The extent to which faults exhibit temporally varying slip rates has important consequences for models of fault mechanics and probabilistic seismic hazard. Here, we explore the temporal behavior of the dextral‐slip Warm Springs Valley fault system, which is part of a network of closely spaced (10–20 km) faults in the northern Walker Lane (California–Nevada border). We develop a late Quaternary slip record for the fault using Quaternary mapping and high‐resolution topographic data from airborne Light Distance and Ranging (LiDAR). The faulted Fort Sage alluvial fan (40.06° N, 119.99° W) is dextrally displaced 98+42/-43 m, and we estimate the age of the alluvial fan to be 41.4+10.0/-4.8 to 55.7±9.2 ka, based on a terrestrial cosmogenic 10Be depth profile and 36Cl analyses on basalt boulders, respectively. The displacement and age constraints for the fan yield a slip rate of 1.8 +0.8/-0.8 mm/yr to 2.4 +1.2/-1.1 mm/yr (2σ) along the northern Warm Springs Valley fault system for the past 41.4–55.7 ka. In contrast to this longer‐term slip rate, shorelines associated with the Sehoo highstand of Lake Lahontan (~15.8 ka) adjacent to the Fort Sage fan are dextrally faulted at most 3 m, which limits a maximum post‐15.8 ka slip rate to 0.2 mm/yr. These relations indicate that the post‐Lahontan slip rate on the fault is only about one‐tenth the longer‐term (41–56 ka) average slip rate. This apparent slip‐rate variation may be related to co‐dependent interaction with the nearby Honey Lake fault system, which shows evidence of an accelerated period of mid‐Holocene earthquakes.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120120020","usgsCitation":"Gold, R., dePolo, C., Briggs, R.W., Crone, A., and Goss, J., 2013, Late quaternary slip-rate variations along the Warm Springs Valley fault system, northern Walker Lane, California-Nevada border: Bulletin of the Seismological Society of America, v. 103, no. 1, p. 542-558, https://doi.org/10.1785/0120120020.","productDescription":"17 p.","startPage":"542","endPage":"558","ipdsId":"IP-038135","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":267417,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Nevada","otherGeospatial":"Walker Lane","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.28106689453125,\n 39.74943369178247\n ],\n [\n -119.74822998046875,\n 39.74943369178247\n ],\n [\n -119.74822998046875,\n 40.02551125229787\n ],\n [\n -120.28106689453125,\n 40.02551125229787\n ],\n [\n -120.28106689453125,\n 39.74943369178247\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"103","issue":"1","noUsgsAuthors":false,"publicationDate":"2013-02-05","publicationStatus":"PW","scienceBaseUri":"511e158de4b071e86a19a463","contributors":{"authors":[{"text":"Gold, Ryan","contributorId":97400,"corporation":false,"usgs":true,"family":"Gold","given":"Ryan","affiliations":[],"preferred":false,"id":464324,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"dePolo, Craig","contributorId":87433,"corporation":false,"usgs":true,"family":"dePolo","given":"Craig","affiliations":[],"preferred":false,"id":464323,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Briggs, Richard W. 0000-0001-8108-0046 rbriggs@usgs.gov","orcid":"https://orcid.org/0000-0001-8108-0046","contributorId":4136,"corporation":false,"usgs":true,"family":"Briggs","given":"Richard","email":"rbriggs@usgs.gov","middleInitial":"W.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":464321,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Crone, Anthony","contributorId":20624,"corporation":false,"usgs":true,"family":"Crone","given":"Anthony","affiliations":[],"preferred":false,"id":464322,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Goss, John","contributorId":240591,"corporation":false,"usgs":false,"family":"Goss","given":"John","email":"","affiliations":[],"preferred":false,"id":798516,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70043201,"text":"70043201 - 2013 - Use of classification trees to apportion single echo detections to species: Application to the pelagic fish community of Lake Superior","interactions":[],"lastModifiedDate":"2013-06-03T10:56:30","indexId":"70043201","displayToPublicDate":"2013-02-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1661,"text":"Fisheries Research","active":true,"publicationSubtype":{"id":10}},"title":"Use of classification trees to apportion single echo detections to species: Application to the pelagic fish community of Lake Superior","docAbstract":"Acoustic methods are used to estimate the density of pelagic fish in large lakes with results of midwater trawling used to assign species composition. Apportionment in lakes having mixed species can be challenging because only a small fraction of the water sampled acoustically is sampled with trawl gear. Here we describe a new method where single echo detections (SEDs) are assigned to species based on classification tree models developed from catch data that separate species based on fish size and the spatial habitats they occupy. During the summer of 2011, we conducted a spatially-balanced lake-wide acoustic and midwater trawl survey of Lake Superior. A total of 51 sites in four bathymetric depth strata (0–30 m, 30–100 m, 100–200 m, and >200 m) were sampled. We developed classification tree models for each stratum and found fish length was the most important variable for separating species. To apply these trees to the acoustic data, we needed to identify a target strength to length (TS-to-L) relationship appropriate for all abundant Lake Superior pelagic species. We tested performance of 7 general (i.e., multi-species) relationships derived from three published studies. The best-performing relationship was identified by comparing predicted and observed catch compositions using a second independent Lake Superior data set. Once identified, the relationship was used to predict lengths of SEDs from the lake-wide survey, and the classification tree models were used to assign each SED to a species. Exotic rainbow smelt (Osmerus mordax) were the most common species at bathymetric depths <100 m with their population estimated at 755 million (3.4 kt). Kiyi (Coregonus kiyi) were the most abundant species at depths >100 m (384 million; 6.0 kt). Cisco (Coregonus artedi) were widely distributed over all strata with their population estimated at 182 million (44 kt). The apportionment method we describe should be transferable to other large lakes provided fish are not tightly aggregated, and an appropriate TS-to-L relationship for abundant pelagic fish species can be determined.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Fisheries Research","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Elsevier","doi":"10.1016/j.fishres.2012.12.012","usgsCitation":"Yule, D., Adams, J.V., Hrabik, T.R., Vinson, M., Woiak, Z., and Ahrenstroff, T.D., 2013, Use of classification trees to apportion single echo detections to species: Application to the pelagic fish community of Lake Superior: Fisheries Research, v. 140, p. 123-132, https://doi.org/10.1016/j.fishres.2012.12.012.","productDescription":"10 p.","startPage":"123","endPage":"132","ipdsId":"IP-043013","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":273087,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":273085,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1016/j.fishres.2012.12.012"}],"country":"United States","otherGeospatial":"Lake Superior","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -89.562,46.4146 ], [ -89.562,48.8488 ], [ -84.354,48.8488 ], [ -84.354,46.4146 ], [ -89.562,46.4146 ] ] ] } } ] }","volume":"140","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51adbaebe4b07c214e64bd4b","contributors":{"authors":[{"text":"Yule, Daniel L.","contributorId":92130,"corporation":false,"usgs":true,"family":"Yule","given":"Daniel L.","affiliations":[],"preferred":false,"id":473158,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Adams, Jean V. 0000-0002-9101-068X jvadams@usgs.gov","orcid":"https://orcid.org/0000-0002-9101-068X","contributorId":3140,"corporation":false,"usgs":true,"family":"Adams","given":"Jean","email":"jvadams@usgs.gov","middleInitial":"V.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":473153,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hrabik, Thomas R.","contributorId":35614,"corporation":false,"usgs":false,"family":"Hrabik","given":"Thomas","email":"","middleInitial":"R.","affiliations":[{"id":6915,"text":"University of Minnesota - Duluth","active":true,"usgs":false}],"preferred":false,"id":473154,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vinson, Mark R.","contributorId":91774,"corporation":false,"usgs":true,"family":"Vinson","given":"Mark R.","affiliations":[],"preferred":false,"id":473157,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Woiak, Zebadiah","contributorId":37232,"corporation":false,"usgs":true,"family":"Woiak","given":"Zebadiah","affiliations":[],"preferred":false,"id":473155,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ahrenstroff, Tyler D.","contributorId":64540,"corporation":false,"usgs":true,"family":"Ahrenstroff","given":"Tyler","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":473156,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70193602,"text":"70193602 - 2013 - The utility of atmospheric analyses for the mitigation of artifacts in InSAR","interactions":[],"lastModifiedDate":"2017-11-02T16:06:14","indexId":"70193602","displayToPublicDate":"2013-02-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2314,"text":"Journal of Geophysical Research B: Solid Earth","active":true,"publicationSubtype":{"id":10}},"title":"The utility of atmospheric analyses for the mitigation of artifacts in InSAR","docAbstract":"The numerical weather models (NWMs) developed by the meteorological community are able to provide accurate analyses of the current state of the atmosphere in addition to the predictions of the future state. To date, most attempts to apply the NWMs to estimate the refractivity of the atmosphere at the time of satellite synthetic aperture radar (SAR) data acquisitions have relied on predictive models. We test the hypothesis that performing a final assimilative routine, ingesting all available meteorological observations for the times of SAR acquisitions, and generating customized analyses of the atmosphere at those times will better mitigate atmospheric artifacts in differential interferograms. We find that, for our study area around Mount St. Helens (Amboy, Washington, USA), this approach is unable to model the refractive changes and provides no mean benefit for interferogram analysis. The performance is improved slightly by ingesting atmospheric delay estimates derived from the limited local GPS network; however, the addition of water vapor products from the GOES satellites reduces the quality of the corrections. We interpret our results to indicate that, even with this advanced approach, NWMs are not a reliable mitigation technique for regions such as Mount St. Helens with highly variable moisture fields and complex topography and atmospheric dynamics. It is possible, however, that the addition of more spatially dense meteorological data to constrain the analyses might significantly improve the performance of weather modeling of atmospheric artifacts in satellite radar interferograms.
","language":"English","publisher":"AGU","doi":"10.1002/jgrb.50093","usgsCitation":"Foster, J., Kealy, J., Cherubini, T., Businger, S., Lu, Z., and Murphy, M., 2013, The utility of atmospheric analyses for the mitigation of artifacts in InSAR: Journal of Geophysical Research B: Solid Earth, v. 118, no. 2, p. 748-758, https://doi.org/10.1002/jgrb.50093.","productDescription":"11 p.","startPage":"748","endPage":"758","ipdsId":"IP-044768","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":496358,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/11603/40220","text":"External Repository"},{"id":348134,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"118","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2013-02-26","publicationStatus":"PW","scienceBaseUri":"59fc2eaee4b0531197b27fe4","contributors":{"authors":[{"text":"Foster, James","contributorId":38598,"corporation":false,"usgs":true,"family":"Foster","given":"James","affiliations":[],"preferred":false,"id":719963,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kealy, John","contributorId":199761,"corporation":false,"usgs":false,"family":"Kealy","given":"John","email":"","affiliations":[],"preferred":false,"id":719964,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Cherubini, Tiziana","contributorId":199762,"corporation":false,"usgs":false,"family":"Cherubini","given":"Tiziana","email":"","affiliations":[],"preferred":false,"id":719965,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Businger, S.","contributorId":65331,"corporation":false,"usgs":true,"family":"Businger","given":"S.","affiliations":[],"preferred":false,"id":719966,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lu, Zhong 0000-0001-9181-1818 lu@usgs.gov","orcid":"https://orcid.org/0000-0001-9181-1818","contributorId":901,"corporation":false,"usgs":true,"family":"Lu","given":"Zhong","email":"lu@usgs.gov","affiliations":[],"preferred":true,"id":719967,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Murphy, Michael","contributorId":199763,"corporation":false,"usgs":false,"family":"Murphy","given":"Michael","affiliations":[],"preferred":false,"id":719968,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70176182,"text":"70176182 - 2013 - Mapping river bathymetry with a small footprint green LiDAR: Applications and challenges","interactions":[],"lastModifiedDate":"2016-09-07T14:45:13","indexId":"70176182","displayToPublicDate":"2013-02-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2529,"text":"Journal of the American Water Resources Association","active":true,"publicationSubtype":{"id":10}},"title":"Mapping river bathymetry with a small footprint green LiDAR: Applications and challenges","docAbstract":"Airborne bathymetric Light Detection And Ranging (LiDAR) systems designed for coastal and marine surveys are increasingly sought after for high-resolution mapping of fluvial systems. To evaluate the potential utility of bathymetric LiDAR for applications of this kind, we compared detailed surveys collected using wading and sonar techniques with measurements from the United States Geological Survey’s hybrid topographic⁄ bathymetric Experimental Advanced Airborne Research LiDAR (EAARL). These comparisons, based upon data collected from the Trinity and Klamath Rivers, California, and the Colorado River, Colorado, demonstrated\nthat environmental conditions and postprocessing algorithms can influence the accuracy and utility of these surveys and must be given consideration. These factors can lead to mapping errors that can have a direct bearing on derivative analyses such as hydraulic modeling and habitat assessment. We discuss the water and substrate characteristics of the sites, compare the conventional and remotely sensed river-bed topographies, and investigate the laser waveforms reflected from submerged targets to provide an evaluation as to the suitability and accuracy of the EAARL system and associated processing algorithms for riverine mapping applications.","language":"English","publisher":"Journal of the American Water Resources Association","doi":"10.1111/jawr.12008","usgsCitation":"Kinzel, P.J., Legleiter, C.J., and Nelson, J.M., 2013, Mapping river bathymetry with a small footprint green LiDAR: Applications and challenges: Journal of the American Water Resources Association, v. 49, no. 1, p. 183-204, https://doi.org/10.1111/jawr.12008.","productDescription":"12 p.","startPage":"183","endPage":"204","ipdsId":"IP-038143","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":328152,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"49","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2012-12-03","publicationStatus":"PW","scienceBaseUri":"57c7ffbae4b0f2f0cebfc2f5","contributors":{"authors":[{"text":"Kinzel, Paul J. 0000-0002-6076-9730 pjkinzel@usgs.gov","orcid":"https://orcid.org/0000-0002-6076-9730","contributorId":743,"corporation":false,"usgs":true,"family":"Kinzel","given":"Paul","email":"pjkinzel@usgs.gov","middleInitial":"J.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":true,"id":647631,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Legleiter, Carl J. 0000-0003-0940-8013 cjl@usgs.gov","orcid":"https://orcid.org/0000-0003-0940-8013","contributorId":169002,"corporation":false,"usgs":true,"family":"Legleiter","given":"Carl","email":"cjl@usgs.gov","middleInitial":"J.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":647632,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nelson, Jonathan M. 0000-0002-7632-8526 jmn@usgs.gov","orcid":"https://orcid.org/0000-0002-7632-8526","contributorId":2812,"corporation":false,"usgs":true,"family":"Nelson","given":"Jonathan","email":"jmn@usgs.gov","middleInitial":"M.","affiliations":[{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":647630,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70188522,"text":"70188522 - 2013 - Diatom evidence for the onset of Pliocene cooling from AND-1B, McMurdo Sound, Antarctica","interactions":[],"lastModifiedDate":"2018-03-23T12:22:36","indexId":"70188522","displayToPublicDate":"2013-01-31T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2996,"text":"Palaeogeography, Palaeoclimatology, Palaeoecology","printIssn":"0031-0182","active":true,"publicationSubtype":{"id":10}},"title":"Diatom evidence for the onset of Pliocene cooling from AND-1B, McMurdo Sound, Antarctica","docAbstract":"The late Pliocene, ~ 3.3–3.0 Ma, is the most recent interval of sustained global warmth in the geologic past. This window is the focus of climate reconstruction efforts by the U.S. Geological Survey's Pliocene Research, Interpretation, and Synoptic Mapping (PRISM) Data/Model Cooperative, and may provide a useful climate analog for the coming century. Reconstructions of past surface ocean conditions proximal to the Antarctic continent are essential to understanding the sensitivity of the cryosphere to this key interval in Earth's climate evolution. An exceptional marine sediment core collected from the southwestern Ross Sea (78° S), Antarctica, during ANDRILL's McMurdo Ice Shelf Project preserves evidence of dramatic fluctuations between grounded ice and productive, open ocean conditions during the late Pliocene, reflecting orbitally-paced glacial/interglacial cycling. In this near-shore record, diatom-rich sediments are recovered from interglacial intervals; two of these diatomites, from ~ 3.2 Ma and 3.03 Ma, are within the PRISM chronologic window. The diatom assemblages identified in PRISM-age late Pliocene diatom-rich sediments are distinct from those in mid-Pliocene and later Pliocene/Pleistocene intervals recovered from AND-1B, and comprise both extant taxa with well-constrained ecological preferences and a diverse extinct flora, some members of which are previously undescribed from Antarctic sediments. Both units are dominated by Chaetoceros resting spores, an indicator of high productivity and stratification that is present at much lower abundance in materials both older and younger than the PRISM-age sediments. Newly described species of the genus Fragilariopsis, which first appear in the AND-1B record at 3.2 Ma, are the most abundant extinct members of the PRISM-age assemblages. Other extant species with established environmental affinities, such as Fragilariopsis sublinearis, F. curta, Stellarima microtrias, and Thalassiothrix antarctica, are present at lower abundances. Environmental inferences drawn from extant diatom assemblages are in good agreement with those from Chaetoceros resting spores and the Fragilariopsis radiation. All three lines of evidence indicate the onset of late Pliocene cooling in the Ross Sea near-shore environment at 3.2 Ma, with intensification and possible regional persistence of summer sea ice by 3.03 Ma. An important implication of this research is the indication that the Ross Ice Shelf fluctuated dramatically on orbital timescales at a time when nearshore Antarctic conditions were only modestly warmer than present.
","language":"English","publisher":"Palaeogeography, Palaeoclimatology, Palaeoecology","doi":"10.1016/j.palaeo.2012.10.014","usgsCitation":"Riesselman, C., and Dunbar, R.B., 2013, Diatom evidence for the onset of Pliocene cooling from AND-1B, McMurdo Sound, Antarctica: Palaeogeography, Palaeoclimatology, Palaeoecology, v. 369, p. 136-153, https://doi.org/10.1016/j.palaeo.2012.10.014.","productDescription":"18 p. ","startPage":"136","endPage":"153","ipdsId":"IP-033564","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":342499,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Antarctica, McMurdo Sound, Ross Ice Shelf, Ross Sea","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -210.9375,\n -80.70399666821143\n ],\n [\n -38.3203125,\n -80.70399666821143\n ],\n [\n -38.3203125,\n -65.21989393613208\n ],\n [\n -210.9375,\n -65.21989393613208\n ],\n [\n -210.9375,\n -80.70399666821143\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"369","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59424b3ce4b0764e6c65dc71","contributors":{"authors":[{"text":"Riesselman, Christina 0000-0002-2436-4306 criesselman@usgs.gov","orcid":"https://orcid.org/0000-0002-2436-4306","contributorId":4290,"corporation":false,"usgs":true,"family":"Riesselman","given":"Christina","email":"criesselman@usgs.gov","affiliations":[],"preferred":true,"id":698131,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dunbar, R. B.","contributorId":192914,"corporation":false,"usgs":false,"family":"Dunbar","given":"R.","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":698132,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70043035,"text":"ds709M - 2013 - Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Panjsher Valley mineral district in Afghanistan: Chapter M in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","interactions":[],"lastModifiedDate":"2013-02-01T11:11:12","indexId":"ds709M","displayToPublicDate":"2013-01-31T00:00:00","publicationYear":"2013","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":"709","chapter":"M","title":"Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Panjsher Valley mineral district in Afghanistan: Chapter M in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","docAbstract":"The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Panjsher Valley mineral district, which has emerald and silver-iron deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA, 2009, 2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band’s picture element based on the digital values of all picture elements within a 315-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area’s local zone (42 for Panjsher Valley) and the WGS84 datum. The final image mosaics were subdivided into two overlapping tiles or quadrants because of the large size of the target area. The two image tiles (or quadrants) for the Panjsher Valley area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image. Within the Panjsher Valley study area, two subareas were designated for detailed field investigations (that is, the Emerald and Silver-Iron subareas); these subareas were extracted from the area’s image mosaic and are provided as separate embedded geotiff images.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan (DS 709)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds709M","collaboration":"Prepared in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations and the Afghanistan Geological Survey. This report is Chapter M in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan. For more information, see: Data Series 709.","usgsCitation":"Davis, P.A., and Cagney, L.E., 2013, Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Panjsher Valley mineral district in Afghanistan: Chapter M in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan: U.S. Geological Survey Data Series 709, Readme; 2 Maps: 11 x 8.5 inches and 30.93 x 30.35 inches; 8 Image Files; 8 Metadata Files; 1 Shapefile; DS 709, https://doi.org/10.3133/ds709M.","productDescription":"Readme; 2 Maps: 11 x 8.5 inches and 30.93 x 30.35 inches; 8 Image Files; 8 Metadata Files; 1 Shapefile; DS 709","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2006-01-24","costCenters":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":266840,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_709_m.jpg"},{"id":266833,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/m/index_maps/Panjsher_Valley_Area-of-Interest_Index_Map.pdf"},{"id":266834,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/m/index_maps/Panjsher_Valley_Image_Index_Map.pdf"},{"id":266835,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/709/m/index_maps/index_maps.html"},{"id":266836,"type":{"id":14,"text":"Image"},"url":"https://pubs.usgs.gov/ds/709/m/image_files/image_files.html"},{"id":266837,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/709/m/metadata/metadata.html"},{"id":266838,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/ds/709/m/shapefiles/shapefiles.html"},{"id":266839,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/ds/709/index.html"},{"id":266831,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/709/m/"},{"id":266832,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/ds/709/m/1_readme.txt"}],"country":"Afghanistan","otherGeospatial":"Panjsher Valley Mineral District","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 69.5,35.25 ], [ 69.5,35.75 ], [ 70.25,35.75 ], [ 70.25,35.25 ], [ 69.5,35.25 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"510b927fe4b0947afa3c854c","contributors":{"authors":[{"text":"Davis, Philip A. pdavis@usgs.gov","contributorId":692,"corporation":false,"usgs":true,"family":"Davis","given":"Philip","email":"pdavis@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":472811,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cagney, Laura E. 0000-0003-3282-2458 lcagney@usgs.gov","orcid":"https://orcid.org/0000-0003-3282-2458","contributorId":4744,"corporation":false,"usgs":true,"family":"Cagney","given":"Laura","email":"lcagney@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":472812,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70042722,"text":"ds706 - 2013 - Groundwater-quality data in the Western San Joaquin Valley study unit, 2010 - Results from the California GAMA Program","interactions":[],"lastModifiedDate":"2026-05-07T17:03:41.974307","indexId":"ds706","displayToPublicDate":"2013-01-31T00:00:00","publicationYear":"2013","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":"706","title":"Groundwater-quality data in the Western San Joaquin Valley study unit, 2010 - Results from the California GAMA Program","docAbstract":"Groundwater quality in the approximately 2,170-square-mile Western San Joaquin Valley (WSJV) study unit was investigated by the U.S. Geological Survey (USGS) from March to July 2010, as part of the California State Water Resources Control Board (SWRCB) Groundwater Ambient Monitoring and Assessment (GAMA) Program's Priority Basin Project (PBP). The GAMA-PBP was developed in response to the California Groundwater Quality Monitoring Act of 2001 and is being conducted in collaboration with the SWRCB and Lawrence Livermore National Laboratory (LLNL). The WSJV study unit was the twenty-ninth study unit to be sampled as part of the GAMA-PBP. The GAMA Western San Joaquin Valley study was designed to provide a spatially unbiased assessment of untreated-groundwater quality in the primary aquifer system, and to facilitate statistically consistent comparisons of untreated groundwater quality throughout California. The primary aquifer system is defined as parts of aquifers corresponding to the perforation intervals of wells listed in the California Department of Public Health (CDPH) database for the WSJV study unit. Groundwater quality in the primary aquifer system may differ from the quality in the shallower or deeper water-bearing zones; shallow groundwater may be more vulnerable to surficial contamination. In the WSJV study unit, groundwater samples were collected from 58 wells in 2 study areas (Delta-Mendota subbasin and Westside subbasin) in Stanislaus, Merced, Madera, Fresno, and Kings Counties. Thirty-nine of the wells were selected by using a spatially distributed, randomized grid-based method to provide statistical representation of the study unit (grid wells), and 19 wells were selected to aid in the understanding of aquifer-system flow and related groundwater-quality issues (understanding wells). The groundwater samples were analyzed for organic constituents (volatile organic compounds [VOCs], low-level fumigants, and pesticides and pesticide degradates), constituents of special interest (perchlorate, N-nitrosodimethylamine [NDMA], and 1,2,3-trichloropropane [1,2,3-TCP]), and naturally occurring inorganic constituents (trace elements, nutrients, dissolved organic carbon [DOC], major and minor ions, silica, total dissolved solids [TDS], alkalinity, total arsenic and iron [unfiltered] and arsenic, chromium, and iron species [filtered]). Isotopic tracers (stable isotopes of hydrogen, oxygen, and boron in water, stable isotopes of nitrogen and oxygen in dissolved nitrate, stable isotopes of sulfur in dissolved sulfate, isotopic ratios of strontium in water, stable isotopes of carbon in dissolved inorganic carbon, activities of tritium, and carbon-14 abundance), dissolved standard gases (methane, carbon dioxide, nitrogen, oxygen, and argon), and dissolved noble gases (argon, helium-4, krypton, neon, and xenon) were measured to help identify sources and ages of sampled groundwater. In total, 245 constituents and 8 water-quality indicators were measured. Quality-control samples (blanks, replicates, or matrix spikes) were collected at 16 percent of the wells in the WSJV study unit, and the results for these samples were used to evaluate the quality of the data from the groundwater samples. Blanks rarely contained detectable concentrations of any constituent, suggesting that contamination from sample collection procedures was not a significant source of bias in the data for the groundwater samples. Replicate samples all were within acceptable limits of variability. Matrix-spike recoveries were within the acceptable range (70 to 130 percent) for approximately 87 percent of the compounds. This study did not evaluate the quality of water delivered to consumers. After withdrawal, groundwater typically is treated, disinfected, and (or) blended with other waters to maintain water quality. Regulatory benchmarks apply to water that is delivered to the consumer, not to untreated groundwater. However, to provide some context for the results, concentrations of constituents measured in the untreated groundwater were compared with regulatory and non-regulatory health-based benchmarks established by the U.S. Environmental Protection Agency (USEPA) and CDPH, and to non-regulatory benchmarks established for aesthetic concerns by CDPH. Comparisons between data collected for this study and benchmarks for drinking water are for illustrative purposes only and are not indicative of compliance or non-compliance with those benchmarks. Most inorganic constituents detected in groundwater samples from the 39 grid wells were detected at concentrations less than health-based benchmarks. Detections of organic and special-interest constituents from grid wells sampled in the WSJV study unit also were less than health-based benchmarks. In total, VOCs were detected in 12 of the 39 grid wells sampled (approximately 31 percent), pesticides and pesticide degradates were detected in 9 grid wells (approximately 23 percent), and perchlorate was detected in 15 grid wells (approximately 38 percent). Trace elements, major and minor ions, and nutrients were sampled for at 39 grid wells; most concentrations were less than health-based benchmarks. Exceptions include two detections of arsenic greater than the USEPA maximum contaminant level (MCL-US) of 10 micrograms per liter (μg/L), 20 detections of boron greater than the CDPH notification level (NL-CA) of 1,000 μg/L, 2 detections of molybdenum greater than the USEPA lifetime health advisory level (HAL-US) of 40 μg/L, 1 detection of selenium greater than the MCL-US of 50 μg/L, 2 detections of strontium greater than the HAL-US of 4,000 μg/L, and 3 detections of nitrate greater than the MCL-US of 10 μg/L. Results for inorganic constituents with non-health-based benchmarks (iron, manganese, chloride, sulfate, and TDS) showed that iron concentrations greater than the CDPH secondary maximum contaminant level (SMCL-CA) of 300 μg/L were detected in five grid wells. Manganese concentrations greater than the SMCL-CA of 50 μg/L were detected in 16 grid wells. Chloride concentrations greater than the recommended SMCL-CA benchmark of 250 milligrams per liter (mg/L) were detected in 14 grid wells, and concentrations in 5 of these wells also were greater than the upper SMCL-CA benchmark of 500 mg/L. Sulfate concentrations greater than the recommended SMCL-CA benchmark of 250 mg/L were measured in 21 grid wells, and concentrations in 13 of these wells also were greater than the SMCL-CA upper benchmark of 500 mg/L. TDS concentrations greater than the SMCL-CA recommended benchmark of 500 mg/L were measured in 36 grid wells, and concentrations in 20 of these wells also were greater than the SMCL-CA upper benchmark of 1,000 mg/L.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds706","collaboration":"A product of the California Groundwater Ambient Monitoring and Assessment (GAMA) Program; Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Mathany, T., Landon, M.K., Shelton, J.L., and Belitz, K., 2013, Groundwater-quality data in the Western San Joaquin Valley study unit, 2010 - Results from the California GAMA Program: U.S. Geological Survey Data Series 706, x, 104 p., https://doi.org/10.3133/ds706.","productDescription":"x, 104 p.","numberOfPages":"116","ipdsId":"IP-027484","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":266860,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/706/"},{"id":266861,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/706/pdf/ds706.pdf"},{"id":504108,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_98125.htm","linkFileType":{"id":5,"text":"html"}},{"id":266862,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_706.jpg"}],"country":"United States","state":"California","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -0.01611111111111111,8.333333333333334E-4 ], [ -0.01611111111111111,0.0011111111111111111 ], [ -0.01638888888888889,0.0011111111111111111 ], [ -0.01638888888888889,8.333333333333334E-4 ], [ -0.01611111111111111,8.333333333333334E-4 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"510b9279e4b0947afa3c8540","contributors":{"authors":[{"text":"Mathany, Timothy M. 0000-0002-4747-5113","orcid":"https://orcid.org/0000-0002-4747-5113","contributorId":99949,"corporation":false,"usgs":true,"family":"Mathany","given":"Timothy M.","affiliations":[],"preferred":false,"id":472117,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Landon, Matthew K. 0000-0002-5766-0494 landon@usgs.gov","orcid":"https://orcid.org/0000-0002-5766-0494","contributorId":392,"corporation":false,"usgs":true,"family":"Landon","given":"Matthew","email":"landon@usgs.gov","middleInitial":"K.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":472114,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shelton, Jennifer L. 0000-0001-8508-0270 jshelton@usgs.gov","orcid":"https://orcid.org/0000-0001-8508-0270","contributorId":1155,"corporation":false,"usgs":true,"family":"Shelton","given":"Jennifer","email":"jshelton@usgs.gov","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":472116,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Belitz, Kenneth 0000-0003-4481-2345 kbelitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":442,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","email":"kbelitz@usgs.gov","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":472115,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70043022,"text":"sir20135005 - 2013 - Water quality, streamflow conditions, and annual flow-duration curves for streams of the San Juan–Chama Project, southern Colorado and northern New Mexico, 1935-2010","interactions":[],"lastModifiedDate":"2013-01-31T09:06:42","indexId":"sir20135005","displayToPublicDate":"2013-01-31T00:00:00","publicationYear":"2013","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":"2013-5005","title":"Water quality, streamflow conditions, and annual flow-duration curves for streams of the San Juan–Chama Project, southern Colorado and northern New Mexico, 1935-2010","docAbstract":"The Albuquerque–Bernalillo County Water Utility Authority supplements the municipal water supply for the Albuquerque metropolitan area, in central New Mexico, with water diverted from the Rio Grande. Water diverted from the Rio Grande for municipal use is derived from the San Juan–Chama Project, which delivers water from streams in the southern San Juan Mountains in the Colorado River Basin in southern Colorado to the Rio Chama watershed and the Rio Grande Basin in northern New Mexico. The U.S. Geological Survey, in cooperation with Albuquerque–Bernalillo County Water Utility Authority, has compiled historical streamflow and water-quality data and collected new water-quality data to characterize the water quality and streamflow conditions and annual flow variability, as characterized by annual flow-duration curves, of streams of the San Juan–Chama Project. Nonparametric statistical methods were applied to calculate annual and monthly summary statistics of streamflow, trends in streamflow conditions were evaluated with the Mann–Kendall trend test, and annual variation in streamflow conditions was evaluated with annual flow-duration curves. The study area is located in northern New Mexico and southern Colorado and includes the Rio Blanco, Little Navajo River, and Navajo River, tributaries of the San Juan River in the Colorado River Basin located in the southern San Juan Mountains, and Willow Creek and Horse Lake Creek, tributaries of the Rio Chama in the Rio Grande Basin. The quality of water in the streams in the study area generally varied by watershed on the basis of the underlying geology and the volume and source of the streamflow. Water from the Rio Blanco and Little Navajo River watersheds, primarily underlain by volcanic deposits, volcaniclastic sediments and landslide deposits derived from these materials, was compositionally similar and had low specific-conductance values relative to the other streams in the study area. Water from the Navajo River, Horse Lake Creek, and Willow Creek watersheds, which are underlain mostly by Cretaceous-aged marine shale, was compositionally similar and had large concentrations of sulfate relative to the other streams in the study area, though the water from the Navajo River had lower specific-conductance values than did the water from Horse Lake Creek above Heron Reservoir and Willow Creek above Azotea Creek. Generally, surface-water quality varied with streamflow conditions throughout the year. Streamflow in spring and summer is generally a mixture of base flow (the component of streamflow derived from groundwater discharged to the stream channel) diluted with runoff from snowmelt and precipitation events, whereas streamflow in fall and winter is generally solely base flow. Major- and trace-element concentrations in the streams sampled were lower than U.S. Environmental Protection Agency primary and secondary drinking-water standards and New Mexico Environment Department surface-water standards for the streams. In general, years with increased annual discharge, compared to years with decreased annual discharge, had a smaller percentage of discharge in March, a larger percentage of discharge in June, an interval of discharge derived from snowmelt runoff that occurred later in the year, and a larger discharge in June. Additionally, years with increased annual discharge generally had a longer duration of runoff, and the streamflow indicators occurred at dates later in the year than the years with less snowmelt runoff. Additionally, the seasonal distribution of streamflow was more strongly controlled by the change in the amount of annual discharge than by changes in streamflow over time. The variation of streamflow conditions over time at one streamflow-gaging station in the study area, Navajo River at Banded Peak Ranch, was not significantly monotonic over the period of record with a Kendall’s tau of 0.0426 and with a p-value of 0.5938 for 1937 to 2009 (a trend was considered statistically significant at a p-value ≤ 0.05). There was a relation, however, such that annual discharge was generally lower than the median during a negative Pacific Decadal Oscillation interval and higher than the median during a positive Pacific Decadal Oscillation interval. Streamflow conditions at Navajo River at Banded Peak Ranch varied nonmonotonically over time and were likely a function of complex climate pattern interactions. Similarly, the monthly distribution of streamflow varied nonmonotonically over time and was likely a function of complex climate pattern interactions that cause variation over time. Study results indicated that the median of the sum of the streamflow available above the minimum monthly bypass requirement from Rio Blanco, Little Navajo River, and Navajo River was 126,240 acre-feet. The results also indicated that diversion of water for the San Juan–Chama Project has been possible for most months of most years.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20135005","isbn":"978-1-4113-3552-3","collaboration":"Prepared in cooperation with the Albuquerque–Bernalillo County Water Utility Authority","usgsCitation":"Falk, S.E., Anderholm, S.K., and Hafich, K.A., 2013, Water quality, streamflow conditions, and annual flow-duration curves for streams of the San Juan–Chama Project, southern Colorado and northern New Mexico, 1935-2010: U.S. Geological Survey Scientific Investigations Report 2013-5005, Report: x, 50 p.; 1 Appendix, https://doi.org/10.3133/sir20135005.","productDescription":"Report: x, 50 p.; 1 Appendix","numberOfPages":"63","additionalOnlineFiles":"Y","temporalStart":"1935-01-01","temporalEnd":"2010-12-31","ipdsId":"IP-034463","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":266785,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2013_5005.gif"},{"id":266784,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2013/5005/app1.xlsx"},{"id":266782,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2013/5005/"},{"id":266783,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2013/5005/sir2013-5005.pdf"}],"projection":"Geographic projection","datum":"North American Datum of 1983","country":"United States","state":"Colorado;New Mexico","county":"Archuleta;Conejos;Mineral;Rio Arriba;Rio Grande","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -107.0,36.5 ], [ -107.0,37.5 ], [ -106.5,37.5 ], [ -106.5,36.5 ], [ -107.0,36.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"510b9281e4b0947afa3c8558","contributors":{"authors":[{"text":"Falk, Sarah E. sefalk@usgs.gov","contributorId":1056,"corporation":false,"usgs":true,"family":"Falk","given":"Sarah","email":"sefalk@usgs.gov","middleInitial":"E.","affiliations":[],"preferred":true,"id":472798,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderholm, Scott K.","contributorId":94270,"corporation":false,"usgs":true,"family":"Anderholm","given":"Scott","email":"","middleInitial":"K.","affiliations":[],"preferred":false,"id":472800,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hafich, Katya A.","contributorId":45604,"corporation":false,"usgs":true,"family":"Hafich","given":"Katya","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":472799,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70043032,"text":"ds709L - 2013 - Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Nalbandon mineral district in Afghanistan: Chapter L in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","interactions":[],"lastModifiedDate":"2013-02-01T11:11:56","indexId":"ds709L","displayToPublicDate":"2013-01-31T00:00:00","publicationYear":"2013","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":"709","chapter":"L","title":"Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Nalbandon mineral district in Afghanistan: Chapter L in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","docAbstract":"The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Nalbandon mineral district, which has lead and zinc deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420–500 nanometer, nm), green (520–600 nm), red (610–690 nm), and near-infrared (760–890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520–770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©JAXA, 2007, 2008, 2010), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band’s picture element based on the digital values of all picture elements within a 500-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area’s local zone (41 for Nalbandon) and the WGS84 datum. The final image mosaics were subdivided into ten overlapping tiles or quadrants because of the large size of the target area. The ten image tiles (or quadrants) for the Nalbandon area are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image. Within the Nalbandon study area, two subareas were designated for detailed field investigations (that is, the Nalbandon District and Gharghananaw-Gawmazar subareas); these subareas were extracted from the area’s image mosaic and are provided as separate embedded geotiff images.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan (DS 709)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds709L","collaboration":"Prepared in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations and the Afghanistan Geological Survey. This report is Chapter L in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan. For more information, see: Data Series 709.","usgsCitation":"Davis, P.A., and Cagney, L.E., 2013, Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Nalbandon mineral district in Afghanistan: Chapter L in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan: U.S. Geological Survey Data Series 709, Readme; 2 Maps: 11 x 8.5 inches and 68.21 x 31.13 inches; 24 Image Files; 24 Metadata Files; 1 Shapefile; DS 709, https://doi.org/10.3133/ds709L.","productDescription":"Readme; 2 Maps: 11 x 8.5 inches and 68.21 x 31.13 inches; 24 Image Files; 24 Metadata Files; 1 Shapefile; DS 709","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2006-01-24","costCenters":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":266830,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_709_l.jpg"},{"id":266825,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/709/l/index_maps/index_maps.html"},{"id":266819,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/709/l/"},{"id":266821,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/ds/709/l/1_readme.txt"},{"id":266826,"type":{"id":14,"text":"Image"},"url":"https://pubs.usgs.gov/ds/709/l/image_files/image_files.html"},{"id":266823,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/l/index_maps/Nalbandon_Area-of-Interest_Index_Map.pdf"},{"id":266824,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/l/index_maps/Nalbandon_Image_Index_Map.pdf"},{"id":266827,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/709/l/metadata/metadata.html"},{"id":266828,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/ds/709/l/shapefiles/shapefiles.html"},{"id":266829,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/ds/709/index.html"}],"country":"Afghanistan","otherGeospatial":"Nalbandon Mineral District","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 63.5,33.9 ], [ 63.5,34.5 ], [ 65.0,34.5 ], [ 65.0,33.9 ], [ 63.5,33.9 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"510b927ee4b0947afa3c8548","contributors":{"authors":[{"text":"Davis, Philip A. pdavis@usgs.gov","contributorId":692,"corporation":false,"usgs":true,"family":"Davis","given":"Philip","email":"pdavis@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":472807,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cagney, Laura E. 0000-0003-3282-2458 lcagney@usgs.gov","orcid":"https://orcid.org/0000-0003-3282-2458","contributorId":4744,"corporation":false,"usgs":true,"family":"Cagney","given":"Laura","email":"lcagney@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":472808,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70043042,"text":"ofr20131011 - 2013 - Digital data from the Great Sand Dunes airborne gravity gradient survey, south-central Colorado","interactions":[],"lastModifiedDate":"2013-01-31T15:23:16","indexId":"ofr20131011","displayToPublicDate":"2013-01-31T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1011","title":"Digital data from the Great Sand Dunes airborne gravity gradient survey, south-central Colorado","docAbstract":"This report contains digital data and supporting explanatory files describing data types, data formats, and survey procedures for a high-resolution airborne gravity gradient (AGG) survey at Great Sand Dunes National Park, Alamosa and Saguache Counties, south-central Colorado. In the San Luis Valley, the Great Sand Dunes survey covers a large part of Great Sand Dunes National Park and Preserve. The data described were collected from a high-resolution AGG survey flown in February 2012, by Fugro Airborne Surveys Corp., on contract to the U.S. Geological Survey. Scientific objectives of the AGG survey are to investigate the subsurface structural framework that may influence groundwater hydrology and seismic hazards, and to investigate AGG methods and resolution using different flight specifications. Funding was provided by an airborne geophysics training program of the U.S. Department of Defense's Task Force for Business & Stability Operations.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131011","usgsCitation":"Drenth, B., Abraham, J., Grauch, V.J., Labson, V., and Hodges, G., 2013, Digital data from the Great Sand Dunes airborne gravity gradient survey, south-central Colorado: U.S. Geological Survey Open-File Report 2013-1011, Report: iii, 5 p.; Appendix; Downloads Directory, https://doi.org/10.3133/ofr20131011.","productDescription":"Report: iii, 5 p.; Appendix; Downloads Directory","numberOfPages":"8","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":266868,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2013_1011.gif"},{"id":266864,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1011/"},{"id":266865,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1011/OF13-1011.pdf"},{"id":266866,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2013/1011/downloads/Appendix.pdf"},{"id":266867,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2013/1011/downloads/"}],"country":"United States","state":"Colorado","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -105.75,37.50 ], [ -105.75,38.00 ], [ -105.30,38.00 ], [ -105.30,37.50 ], [ -105.75,37.50 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"510b925fe4b0947afa3c853b","contributors":{"authors":[{"text":"Drenth, B. J.","contributorId":49885,"corporation":false,"usgs":true,"family":"Drenth","given":"B. J.","affiliations":[],"preferred":false,"id":472827,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Abraham, J.D.","contributorId":20686,"corporation":false,"usgs":true,"family":"Abraham","given":"J.D.","email":"","affiliations":[],"preferred":false,"id":472825,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grauch, V. J. S. 0000-0002-0761-3489","orcid":"https://orcid.org/0000-0002-0761-3489","contributorId":34125,"corporation":false,"usgs":true,"family":"Grauch","given":"V.","email":"","middleInitial":"J. S.","affiliations":[],"preferred":false,"id":472826,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Labson, V.F.","contributorId":20506,"corporation":false,"usgs":true,"family":"Labson","given":"V.F.","email":"","affiliations":[],"preferred":false,"id":472824,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hodges, G.","contributorId":93354,"corporation":false,"usgs":true,"family":"Hodges","given":"G.","email":"","affiliations":[],"preferred":false,"id":472828,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70043052,"text":"ds709N - 2013 - Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Katawas mineral district in Afghanistan: Chapter N in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","interactions":[],"lastModifiedDate":"2013-02-01T10:29:31","indexId":"ds709N","displayToPublicDate":"2013-01-31T00:00:00","publicationYear":"2013","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":"709","chapter":"N","title":"Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Katawas mineral district in Afghanistan: Chapter N in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan","docAbstract":"The U.S. Geological Survey (USGS), in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations, prepared databases for mineral-resource target areas in Afghanistan. The purpose of the databases is to (1) provide useful data to ground-survey crews for use in performing detailed assessments of the areas and (2) provide useful information to private investors who are considering investment in a particular area for development of its natural resources. The set of satellite-image mosaics provided in this Data Series (DS) is one such database. Although airborne digital color-infrared imagery was acquired for parts of Afghanistan in 2006, the image data have radiometric variations that preclude their use in creating a consistent image mosaic for geologic analysis. Consequently, image mosaics were created using ALOS (Advanced Land Observation Satellite; renamed Daichi) satellite images, whose radiometry has been well determined (Saunier, 2007a,b). This part of the DS consists of the locally enhanced ALOS image mosaics for the Katawas mineral district, which has gold deposits. ALOS was launched on January 24, 2006, and provides multispectral images from the AVNIR (Advanced Visible and Near-Infrared Radiometer) sensor in blue (420-500 nanometer, nm), green (520-600 nm), red (610-690 nm), and near-infrared (760-890 nm) wavelength bands with an 8-bit dynamic range and a 10-meter (m) ground resolution. The satellite also provides a panchromatic band image from the PRISM (Panchromatic Remote-sensing Instrument for Stereo Mapping) sensor (520-770 nm) with the same dynamic range but a 2.5-m ground resolution. The image products in this DS incorporate copyrighted data provided by the Japan Aerospace Exploration Agency (©AXA, 2008), but the image processing has altered the original pixel structure and all image values of the JAXA ALOS data, such that original image values cannot be recreated from this DS. As such, the DS products match JAXA criteria for value added products, which are not copyrighted, according to the ALOS end-user license agreement. The selection criteria for the satellite imagery used in our mosaics were images having (1) the highest solar-elevation angles (near summer solstice) and (2) the least cloud, cloud-shadow, and snow cover. The multispectral and panchromatic data were orthorectified with ALOS satellite ephemeris data, a process which is not as accurate as orthorectification using digital elevation models (DEMs); however, the ALOS processing center did not have a precise DEM. As a result, the multispectral and panchromatic image pairs were generally not well registered to the surface and not coregistered well enough to perform resolution enhancement on the multispectral data. Therefore, it was necessary to (1) register the 10-m AVNIR multispectral imagery to a well-controlled Landsat image base, (2) mosaic the individual multispectral images into a single image of the entire area of interest, (3) register each panchromatic image to the registered multispectral image base, and (4) mosaic the individual panchromatic images into a single image of the entire area of interest. The two image-registration steps were facilitated using an automated control-point algorithm developed by the USGS that allows image coregistration to within one picture element. Before rectification, the multispectral and panchromatic images were converted to radiance values and then to relative-reflectance values using the methods described in Davis (2006). Mosaicking the multispectral or panchromatic images started with the image with the highest sun-elevation angle and the least atmospheric scattering, which was treated as the standard image. The band-reflectance values of all other multispectral or panchromatic images within the area were sequentially adjusted to that of the standard image by determining band-reflectance correspondence between overlapping images using linear least-squares analysis. The resolution of the multispectral image mosaic was then increased to that of the panchromatic image mosaic using the SPARKLE logic, which is described in Davis (2006). Each of the four-band images within the resolution-enhanced image mosaic was individually subjected to a local-area histogram stretch algorithm (described in Davis, 2007), which stretches each band's picture element based on the digital values of all picture elements within a 315-m radius. The final databases, which are provided in this DS, are three-band, color-composite images of the local-area-enhanced, natural-color data (the blue, green, and red wavelength bands) and color-infrared data (the green, red, and near-infrared wavelength bands). All image data were initially projected and maintained in Universal Transverse Mercator (UTM) map projection using the target area's local zone (42 for Katawas) and the WGS84 datum. The final image mosaics are provided as embedded geotiff images, which can be read and used by most geographic information system (GIS) and image-processing software. The tiff world files (tfw) are provided, even though they are generally not needed for most software to read an embedded geotiff image. Within the Katawas study area, one subarea was designated for detailed field investigation (that is, the Gold subarea); this subarea was extracted from the area's image mosaic and is provided as a separate embedded geotiff image.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan (DS 709)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds709N","collaboration":"Prepared in cooperation with the U.S. Department of Defense Task Force for Business and Stability Operations and the Afghanistan Geological Survey. This report is Chapter N in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan. For more information, see: Data Series 709.","usgsCitation":"Davis, P.A., and Cagney, L.E., 2013, Local-area-enhanced, 2.5-meter resolution natural-color and color-infrared satellite-image mosaics of the Katawas mineral district in Afghanistan: Chapter N in Local-area-enhanced, high-resolution natural-color and color-infrared satellite-image mosaics of mineral districts in Afghanistan: U.S. Geological Survey Data Series 709, Readme; 2 Maps: 11 x 8.5 inches and 25.39 x 27.57 inches; 4 Image Files; 4 Metadata Files; 1 Shapefile, DS 709, https://doi.org/10.3133/ds709N.","productDescription":"Readme; 2 Maps: 11 x 8.5 inches and 25.39 x 27.57 inches; 4 Image Files; 4 Metadata Files; 1 Shapefile, DS 709","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":387,"text":"Mineral Resources Program","active":true,"usgs":true}],"links":[{"id":266891,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_709_n.jpg"},{"id":266885,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/n/index_maps/Katawas_Area-of-Interest_Index_Map.pdf"},{"id":266886,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/ds/709/n/index_maps/Katawas_Image_Index_Map.pdf"},{"id":266887,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/ds/709/n/image_files/image_files.html"},{"id":266888,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/ds/709/n/metadata/metadata.html"},{"id":266889,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/ds/709/n/shapefiles/shapefiles.html"},{"id":266890,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/ds/709/"},{"id":266883,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/709/n/"},{"id":266884,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/ds/709/n/1_readme.txt"}],"country":"Afghanistan","otherGeospatial":"Katawas Mineral District","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 69,33 ], [ 69,33.33 ], [ 68.83,33.33 ], [ 68.83,33 ], [ 69,33 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"510cf20de4b0ae2ee50d965c","contributors":{"authors":[{"text":"Davis, Philip A. pdavis@usgs.gov","contributorId":692,"corporation":false,"usgs":true,"family":"Davis","given":"Philip","email":"pdavis@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":472873,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cagney, Laura E. 0000-0003-3282-2458 lcagney@usgs.gov","orcid":"https://orcid.org/0000-0003-3282-2458","contributorId":4744,"corporation":false,"usgs":true,"family":"Cagney","given":"Laura","email":"lcagney@usgs.gov","middleInitial":"E.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":472874,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70043012,"text":"sir20125266 - 2013 - A regional classification of the effectiveness of depressional wetlands at mitigating nitrogen transport to surface waters in the Northern Atlantic Coastal Plain","interactions":[],"lastModifiedDate":"2023-03-09T20:14:47.955364","indexId":"sir20125266","displayToPublicDate":"2013-01-30T00:00:00","publicationYear":"2013","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":"2012-5266","title":"A regional classification of the effectiveness of depressional wetlands at mitigating nitrogen transport to surface waters in the Northern Atlantic Coastal Plain","docAbstract":"Nitrogen from nonpoint sources contributes to eutrophication, hypoxia, and related ecological degradation in Atlantic Coastal Plain streams and adjacent coastal estuaries such as Chesapeake Bay and Pamlico Sound. Although denitrification in depressional (non-riparian) wetlands common to the Coastal Plain can be a significant landscape sink for nitrogen, the effectiveness of individual wetlands at removing nitrogen varies substantially due to varying hydrogeologic, geochemical, and other landscape conditions, which are often poorly or inconsistently mapped over large areas. A geographic model describing the spatial variability in the likely effectiveness of depressional wetlands in watershed uplands at mitigating nitrogen transport from nonpoint sources to surface waters was constructed for the Northern Atlantic Coastal Plain (NACP), from North Carolina through New Jersey. Geographic and statistical techniques were used to develop the model. Available medium-resolution (1:100,000-scale) stream hydrography was used to define 33,799 individual watershed catchments in the study area. Sixteen landscape metrics relevant to the occurrence of depressional wetlands and their effectiveness as nitrogen sinks were defined for each catchment, based primarily on available topographic and soils data. Cluster analysis was used to aggregate the 33,799 catchments into eight wetland landscape regions (WLRs) based on the value of three principal components computed for the 16 original landscape metrics. Significant differences in topography, soil, and land cover among the eight WLRs demonstrate the effectiveness of the clustering technique. Results were used to interpret the relative likelihood of depressional wetlands in each WLR and their likely effectiveness at mitigating nitrogen transport from upland source areas to surface waters. The potential effectiveness of depressional wetlands at mitigating nitrogen transport varies substantially over different parts of the NACP. Depressional wetlands are common in three WLRs covering 32 percent of the area, and have a relatively high potential to mitigate nitrogen transport from nonpoint sources. Conversely, 37 percent of the study area includes rolling hills with relatively high slope and relief, and little likelihood of depressional wetlands. The remainder of the Coastal Plain includes relatively flat watersheds with moderate to low relative likelihood of nitrogen mitigation. The delineation of WLRs in this model should be useful for targeting wetland conservation or restoration efforts, and for estimating the effects of depressional wetlands on the regional nitrogen budget, but should be considered in light of limitations and assumptions inherent in the model.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125266","collaboration":"Prepared in cooperation with the U.S. Department of Agriculture","usgsCitation":"Ator, S.W., Denver, J., LaMotte, A.E., and Sekellick, A.J., 2013, A regional classification of the effectiveness of depressional wetlands at mitigating nitrogen transport to surface waters in the Northern Atlantic Coastal Plain: U.S. Geological Survey Scientific Investigations Report 2012-5266, v, 23 p.; Data, https://doi.org/10.3133/sir20125266.","productDescription":"v, 23 p.; Data","startPage":"i","endPage":"23","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":41514,"text":"Maryland-Delaware-District of Columbia Water Science Center","active":true,"usgs":true}],"links":[{"id":266765,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5266/pdf/sir2012-5266.pdf"},{"id":266764,"rank":3,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5266/"},{"id":266766,"rank":1,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2012/5266/nacp_wlrs.csv"},{"id":266767,"rank":4,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5266.gif"}],"otherGeospatial":"Atlantic Coastal Plain","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -84.0,32.0 ], [ -84.0,44.0 ], [ -66.0,44.0 ], [ -66.0,32.0 ], [ -84.0,32.0 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"510a40e2e4b0de10a2aaab71","contributors":{"authors":[{"text":"Ator, Scott W. 0000-0002-9186-4837 swator@usgs.gov","orcid":"https://orcid.org/0000-0002-9186-4837","contributorId":781,"corporation":false,"usgs":true,"family":"Ator","given":"Scott","email":"swator@usgs.gov","middleInitial":"W.","affiliations":[{"id":375,"text":"Maryland, Delaware, and the District of Columbia Water Science Center","active":false,"usgs":true}],"preferred":false,"id":472784,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Denver, Judith M. jmdenver@usgs.gov","contributorId":780,"corporation":false,"usgs":true,"family":"Denver","given":"Judith M.","email":"jmdenver@usgs.gov","affiliations":[{"id":375,"text":"Maryland, Delaware, and the District of Columbia Water Science Center","active":false,"usgs":true}],"preferred":false,"id":472783,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"LaMotte, Andrew E. 0000-0002-1434-6518 alamotte@usgs.gov","orcid":"https://orcid.org/0000-0002-1434-6518","contributorId":2842,"corporation":false,"usgs":true,"family":"LaMotte","given":"Andrew","email":"alamotte@usgs.gov","middleInitial":"E.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":472785,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sekellick, Andrew J. 0000-0002-0440-7655 ajsekell@usgs.gov","orcid":"https://orcid.org/0000-0002-0440-7655","contributorId":4125,"corporation":false,"usgs":true,"family":"Sekellick","given":"Andrew","email":"ajsekell@usgs.gov","middleInitial":"J.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":472786,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70043004,"text":"sir20125276 - 2013 - Preliminary hydrogeologic assessment near Tassi and Pakoon Springs, western part of Grand Canyon-Parashant National Monument, Arizona","interactions":[],"lastModifiedDate":"2013-01-30T13:28:31","indexId":"sir20125276","displayToPublicDate":"2013-01-30T00:00:00","publicationYear":"2013","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":"2012-5276","title":"Preliminary hydrogeologic assessment near Tassi and Pakoon Springs, western part of Grand Canyon-Parashant National Monument, Arizona","docAbstract":"Tassi and Pakoon Springs are both in the Grand Wash Trough in the western part of Grand Canyon-Parashant National Monument on the Arizona Strip. The monument is jointly managed by the National Park Service (NPS) and the Bureau of Land Management. This study was in response to NPS’s need to better understand the influence from regional increases in groundwater withdrawals near Grand Canyon-Parashant on the groundwater discharge from Tassi and Pakoon Springs. The climate of the Arizona Strip is generally semiarid to arid, and springs in the monument provide the water for the fragile ecosystems that are commonly separated by large areas of dry washes in canyons with pinyon and juniper. Available hydrogeologic data from previous investigations included water levels from the few existing wells, location information for springs, water chemistry from springs, and geologic maps. Available groundwater-elevation data from the wells and springs in the monument indicate that groundwater in the Grand Wash Trough is moving from north to south, discharging to springs and into the Colorado River. Groundwater may also be moving from east to west from Paleozoic rocks in the Grand Wash Cliffs into sedimentary deposits in the Grand Wash Trough. Finally, groundwater may be moving from the northwest in the Mesoproterozoic crystalline rocks of the Virgin Mountains into the northern part of the Grand Wash Trough. Water discharging from Tassi and Pakoon Springs has a major-ion chemistry similar to that of other springs in the western part of Grand Canyon-Parashant. Stable-isotopic signatures for oxygen-18 and hydrogen-2 are depleted in the water from both Tassi and Pakoon Springs in comparison to other springs on the Arizona Strip. Tassi Spring discharges from multiple seeps along the Wheeler Fault, and the depleted isotopic signatures suggest that water may be flowing from multiple places into Lake Mead and seems to have a higher elevation or an older climate source. Elevated water temperatures and a depleted stable-isotopic signature for Pakoon Springs suggest that the water may be traveling along a deep circulating flowpath, have multiple sources of water, been recharged at a high elevation, and (or) has an older climate source.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125276","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Truini, M., 2013, Preliminary hydrogeologic assessment near Tassi and Pakoon Springs, western part of Grand Canyon-Parashant National Monument, Arizona: U.S. Geological Survey Scientific Investigations Report 2012-5276, iv, 12 p., https://doi.org/10.3133/sir20125276.","productDescription":"iv, 12 p.","startPage":"i","endPage":"12","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":266755,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5276.gif"},{"id":266753,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5276/"},{"id":266754,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5276/sir2012-5276.pdf"}],"country":"United States","state":"Arizona","otherGeospatial":"Grand Canyon-parashant National Monument;Tassi Spring;Pakoon Spring","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -114.82,31.33 ], [ -114.82,37.0 ], [ -109.05,37.0 ], [ -109.05,31.33 ], [ -114.82,31.33 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"510a40efe4b0de10a2aaab7d","contributors":{"authors":[{"text":"Truini, Margot mtruini@usgs.gov","contributorId":599,"corporation":false,"usgs":true,"family":"Truini","given":"Margot","email":"mtruini@usgs.gov","affiliations":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"preferred":true,"id":472776,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70043003,"text":"sir20125138 - 2013 - Methods for estimating selected low-flow statistics and development of annual flow-duration statistics for Ohio","interactions":[],"lastModifiedDate":"2013-01-30T13:13:51","indexId":"sir20125138","displayToPublicDate":"2013-01-30T00:00:00","publicationYear":"2013","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":"2012-5138","title":"Methods for estimating selected low-flow statistics and development of annual flow-duration statistics for Ohio","docAbstract":"This report presents the results of a study to develop methods for estimating selected low-flow statistics and for determining annual flow-duration statistics for Ohio streams. Regression techniques were used to develop equations for estimating 10-year recurrence-interval (10-percent annual-nonexceedance probability) low-flow yields, in cubic feet per second per square mile, with averaging periods of 1, 7, 30, and 90-day(s), and for estimating the yield corresponding to the long-term 80-percent duration flow. These equations, which estimate low-flow yields as a function of a streamflow-variability index, are based on previously published low-flow statistics for 79 long-term continuous-record streamgages with at least 10 years of data collected through water year 1997. When applied to the calibration dataset, average absolute percent errors for the regression equations ranged from 15.8 to 42.0 percent. The regression results have been incorporated into the U.S. Geological Survey (USGS) StreamStats application for Ohio (http://water.usgs.gov/osw/streamstats/ohio.html) in the form of a yield grid to facilitate estimation of the corresponding streamflow statistics in cubic feet per second. Logistic-regression equations also were developed and incorporated into the USGS StreamStats application for Ohio for selected low-flow statistics to help identify occurrences of zero-valued statistics. Quantiles of daily and 7-day mean streamflows were determined for annual and annual-seasonal (September–November) periods for each complete climatic year of streamflow-gaging station record for 110 selected streamflow-gaging stations with 20 or more years of record. The quantiles determined for each climatic year were the 99-, 98-, 95-, 90-, 80-, 75-, 70-, 60-, 50-, 40-, 30-, 25-, 20-, 10-, 5-, 2-, and 1-percent exceedance streamflows. Selected exceedance percentiles of the annual-exceedance percentiles were subsequently computed and tabulated to help facilitate consideration of the annual risk of exceedance or nonexceedance of annual and annual-seasonal-period flow-duration values. The quantiles are based on streamflow data collected through climatic year 2008.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125138","collaboration":"Prepared in cooperation with the Ohio Water Development Authority","usgsCitation":"Koltun, G., and Kula, S.P., 2013, Methods for estimating selected low-flow statistics and development of annual flow-duration statistics for Ohio: U.S. Geological Survey Scientific Investigations Report 2012-5138, v, 195 p.; Table 2-1, https://doi.org/10.3133/sir20125138.","productDescription":"v, 195 p.; Table 2-1","startPage":"i","endPage":"195","numberOfPages":"206","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"links":[{"id":266749,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5138/"},{"id":266750,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5138/sir2012-5138.pdf"},{"id":266751,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/sir/2012/5138/table2-1.pdf"},{"id":266752,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5138.gif"}],"country":"United States","state":"Ohio","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -84.82,38.4 ], [ -84.82,42.0 ], [ -80.52,42.0 ], [ -80.52,38.4 ], [ -84.82,38.4 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"510a40eee4b0de10a2aaab79","contributors":{"authors":[{"text":"Koltun, G. F. 0000-0003-0255-2960","orcid":"https://orcid.org/0000-0003-0255-2960","contributorId":49817,"corporation":false,"usgs":true,"family":"Koltun","given":"G. F.","affiliations":[],"preferred":false,"id":472775,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kula, Stephanie P. spkula@usgs.gov","contributorId":4666,"corporation":false,"usgs":true,"family":"Kula","given":"Stephanie","email":"spkula@usgs.gov","middleInitial":"P.","affiliations":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"preferred":true,"id":472774,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70042992,"text":"pp17137 - 2013 - The three-dimensional geologic model used for the 2003 National Oil and Gas Assessment of the San Joaquin Basin Province, California: Chapter 7 in Petroleum systems and geologic assessment of oil and gas in the San Joaquin Basin Province, California","interactions":[],"lastModifiedDate":"2018-08-31T11:49:27","indexId":"pp17137","displayToPublicDate":"2013-01-30T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1713-7","title":"The three-dimensional geologic model used for the 2003 National Oil and Gas Assessment of the San Joaquin Basin Province, California: Chapter 7 in Petroleum systems and geologic assessment of oil and gas in the San Joaquin Basin Province, California","docAbstract":"We present a three-dimensional geologic model of the San Joaquin Basin (SJB) that may be the first compilation of subsurface data spanning the entire basin. The model volume spans 200 × 90 miles, oriented along the basin axis, and extends to ~11 miles depth, for a total of more than 1 million grid nodes. This model supported the 2003 U.S. Geological Survey assessment of future additions to reserves of oil and gas in the SJB. Data sources include well-top picks from more than 3,200 wildcat and production wells, published cross sections, regional seismic grids, and fault maps. The model consists of 15 chronostratigraphic horizons ranging from the Mesozoic crystalline basement to the topographic surface. Many of the model units are hydrocarbon reservoir rocks and three—the Cretaceous Moreno Formation, the Eocene Kreyenhagen Formation, and the Miocene Monterey Formation—are hydrocarbon source rocks. The White Wolf Fault near the southern end of the basin divides the map volume into 2 separate fault blocks. The construction of a three-dimensional model of the entire SJB encountered many challenges, including complex and inconsistent stratigraphic nomenclature, significant facies changes across and along the basin axis, time-transgressive formation tops, uncertain correlation of outcrops with their subsurface equivalents, and contradictory formation top data. Although some areas of the model are better resolved than others, the model facilitated the 2003 resource assessment in several ways, including forming the basis of a petroleum system model and allowing a precise definition of assessment unit volumes.","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Petroleum systems and geologic assessment of oil and gas in the San Joaquin Basin Province, California (PP 1713)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp17137","usgsCitation":"Hosford Scheirer, A., 2013, The three-dimensional geologic model used for the 2003 National Oil and Gas Assessment of the San Joaquin Basin Province, California: Chapter 7 in Petroleum systems and geologic assessment of oil and gas in the San Joaquin Basin Province, California: U.S. Geological Survey Professional Paper 1713-7, Chapter 7: 81 p., https://doi.org/10.3133/pp17137.","productDescription":"Chapter 7: 81 p.","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2003-01-01","temporalEnd":"2003-12-31","costCenters":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"links":[{"id":266746,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/pp_1713_7.jpg","text":"Index Page","linkFileType":{"id":5,"text":"html"}},{"id":266747,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/pp1713/"},{"id":266748,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/pp1713/07/pp1713_ch07.pdf"}],"country":"United States","state":"California","otherGeospatial":"San Joaquin Basin","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -121.75,34.75 ], [ -121.75,38.0 ], [ -118.75,38.0 ], [ -118.75,34.75 ], [ -121.75,34.75 ] ] ] } } ] }","publicComments":"This report is Chapter 7 in Petroleum systems and geologic assessment of oil and gas in the San Joaquin Basin Province, California. Please see Professional Paper 1713 for other chapters.","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"510a40f0e4b0de10a2aaab81","contributors":{"authors":[{"text":"Hosford Scheirer, Allegra","contributorId":22217,"corporation":false,"usgs":true,"family":"Hosford Scheirer","given":"Allegra","email":"","affiliations":[],"preferred":false,"id":472765,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70173522,"text":"70173522 - 2013 - Estimating transmission of avian influenza in wild birds from incomplete epizootic data: implications for surveillance and disease spreac","interactions":[],"lastModifiedDate":"2016-06-16T13:08:47","indexId":"70173522","displayToPublicDate":"2013-01-30T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2163,"text":"Journal of Applied Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Estimating transmission of avian influenza in wild birds from incomplete epizootic data: implications for surveillance and disease spreac","docAbstract":"This document presents protocols and guidelines to persons sampling fishes in the Grand Canyon, to help ensure consistency in fish handling, fish tagging, and data collection among different projects and organizations. Most such research and monitoring projects are conducted under the general umbrella of the Glen Canyon Dam Adaptive Management Program and include studies by the U.S. Geological Survey (USGS), U.S. Fish and Wildlife Service (FWS), National Park Service (NPS), the Arizona Game and Fish Department (AGFD), various universities, and private contractors. This document is intended to provide guidance to fieldworkers regarding protocols that may vary from year to year depending on specific projects and objectives. We also provide herein documentation of standard methods used in the Grand Canyon that can be cited in scientific publications, as well as a summary of changes in protocols since the document was first created in 2002.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Section A: Biological science in Book 2 Collection of Environmental Data","largerWorkSubtype":{"id":6,"text":"USGS Unnumbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/tm2A12","usgsCitation":"Persons, W.R., Ward, D.L., and Avery, L.A., 2013, Standardized methods for Grand Canyon fisheries research 2015 (Originally posted January 15, 2013; Version 1.1: February 3, 2015): U.S. Geological Survey Techniques and Methods 2-A12, iv, 19 p., https://doi.org/10.3133/tm2A12.","productDescription":"iv, 19 p.","startPage":"i","endPage":"19","numberOfPages":"26","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2012-01-01","temporalEnd":"2012-12-31","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":266700,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/tm2A12.PNG"},{"id":266698,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/tm/tm2a12/"},{"id":266699,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/tm/tm2a12/tm2a12.pdf","text":"Report","size":"7.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"country":"United States","otherGeospatial":"Grand Canyon","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -113.9799,35.7503 ], [ -113.9799,36.8654 ], [ -111.5871,36.8654 ], [ -111.5871,35.7503 ], [ -113.9799,35.7503 ] ] ] } } ] }","edition":"Originally posted January 15, 2013; Version 1.1: February 3, 2015","publicComments":"This report is Chapter 12 of Section A: Biological science in Book 2 Collection of Environmental Data.","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5108ef76e4b0d965cd9f22cc","contributors":{"authors":[{"text":"Persons, William R. wpersons@usgs.gov","contributorId":4028,"corporation":false,"usgs":true,"family":"Persons","given":"William","email":"wpersons@usgs.gov","middleInitial":"R.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":472652,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ward, David L. 0000-0002-3355-0637 dlward@usgs.gov","orcid":"https://orcid.org/0000-0002-3355-0637","contributorId":3879,"corporation":false,"usgs":true,"family":"Ward","given":"David","email":"dlward@usgs.gov","middleInitial":"L.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":472651,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Avery, Luke A. lavery@usgs.gov","contributorId":4340,"corporation":false,"usgs":true,"family":"Avery","given":"Luke","email":"lavery@usgs.gov","middleInitial":"A.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":472653,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70102982,"text":"70102982 - 2013 - Faulting and groundwater in a desert environment: constraining hydrogeology using time-domain electromagnetic data","interactions":[],"lastModifiedDate":"2014-04-28T13:15:16","indexId":"70102982","displayToPublicDate":"2013-01-28T13:10:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2850,"text":"Near Surface Geophysics","active":true,"publicationSubtype":{"id":10}},"title":"Faulting and groundwater in a desert environment: constraining hydrogeology using time-domain electromagnetic data","docAbstract":"Within the south-western Mojave Desert, the Joshua Basin Water District is considering applying imported water into infiltration ponds in the Joshua Tree groundwater sub-basin in an attempt to artificially recharge the underlying aquifer. Scarce subsurface hydrogeological data are available near the proposed recharge site; therefore, time-domain electromagnetic (TDEM) data were collected and analysed to characterize the subsurface. TDEM soundings were acquired to estimate the depth to water on either side of the Pinto Mountain Fault, a major east-west trending strike-slip fault that transects the proposed recharge site. While TDEM is a standard technique for groundwater investigations, special care must be taken when acquiring and interpreting TDEM data in a twodimensional (2D) faulted environment. A subset of the TDEM data consistent with a layered-earth interpretation was identified through a combination of three-dimensional (3D) forward modelling and diffusion time-distance estimates. Inverse modelling indicates an offset in water table elevation of nearly 40 m across the fault. These findings imply that the fault acts as a low-permeability barrier to groundwater flow in the vicinity of the proposed recharge site. Existing production wells on the south side of the fault, together with a thick unsaturated zone and permeable near-surface deposits, suggest the southern half of the study area is suitable for artificial recharge. These results illustrate the effectiveness of targeted TDEM in support of hydrological studies in a heavily faulted desert environment where data are scarce and the cost of obtaining these data by conventional drilling techniques is prohibitive.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Near Surface Geophysics","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"European Association of Geoscientists & Engineers","doi":"10.3997/1873-0604.2013043","usgsCitation":"Bedrosian, P.A., Burgess, M.K., and Nishikawa, T., 2013, Faulting and groundwater in a desert environment: constraining hydrogeology using time-domain electromagnetic data: Near Surface Geophysics, v. 11, no. 5, p. 545-555, https://doi.org/10.3997/1873-0604.2013043.","productDescription":"9 p.","startPage":"545","endPage":"555","ipdsId":"IP-011505","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":286725,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":286668,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.3997/1873-0604.2013043"}],"volume":"11","issue":"5","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"535f786de4b078dca33ae365","contributors":{"authors":[{"text":"Bedrosian, Paul A. 0000-0002-6786-1038 pbedrosian@usgs.gov","orcid":"https://orcid.org/0000-0002-6786-1038","contributorId":839,"corporation":false,"usgs":true,"family":"Bedrosian","given":"Paul","email":"pbedrosian@usgs.gov","middleInitial":"A.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":493090,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Burgess, Matthew K. 0000-0002-2828-8910 mburgess@usgs.gov","orcid":"https://orcid.org/0000-0002-2828-8910","contributorId":2115,"corporation":false,"usgs":true,"family":"Burgess","given":"Matthew","email":"mburgess@usgs.gov","middleInitial":"K.","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":493092,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Nishikawa, Tracy 0000-0002-7348-3838 tnish@usgs.gov","orcid":"https://orcid.org/0000-0002-7348-3838","contributorId":1515,"corporation":false,"usgs":true,"family":"Nishikawa","given":"Tracy","email":"tnish@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":493091,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70042894,"text":"sir20125226 - 2013 - Determination of flow losses in the Cape Fear River between B. Everett Jordan Lake and Lillington, North Carolina, 2008-2010","interactions":[],"lastModifiedDate":"2013-01-28T20:02:17","indexId":"sir20125226","displayToPublicDate":"2013-01-28T00:00:00","publicationYear":"2013","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":"2012-5226","title":"Determination of flow losses in the Cape Fear River between B. Everett Jordan Lake and Lillington, North Carolina, 2008-2010","docAbstract":"During 2008-2010, the U.S. Geological Survey conducted a hydrologic investigation in cooperation with the Triangle J Council of Governments Cape Fear River Flow Study Committee and the North Carolina Division of Water Resources to collect hydrologic data in the Cape Fear River between B. Everett Jordan Lake and Lillington in central North Carolina to help determine if suspected flow losses occur in the reach. Flow loss analyses were completed by summing the daily flow releases at Jordan Lake Dam with the daily discharges at Deep River at Moncure and Buckhorn Creek near Corinth, then subtracting these values from the daily discharges at Cape Fear River at Lillington. Examination of long-term records revealed that during 10,227 days of the 1983-2010 water years, 408 days (4.0 percent) had flow loss when conditions were relatively steady with respect to the previous day's records. The flow loss that occurred on these 40 days ranged from 0.49 to 2,150 cubic feet per second with a median flow loss of 37.2 cubic feet per second. The months with the highest number of days with flow losses were June (16. percent), September (16.9 percent), and October (19.4 percent). A series of synoptic discharge measurements made on six separate days in 2009 provided \"snapshots\" of overall flow conditions along the study reach. The largest water diversion is just downstream from the confluence of the Haw and Deep Rivers, and discharges substantially decrease in the main stem downstream from the intake point. Downstream from Buckhorn Dam, minimal gain or loss between the dam and Raven Rock State Park was noted. Analyses of discharge measurements and ratings for two streamgages-one at Deep River at Moncure and the other at Cape Fear River at Lillington-were completed to address the accuracy of the relation between stage and discharge at these sites. The ratings analyses did not indicate a particular time during the 1982-2011 water years in which a consistent bias occurred in the computations of discharge records that would indicate false flow losses. A total of 34 measured discharges at a streamgage on the Haw River below B. Everett Jordan Lake near Moncure were compared with the reported hourly flow releases from Jordan Lake Dam. Because 28 of 34 measurements were within plus or minus 10 percent of the hourly flow releases reported by the U.S Army Corps of Engineers, use of the current discharge computation tables for reporting Jordan Lake Dam flow releases is generally supported. A stage gage was operated on the Cape Fear River at Buckhorn Dam near Corinth to collect continuous stage-only records. Throughout the study period, flow over the dam was observed along its length, and flow loss within the study reach is not attributed to river-level fluctuations at the dam. Water-use information and (or) data were obtained for five industrial facilities, a regional power utility, two municipalities, one small hydropower facility on the Deep River, and one quarry operation also adjacent to the Deep River. The largest water users are the regional power producer, a small hydropower operation, and the two municipalities. The total water-use diversions for these facilities range from almost 25.5 to 38.5 cubic feet per second (39.5 to 59.5 million gallons per day) during the winter and summer periods, respectively. This range is equivalent to 69 to 104 percent of the 37 cubic feet per second median flow loss. The Lockville hydropower station is on the Deep River about 1 mile downstream from the streamgage near Moncure. Run-of-river operations at the facility do not appear to affect flow losses in the study reach. The largest water user in the study area is a regional power producer at a coal-fired power-generation plant located immediately adjacent to the Cape Fear River just downstream from the confluence of the Haw an Deep Rivers. Comparisons of daily water withdrawals, sup-plied by the regional power producer, and discharge records at a streamgage on the diversion canal indicated many days when consumption exceeded the producer's estimates for the cooling towers. Uncertainty surrounding reasonable estimates of consumption remained in effect at the end of the study. Data concerning evaporative losses were compiled using two approaches-an analysis of available pan-evaporation data from a National Weather Service cooperative observer station in Chapel Hill, North Carolina; and a compilation of reference open-water evaporation computed by the State Climate Office of North Carolina. The potential flow loss by evaporation from the main stem and the Deep River was estimated to be in the range of 4 to 14 cubic feet per second during May through October, equivalent to 10 to 38 percent of the 37 cubic feet per second median flow loss. Daily water-use diversions and evaporation losses were compared to flow-loss occurrences during the period April 2008 through September 2010. In comparing the surface-water, water-use, and evaporation data compiled for 2008-2010, it is evident that documented water diversions combined with flow losses by open-water evaporation can exceed the net flow gain in the study area and result in flow losses from the reach. Analysis of data from a streamgage downstream from the regional power plant on the diversion canal adjacent to the Cape Fear River provided insight into the occurrence of an apparent flow loss at the streamgage at Lillington. Assessment of the daily discharges and subsequent hydrographs for the canal streamgage indicated at least 24 instances during the study when the flows suddenly changed by magnitudes of 100 to more that 200 cubic feet per second, resulting in a noted time-lag effect on the downstream discharges at the Lillington streamgage, beginning 8 to 16 hours after the sudden flow change. A fiber-optic distributed temperature-sensing survey was conducted on the Cape Fear River at the Raven Rock State Park reach August 12-14, 2009, to determine if the presence of diabase dikes were preferentially directing groundwater discharge. No temperature anomalies of colder water were measured during the survey, which indicated that at the time of the survey that particular reach of the Cape Fear River was a \"no-flow\" or losing stream. An aerial thermal-infrared survey was conducted on the Haw and Cape Fear Rivers on February 27, 2010, from Jordan Lake Dam to Lillington to qualitatively delineate areas of groundwater discharge on the basis of the contrast between warm groundwater discharge and cold surface-water temperatures. Dis-charge generally was noted as diffuse seepage, but in a few cases springs were detected as inflow at a discrete point of discharge. Two reaches of the Cape Fear River (regional power plant and Bradley Road reaches) were selected for groundwater monitoring with a transect of piezometers installed within the flood plain. Groundwater-level altitudes at these reaches were analyzed for 1 water year (October 1, 2009, to September 30, 2010). Data collected as part of this study represent only a brief period of time and may not represent all conditions and all years; however, the data indicate that, during the dry summer months, the Cape Fear River within the study area is losing an undetermined quantity of water through seepage. Analyses completed during this investigation indicate a study reach with complex flow patterns affected by numerous concurrent factors resulting in flow losses. The causes of flow loss could not be solely attributed to any one factor. Among the factors considered, the occurrences of water diversions and evaporative losses were determined to be sufficient on some days (particularly during the base-flow period) to exceed the net gain in flows between the upstream and downstream ends of the study area. Losses by diversions and evaporation can exceed the median flow loss of 3 cubic feet per second, which indicates that flow loss from the study reach is real. Groundwater data collected during 2009-2010 indicate the possibility of localized flow loss during the summer, particularly in the impounded reach above Buckhorn Dam. However, no indication of unusual patterns was noted that would cause substantial flow loss by groundwater and surface-water interaction at the river bottom.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125226","collaboration":"Prepared in cooperation with the Triangle J Council of Governments Cape Fear River Flow Study Committee and the North Carolina Department of Environment and Natural Resources, Division of Water Resources","usgsCitation":"Weaver, J., and McSwain, K., 2013, Determination of flow losses in the Cape Fear River between B. Everett Jordan Lake and Lillington, North Carolina, 2008-2010: U.S. Geological Survey Scientific Investigations Report 2012-5226, x, 76 p., https://doi.org/10.3133/sir20125226.","productDescription":"x, 76 p.","numberOfPages":"90","onlineOnly":"Y","temporalStart":"2008-01-01","temporalEnd":"2010-12-31","costCenters":[{"id":476,"text":"North Carolina Water Science Center","active":true,"usgs":true}],"links":[{"id":266624,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5226.gif"},{"id":266620,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5226/"},{"id":266621,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5226/pdf/sir2012-5226_v3.pdf"}],"scale":"100000","country":"United States","state":"North Carolina","city":"Lillington","otherGeospatial":"B. Everett Jordan Lake;Cape Fear River;Shearon Harris Lake","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -79.161987,35.417314 ], [ -79.161987,35.612372 ], [ -78.798752,35.612372 ], [ -78.798752,35.417314 ], [ -79.161987,35.417314 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51079deae4b0df796f216e0c","contributors":{"authors":[{"text":"Weaver, J. Curtis","contributorId":42260,"corporation":false,"usgs":true,"family":"Weaver","given":"J. Curtis","affiliations":[],"preferred":false,"id":472522,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McSwain, Kristen Bukowski","contributorId":104458,"corporation":false,"usgs":true,"family":"McSwain","given":"Kristen Bukowski","affiliations":[],"preferred":false,"id":472523,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70042968,"text":"70042968 - 2013 - Detecting insect pollinator declines on regional and global scales","interactions":[],"lastModifiedDate":"2013-01-31T10:01:20","indexId":"70042968","displayToPublicDate":"2013-01-28T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1321,"text":"Conservation Biology","active":true,"publicationSubtype":{"id":10}},"title":"Detecting insect pollinator declines on regional and global scales","docAbstract":"Recently there has been considerable concern about declines in bee communities in agricultural and natural habitats. The value of pollination to agriculture, provided primarily by bees, is >$200 billion/year worldwide, and in natural ecosystems it is thought to be even greater. However, no monitoring program exists to accurately detect declines in abundance of insect pollinators; thus, it is difficult to quantify the status of bee communities or estimate the extent of declines. We used data from 11 multiyear studies of bee communities to devise a program to monitor pollinators at regional, national, or international scales. In these studies, 7 different methods for sampling bees were used and bees were sampled on 3 different continents. We estimated that a monitoring program with 200-250 sampling locations each sampled twice over 5 years would provide sufficient power to detect small (2-5%) annual declines in the number of species and in total abundance and would cost U.S.$2,000,000. To detect declines as small as 1% annually over the same period would require >300 sampling locations. Given the role of pollinators in food security and ecosystem function, we recommend establishment of integrated regional and international monitoring programs to detect changes in pollinator communities.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Conservation Biology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","publisherLocation":"Hoboken, NJ","doi":"10.1111/j.1523-1739.2012.01962.x","usgsCitation":"Lubuhn, G., Droege, S., Connor, E., Gemmill-Herren, B., Potts, S.G., Minckley, R.L., Griswold, T., Jean, R., Kula, E., Roubik, D.W., Cane, J., Wright, K.W., Frankie, G., and Parker, F., 2013, Detecting insect pollinator declines on regional and global scales: Conservation Biology, v. 27, no. 1, p. 113-120, https://doi.org/10.1111/j.1523-1739.2012.01962.x.","productDescription":"8 p.","startPage":"113","endPage":"120","numberOfPages":"8","ipdsId":"IP-016950","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":266791,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":266790,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.1523-1739.2012.01962.x"}],"otherGeospatial":"Europe;North America;South America","volume":"27","issue":"1","noUsgsAuthors":false,"publicationDate":"2012-12-12","publicationStatus":"PW","scienceBaseUri":"510ba081e4b0947afa3c857f","contributors":{"authors":[{"text":"Lubuhn, Gretchen","contributorId":21436,"corporation":false,"usgs":true,"family":"Lubuhn","given":"Gretchen","email":"","affiliations":[],"preferred":false,"id":472686,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Droege, Sam sdroege@usgs.gov","contributorId":3464,"corporation":false,"usgs":true,"family":"Droege","given":"Sam","email":"sdroege@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":472682,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Connor, Edward F.","contributorId":17503,"corporation":false,"usgs":true,"family":"Connor","given":"Edward F.","affiliations":[],"preferred":false,"id":472685,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gemmill-Herren, Barbara","contributorId":6741,"corporation":false,"usgs":true,"family":"Gemmill-Herren","given":"Barbara","email":"","affiliations":[],"preferred":false,"id":472683,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Potts, Simon G.","contributorId":108373,"corporation":false,"usgs":true,"family":"Potts","given":"Simon","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":472695,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Minckley, Robert L.","contributorId":86652,"corporation":false,"usgs":true,"family":"Minckley","given":"Robert","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":472690,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Griswold, Terry","contributorId":9548,"corporation":false,"usgs":true,"family":"Griswold","given":"Terry","email":"","affiliations":[],"preferred":false,"id":472684,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Jean, Robert","contributorId":89424,"corporation":false,"usgs":true,"family":"Jean","given":"Robert","email":"","affiliations":[],"preferred":false,"id":472691,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Kula, Emanuel","contributorId":96981,"corporation":false,"usgs":true,"family":"Kula","given":"Emanuel","email":"","affiliations":[],"preferred":false,"id":472694,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Roubik, David W.","contributorId":36822,"corporation":false,"usgs":true,"family":"Roubik","given":"David","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":472687,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Cane, Jim","contributorId":84238,"corporation":false,"usgs":true,"family":"Cane","given":"Jim","affiliations":[],"preferred":false,"id":472689,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Wright, Karen W.","contributorId":95772,"corporation":false,"usgs":true,"family":"Wright","given":"Karen","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":472692,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Frankie, Gordon","contributorId":96563,"corporation":false,"usgs":true,"family":"Frankie","given":"Gordon","email":"","affiliations":[],"preferred":false,"id":472693,"contributorType":{"id":1,"text":"Authors"},"rank":13},{"text":"Parker, Frank","contributorId":42855,"corporation":false,"usgs":true,"family":"Parker","given":"Frank","affiliations":[],"preferred":false,"id":472688,"contributorType":{"id":1,"text":"Authors"},"rank":14}]}} ,{"id":70042867,"text":"ofr20131026 - 2013 - Abstracts for the October 2012 meeting on Volcanism in the American Southwest, Flagstaff, Arizona","interactions":[],"lastModifiedDate":"2013-01-29T16:29:22","indexId":"ofr20131026","displayToPublicDate":"2013-01-25T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1026","title":"Abstracts for the October 2012 meeting on Volcanism in the American Southwest, Flagstaff, Arizona","docAbstract":"Though volcanic eruptions are comparatively rare in the American Southwest, the States of Arizona, Colorado, New Mexico, Nevada, and Utah host Holocene volcanic eruption deposits and are vulnerable to future volcanic activity. Compared with other parts of the western United States, comparatively little research has been focused on this area, and eruption probabilities are poorly constrained. Monitoring infrastructure consists of a variety of local seismic networks, and ”backbone“ geodetic networks with little integration. Emergency response planning for volcanic unrest has received little attention by either Federal or State agencies. On October 18–20, 2012, 90 people met at the U.S. Geological Survey campus in Flagstaff, Arizona, providing an opportunity for volcanologists, land managers, and emergency responders to meet, converse, and begin to plan protocols for any future activity. Geologists contributed data on recent findings of eruptive ages, eruption probabilities, and hazards extents (plume heights, ash dispersal). Geophysicists discussed evidence for magma intrusions from seismic, geodetic, and other geophysical techniques. Network operators publicized their recent work and the relevance of their equipment to volcanic regions. Land managers and emergency responders shared their experiences with emergency planning for earthquakes. The meeting was organized out of the recognition that little attention had been paid to planning for or mitigation of volcanic hazards in the American Southwest. Moreover, few geological meetings have hosted a session specifically devoted to this topic. This volume represents one official outcome of the meeting—a collection of abstracts related to talks and poster presentations shared during the first two days of the meeting. In addition, this report includes the meeting agenda as a record of the proceedings. One additional intended outcome will be greater discussion and coordination among emergency responders, geologists, geophysicists, and land managers regarding geologic hazards in the Southwest.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131026","usgsCitation":"Lowenstern, J.B., 2013, Abstracts for the October 2012 meeting on Volcanism in the American Southwest, Flagstaff, Arizona: U.S. Geological Survey Open-File Report 2013-1026, vii, 39 p., https://doi.org/10.3133/ofr20131026.","productDescription":"vii, 39 p.","startPage":"i","endPage":"39","numberOfPages":"49","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":619,"text":"Volcano Science Center-Menlo Park","active":false,"usgs":true}],"links":[{"id":266544,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2013_1026.gif"},{"id":266542,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1026/of2013-1026.pdf"},{"id":266543,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1026/"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 172.5,18.9 ], [ 172.5,71.4 ], [ -66.9,71.4 ], [ -66.9,18.9 ], [ 172.5,18.9 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5104fae2e4b091226576e996","contributors":{"authors":[{"text":"Lowenstern, Jacob B. 0000-0003-0464-7779 jlwnstrn@usgs.gov","orcid":"https://orcid.org/0000-0003-0464-7779","contributorId":2755,"corporation":false,"usgs":true,"family":"Lowenstern","given":"Jacob","email":"jlwnstrn@usgs.gov","middleInitial":"B.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":472445,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ]}