The Sacramento–San Joaquin Delta is an inland delta at the western extent of the Central Valley. Levees were built around swampy islands starting after the Civil War to reclaim these lands for farming. Various studies show that these levees could fail in concert from shaking from a major local or regional earthquake resulting in salty water from the San Francisco Bay contaminating the water in the Delta. We installed seismographs around the Delta and on levees to assess the contribution of site response to the seismic hazard of the levees. Cone penetrometer testing shows that the upper 10 s of meters of soil in the Delta have shear‐wave velocities of about 200 m/s, which would give a strong site response. Seismographs were sited following two strategies: pairs of stations to compare the response of the levees to nearby sites, and a more regional deployment in the Delta. Site response was determined in two different ways: a traditional spectral ratio (TSR) approach of S waves using station BDM of the Berkeley Digital Seismic Net as a reference site, and using SH/SV ratios of noise (or Nakamura’s method). Both estimates usually agree in spectral character for stations whose response is dominated by a resonant peak, but the most obvious peaks in the SH/SV ratios usually are about two‐thirds as large as the main peaks in the TSRs. Levee sites typically have large narrow resonances in the site response function compared to sites in the farmland of the Delta. These resonances, at a frequency of about 1–3 Hz, have amplitudes of about 15 with TSR and 10–12 with Nakamura’s method. Sites on farmland in the Delta also have amplifications, but these are typically broader and not as resonant in appearance. Late (slow) Rayleigh waves were recorded at stations in the Delta, have a dominant period of about one second, and are highly monochromatic. Results from a three‐station array at the Holland Marina suggest that they have a phase velocity of about 600 m/s and arrive at about the same azimuth as the straight‐line back azimuth to the source. A dispersion curve determined for the basin or valley waves yields a shallow velocity profile that increases from about 350 m/s in the upper 0.2 km to about 1.1 km/s at a depth of about 2 km.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120110347","usgsCitation":"Fletcher, J.P., and Boatwright, J., 2013, Site Response and Basin Waves in the Sacramento–San Joaquin Delta, California: Bulletin of the Seismological Society of America, v. 103, no. 1, p. 196-210, https://doi.org/10.1785/0120110347.","productDescription":"15 p.","startPage":"196","endPage":"210","ipdsId":"IP-026726","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":381518,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Sacramento–San Joaquin Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.28744506835938,\n 37.0333\n ],\n [\n -121.0667,\n 37.0333\n ],\n [\n -121.0667,\n 38.16587506003647\n ],\n [\n -122.28744506835938,\n 38.16587506003647\n ],\n [\n -122.28744506835938,\n 37.0333\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"103","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2013-02-05","publicationStatus":"PW","scienceBaseUri":"59f98bbde4b0531197afa038","contributors":{"authors":[{"text":"Fletcher, Jon Peter B. 0000-0001-8885-6177 jfletcher@usgs.gov","orcid":"https://orcid.org/0000-0001-8885-6177","contributorId":1216,"corporation":false,"usgs":true,"family":"Fletcher","given":"Jon","email":"jfletcher@usgs.gov","middleInitial":"Peter B.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":714840,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boatwright, John 0000-0002-6931-5241 boat@usgs.gov","orcid":"https://orcid.org/0000-0002-6931-5241","contributorId":1938,"corporation":false,"usgs":true,"family":"Boatwright","given":"John","email":"boat@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":714839,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"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":70044050,"text":"70044050 - 2013 - Rupture history of the 2008 Mw 7.9 Wenchuan, China, earthquake: Evaluation of separate and joint inversions of geodetic, teleseismic, and strong-motion data","interactions":[],"lastModifiedDate":"2016-01-27T16:01:18","indexId":"70044050","displayToPublicDate":"2013-02-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"Rupture history of the 2008 Mw 7.9 Wenchuan, China, earthquake: Evaluation of separate and joint inversions of geodetic, teleseismic, and strong-motion data","docAbstract":"An extensive data set of teleseismic and strong-motion waveforms and geodetic offsets is used to study the rupture history of the 2008 Wenchuan, China, earthquake. A linear multiple-time-window approach is used to parameterize the rupture. Because of the complexity of the Wenchuan faulting, three separate planes are used to represent the rupturing surfaces. This earthquake clearly demonstrates the strengths and limitations of geodetic, teleseismic, and strong-motion data sets. Geodetic data (static offsets) are valuable for determining the distribution of shallower slip but are insensitive to deeper faulting and reveal nothing about the timing of slip. Teleseismic data in the distance range 30°–90° generally involve no modeling difficulties because of simple ray paths and can distinguish shallow from deep slip. Teleseismic data, however, cannot distinguish between different slip scenarios when multiple fault planes are involved because steep takeoff angles lead to ambiguity in timing. Local strong-motion data, on the other hand, are ideal for determining the direction of rupture from directivity but can easily be over modeled with inaccurate Green’s functions, leading to misinterpretation of the slip distribution. We show that all three data sets are required to give an accurate description of the Wenchuan rupture. The moment is estimated to be approximately 1.0 × 1021 N · m with the slip characterized by multiple large patches with slips up to 10 m. Rupture initiates on the southern end of the Pengguan fault and proceeds unilaterally to the northeast. Upon reaching the cross-cutting Xiaoyudong fault, rupture of the adjacent Beichuan fault starts at this juncture and proceeds bilaterally to the northeast and southwest.
","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Bulletin of the Seismological Society of America","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Seismological Society of America","publisherLocation":"Stanford","doi":"10.1785/0120120108","usgsCitation":"Hartzell, S.H., Mendoza, C., Ramírez-Guzmán, L., Zeng, Y., and Mooney, W., 2013, Rupture history of the 2008 Mw 7.9 Wenchuan, China, earthquake: Evaluation of separate and joint inversions of geodetic, teleseismic, and strong-motion data: Bulletin of the Seismological Society of America, v. 103, no. 1, p. 353-370, https://doi.org/10.1785/0120120108.","productDescription":"18 p.","startPage":"353","endPage":"370","numberOfPages":"18","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-038915","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":273330,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":273328,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1785/0120120108"}],"country":"China","otherGeospatial":"Wenchuan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 101.8487548828125,\n 31.891550612684366\n ],\n [\n 102.89794921875,\n 32.43561304116276\n ],\n [\n 103.612060546875,\n 32.52365781569917\n ],\n [\n 104.23278808593749,\n 32.25462006000722\n ],\n [\n 104.6173095703125,\n 31.83089906339438\n ],\n [\n 104.0240478515625,\n 31.31140838620163\n ],\n [\n 103.45275878906249,\n 30.779598396611537\n ],\n [\n 103.2989501953125,\n 30.37761431777479\n ],\n [\n 102.227783203125,\n 30.443937998291165\n ],\n [\n 101.876220703125,\n 30.954057859276126\n ],\n [\n 101.8487548828125,\n 31.891550612684366\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"103","issue":"1","noUsgsAuthors":false,"publicationDate":"2013-02-05","publicationStatus":"PW","scienceBaseUri":"51b05dede4b030b5198012ed","contributors":{"authors":[{"text":"Hartzell, Stephen H. 0000-0003-0858-9043 shartzell@usgs.gov","orcid":"https://orcid.org/0000-0003-0858-9043","contributorId":2594,"corporation":false,"usgs":true,"family":"Hartzell","given":"Stephen","email":"shartzell@usgs.gov","middleInitial":"H.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":474703,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mendoza, Carlos","contributorId":10313,"corporation":false,"usgs":true,"family":"Mendoza","given":"Carlos","affiliations":[],"preferred":false,"id":474704,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ramírez-Guzmán, Leonardo","contributorId":45946,"corporation":false,"usgs":true,"family":"Ramírez-Guzmán","given":"Leonardo","affiliations":[],"preferred":false,"id":474706,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zeng, Yuesha","contributorId":52068,"corporation":false,"usgs":true,"family":"Zeng","given":"Yuesha","email":"","affiliations":[],"preferred":false,"id":474707,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mooney, Walter","contributorId":40952,"corporation":false,"usgs":true,"family":"Mooney","given":"Walter","affiliations":[],"preferred":false,"id":474705,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70043583,"text":"70043583 - 2013 - Frequency and Severity of Trauma in Fishes Subjected to Multiple-pass Depletion Electrofishing","interactions":[],"lastModifiedDate":"2013-02-17T19:49:21","indexId":"70043583","displayToPublicDate":"2013-02-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2886,"text":"North American Journal of Fisheries Management","active":true,"publicationSubtype":{"id":10}},"title":"Frequency and Severity of Trauma in Fishes Subjected to Multiple-pass Depletion Electrofishing","docAbstract":"The incidence and severity of trauma associated with multiple-pass electrofishing and the effects on short-term (30-d) survival and growth of Rainbow Trout Oncorhynchus mykiss, Brook Trout Salvelinus fontinalis, and five representative co-inhabiting nontarget or bycatch species were examined. Fish were held in four rectangular fiberglass tanks (190 × 66 cm) equipped with electrodes, a gravel–cobble stream substrate, and continuous water flow. Fish were exposed to one, two, or three electroshocks (100-V, 60-Hz pulsed DC) spaced 1 h apart or were held as a control. The heterogeneous field produced a mean (±SD) voltage gradient of 0.23 ± 0.024 V/cm (range = 0.20–0.30 V/cm) with a duty cycle of 30% and a 5-s exposure. Radiographs of 355 fish were examined for evidence of spinal injuries, and necropsies were performed on 303 fish to assess hemorrhagic trauma in soft tissue. Using linear regression, we demonstrated significant relationships between the number of electrical shocks and the frequency and severity of hemorrhagic and spinal trauma in each of the nontarget species (Potomac Sculpin Cottus girardi, Channel Catfish Ictalurus punctatus, Fathead Minnow Pimephales promelas, Green Sunfish Lepomis cyanellus, and Largemouth Bass Micropterus salmoides). Most of the injuries in these species were either minor or moderate. Rainbow Trout and Brook Trout generally sustained the highest incidence and severity of injuries, but those injuries were generally independent of the number of treatments. The 30-d postshock survival for the trout species was greater than 94%; survival for the bycatch species ranged from 80% (Fathead Minnow) to 100% (Green Sunfish and Channel Catfish). There were no significant differences in 30-d postshock condition factors despite observations of altered feeding behavior lasting several days to 1 week posttreatment in several of the study species.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"North American Journal of Fisheries Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Taylor and Francis","doi":"10.1080/02755947.2012.754803","usgsCitation":"Panek, F., and Densmore, C.L., 2013, Frequency and Severity of Trauma in Fishes Subjected to Multiple-pass Depletion Electrofishing: North American Journal of Fisheries Management, v. 33, no. 1, p. 178-185, https://doi.org/10.1080/02755947.2012.754803.","startPage":"178","endPage":"185","ipdsId":"IP-041634","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"links":[{"id":267611,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1080/02755947.2012.754803"},{"id":267612,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","volume":"33","issue":"1","noUsgsAuthors":false,"publicationDate":"2013-01-29","publicationStatus":"PW","scienceBaseUri":"512209f0e4b0b37542fda866","contributors":{"authors":[{"text":"Panek, Frank fpanek@usgs.gov","contributorId":791,"corporation":false,"usgs":true,"family":"Panek","given":"Frank","email":"fpanek@usgs.gov","affiliations":[],"preferred":true,"id":473894,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Densmore, Christine L. 0000-0001-6440-0781 cdensmore@usgs.gov","orcid":"https://orcid.org/0000-0001-6440-0781","contributorId":4560,"corporation":false,"usgs":true,"family":"Densmore","given":"Christine","email":"cdensmore@usgs.gov","middleInitial":"L.","affiliations":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true}],"preferred":true,"id":473895,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70043058,"text":"ofr20131008 - 2013 - A preliminary deposit model for lithium-cesium-tantalum (LCT) pegmatites","interactions":[],"lastModifiedDate":"2016-12-21T09:41:03","indexId":"ofr20131008","displayToPublicDate":"2013-02-01T00:00:00","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":"2013-1008","title":"A preliminary deposit model for lithium-cesium-tantalum (LCT) pegmatites","docAbstract":"This report is part of an effort by the U.S. Geological Survey to update existing mineral deposit models and to develop new ones. We emphasize practical aspects of pegmatite geology that might directly or indirectly help in exploration for lithium-cesium-tantalum (LCT) pegmatites, or for assessing regions for pegmatite-related mineral resource potential. These deposits are an important link in the world’s supply chain of rare and strategic elements, accounting for about one-third of world lithium production, most of the tantalum, and all of the cesium.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131008","usgsCitation":"Bradley, D., and McCauley, A., 2013, A preliminary deposit model for lithium-cesium-tantalum (LCT) pegmatites (Version 1.0: February 1, 2013; Version 1.1: December 20, 2016): U.S. Geological Survey Open-File Report 2013-1008, iii, 7 p., https://doi.org/10.3133/ofr20131008.","productDescription":"iii, 7 p.","numberOfPages":"10","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":171,"text":"Central Mineral and Environmental Resources Science Center","active":true,"usgs":true}],"links":[{"id":266897,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2013/1008/images/coverthb.jpg"},{"id":266895,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1008/"},{"id":266896,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1008/OF13-1008.pdf"},{"id":332288,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2013/1008/versionHist.txt","text":"Version History","size":"1.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2013-1008 Version History"}],"edition":"Version 1.0: February 1, 2013; Version 1.1: December 20, 2016","revisedDate":"2016-12-20","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"510ce3ede4b0ae2ee50d95e7","contributors":{"authors":[{"text":"Bradley, Dwight","contributorId":32641,"corporation":false,"usgs":true,"family":"Bradley","given":"Dwight","affiliations":[],"preferred":false,"id":472880,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"McCauley, Andrew","contributorId":48846,"corporation":false,"usgs":true,"family":"McCauley","given":"Andrew","affiliations":[],"preferred":false,"id":472881,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70043370,"text":"70043370 - 2013 - Towards integration of GLAS data into a national fuels mapping program","interactions":[],"lastModifiedDate":"2013-05-30T12:17:31","indexId":"70043370","displayToPublicDate":"2013-02-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3052,"text":"Photogrammetric Engineering and Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Towards integration of GLAS data into a national fuels mapping program","docAbstract":"Comprehensive canopy structure and fuel data are critical for understanding and modeling wildland fire. The LANDFIRE project produces such data nationwide based on a collection of field observations, Landsat imagery, and other geospatial data. Where field data are not available, alternate strategies are being investigated. In this study, vegetation structure data available from GLAS were used to fill this data gap for the Yukon Flats Ecoregion of interior Alaska. The GLAS-derived structure and fuel layers and the original LANDFIRE layers were subsequently used as inputs into a fire behavior model to determine what effect the revised inputs would have on the model outputs. The outputs showed that inclusion of the GLAS data enabled better landscape-level characterization of\nvegetation structure and therefore enabled a broader wildland fire modeling capability. The results of this work underscore how GLAS data can be incorporated into LANDFIRE canopy structure and fuel mapping.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Photogrammetric Engineering and Remote Sensing","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Society for Photogrammetry","usgsCitation":"Peterson, B.E., Nelson, K., and Wylie, B., 2013, Towards integration of GLAS data into a national fuels mapping program: Photogrammetric Engineering and Remote Sensing, v. 79, no. 2, p. 175-183.","productDescription":"9 p.","startPage":"175","endPage":"183","ipdsId":"IP-038047","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":273015,"type":{"id":11,"text":"Document"},"url":"https://www.conservationgateway.org/ConservationPractices/FireLandscapes/LANDFIRE/Documents/Peterson%20et%20all%20GLAS%20and%20Fuel%20Mapping.pdf"},{"id":273016,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Yukon Flats Ecoregion","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -149.55,65.47 ], [ -149.55,67.47 ], [ -142.43,67.47 ], [ -142.43,65.47 ], [ -149.55,65.47 ] ] ] } } ] }","volume":"79","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51a874ece4b082d85d5ed90a","contributors":{"authors":[{"text":"Peterson, Birgit E. 0000-0002-4356-1540 bpeterson@usgs.gov","orcid":"https://orcid.org/0000-0002-4356-1540","contributorId":3599,"corporation":false,"usgs":true,"family":"Peterson","given":"Birgit","email":"bpeterson@usgs.gov","middleInitial":"E.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":false,"id":473475,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Nelson, Kurtis 0000-0003-4911-4511 knelson@usgs.gov","orcid":"https://orcid.org/0000-0003-4911-4511","contributorId":3602,"corporation":false,"usgs":true,"family":"Nelson","given":"Kurtis","email":"knelson@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":473476,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wylie, Bruce 0000-0002-7374-1083","orcid":"https://orcid.org/0000-0002-7374-1083","contributorId":107996,"corporation":false,"usgs":true,"family":"Wylie","given":"Bruce","affiliations":[],"preferred":false,"id":473477,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70154759,"text":"70154759 - 2013 - Observations on the identification of larval and juvenile Scaphirhynchus spp. in the lower Mississippi River","interactions":[],"lastModifiedDate":"2015-07-01T11:07:10","indexId":"70154759","displayToPublicDate":"2013-02-01T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3444,"text":"Southeastern Naturalist","active":true,"publicationSubtype":{"id":10}},"title":"Observations on the identification of larval and juvenile Scaphirhynchus spp. in the lower Mississippi River","docAbstract":"Scaphirhynchus albus (Pallid Sturgeon) and S. platorynchus (Shovelnose Sturgeon) are sympatric and not uncommon in the lower Mississippi River from the confluence of the Ohio River to the Gulf of Mexico, and in its distributary, the Atchafalaya River. Reports of sturgeon larvae have been rare in the Mississippi River but have been increasing with more effective collection methods. A suite of characters identified in hatchery-reared larval Pallid Sturgeon and Shovelnose Sturgeon from the Yellowstone and upper Missouri rivers has been used to distinguish larval Scaphirhynchus spp. In the Mississippi River; however, a large proportion of wild Scaphirhynchus spp. larvae are intermediate in these characters and have been identified by some as hybridized Pallid Sturgeon and Shovelnose Sturgeon. We applied three diagnostic characters developed from Missouri River sturgeon larvae to hatchery-reared progeny of Atchafalaya River Pallid Sturgeon and found them inadequate to identify most of the known Pallid sturgeon larvae. Additionally, fewer than 10% of a large sample of wild Scaphirhynchusspp. larvae from the lower Mississippi River conformed to either Pallid Sturgeon or Shovelnose Sturgeon at two or more of the characters. We also found a small mouth width relative to head width and a concave forward barbel position may be useful for the identification of 30% or more Scaphirhynchus spp. larvae and postlarval young-of-year as Shovelnose Sturgeon. Established adult character indices and diagnostic measurement proportionalities also failed to correctly identify any hatchery-reared Pallid Sturgeon juveniles recaptured 6–7 years following their release.
","language":"English","publisher":"Eagle Hill Institute","doi":"10.1656/058.012.0202","usgsCitation":"Hartfield, P., Kuntz, N.M., and Schramm, H.L., 2013, Observations on the identification of larval and juvenile Scaphirhynchus spp. in the lower Mississippi River: Southeastern Naturalist, v. 12, no. 2, p. 251-266, https://doi.org/10.1656/058.012.0202.","productDescription":"16 p.","startPage":"251","endPage":"266","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-041405","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":305525,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"2","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"55950f35e4b0b6d21dd6cbf5","contributors":{"authors":[{"text":"Hartfield, Paul D.","contributorId":103960,"corporation":false,"usgs":true,"family":"Hartfield","given":"Paul D.","affiliations":[],"preferred":false,"id":564031,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kuntz, Nathan M.","contributorId":145433,"corporation":false,"usgs":false,"family":"Kuntz","given":"Nathan","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":564032,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schramm, Harold L. Jr. hschramm@usgs.gov","contributorId":145424,"corporation":false,"usgs":true,"family":"Schramm","given":"Harold","suffix":"Jr.","email":"hschramm@usgs.gov","middleInitial":"L.","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":false,"id":563980,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70039302,"text":"70039302 - 2013 - Worldwide trends in fishing interest indicated by Internet search volume","interactions":[],"lastModifiedDate":"2013-03-18T13:18:53","indexId":"70039302","displayToPublicDate":"2013-01-31T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1659,"text":"Fisheries Management and Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Worldwide trends in fishing interest indicated by Internet search volume","docAbstract":"There is a growing body of literature that shows internet search volume on a topic, such as fishing, is a viable measure of salience. Herein, internet search volume for 'fishing' and 'angling' is used as a measure of public interest in fishing, in particular, recreational fishing. An online tool, Google Insights for Search, which allows one to study internet search terms and their volume since 2004, is used to examine trends in interest in fishing for 50 countries. Trends in normalised fishing search volume, during 2004 through 2011, varied from a 72.6% decrease (Russian Federation) to a 133.7% increase (Hungary). Normalised fishing search volume declined in 40 (80%) of the countries studied. The decline has been relatively large in English-speaking countries, but also has been large in Central and South American, and European countries. Analyses of search queries provide a low-cost means of gaining insight into angler interests and, possibly, behaviour in countries around the world.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Fisheries Management and Ecology","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","publisherLocation":"Hoboken, NJ","doi":"10.1111/fme.12009","usgsCitation":"Wilde, G., and Pope, K., 2013, Worldwide trends in fishing interest indicated by Internet search volume: Fisheries Management and Ecology, v. 20, no. 2-3, p. 211-222, https://doi.org/10.1111/fme.12009.","productDescription":"12 p.","startPage":"211","endPage":"222","ipdsId":"IP-039450","costCenters":[{"id":463,"text":"Nebraska Cooperative Fish and Wildlife Research Unit","active":false,"usgs":true}],"links":[{"id":269664,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":267771,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/fme.12009"}],"volume":"20","issue":"2-3","noUsgsAuthors":false,"publicationDate":"2012-12-11","publicationStatus":"PW","scienceBaseUri":"514837b3e4b022dd171aff19","contributors":{"authors":[{"text":"Wilde, G.R.","contributorId":54799,"corporation":false,"usgs":true,"family":"Wilde","given":"G.R.","email":"","affiliations":[],"preferred":false,"id":466008,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pope, K.L.","contributorId":20454,"corporation":false,"usgs":true,"family":"Pope","given":"K.L.","email":"","affiliations":[],"preferred":false,"id":466007,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70043046,"text":"ofr20101083K - 2013 - Seismicity of the Earth 1900–2010 Middle East and vicinity","interactions":[],"lastModifiedDate":"2014-01-30T13:53:25","indexId":"ofr20101083K","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":"2010-1083","chapter":"K","title":"Seismicity of the Earth 1900–2010 Middle East and vicinity","docAbstract":"No fewer than four major tectonic plates (Arabia, Eurasia, India, and Africa) and one smaller tectonic block (Anatolia) are responsible for seismicity and tectonics in the Middle East and surrounding region. Geologic development of the region is a consequence of a number of first-order plate tectonic processes that include subduction, large-scale transform faulting, compressional mountain building, and crustal extension. In the east, tectonics are dominated by the collision of the India plate with Eurasia, driving the uplift of the Himalaya, Karakorum, Pamir and Hindu Kush mountain ranges. Beneath the Pamir‒Hindu Kush Mountains of northern Afghanistan, earthquakes occur to depths as great as 200 km as a result of remnant lithospheric subduction. Along the western margin of the India plate, relative motions between India and Eurasia are accommodated by strike-slip, reverse, and oblique-slip faulting, resulting in the complex Sulaiman Range fold and thrust belt, and the major translational Chaman Fault in Afghanistan. Off the south coasts of Pakistan and Iran, the Makran trench is the surface expression of active subduction of the Arabia plate beneath Eurasia. Northwest of this subduction zone, collision between the two plates forms the approximately 1,500-km-long fold and thrust belts of the Zagros Mountains, which cross the whole of western Iran and extend into northeastern Iraq. Tectonics in the eastern Mediterranean region are dominated by complex interactions between the Africa, Arabia, and Eurasia plates, and the Anatolia block. Dominant structures in this region include: the Red Sea Rift, the spreading center between the Africa and Arabia plates; the Dead Sea Transform, a major strike-slip fault, also accommodating Africa-Arabia relative motions; the North Anatolia Fault, a right-lateral strike-slip structure in northern Turkey accommodating much of the translational motion of the Anatolia block westwards with respect to Eurasia and Africa; and the Cyprian Arc, a convergent boundary between the Africa plate to the south, and Anatolia Block to the north.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20101083K","usgsCitation":"Jenkins, J., Turner, B., Turner, R., Hayes, G., Davies, S., Dart, R.L., Tarr, A.C., Villaseñor, A., and Benz, H.M., 2013, Seismicity of the Earth 1900–2010 Middle East and vicinity (Originally posted January 31, 2013; Revised January 28, 2014): U.S. Geological Survey Open-File Report 2010-1083, Map: 1 Sheet: 37 x 24 inches, https://doi.org/10.3133/ofr20101083K.","productDescription":"Map: 1 Sheet: 37 x 24 inches","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":266873,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2010_1083_k.jpg"},{"id":266871,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2010/1083/k/"},{"id":266872,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2010/1083/k/OF2010-1083-K.pdf"}],"otherGeospatial":"Middle East","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 72.0,16.0 ], [ 72.0,46.0 ], [ 84.0,46.0 ], [ 84.0,16.0 ], [ 72.0,16.0 ] ] ] } } ] }","edition":"Originally posted January 31, 2013; Revised January 28, 2014","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"510b9280e4b0947afa3c8550","contributors":{"authors":[{"text":"Jenkins, Jennifer","contributorId":68186,"corporation":false,"usgs":true,"family":"Jenkins","given":"Jennifer","affiliations":[],"preferred":false,"id":472837,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Turner, Bethan","contributorId":97786,"corporation":false,"usgs":true,"family":"Turner","given":"Bethan","email":"","affiliations":[],"preferred":false,"id":472839,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Turner, Rebecca","contributorId":38032,"corporation":false,"usgs":true,"family":"Turner","given":"Rebecca","email":"","affiliations":[],"preferred":false,"id":472836,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hayes, Gavin P. 0000-0003-3323-0112","orcid":"https://orcid.org/0000-0003-3323-0112","contributorId":6157,"corporation":false,"usgs":true,"family":"Hayes","given":"Gavin P.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":472835,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Davies, Sian","contributorId":87828,"corporation":false,"usgs":true,"family":"Davies","given":"Sian","affiliations":[],"preferred":false,"id":472838,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dart, Richard L. dart@usgs.gov","contributorId":1209,"corporation":false,"usgs":true,"family":"Dart","given":"Richard","email":"dart@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":true,"id":472833,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Tarr, Arthur C. atarr@usgs.gov","contributorId":1925,"corporation":false,"usgs":true,"family":"Tarr","given":"Arthur","email":"atarr@usgs.gov","middleInitial":"C.","affiliations":[],"preferred":true,"id":472834,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Villaseñor, Antonio","contributorId":100969,"corporation":false,"usgs":true,"family":"Villaseñor","given":"Antonio","affiliations":[],"preferred":false,"id":472840,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Benz, Harley M. 0000-0002-6860-2134 benz@usgs.gov","orcid":"https://orcid.org/0000-0002-6860-2134","contributorId":794,"corporation":false,"usgs":true,"family":"Benz","given":"Harley","email":"benz@usgs.gov","middleInitial":"M.","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":472832,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"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":70189181,"text":"70189181 - 2013 - Evaluating model structure adequacy: The case of the Maggia Valley groundwater system, southern Switzerland","interactions":[],"lastModifiedDate":"2017-07-06T15:03:29","indexId":"70189181","displayToPublicDate":"2013-01-31T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Evaluating model structure adequacy: The case of the Maggia Valley groundwater system, southern Switzerland","docAbstract":"Model adequacy is evaluated with alternative models rated using model selection criteria (AICc, BIC, and KIC) and three other statistics. Model selection criteria are tested with cross-validation experiments and insights for using alternative models to evaluate model structural adequacy are provided. The study is conducted using the computer codes UCODE_2005 and MMA (MultiModel Analysis). One recharge alternative is simulated using the TOPKAPI hydrological model. The predictions evaluated include eight heads and three flows located where ecological consequences and model precision are of concern. Cross-validation is used to obtain measures of prediction accuracy. Sixty-four models were designed deterministically and differ in representation of river, recharge, bedrock topography, and hydraulic conductivity. Results include: (1) What may seem like inconsequential choices in model construction may be important to predictions. Analysis of predictions from alternative models is advised. (2) None of the model selection criteria consistently identified models with more accurate predictions. This is a disturbing result that suggests to reconsider the utility of model selection criteria, and/or the cross-validation measures used in this work to measure model accuracy. (3) KIC displayed poor performance for the present regression problems; theoretical considerations suggest that difficulties are associated with wide variations in the sensitivity term of KIC resulting from the models being nonlinear and the problems being ill-posed due to parameter correlations and insensitivity. The other criteria performed somewhat better, and similarly to each other. (4) Quantities with high leverage are more difficult to predict. The results are expected to be generally applicable to models of environmental systems.","language":"English","publisher":"Water Resources Research","doi":"10.1029/2011WR011779","usgsCitation":"Hill, M.C., Foglia, L., Mehl, S.W., and Burlando, P., 2013, Evaluating model structure adequacy: The case of the Maggia Valley groundwater system, southern Switzerland: Water Resources Research, v. 49, no. 1, p. 260-282, https://doi.org/10.1029/2011WR011779.","productDescription":"23 p. ","startPage":"260","endPage":"282","ipdsId":"IP-042379","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":473968,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2011wr011779","text":"Publisher Index Page"},{"id":343439,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Switzerland","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 8.460845947265625,\n 46.095138483907725\n ],\n [\n 9.010162353515623,\n 46.095138483907725\n ],\n [\n 9.010162353515623,\n 46.46813299215554\n ],\n [\n 8.460845947265625,\n 46.46813299215554\n ],\n [\n 8.460845947265625,\n 46.095138483907725\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"49","issue":"1","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2013-01-24","publicationStatus":"PW","scienceBaseUri":"595f4c44e4b0d1f9f057e36e","contributors":{"authors":[{"text":"Hill, Mary C. mchill@usgs.gov","contributorId":974,"corporation":false,"usgs":true,"family":"Hill","given":"Mary","email":"mchill@usgs.gov","middleInitial":"C.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":703384,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Foglia, L.","contributorId":194179,"corporation":false,"usgs":false,"family":"Foglia","given":"L.","email":"","affiliations":[],"preferred":false,"id":703385,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Mehl, S. W.","contributorId":194181,"corporation":false,"usgs":false,"family":"Mehl","given":"S.","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":703387,"contributorType":{"id":1,"text":"Authors"},"rank":12},{"text":"Burlando, P.","contributorId":194180,"corporation":false,"usgs":false,"family":"Burlando","given":"P.","email":"","affiliations":[],"preferred":false,"id":703386,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70043030,"text":"ofr20131019 - 2013 - Initial results from a reconnaissance of cyanobacteria and associated toxins in Illinois, August--October 2012","interactions":[],"lastModifiedDate":"2013-01-31T09:59:23","indexId":"ofr20131019","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":"2013-1019","title":"Initial results from a reconnaissance of cyanobacteria and associated toxins in Illinois, August--October 2012","docAbstract":"Ten lakes and two rivers in Illinois were sampled in August–October 2012 to determine the concentrations and spatial distribution of cyanobacteria and associated cyanotoxins throughout the State. The reconnaissance was a collaborative effort of the U.S. Geological Survey and the Illinois Environmental Protection Agency. Sample results indicated that concentrations of both total cyanobacterial cells and microcystin were commonly at levels likely to result in adverse human health effects, according to World Health Organization guidance values. Concentrations generally decreased from August to October following precipitation events and lower temperatures.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131019","usgsCitation":"Terrio, P.J., Ostrodka, L.M., Loftin, K.A., Good, G., and Holland, T., 2013, Initial results from a reconnaissance of cyanobacteria and associated toxins in Illinois, August--October 2012: U.S. Geological Survey Open-File Report 2013-1019, 4 p., https://doi.org/10.3133/ofr20131019.","productDescription":"4 p.","numberOfPages":"4","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2012-08-01","temporalEnd":"2012-10-31","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":266789,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2013_1019.gif"},{"id":266787,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1019/"},{"id":266788,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1019/pdf/ofr2013-1019.pdf"}],"country":"United States","state":"Illinois","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -91.51,36.97 ], [ -91.51,42.51 ], [ -87.5,42.51 ], [ -87.5,36.97 ], [ -91.51,36.97 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"510b927de4b0947afa3c8544","contributors":{"authors":[{"text":"Terrio, Paul J. 0000-0002-1515-9570 pjterrio@usgs.gov","orcid":"https://orcid.org/0000-0002-1515-9570","contributorId":3313,"corporation":false,"usgs":true,"family":"Terrio","given":"Paul","email":"pjterrio@usgs.gov","middleInitial":"J.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":472802,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ostrodka, Lenna M.","contributorId":6350,"corporation":false,"usgs":true,"family":"Ostrodka","given":"Lenna","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":472803,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Loftin, Keith A. 0000-0001-5291-876X kloftin@usgs.gov","orcid":"https://orcid.org/0000-0001-5291-876X","contributorId":868,"corporation":false,"usgs":true,"family":"Loftin","given":"Keith","email":"kloftin@usgs.gov","middleInitial":"A.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":472801,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Good, Gregg","contributorId":65356,"corporation":false,"usgs":true,"family":"Good","given":"Gregg","email":"","affiliations":[],"preferred":false,"id":472805,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Holland, Teri","contributorId":38448,"corporation":false,"usgs":true,"family":"Holland","given":"Teri","email":"","affiliations":[],"preferred":false,"id":472804,"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":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":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":70043039,"text":"ofr20131001 - 2013 - Variability of oil and gas well productivities for continuous (unconventional) petroleum accumulations","interactions":[],"lastModifiedDate":"2013-01-31T13:23:59","indexId":"ofr20131001","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":"2013-1001","title":"Variability of oil and gas well productivities for continuous (unconventional) petroleum accumulations","docAbstract":"Over the last decade, oil and gas well productivities were estimated using decline-curve analysis for thousands of wells as part of U.S. Geological Survey (USGS) studies of continuous (unconventional) oil and gas resources in the United States. The estimated ultimate recoveries (EURs) of these wells show great variability that was analyzed at three scales: within an assessment unit (AU), among AUs of similar reservoir type, and among groups of AUs with different reservoir types. Within a particular oil or gas AU (such as the Barnett Shale), EURs vary by about two orders of magnitude between the most productive wells and the least productive ones (excluding those that are dry and abandoned). The distributions of EURs are highly skewed, with most of the wells in the lower part of the range. Continuous AUs were divided into four categories based on reservoir type and major commodity (oil or gas): coalbed gas, shale gas, other low-permeability gas AUs (such as tight sands), and low-permeability oil AUs. Within each of these categories, there is great variability from AU to AU, as shown by plots of multiple EUR distributions. Comparing the means of each distribution within a category shows that the means themselves have a skewed distribution, with a range of approximately one to two orders of magnitude. A comparison of the three gas categories (coalbed gas, shale gas, and other low-permeability gas AUs) shows large overlap in the ranges of EUR distributions. Generally, coalbed gas AUs have lower EUR distributions, shale gas AUs have intermediate sizes, and the other low-permeability gas AUs have higher EUR distributions. The plot of EUR distributions for each category shows the range of variation among developed AUs in an appropriate context for viewing the historical development within a particular AU. The Barnett Shale is used as an example to demonstrate that dividing wells into groups by time allows one to see the changes in EUR distribution. Subdivision into groups can also be done by vertical versus horizontal wells, by length of horizontal completion, by distance to closest previously drilled well, by thickness of reservoir interval, or by any other variable for which one has or can calculate values for each well. The resulting plots show how one can subdivide the total range of productivity in shale-gas wells into smaller subsets that are more appropriate for use as analogs.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131001","collaboration":"Order a Plotter Print from the USGS Store. From this link, you can search for and order a Print-on-Demand quadrangle(s).","usgsCitation":"Charpentier, R., and Cook, T.A., 2013, Variability of oil and gas well productivities for continuous (unconventional) petroleum accumulations: U.S. Geological Survey Open-File Report 2013-1001, 3 Sheets: 72 x 36, https://doi.org/10.3133/ofr20131001.","productDescription":"3 Sheets: 72 x 36","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":266853,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2013_1001.jpg"},{"id":266845,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1001/"},{"id":266847,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2013/1001/OF13-1001_sheet1-508.pdf"},{"id":266849,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2013/1001/OF13-1001_sheet2-508.pdf"},{"id":266850,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2013/1001/OF13-1001_sheet3-508.pdf"}],"country":"United States","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ 173.0,16.9 ], [ 173.0,71.83 ], [ -66.95,71.83 ], [ -66.95,16.9 ], [ 173.0,16.9 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"510b9281e4b0947afa3c8554","contributors":{"authors":[{"text":"Charpentier, Ronald R. charpentier@usgs.gov","contributorId":934,"corporation":false,"usgs":true,"family":"Charpentier","given":"Ronald R.","email":"charpentier@usgs.gov","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":472822,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cook, Troy A.","contributorId":52519,"corporation":false,"usgs":true,"family":"Cook","given":"Troy","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":472823,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"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":"2013-01-31T15:01:03","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":266862,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds_706.jpg"},{"id":266861,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/706/pdf/ds706.pdf"},{"id":266860,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/706/"}],"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":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":472115,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70043318,"text":"70043318 - 2013 - Wetland dynamics influence mid-continent duck recruitment","interactions":[],"lastModifiedDate":"2016-06-23T15:35:16","indexId":"70043318","displayToPublicDate":"2013-01-31T00:00:00","publicationYear":"2013","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Wetland dynamics influence mid-continent duck recruitment","docAbstract":"Recruitment is a key factor influencing duck population dynamics. Understanding what regulates recruitment of ducks is a prerequisite to informed habitat and harvest management. Quantity of May ponds (MP) has been linked to recruitment and population size (Kaminski and Gluesing 1987, Raveling and Heitmeyer 1989). However, wetland productivity (quality) is driven by inter-annual hydrological fluctuations. Periodic drying of wetlands due to wet-dry climate cycles releases nutrients and increases invertebrate populations when wet conditions return (Euliss et al. 1999). Wetlands may also become wet or dry within a breeding season. Accordingly, inter-annual and intra-seasonal hydrologic variation potentially influence duck recruitment. Here, we examined influences of wetland quantity, quality, and intra-seasonal dynamics on recruitment of ducks. We indexed duck recruitment by vulnerability-corrected age ratios (juveniles/adult females) for mid-continent Gadwall (Anas strepera). We chose Gadwall because the majority of the continental population breeds in the Prairie Pothole Region (PPR), where annual estimates of MP exist since 1974. We indexed wetland quality by calculating change in MP (?MP) over the past two years (?MP = 0.6[MPt – MPt-1] + 0.4[MPt – MPt-2]). We indexed intra-seasonal change in number of ponds by dividing the PPR mean standardized precipitation index for July by MP (hereafter summer index). MP and ?MP were positively correlated (r = 0.65); therefore, we calculated residual ?MP (?MPr) with a simple linear regression using MP, creating orthogonal variables. Finally, we conducted a multiple regression to examine how MP, ?MPr, and summer index explained variation in recruitment of Gadwall from 1976–2010. Our model explained 67% of the variation in mid-continent Gadwall recruitment and all three hydrologic indices were positively correlated with recruitment (Figure 1). Type II semi-partial R2 estimates indicated that MP accounted for 41%, ?MPr accounted for an additional 22%, and summer index accounted for the remaining 4% of the variation in recruitment. Our results are consistent with previous findings that quantity of MP was important for explaining variation in recruitment of ducks. However, our results also indicated that considering hydrologic dynamics was important for explaining recruitment. Additionally, the index for retention of MP within breeding year also was important, despite its coarse resolution as an average of precipitation events that can vary greatly spatially and in intensity within the PPR. Our results support the idea that wetland ecosystems in the PPR are ultimately regulated through bottom-up process driven by inter- and intra-annual hydrological dynamics. However from the ducks' perspective, hydrological dynamics could influence recruitment proximately through both bottom-up and top-down processes. Specifically, hydrological fluctuations may influence predator populations, prey switching by predators, or duckling vulnerability to predators (Cox et al. 1998). We will propose a conceptual model for understanding the potential role of bottom-up and top-down regulation of duck recruitment based on different hydrological contexts. Clearly, a better understanding of ultimate and proximate factors regulating duck recruitment would improve the effectiveness and efficiency of habitat conservation for ducks. Lastly, our findings could be used to improve models that predict fall flights for the purposes of informing harvest regulations.
","largerWorkType":{"id":24,"text":"Conference Paper"},"largerWorkTitle":"Proceedings of North American Duck Symposium and Workshop","conferenceTitle":"North American Duck Symposium and Workshop","conferenceDate":"January 27-31, 2013","conferenceLocation":"Memphis, TN","language":"English","publisher":"North American Duck Symposium and Workshop","usgsCitation":"Anteau, M.J., Pearse, A.T., and Szymankski, M.L., 2013, Wetland dynamics influence mid-continent duck recruitment, in Proceedings of North American Duck Symposium and Workshop, Memphis, TN, January 27-31, 2013, 2 p.","productDescription":"2 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-038992","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":324310,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"576d083ae4b07657d1a3759a","contributors":{"authors":[{"text":"Anteau, Michael J. 0000-0002-5173-5870 manteau@usgs.gov","orcid":"https://orcid.org/0000-0002-5173-5870","contributorId":3427,"corporation":false,"usgs":true,"family":"Anteau","given":"Michael","email":"manteau@usgs.gov","middleInitial":"J.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":640577,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pearse, Aaron T. 0000-0002-6137-1556 apearse@usgs.gov","orcid":"https://orcid.org/0000-0002-6137-1556","contributorId":1772,"corporation":false,"usgs":true,"family":"Pearse","given":"Aaron","email":"apearse@usgs.gov","middleInitial":"T.","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":640578,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Szymankski, Michael L.","contributorId":117689,"corporation":false,"usgs":true,"family":"Szymankski","given":"Michael","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":516496,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"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":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":70043011,"text":"ofr20131007 - 2013 - Bedrock and surficial geologic map of the Satan Butte and Greasewood 7.5’ quadrangles, Navajo and Apache Counties, northern Arizona","interactions":[],"lastModifiedDate":"2023-06-05T15:53:46.651701","indexId":"ofr20131007","displayToPublicDate":"2013-01-30T00:00:00","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":"2013-1007","title":"Bedrock and surficial geologic map of the Satan Butte and Greasewood 7.5’ quadrangles, Navajo and Apache Counties, northern Arizona","docAbstract":"The geologic map of the Satan Butte and Greasewood 7.5’ quadrangles is the result of a cooperative effort of the U.S. Geological Survey (USGS) and the Navajo Nation to provide regional geologic information for management and planning officials. This map provides geologic information useful for range management, plant and animal studies, flood control, water resource investigations, and natural hazards associated with sand-dune mobility. The map provides connectivity to the regional geologic framework of the Grand Canyon area of northern Arizona. The map area encompasses approximately 314 km2 (123 mi2) within Navajo and Apache Counties of northern Arizona and is bounded by lat 35°37'30\" to 35°30' N., long 109°45' to 110° W. The quadrangles lie within the southern Colorado Plateau geologic province and within the northeastern portion of the Hopi Buttes (Tsézhin Bií). Large ephemeral drainages, Pueblo Colorado Wash and Steamboat Wash, originate north of the map area on the Defiance Plateau and Balakai Mesa respectively. Elevations range from 1,930 m (6,330 ft) at the top of Satan Butte to about 1,787 m (5,860 ft) at Pueblo Colorado Wash where it exits the southwest corner of the Greasewood quadrangle. The only settlement within the map area is Greasewood, Arizona, on the north side of Pueblo Colorado Wash. Navajo Highway 15 crosses both quadrangles and joins State Highway 264 northwest of Ganado. Unimproved dirt roads provide access to remote parts of the Navajo Reservation.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20131007","collaboration":"Prepared in cooperation with the Navajo Nation","usgsCitation":"Amoroso, L., Priest, S.S., and Hiza-Redsteer, M., 2013, Bedrock and surficial geologic map of the Satan Butte and Greasewood 7.5’ quadrangles, Navajo and Apache Counties, northern Arizona: U.S. Geological Survey Open-File Report 2013-1007, 1 Sheet: 42.07 x 45.07; Pamphlet: iii, 24 p.; Readme; Metadata; GIS Database; Shapefiles, https://doi.org/10.3133/ofr20131007.","productDescription":"1 Sheet: 42.07 x 45.07; Pamphlet: iii, 24 p.; Readme; Metadata; GIS Database; Shapefiles","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":266763,"rank":8,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2013_1007.png"},{"id":266759,"rank":7,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/of/2013/1007/of2013-1007_readme.txt"},{"id":417739,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_98121.htm","linkFileType":{"id":5,"text":"html"}},{"id":266757,"rank":6,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2013/1007/of2013-1007_map.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":266756,"rank":4,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2013/1007/","linkFileType":{"id":5,"text":"html"}},{"id":266762,"rank":1,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/of/2013/1007/sbgw_shape.zip"},{"id":266761,"rank":2,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/of/2013/1007/sbgw_db.zip"},{"id":266760,"rank":5,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/2013/1007/of2013-1007_metadata.txt"},{"id":266758,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2013/1007/of2013-1007_pamphlet.pdf","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Arizona","county":"Apache County, Navajo County","otherGeospatial":"Satan Butte and Greasewood 7.5’ quadrangles,","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110,\n 35.5\n ],\n [\n -110,\n 35.625\n ],\n [\n -109.75,\n 35.625\n ],\n [\n -109.75,\n 35.5\n ],\n [\n -110,\n 35.5\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"510a40ece4b0de10a2aaab75","contributors":{"authors":[{"text":"Amoroso, Lee lamoroso@usgs.gov","contributorId":3069,"corporation":false,"usgs":true,"family":"Amoroso","given":"Lee","email":"lamoroso@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":472780,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Priest, Susan S. spriest@usgs.gov","contributorId":30204,"corporation":false,"usgs":true,"family":"Priest","given":"Susan","email":"spriest@usgs.gov","middleInitial":"S.","affiliations":[],"preferred":false,"id":472781,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hiza-Redsteer, Margaret","contributorId":77020,"corporation":false,"usgs":true,"family":"Hiza-Redsteer","given":"Margaret","email":"","affiliations":[],"preferred":false,"id":472782,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"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}]}} ]}