in the Black Hills. In the Badlands, male bobcat locations were closer (P ≤ 0.002) to prairie dog towns and drainages and had greater (P < 0.05) percent forbs and forb height than random sites, whereas females were closer to badland formations (P < 0.001) than random sites. In the Black Hills, male locations were at greater elevation (P < 0.001) and female locations were characterized by greater (P ≤ 0.02) grass height, shrub height, low cover, and total cover than random sites. Logistic regression indicated that microhabitat selection was similar between study areas; odds ratios indicated that odds of bobcat use increased by 0.998 (95% CI = 0.997–0.999) per 1 m increase in distance to drainage, \n0.986 (95% CI = 0.978–0.993) per 1.0% increase in grass cover, by 1.024 (95% CI = 1.011–1.036) per 1 cm increase in grass height, by 1.013 (95% CI = 1.003–1.024) per 1% increase in forb cover, and by 1.028 (95% CI = 1.017–1.039) per 1% increase in medium cover. Our results were similar to other bobcat microhabitat selection studies, where bobcat relocations were associated with understory vegetation, drainages, and rugged terrain. These results identify the adaptability of the species to meet life history requirements in a variety of landscapes, and provide insight to how land use requirements vary within regional and management boundaries.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"The Prairie Naturalist","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"South Dakota State University","publisherLocation":"Brookings, SD","usgsCitation":"Mosby, C.E., Grovenburg, T.W., Klaver, R.W., Schroeder, G.M., Schmitz, L.E., and Jenks, J., 2012, Microhabitat selection by bobcats in the badlands and Black Hills of South Dakota, USA: a comparison of Prairie and forested habitats: The Prairie Naturalist, v. 44, no. 1, p. 47-57.","productDescription":"11 p.","startPage":"47","endPage":"57","ipdsId":"IP-026243","costCenters":[{"id":350,"text":"Iowa Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"links":[{"id":278484,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":278483,"type":{"id":11,"text":"Document"},"url":"https://s3.amazonaws.com/file-storage.INDIVIDUAL-ACTIVITIES-CooperativeResearchUnits.digitalmeasures.usgs.edu/bklaver/intellcont/Mosby%20et%20al%20Prairie%20Naturalist-1.pdf"}],"country":"United States","state":"South Dakota","otherGeospatial":"Badlands;Black Hills","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -104.7945,43.2665 ], [ -104.7945,44.7866 ], [ -102.7523,44.7866 ], [ -102.7523,43.2665 ], [ -104.7945,43.2665 ] ] ] } } ] }","volume":"44","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"526f8778e4b0493c992ecd9b","contributors":{"authors":[{"text":"Mosby, Cory E.","contributorId":101178,"corporation":false,"usgs":true,"family":"Mosby","given":"Cory","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":349706,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grovenburg, Troy W.","contributorId":57712,"corporation":false,"usgs":true,"family":"Grovenburg","given":"Troy","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":349704,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Klaver, Robert W. 0000-0002-3263-9701 bklaver@usgs.gov","orcid":"https://orcid.org/0000-0002-3263-9701","contributorId":3285,"corporation":false,"usgs":true,"family":"Klaver","given":"Robert","email":"bklaver@usgs.gov","middleInitial":"W.","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":349701,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schroeder, Greg M.","contributorId":54845,"corporation":false,"usgs":true,"family":"Schroeder","given":"Greg","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":349703,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schmitz, Lowell E.","contributorId":78236,"corporation":false,"usgs":true,"family":"Schmitz","given":"Lowell","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":349705,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Jenks, Jonathan A.","contributorId":51591,"corporation":false,"usgs":true,"family":"Jenks","given":"Jonathan A.","affiliations":[],"preferred":false,"id":349702,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70007240,"text":"fs20123004 - 2012 - Phosphorus and groundwater: Establishing links between agricultural use and transport to streams","interactions":[],"lastModifiedDate":"2018-08-27T13:04:57","indexId":"fs20123004","displayToPublicDate":"2012-01-28T11:51:00","publicationYear":"2012","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":"2012-3004","title":"Phosphorus and groundwater: Establishing links between agricultural use and transport to streams","docAbstract":"Phosphorus is a highly reactive element that is essential for life and forms a variety of compounds in terrestrial and aquatic ecosystems. In water, phosphorus may be present as the orthophosphate ion (PO43-) and is also present in all life forms as an essential component of cellular material. In natural ecosystems, phosphorus is derived from the erosion of rocks and is conserved for plant growth as it is returned to the soil through animal waste and the decomposition of plant and animal tissue; but in agricultural systems, a portion of the phosphorus is removed with each harvest, especially since phosphorus is concentrated in the seeds and fruit. Phosphorus is added to soil by using chemical fertilizers, manure, and composted materials. Agricultural use of chemical phosphorus fertilizer, in the United States, in 2008 was 4,247,000 tons, which is an increase of 25 percent since 1964 (http://www.ers.usda.gov/Data/FertilizerUse/). Widely grown corn, soybeans, and wheat use the greatest amount of phosphorus fertilizer among agricultural crops.
\nPhosphorus is largely retained in soil by a process called adsorption. Soils have a limited capacity to store phosphorus, and once the capacity of soil to adsorb phosphorus is exceeded, the excess will dissolve and move more freely with water either directly to a stream or downward to an aquifer. Surface-water runoff from rainstorms or excess irrigation is the primary way that phosphorus or soil containing phosphorus is transported to streams in most watersheds. There is a growing awareness that long-term over-application of manure and chemical fertilizer contributes to phosphorus movement into the groundwater system, resulting in a significant groundwater source of phosphorus to streams and lakes, as well as potential contamination of the groundwater resources.
\nLeaching of applied fertilizer and surface runoff of phosphorus from the soil can contribute to excess growth of algae in downstream water bodies, a condition known as eutrophication. Excessive amounts of algae in eutrophic water bodies can cause large daily changes in the amount of dissolved oxygen in the water because oxygen concentrations tend to be high during daylight hours as a result of photosynthetic activity but then decrease at night. Low concentrations of dissolved oxygen can stress or kill sensitive species living in the water.
\nThis study examined concentrations and movement of phosphorus in the soils and groundwater in five agricultural settings across the United States characterized by differences in soil geochemistry, climate, irrigation usage, and cropping systems to assess potential phosphorus movement in the soil and groundwater under common agricultural conditions. The study design included assessment of a variety of agricultural practices, especially cropping patterns and irrigation, so that the factors that contribute to phosphorus movement to groundwater, or sequestration of the phosphorus to soil could be compared and examined. This type of information could potentially be used to formulate best management practices to limit the transport of phosphorus from the agricultural fields.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20123004","collaboration":"Prepared as part of the National Water-Quality Assessment Program, Agricultural Chemicals Team (ACT)","usgsCitation":"Domagalski, J.L., and Johnson, H., 2012, Phosphorus and groundwater: Establishing links between agricultural use and transport to streams: U.S. Geological Survey Fact Sheet 2012-3004, 4 p., https://doi.org/10.3133/fs20123004.","productDescription":"4 p.","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":116343,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2012_3004.JPG"},{"id":115735,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2012/3004/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a78b1e4b0c8380cd78762","contributors":{"authors":[{"text":"Domagalski, Joseph L. 0000-0002-6032-757X joed@usgs.gov","orcid":"https://orcid.org/0000-0002-6032-757X","contributorId":1330,"corporation":false,"usgs":true,"family":"Domagalski","given":"Joseph","email":"joed@usgs.gov","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":356156,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Henry 0000-0002-7571-4994","orcid":"https://orcid.org/0000-0002-7571-4994","contributorId":71693,"corporation":false,"usgs":true,"family":"Johnson","given":"Henry","affiliations":[],"preferred":false,"id":356157,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70007247,"text":"70007247 - 2012 - Ocean-atmosphere dynamics during Hurricane Ida and Nor'Ida: An application of the coupled ocean-;atmosphere–wave–sediment transport (COAWST) modeling system","interactions":[],"lastModifiedDate":"2017-04-06T15:04:03","indexId":"70007247","displayToPublicDate":"2012-01-27T09:39:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2925,"text":"Ocean Modelling","active":true,"publicationSubtype":{"id":10}},"title":"Ocean-atmosphere dynamics during Hurricane Ida and Nor'Ida: An application of the coupled ocean-;atmosphere–wave–sediment transport (COAWST) modeling system","docAbstract":"The coupled ocean–atmosphere–wave–sediment transport (COAWST) modeling system was used to investigate atmosphere–ocean–wave interactions in November 2009 during Hurricane Ida and its subsequent evolution to Nor'Ida, which was one of the most costly storm systems of the past two decades. One interesting aspect of this event is that it included two unique atmospheric extreme conditions, a hurricane and a nor'easter storm, which developed in regions with different oceanographic characteristics. Our modeled results were compared with several data sources, including GOES satellite infrared data, JASON-1 and JASON-2 altimeter data, CODAR measurements, and wave and tidal information from the National Data Buoy Center (NDBC) and the National Tidal Database. By performing a series of numerical runs, we were able to isolate the effect of the interaction terms between the atmosphere (modeled with Weather Research and Forecasting, the WRF model), the ocean (modeled with Regional Ocean Modeling System (ROMS)), and the wave propagation and generation model (modeled with Simulating Waves Nearshore (SWAN)). Special attention was given to the role of the ocean surface roughness. Three different ocean roughness closure models were analyzed: DGHQ (which is based on wave age), TY2001 (which is based on wave steepness), and OOST (which considers both the effects of wave age and steepness). Including the ocean roughness in the atmospheric module improved the wind intensity estimation and therefore also the wind waves, surface currents, and storm surge amplitude. For example, during the passage of Hurricane Ida through the Gulf of Mexico, the wind speeds were reduced due to wave-induced ocean roughness, resulting in better agreement with the measured winds. During Nor'Ida, including the wave-induced surface roughness changed the form and dimension of the main low pressure cell, affecting the intensity and direction of the winds. The combined wave age- and wave steepness-based parameterization (OOST) provided the best results for wind and wave growth prediction. However, the best agreement between the measured (CODAR) and computed surface currents and storm surge values was obtained with the wave steepness-based roughness parameterization (TY2001), although the differences obtained with respect to DGHQ were not significant. The influence of sea surface temperature (SST) fields on the atmospheric boundary layer dynamics was examined; in particular, we evaluated how the SST affects wind wave generation, surface currents and storm surges. The integrated hydrograph and integrated wave height, parameters that are highly correlated with the storm damage potential, were found to be highly sensitive to the ocean surface roughness parameterization.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ocean Modelling","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","publisherLocation":"Amsterdam, Netherlands","doi":"10.1016/j.ocemod.2011.12.008","usgsCitation":"Olabarrieta, M., Warner, J., Armstrong, B., Zambon, J.B., and He, R., 2012, Ocean-atmosphere dynamics during Hurricane Ida and Nor'Ida: An application of the coupled ocean-;atmosphere–wave–sediment transport (COAWST) modeling system: Ocean Modelling, v. 43-44, p. 112-137, https://doi.org/10.1016/j.ocemod.2011.12.008.","productDescription":"26 p.","startPage":"112","endPage":"137","numberOfPages":"25","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":474584,"rank":101,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/1912/5124","text":"External Repository"},{"id":204581,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":115753,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://dx.doi.org/10.1016/j.ocemod.2011.12.008","linkFileType":{"id":5,"text":"html"}}],"volume":"43-44","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a6c98e4b0c8380cd74ce7","contributors":{"authors":[{"text":"Olabarrieta, Maitane 0000-0002-7619-7992 molabarrieta@usgs.gov","orcid":"https://orcid.org/0000-0002-7619-7992","contributorId":81631,"corporation":false,"usgs":true,"family":"Olabarrieta","given":"Maitane","email":"molabarrieta@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":356183,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Warner, John C. 0000-0002-3734-8903 jcwarner@usgs.gov","orcid":"https://orcid.org/0000-0002-3734-8903","contributorId":2681,"corporation":false,"usgs":true,"family":"Warner","given":"John C.","email":"jcwarner@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":356179,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Armstrong, Brandy N. barmstrong@usgs.gov","contributorId":5897,"corporation":false,"usgs":true,"family":"Armstrong","given":"Brandy N.","email":"barmstrong@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":356180,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zambon, Joseph B.","contributorId":8222,"corporation":false,"usgs":true,"family":"Zambon","given":"Joseph","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":356181,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"He, Ruoying","contributorId":68029,"corporation":false,"usgs":true,"family":"He","given":"Ruoying","affiliations":[],"preferred":false,"id":356182,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70007256,"text":"70007256 - 2012 - Flat-plate techniques for measuring reflectance of macro-algae (Ulva curvata)","interactions":[],"lastModifiedDate":"2012-02-02T00:16:02","indexId":"70007256","displayToPublicDate":"2012-01-27T09:27:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2068,"text":"International Journal of Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Flat-plate techniques for measuring reflectance of macro-algae (Ulva curvata)","docAbstract":"We tested the consistency and accuracy of flat-plate spectral measurements (400–1000 nm) of the marine macrophyte Ulva curvata. With sequential addition of Ulva thallus layers, the reflectance progressively increased from 6% to 9% with six thalli in the visible (VIS) and from 5% to 19% with ten thalli in the near infrared (NIR). This progressive increase was simulated by a mathematical calculation based on an Ulva thallus diffuse reflectance weighted by a transmittance power series. Experimental and simulated reflectance differences that were particularly high in the NIR most likely resulted from residual water and layering structure unevenness in the experimental progression. High spectral overlap existed between fouled and non-fouled Ulva mats and the coexistent lagoon mud in the VIS, whereas in the NIR, spectral contrast was retained but substantially dampened by fouling.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"International Journal of Remote Sensing","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Taylor & Francis","publisherLocation":"Philadelphia, PA","doi":"10.1080/01431161.2011.633124","usgsCitation":"Ramsey, E., Rangoonwala, A., Thomsen, M.S., and Schwarzschild, A., 2012, Flat-plate techniques for measuring reflectance of macro-algae (Ulva curvata): International Journal of Remote Sensing, v. 33, no. 10, p. 3147-3155, https://doi.org/10.1080/01431161.2011.633124.","productDescription":"9 p.","startPage":"3147","endPage":"3155","numberOfPages":"8","costCenters":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"links":[{"id":204587,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":115752,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://dx.doi.org/10.1080/01431161.2011.633124","linkFileType":{"id":5,"text":"html"}}],"volume":"33","issue":"10","noUsgsAuthors":false,"publicationDate":"2011-11-11","publicationStatus":"PW","scienceBaseUri":"505a10d3e4b0c8380cd53e0d","contributors":{"authors":[{"text":"Ramsey, Elijah W. III 0000-0002-4518-5796","orcid":"https://orcid.org/0000-0002-4518-5796","contributorId":72769,"corporation":false,"usgs":true,"family":"Ramsey","given":"Elijah W.","suffix":"III","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":false,"id":356194,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rangoonwala, Amina 0000-0002-0556-0598 rangoonwalaa@usgs.gov","orcid":"https://orcid.org/0000-0002-0556-0598","contributorId":3455,"corporation":false,"usgs":true,"family":"Rangoonwala","given":"Amina","email":"rangoonwalaa@usgs.gov","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":356191,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Thomsen, Mads Solgaard","contributorId":49514,"corporation":false,"usgs":true,"family":"Thomsen","given":"Mads","email":"","middleInitial":"Solgaard","affiliations":[],"preferred":false,"id":356192,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schwarzschild, Arthur","contributorId":62740,"corporation":false,"usgs":true,"family":"Schwarzschild","given":"Arthur","email":"","affiliations":[],"preferred":false,"id":356193,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70007235,"text":"gip137 - 2012 - GloVis","interactions":[],"lastModifiedDate":"2012-02-02T00:15:56","indexId":"gip137","displayToPublicDate":"2012-01-27T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":315,"text":"General Information Product","code":"GIP","onlineIssn":"2332-354X","printIssn":"2332-3531","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"137","title":"GloVis","docAbstract":"The Global Visualization Viewer (GloVis) trifold provides basic information for online access to a subset of satellite and aerial photography collections from the U.S. Geological Survey Earth Resources Observation and Science (EROS) Center archive. The GloVis (http://glovis.usgs.gov/) browser-based utility allows users to search and download National Aerial Photography Program (NAPP), National High Altitude Photography (NHAP), Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Earth Observing-1 (EO-1), Global Land Survey, Moderate Resolution Imaging Spectroradiometer (MODIS), and TerraLook data. Minimum computer system requirements and customer service contact information also are included in the brochure.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/gip137","usgsCitation":"Houska, T., and Johnson, A., 2012, GloVis: U.S. Geological Survey General Information Product 137, 2 p., https://doi.org/10.3133/gip137.","productDescription":"2 p.","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":116454,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/gip_137.jpg"},{"id":115721,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/gip/137/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a292ee4b0c8380cd5a71d","contributors":{"authors":[{"text":"Houska, Treva R. 0000-0002-4358-6131","orcid":"https://orcid.org/0000-0002-4358-6131","contributorId":45460,"corporation":false,"usgs":true,"family":"Houska","given":"Treva R.","affiliations":[],"preferred":false,"id":356155,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, A.P.","contributorId":22495,"corporation":false,"usgs":true,"family":"Johnson","given":"A.P.","email":"","affiliations":[],"preferred":false,"id":356154,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70007223,"text":"sim3190 - 2012 - Description and validation of an automated methodology for mapping mineralogy, vegetation, and hydrothermal alteration type from ASTER satellite imagery with examples from the San Juan Mountains, Colorado","interactions":[],"lastModifiedDate":"2012-02-10T00:12:01","indexId":"sim3190","displayToPublicDate":"2012-01-26T00:00:00","publicationYear":"2012","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":"3190","title":"Description and validation of an automated methodology for mapping mineralogy, vegetation, and hydrothermal alteration type from ASTER satellite imagery with examples from the San Juan Mountains, Colorado","docAbstract":"The efficacy of airborne spectroscopic, or \"hyperspectral,\" remote sensing for geoenvironmental watershed evaluations and deposit-scale mapping of exposed mineral deposits has been demonstrated. However, the acquisition, processing, and analysis of such airborne data at regional and national scales can be time and cost prohibitive. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor carried by the NASA Earth Observing System Terra satellite was designed for mineral mapping and the acquired data can be efficiently used to generate uniform mineral maps over very large areas. Multispectral remote sensing data acquired by the ASTER sensor were analyzed to identify and map minerals, mineral groups, hydrothermal alteration types, and vegetation groups in the western San Juan Mountains, Colorado, including the Silverton and Lake City calderas. This mapping was performed in support of multidisciplinary studies involving the predictive modeling of surface water geochemistry at watershed and regional scales. Detailed maps of minerals, vegetation groups, and water were produced from an ASTER scene using spectroscopic, expert system-based analysis techniques which have been previously described. New methodologies are presented for the modeling of hydrothermal alteration type based on the Boolean combination of the detailed mineral maps, and for the entirely automated mapping of alteration types, mineral groups, and green vegetation. Results of these methodologies are compared with the more detailed maps and with previously published mineral mapping results derived from analysis of high-resolution spectroscopic data acquired by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) sensor. Such comparisons are also presented for other mineralized and (or) altered areas including the Goldfield and Cuprite mining districts, Nevada and the central Marysvale volcanic field, Wah Wah Mountains, and San Francisco Mountains, Utah. The automated mineral group mapping products described in this study are ideal for application to mineral resource and mineral-environmental assessments at regional and national scales.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3190","usgsCitation":"Rockwell, B.W., 2012, Description and validation of an automated methodology for mapping mineralogy, vegetation, and hydrothermal alteration type from ASTER satellite imagery with examples from the San Juan Mountains, Colorado: U.S. Geological Survey Scientific Investigations Map 3190, Pamphlet: v, 35 p. ;5 Sheets; Sheet 1: 32 inches x 39 inches; Sheet 2: 32 inches x 39 inches; Sheet 3: 32 inches x 39 inches; Sheet 4: 32 inches x 39 inches; Sheet 5: 32 inches x 39 inches; Metadata; Additional Data, https://doi.org/10.3133/sim3190.","productDescription":"Pamphlet: v, 35 p. ;5 Sheets; Sheet 1: 32 inches x 39 inches; Sheet 2: 32 inches x 39 inches; Sheet 3: 32 inches x 39 inches; Sheet 4: 32 inches x 39 inches; Sheet 5: 32 inches x 39 inches; Metadata; Additional Data","numberOfPages":"35","additionalOnlineFiles":"Y","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":116450,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim_3190.png"},{"id":115712,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3190/","linkFileType":{"id":5,"text":"html"}}],"scale":"100000","country":"United States","state":"Colorado","otherGeospatial":"San Juan Mountains","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -108,37.46666666666667 ], [ -108,38.083333333333336 ], [ -107.15,38.083333333333336 ], [ -107.15,37.46666666666667 ], [ -108,37.46666666666667 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059feeee4b0c8380cd4efbb","contributors":{"authors":[{"text":"Rockwell, Barnaby W. 0000-0002-9549-0617 barnabyr@usgs.gov","orcid":"https://orcid.org/0000-0002-9549-0617","contributorId":2195,"corporation":false,"usgs":true,"family":"Rockwell","given":"Barnaby","email":"barnabyr@usgs.gov","middleInitial":"W.","affiliations":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":356135,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70007222,"text":"sir20125005 - 2012 - A comparison of consumptive-use estimates derived from the simplified surface energy balance approach and indirect reporting methods","interactions":[],"lastModifiedDate":"2017-03-29T14:26:09","indexId":"sir20125005","displayToPublicDate":"2012-01-26T00:00:00","publicationYear":"2012","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":"2012-5005","title":"A comparison of consumptive-use estimates derived from the simplified surface energy balance approach and indirect reporting methods","docAbstract":"Recent advances in remote-sensing technology and Simplified Surface Energy Balance (SSEB) methods can provide accurate and repeatable estimates of evapotranspiration (ET) when used with satellite observations of irrigated lands. Estimates of ET are generally considered equivalent to consumptive use (CU) because they represent the part of applied irrigation water that is evaporated, transpired, or otherwise not available for immediate reuse. The U.S. Geological Survey compared ET estimates from SSEB methods to CU data collected for 1995 using indirect methods as part of the National Water Use Information Program (NWUIP). Ten-year (2000-2009) average ET estimates from SSEB methods were derived using Moderate Resolution Imaging Spectroradiometer (MODIS) 1-kilometer satellite land surface temperature and gridded weather datasets from the Global Data Assimilation System (GDAS). County-level CU estimates for 1995 were assembled and referenced to 1-kilometer grid cells to synchronize with the SSEB ET estimates. Both datasets were seasonally and spatially weighted to represent the irrigation season (June-September) and those lands that were identified in the county as irrigated. A strong relation (R2 greater than 0.7) was determined between NWUIP CU and SSEB ET data. Regionally, the relation is stronger in arid western states than in humid eastern states, and positive and negative biases are both present at state-level comparisons. SSEB ET estimates can play a major role in monitoring and updating county-based CU estimates by providing a quick and cost-effective method to detect major year-to-year changes at county levels, as well as providing a means to disaggregate county-based ET estimates to sub-county levels. More research is needed to identify the causes for differences in state-based relations.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125005","collaboration":"Groundwater Resources Program","usgsCitation":"Maupin, M.A., Senay, G., Kenny, J., and Savoca, M.E., 2012, A comparison of consumptive-use estimates derived from the simplified surface energy balance approach and indirect reporting methods: U.S. Geological Survey Scientific Investigations Report 2012-5005, iv, 8 p., https://doi.org/10.3133/sir20125005.","productDescription":"iv, 8 p.","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":116452,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5005.jpg"},{"id":115711,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5005/","linkFileType":{"id":5,"text":"html"}},{"id":338663,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5005/pdf/sir20125005.pdf"}],"country":"United States","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059e359e4b0c8380cd45fa9","contributors":{"authors":[{"text":"Maupin, Molly A. 0000-0002-2695-5505 mamaupin@usgs.gov","orcid":"https://orcid.org/0000-0002-2695-5505","contributorId":951,"corporation":false,"usgs":true,"family":"Maupin","given":"Molly","email":"mamaupin@usgs.gov","middleInitial":"A.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":356131,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Senay, Gabriel B. 0000-0002-8810-8539","orcid":"https://orcid.org/0000-0002-8810-8539","contributorId":66808,"corporation":false,"usgs":true,"family":"Senay","given":"Gabriel B.","affiliations":[],"preferred":false,"id":356133,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kenny, Joan F.","contributorId":69132,"corporation":false,"usgs":true,"family":"Kenny","given":"Joan F.","affiliations":[],"preferred":false,"id":356134,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Savoca, Mark E. mesavoca@usgs.gov","contributorId":1961,"corporation":false,"usgs":true,"family":"Savoca","given":"Mark","email":"mesavoca@usgs.gov","middleInitial":"E.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":356132,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70007227,"text":"ds660 - 2012 - Construction diagrams, geophysical logs, and lithologic descriptions for boreholes USGS 103, 105, 108, 131, 135, NRF-15, and NRF-16, Idaho National Laboratory, Idaho","interactions":[],"lastModifiedDate":"2012-03-08T17:16:43","indexId":"ds660","displayToPublicDate":"2012-01-26T00:00:00","publicationYear":"2012","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":"660","title":"Construction diagrams, geophysical logs, and lithologic descriptions for boreholes USGS 103, 105, 108, 131, 135, NRF-15, and NRF-16, Idaho National Laboratory, Idaho","docAbstract":"This report, prepared in cooperation with the U.S. Department of Energy, summarizes construction, geophysical, and lithologic data collected from about 4,509 feet of core from seven boreholes deepened or drilled by the U.S. Geological Survey (USGS), Idaho National Laboratory (INL) Project Office, from 2006 to 2009 at the INL. USGS 103, 105, 108, and 131 were deepened and cored from 759 to 1,307 feet, 800 to 1,409 feet, 760 to 1,218 feet, and 808 to 1,239 feet, respectively. Boreholes USGS 135, NRF-15, and NRF-16 were drilled and continuously cored from land surface to 1,198, 759, and 425 feet, respectively. Cores were photographed and digitally logged by using commercially available software. Borehole descriptions summarize location, completion date, and amount and type of core recovered.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds660","collaboration":"Prepared in cooperation with the U.S. Department of Energy, DOE/ID-22217","usgsCitation":"Hodges, M., Orr, S.M., Potter, K.E., and LeMaitre, T., 2012, Construction diagrams, geophysical logs, and lithologic descriptions for boreholes USGS 103, 105, 108, 131, 135, NRF-15, and NRF-16, Idaho National Laboratory, Idaho: U.S. Geological Survey Data Series 660, vi, 33 p.; Appendices; Downloadable Appendices A-G, https://doi.org/10.3133/ds660.","productDescription":"vi, 33 p.; Appendices; Downloadable Appendices A-G","temporalStart":"2006-01-01","temporalEnd":"2009-12-31","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":116448,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_660.jpg"},{"id":115709,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/660/","linkFileType":{"id":5,"text":"html"}}],"scale":"24000","projection":"Universal Transverse Mercator projection, Zone 12","datum":"Datum is North American Datum of 1927","country":"United States","state":"Idaho","otherGeospatial":"Eastern Snake River Plain;Idaho National Laboratory","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -113.5,43.25 ], [ -113.5,44 ], [ -112.5,44 ], [ -112.5,43.25 ], [ -113.5,43.25 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059fa17e4b0c8380cd4d926","contributors":{"authors":[{"text":"Hodges, Mary K.V.","contributorId":66848,"corporation":false,"usgs":true,"family":"Hodges","given":"Mary K.V.","affiliations":[],"preferred":false,"id":356144,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Orr, Stephanie M.","contributorId":22089,"corporation":false,"usgs":true,"family":"Orr","given":"Stephanie","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":356142,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Potter, Katherine E.","contributorId":76886,"corporation":false,"usgs":true,"family":"Potter","given":"Katherine","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":356145,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"LeMaitre, Tynan","contributorId":51455,"corporation":false,"usgs":true,"family":"LeMaitre","given":"Tynan","email":"","affiliations":[],"preferred":false,"id":356143,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70007228,"text":"ds657 - 2012 - Selected water-quality data from the Cedar River and Cedar Rapids well fields, Cedar Rapids, Iowa, 2006-10","interactions":[],"lastModifiedDate":"2012-03-08T17:16:43","indexId":"ds657","displayToPublicDate":"2012-01-26T00:00:00","publicationYear":"2012","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":"657","title":"Selected water-quality data from the Cedar River and Cedar Rapids well fields, Cedar Rapids, Iowa, 2006-10","docAbstract":"The Cedar River alluvial aquifer is the primary source of municipal water in the Cedar Rapids, Iowa area. Municipal wells are completed in the alluvial aquifer approximately 40 to 80 feet below land surface. The City of Cedar Rapids and the U.S. Geological Survey have been conducting a cooperative study of the groundwater-flow system and water quality of the aquifer since 1992. Cooperative reports between the City of Cedar Rapids and the U.S. Geological Survey have documented hydrologic and water-quality data, geochemistry, and groundwater models. Water-quality samples were collected for studies involving well field monitoring, trends, source-water protection, groundwater geochemistry, surface-water-groundwater interaction, and pesticides in groundwater and surface water. Water-quality analyses were conducted for major ions (boron, bromide, calcium, chloride, fluoride, iron, magnesium, manganese, potassium, silica, sodium, and sulfate), nutrients (ammonia as nitrogen, nitrite as nitrogen, nitrite plus nitrate as nitrogen, and orthophosphate as phosphorus), dissolved organic carbon, and selected pesticides including two degradates of the herbicide atrazine. Physical characteristics (alkalinity, dissolved oxygen, pH, specific conductance and water temperature) were measured in the field and recorded for each water sample collected. This report presents the results of routine water-quality data-collection activities from January 2006 through December 2010. Methods of data collection, quality-assurance, and water-quality analyses are presented. Data include the results of water-quality analyses from quarterly sampling from monitoring wells, municipal wells, and the Cedar River.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds657","collaboration":"Prepared in cooperation with the City of Cedar Rapids","usgsCitation":"Littin, G.R., 2012, Selected water-quality data from the Cedar River and Cedar Rapids well fields, Cedar Rapids, Iowa, 2006-10: U.S. Geological Survey Data Series 657, vi, 32 p., https://doi.org/10.3133/ds657.","productDescription":"vi, 32 p.","onlineOnly":"Y","temporalStart":"2006-01-01","temporalEnd":"2010-12-31","costCenters":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"links":[{"id":116449,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_657.jpg"},{"id":115710,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/657/","linkFileType":{"id":5,"text":"html"}}],"scale":"1000000","projection":"Universal Transverse Mercator projection, Zone 15","datum":"North American Datum of 1983","country":"United States","state":"Iowa","county":"Linn","city":"Cedar Rapids","otherGeospatial":"Cedar River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -91.75,41.96666666666667 ], [ -91.75,42.03333333333333 ], [ -91.66666666666667,42.03333333333333 ], [ -91.66666666666667,41.96666666666667 ], [ -91.75,41.96666666666667 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505b8cc3e4b08c986b3180ef","contributors":{"authors":[{"text":"Littin, Gregory R. grlittin@usgs.gov","contributorId":1732,"corporation":false,"usgs":true,"family":"Littin","given":"Gregory","email":"grlittin@usgs.gov","middleInitial":"R.","affiliations":[],"preferred":true,"id":356146,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70007226,"text":"cir1371 - 2012 - Lithium use in batteries","interactions":[],"lastModifiedDate":"2015-02-18T10:04:51","indexId":"cir1371","displayToPublicDate":"2012-01-26T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1371","title":"Lithium use in batteries","docAbstract":"Lithium has a number of uses but one of the most valuable is as a component of high energy-density rechargeable lithium-ion batteries. Because of concerns over carbon dioxide footprint and increasing hydrocarbon fuel cost (reduced supply), lithium may become even more important in large batteries for powering all-electric and hybrid vehicles. It would take 1.4 to 3.0 kilograms of lithium equivalent (7.5 to 16.0 kilograms of lithium carbonate) to support a 40-mile trip in an electric vehicle before requiring recharge. This could create a large demand for lithium. Estimates of future lithium demand vary, based on numerous variables. Some of those variables include the potential for recycling, widespread public acceptance of electric vehicles, or the possibility of incentives for converting to lithium-ion-powered engines. Increased electric usage could cause electricity prices to increase. Because of reduced demand, hydrocarbon fuel prices would likely decrease, making hydrocarbon fuel more desirable. In 2009, 13 percent of worldwide lithium reserves, expressed in terms of contained lithium, were reported to be within hard rock mineral deposits, and 87 percent, within brine deposits. Most of the lithium recovered from brine came from Chile, with smaller amounts from China, Argentina, and the United States. Chile also has lithium mineral reserves, as does Australia. Another source of lithium is from recycled batteries. When lithium-ion batteries begin to power vehicles, it is expected that battery recycling rates will increase because vehicle battery recycling systems can be used to produce new lithium-ion batteries.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1371","usgsCitation":"Goonan, T.G., 2012, Lithium use in batteries: U.S. Geological Survey Circular 1371, iv, 14 p., https://doi.org/10.3133/cir1371.","productDescription":"iv, 14 p.","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":218,"text":"Denver Federal Center","active":false,"usgs":true}],"links":[{"id":116453,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/cir_1371.gif"},{"id":298023,"rank":101,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1371/pdf/circ1371_508.pdf","text":"Report","size":"1.31 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":115708,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/circ/1371/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a482de4b0c8380cd67c7d","contributors":{"authors":[{"text":"Goonan, Thomas G. goonan@usgs.gov","contributorId":2761,"corporation":false,"usgs":true,"family":"Goonan","given":"Thomas","email":"goonan@usgs.gov","middleInitial":"G.","affiliations":[{"id":432,"text":"National Minerals Information Center","active":true,"usgs":true}],"preferred":true,"id":356141,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70005180,"text":"70005180 - 2012 - Using existing data to estimate aquifer properties, Great Lakes Region, USA","interactions":[],"lastModifiedDate":"2012-06-14T01:01:39","indexId":"70005180","displayToPublicDate":"2012-01-24T09:55:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1861,"text":"Ground Water","active":true,"publicationSubtype":{"id":10}},"title":"Using existing data to estimate aquifer properties, Great Lakes Region, USA","docAbstract":"To determine specific storage and porosity, areally limited and time-consuming aquifer tests are frequently done. Hydrogeologic studies often do not have the resources to collect such data and rely on existing data sources for aquifer properties. An alternative tool for determining these aquifer properties is the analysis of earth tides. The objective of this study was to determine whether existing water-level and barometric-pressure data could be used to determine aquifer properties, such as porosity and specific storage, on a regional scale. In this study, national databases from the Great Lakes Region were queried for continuous records of groundwater-level and barometric-pressure data. Records from 37 selected wells were then analyzed for barometric efficiency and earth-tide responses. Specific-storage (Ss) and porosity values were determined, and the quality of the results were assessed with a measure of the \"goodness of fit\" (percent variance) of reconstruction of the response. Records from wells completed in several aquifer systems were analyzed with varying degrees of success. Aquifer Ss values ranging from 5.9 x 10-8 to 3.8 x 10-6/m were derived, with percent variance of reconstruction ranging from 1% to 78%. Comparisons with aquifer and laboratory testing of Ss and porosity are favorable if the percent variance of reconstruction is above about 30%. Although the earth-tide-analysis method is not suitable for every situation, the Ss and porosity of aquifers can, in many places, be estimated with existing water-level and barometric-pressure data or with data that are relatively inexpensive to collect.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Ground Water","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"National Ground Water Assocation","publisherLocation":"Westerville, OH","doi":"10.1111/j.1745-6584.2011.00848.x","usgsCitation":"Darner, R.A., and Sheets, R., 2012, Using existing data to estimate aquifer properties, Great Lakes Region, USA: Ground Water, v. 50, no. 3, https://doi.org/10.1111/j.1745-6584.2011.00848.x.","costCenters":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"links":[{"id":257571,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":257554,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.1745-6584.2011.00848.x","linkFileType":{"id":5,"text":"html"}}],"country":"United States","otherGeospatial":"Great Lakes","volume":"50","issue":"3","noUsgsAuthors":false,"publicationDate":"2011-07-28","publicationStatus":"PW","scienceBaseUri":"505bc04be4b08c986b32a03c","contributors":{"authors":[{"text":"Darner, Robert A. 0000-0003-1333-8265 radarner@usgs.gov","orcid":"https://orcid.org/0000-0003-1333-8265","contributorId":1972,"corporation":false,"usgs":true,"family":"Darner","given":"Robert","email":"radarner@usgs.gov","middleInitial":"A.","affiliations":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":352051,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sheets, Rodney A. rasheets@usgs.gov","contributorId":1848,"corporation":false,"usgs":true,"family":"Sheets","given":"Rodney A.","email":"rasheets@usgs.gov","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":352050,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70118322,"text":"70118322 - 2012 - Inflation rates, rifts, and bands in a pāhoehoe sheet flow","interactions":[],"lastModifiedDate":"2019-05-30T12:33:11","indexId":"70118322","displayToPublicDate":"2012-01-23T13:30:09","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1820,"text":"Geosphere","active":true,"publicationSubtype":{"id":10}},"title":"Inflation rates, rifts, and bands in a pāhoehoe sheet flow","docAbstract":"The margins of sheet flows—pāhoehoe lavas emplaced on surfaces sloping <2°—are typically delineated by structures that form to accommodate vertical flow inflation. We refer to these structures as inflation rifts. The surfaces of inflation rifts almost always exhibit bands of varying color and texture. Various explanations for the bands have been proposed, but active band formation has never been documented. In order to test our hypothesis that banding is caused by changes in the inflation rate, we collected time-lapse photographs of the margin of an actively inflating flow and simultaneously measured the height of the flow with an extensometer. Data collected over a period of ∼1 d indicate that the height of the flow margin changed in a stepwise manner and that rate changes correlate with band formation. This confirms our hypothesis.
\nInflation and rift-band formation is probably cyclic, because the pattern we observed suggests episodic or crude cyclic behavior. Furthermore, some inflation rifts contain numerous bands whose spacing and general appearances are remarkably similar.
\nWe propose a conceptual model wherein the inferred cyclicity is due to the competition between the fluid pressure in the flow's liquid core and the tensile strength of the viscoelastic layer where it is weakest—in inflation rifts. The viscoelastic layer consists of lava that has cooled to temperatures between 800 and 1070 °C. This layer is the key parameter in our model because, in its absence, rift banding and stepwise changes in the flow height would not occur.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Geosphere","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Geological Society of America","publisherLocation":"Boulder, CO","doi":"10.1130/GES00656.1","usgsCitation":"Hoblitt, R.P., Orr, T., Heliker, C., Denlinger, R.P., Hon, K., and Cervelli, P.F., 2012, Inflation rates, rifts, and bands in a pāhoehoe sheet flow: Geosphere, v. 8, no. 1, p. 179-195, https://doi.org/10.1130/GES00656.1.","productDescription":"17 p.","startPage":"179","endPage":"195","numberOfPages":"17","costCenters":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"links":[{"id":474585,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges00656.1","text":"Publisher Index Page"},{"id":291178,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":291177,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1130/GES00656.1"}],"volume":"8","issue":"1","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57f7f537e4b0bc0bec0a14d8","contributors":{"authors":[{"text":"Hoblitt, Richard P. rhoblitt@usgs.gov","contributorId":1937,"corporation":false,"usgs":true,"family":"Hoblitt","given":"Richard","email":"rhoblitt@usgs.gov","middleInitial":"P.","affiliations":[{"id":157,"text":"Cascades Volcano Observatory","active":false,"usgs":true}],"preferred":false,"id":496753,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Orr, Tim R.","contributorId":86859,"corporation":false,"usgs":true,"family":"Orr","given":"Tim R.","affiliations":[{"id":336,"text":"Hawaiian Volcano Observatory","active":false,"usgs":true}],"preferred":false,"id":496757,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Heliker, Christina","contributorId":53353,"corporation":false,"usgs":true,"family":"Heliker","given":"Christina","affiliations":[{"id":336,"text":"Hawaiian Volcano Observatory","active":false,"usgs":true}],"preferred":false,"id":496756,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Denlinger, Roger P. 0000-0003-0930-0635 roger@usgs.gov","orcid":"https://orcid.org/0000-0003-0930-0635","contributorId":2679,"corporation":false,"usgs":true,"family":"Denlinger","given":"Roger","email":"roger@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"preferred":true,"id":496754,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hon, Ken","contributorId":19163,"corporation":false,"usgs":true,"family":"Hon","given":"Ken","affiliations":[],"preferred":false,"id":496755,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Cervelli, Peter F. 0000-0001-6765-1009 pcervelli@usgs.gov","orcid":"https://orcid.org/0000-0001-6765-1009","contributorId":1936,"corporation":false,"usgs":true,"family":"Cervelli","given":"Peter","email":"pcervelli@usgs.gov","middleInitial":"F.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":496752,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ]}