Hurricane Matthew moved adjacent to the coasts of Florida, Georgia, South Carolina, and North Carolina. The hurricane made landfall once near McClellanville, South Carolina, on October 8, 2016, as a Category 1 hurricane on the Saffir-Simpson Hurricane Wind Scale. The U.S. Geological Survey (USGS) deployed a temporary monitoring network of storm-tide sensors at 284 sites along the Atlantic coast from Florida to North Carolina to record the timing, areal extent, and magnitude of hurricane storm tide and coastal flooding generated by Hurricane Matthew. Storm tide, as defined by the National Oceanic and Atmospheric Administration, is the water-level rise generated by a combination of storm surge and astronomical tide during a coastal storm.
The deployment for Hurricane Matthew was the largest deployment of storm-tide sensors in USGS history and was completed as part of a coordinated Federal emergency response as outlined by the Stafford Act (Public Law 92–288, 42 U.S.C. 5121–5207) under a directed mission assignment by the Federal Emergency Management Agency. In total, 543 high-water marks (HWMs) also were collected after Hurricane Matthew, and this was the second largest HWM recovery effort in USGS history after Hurricane Sandy in 2012.
During the hurricane, real-time water-level data collected at temporary rapid deployment gages (RDGs) and long-term USGS streamgage stations were relayed immediately for display on the USGS Flood Event Viewer (https://stn.wim.usgs.gov/FEV/#MatthewOctober2016). These data provided emergency managers and responders with critical information for tracking flood-effected areas and directing assistance to effected communities. Data collected from this hurricane can be used to calibrate and evaluate the performance of storm-tide models for maximum and incremental water level and flood extent, and the site-specific effects of storm tide on natural and anthropogenic features of the environment.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171122","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency","usgsCitation":"Frantz, E.R., Byrne, M.J., Sr., Caldwell, A.W., and Harden, S.L., 2017, Monitoring storm tide and flooding from Hurricane Matthew along the Atlantic coast of the United States, October 2016: U.S. Geological Survey Open-File Report 2017–1122, 37 p., https://doi.org/10.3133/ofr20171122.","productDescription":"vi, 37 p.","numberOfPages":"48","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-081187","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":347956,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1122/ofr20171122.pdf","text":"Report","size":"5.25 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1122"},{"id":347955,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1122/coverthb.jpg"}],"country":"United States","state":"Florida, Georgia, North Carolina, South Carolina","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78.57421875,\n 36.56260003738545\n ],\n [\n -78.50830078125,\n 35.585851593232356\n ],\n [\n -79.69482421875,\n 34.903952965590065\n ],\n [\n -81.9140625,\n 33.358061612778876\n ],\n [\n -82.44140625,\n 31.70947636001935\n ],\n [\n -82.7490234375,\n 30.713503990354965\n ],\n [\n -82.0458984375,\n 28.998531814051795\n ],\n [\n -81.2548828125,\n 27.00040800352175\n ],\n [\n -81.650390625,\n 25.224820176765036\n ],\n [\n -80.595703125,\n 24.666986385216273\n ],\n [\n -79.3212890625,\n 25.20494115356912\n ],\n [\n -79.4970703125,\n 26.96124577052697\n ],\n [\n -79.82666015625,\n 27.994401411046148\n ],\n [\n -80.26611328125,\n 29.592565403314087\n ],\n [\n -80.35400390625,\n 31.259769987394286\n ],\n [\n -78.57421875,\n 32.80574473290688\n ],\n [\n -76.3330078125,\n 33.46810795527896\n ],\n [\n -74.619140625,\n 34.397844946449865\n ],\n [\n -73.32275390625,\n 36.56260003738545\n ],\n [\n -78.57421875,\n 36.56260003738545\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Columbia, SC 29210
The U.S. Geological Survey (USGS) National Water Use Science Project (NWUSP), part of the USGS Water Availability and Use Science Program (WAUSP), has estimated water use in the United States every 5 years since 1950. This report provides an overview of total population, public-supply use, including the population that is served by public-supply systems and the domestic deliveries to those users, and self-supplied domestic water use in the United States for 2015, continuing the task of estimating water use in the United States every 5 years. In this report, estimates for the United States include the 50 States, the District of Columbia, Puerto Rico, and the U.S. Virgin Islands (hereafter referred to as “states” for brevity).
County-level data for total population, public-supply withdrawals and the population served by public-supply systems, and domestic withdrawals for 2015 were published in a data release in an effort to provide data to the public in a timely manner. Data in the current version (1.0) of Dieter and others (2017) contains county-level total withdrawals from groundwater and surface-water sources (both fresh and saline) for public-water supply, the deliveries from those suppliers to domestic users, and the quantities of water from groundwater and surface-water sources for self-supplied domestic users, and total population. Methods used to estimate the various data elements for the public-supply and domestic use categories at the county level are described by Bradley (2017).
This Open-File Report is an interim report summarizing the data published in Dieter and others (2017) at the state and national level. This report includes discussions on the total population, totals for public-supply withdrawals and population served, total domestic withdrawals, and provides comparisons of the 2015 estimates to 2010 estimates (Maupin and others, 2014). Total domestic water use, as described in this report, represents the summation of deliveries from public-water supply to domestic users plus self-supplied domestic withdrawals.
Values for 2010 are the best available data for 2010 from the USGS Aggregate Water-Use Data System (AWUDS). The 2010 values presented in this report may have been revised from 2010 values published in Maupin and others (2014), and therefore values for 2010 in this report may not exactly match values in Maupin and others (2014).
Withdrawal and population values in this report are rounded to three significant figures. All values are rounded independently, so the sums of individually rounded numbers may not equal the totals. Percent change is calculated on unrounded data and is expressed as an integer. Differences between 2010 and 2015 values are calculated on unrounded data, then the differences are rounded.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171131","usgsCitation":"Dieter, C.A., and Maupin, M.A., 2017, Public supply and domestic water use in the United States, 2015: U.S. Geological Survey Open-File ReportDirector, MD-DE-DC Water Science Center
U.S. Geological Survey
5522 Research Park Drive
Baltimore, MD 21228
Trace-metal concentrations in sediment and in the clam Macoma petalum (formerly reported as Macoma balthica), clam reproductive activity, and benthic macroinvertebrate community structure were investigated in a mudflat 1 kilometer south of the discharge of the Palo Alto Regional Water Quality Control Plant (PARWQCP) in south San Francisco Bay, Calif. This report includes the data collected by U.S. Geological Survey (USGS) scientists for the period January 2014 to December 2016. These append to long-term datasets extending back to 1974. A major focus of the report is an integrated description of the 2016 data within the context of the longer, multi-decadal dataset. This dataset supports the City of Palo Alto’s Near-Field Receiving Water Monitoring Program, initiated in 1994.
Significant reductions in silver and copper concentrations in sediment and M. petalum occurred at the site in the 1980s following the implementation by PARWQCP of advanced wastewater treatment and source control measures. Since the 1990s, concentrations of these elements appear to have stabilized at concentrations somewhat above (silver) or near (copper) regional background concentrations Data for other metals, including chromium (Cr), mercury (Hg), nickel (Ni), selenium (Se), and zinc (Zn), have been collected since 1994. Over this period, concentrations of these elements have remained relatively constant, aside from seasonal variation that is common to all elements. In 2016, concentrations of silver and copper in M. petalum varied seasonally in response to a combination of site-specific metal exposures and annual growth and reproduction, as reported previously. Seasonal patterns for other elements, including Cr, Ni, Zn, Hg, and Se, were generally similar in timing and magnitude as those for Ag and Cu. This record suggests that legacy contamination and regional-scale factors now largely control sedimentary and bioavailable concentrations of silver and copper, as well as other elements of regulatory interest, at the Palo Alto site.
Analyses of the benthic community structure of a mudflat in south San Francisco Bay over a 40-year period show that changes in the community have occurred concurrent with reduced concentrations of metals in the sediment and in the tissues of the biosentinel clam, M. petalum, from the same area. Analysis of M. petalum shows increases in reproductive activity concurrent with the decline in metal concentrations in the tissues of this organism. Reproductive activity is presently stable (2016), with almost all animals initiating reproduction in the fall and spawning the following spring. The entire infaunal community has shifted from being dominated by several opportunistic species to a community where the species are more similar in abundance, a pattern that indicates a more stable community that is subjected to fewer stressors. In addition, two of the opportunistic species (Ampelisca abdita and Streblospio benedicti) that brood their young and live on the surface of the sediment in tubes have shown a continual decline in dominance coincident with the decline in metals; both species had short-lived rebounds in abundance in 2008, 2009, and 2010 and showed signs of increasing abundance in 2016. Heteromastus filiformis (a subsurface polychaete worm that lives in the sediment, consumes sediment and organic particles residing in the sediment, and reproduces by laying its eggs on or in the sediment) showed a concurrent increase in dominance and, in the last several years before 2008, showed a stable population. H. filiformis abundance increased slightly in 2011–2012 and returned to pre-2011 numbers in 2016. An unidentified disturbance occurred on the mudflat in early 2008 that resulted in the loss of the benthic animals, except for deep-dwelling animals like Macoma petalum. However, within two months of this event animals returned to the mudflat. The resilience of the community suggested that the disturbance was not due to a persistent toxin or anoxia. The reproductive mode of most species present in 2016 is reflective of species that were available either as pelagic larvae or as mobile adults. Although oviparous species were lower in number in this group, the authors hypothesize that these species will return slowly as more species move back into the area. The use of functional ecology was highlighted in the 2016 benthic community data, which showed that the animals that have now returned to the mudflat are those that can respond successfully to a physical, nontoxic disturbance. Today, community data show a mix of species that consume the sediment, or filter feed, have pelagic larvae that must survive landing on the sediment, and those that brood their young. USGS scientists view the 2008 disturbance event as a response by the infaunal community to an episodic natural stressor (possibly sediment accretion or a pulse of freshwater), in contrast to the long-term recovery from metal contamination. We will compare this recovery to the long-term recovery observed after the 1970s when the decline in sediment pollutants was the dominating factor.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171135","collaboration":"Prepared in cooperation with the City of Palo Alto, California","usgsCitation":"Cain, D.J., Thompson, J.K., Parchaso, F., Pearson, S., Stewart, R., Turner, M., Barasch, D., and Luoma, S.N., 2017, Near-field receiving water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California; 2016: U.S. Geological Survey Open-File Report 2017–1135, 75 p., https://doi.org/10.3133/ofr20171135.","productDescription":"vi, 75 p.","numberOfPages":"82","onlineOnly":"Y","ipdsId":"IP-088104","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":416202,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20231017","text":"Open-File Report 2023-1017","linkHelpText":"- Near-Field Receiving-Water Monitoring of Trace Metals and a Benthic Community Near the Palo Alto Regional Water Quality Control Plant in South San Francisco Bay, California—2020"},{"id":416201,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20211079","text":"Open-File Report 2021-1079","linkHelpText":"- Near-Field Receiving-Water Monitoring of Trace Metals and a Benthic Community Near the Palo Alto Regional Water Quality Control Plant in South San Francisco Bay, California—2019"},{"id":416200,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20191084","text":"Open-File Report 2019-1084","linkHelpText":"- Near-Field Receiving-Water Monitoring of Trace Metals and a Benthic Community Near the Palo Alto Regional Water Quality Control Plant in South San Francisco Bay, California—2018"},{"id":416199,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20181107","text":"Open-File Report 2018-1107","linkHelpText":"- Near-field receiving-water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California—2017"},{"id":416198,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20161118","text":"Open-File Report 2016-1118","linkHelpText":"- Near-field receiving water monitoring of trace metals and a benthic community near the Palo Alto Regional Water Quality Control Plant in south San Francisco Bay, California; 2015"},{"id":347750,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1135/coverthb_.jpg"},{"id":347751,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1135/ofr.20171135.pdf","text":"Report","size":"4.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1135"}],"country":"United States","state":"California","city":"Palo Alto","otherGeospatial":"south San Francisco bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.16590881347656,\n 37.398528132728615\n ],\n [\n -121.91184997558595,\n 37.398528132728615\n ],\n [\n -121.91184997558595,\n 37.54566616715801\n ],\n [\n -122.16590881347656,\n 37.54566616715801\n ],\n [\n -122.16590881347656,\n 37.398528132728615\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"NRP staff
National Research Program
U.S. Geological Survey
345 Middlefield Road, MS-435
Menlo Park, CA 94025
The National Land Cover Database (NLCD) provides thematic land cover and land cover change data at 30-meter spatial resolution for the United States. Although the NLCD is considered to be the leading thematic land cover/land use product and overall classification accuracy across the NLCD is high, performance and consistency in the vast shrub and grasslands of the Western United States is lower than desired. To address these issues and fulfill the needs of stakeholders requiring more accurate rangeland data, the USGS has developed a method to quantify these areas in terms of the continuous cover of several cover components. These components include the cover of shrub, sagebrush (Artemisia spp), big sagebrush (Artemisia tridentata spp.), herbaceous, annual herbaceous, litter, and bare ground, and shrub and sagebrush height. To produce maps of component cover, we collected field data that were then associated with spectral values in WorldView-2 and Landsat imagery using regression tree models. The current report outlines the procedures and results of converting these continuous cover components to three thematic NLCD classes: barren, shrubland, and grassland. To accomplish this, we developed a series of indices and conditional models using continuous cover of shrub, bare ground, herbaceous, and litter as inputs. The continuous cover data are currently available for two large regions in the Western United States. Accuracy of the “cross-walked” product was assessed relative to that of NLCD 2011 at independent validation points (n=787) across these two regions. Overall thematic accuracy of the “cross-walked” product was 0.70, compared to 0.63 for NLCD 2011. The kappa value was considerably higher for the “cross-walked” product at 0.41 compared to 0.28 for NLCD 2011. Accuracy was also evaluated relative to the values of training points (n=75,000) used in the development of the continuous cover components. Again, the “cross-walked” product outperformed NLCD 2011, with an overall accuracy of 0.81, compared to 0.66 for NLCD 2011. These results demonstrated that our continuous cover predictions and models were successful in increasing thematic classification accuracy in Western United States shrublands. We plan to directly use the “cross-walked” product, where available, in the NLCD 2016 product.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171119","usgsCitation":"Rigge, M.B., Gass, Leila, Homer, C.G., and Xian, G.Z., 2017, Methods for converting continuous shrubland ecosystem component values to thematic National Land Cover Database classes: U.S. Geological Survey Open-File Report 2017–1119, 10 p., https://doi.org/10.3133/ofr20171119.","productDescription":"iv, 10 p.","numberOfPages":"18","onlineOnly":"Y","ipdsId":"IP-089077","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":347404,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1119/coverthb.jpg"},{"id":347405,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1119/ofr20171119.pdf","text":"Report","size":"2.43 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017–1119"}],"contact":"Director, Earth Resources Observation and Science (EROS) Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
In 2017, the U.S. Geological Survey (USGS) completed an updated assessment of undiscovered, technically recoverable oil and gas resources in the Spraberry Formation of the Midland Basin (Permian Basin Province) in southwestern Texas (Marra and others, 2017). The Spraberry Formation was assessed using both the standard continuous (unconventional) and conventional methodologies established by the USGS for three assessment units (AUs): (1) Lower Spraberry Continuous Oil Trend AU, (2) Middle Spraberry Continuous Oil Trend AU, and (3) Northern Spraberry Conventional Oil AU. The revised assessment resulted in total estimated mean resources of 4,245 million barrels of oil, 3,112 billion cubic feet of gas, and 311 million barrels of natural gas liquids. The purpose of this report is to provide supplemental documentation of the input parameters used in the USGS 2017 Spraberry Formation assessment.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171117","usgsCitation":"Marra, K.R., 2017, U.S. Geological Survey input-data forms for the assessment of the Spraberry Formation of the Midland Basin, Permian Basin Province, Texas, 2017: U.S. Geological Survey Open-File Report 2017–1117, 46 p., https://doi.org/10.3133/ofr20171117.","productDescription":"iii, 46 p.","numberOfPages":"54","onlineOnly":"Y","ipdsId":"IP-089773","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":347263,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/fs20173029","text":"Fact Sheet 2017–3029:","linkHelpText":"Assessment of Undiscovered Oil and Gas Resources in the Spraberry Formation of the Midland Basin, Permian Basin Province, Texas, 2017"},{"id":347257,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1117/coverthb.jpg"},{"id":347258,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1117/ofr20171117.pdf","text":"Report","size":"372 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1117"}],"country":"United States","state":"Texas","otherGeospatial":"Spraberry Formation of the Midland Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -103.75,\n 30.3333\n ],\n [\n -99.25,\n 30.3333\n ],\n [\n -99.25,\n 34\n ],\n [\n -103.75,\n 34\n ],\n [\n -103.75,\n 30.3333\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver, CO 80225-0046
The geologic maps and cross sections presented in this report are redrafted and modified versions of the Geologic map and map of useful minerals of the Dusar area (scale 1:50,000) and Geologic sketch map of the Dusar and Namak-sory ore occurrences (scale 1:10,000), located in the Herat Province, Afghanistan. The original maps and cross sections are contained in unpublished Soviet report no. 0290 (Tarasenko and others, 1973) prepared in cooperation with the Ministry of Mines and Industries of the Royal Government of Afghanistan, in Kabul during 1973 under contract no. 50728. The redrafted maps and cross sections (modified from Tarasenko and others, 1973) illustrate the geological structure and mineral occurrences of the Dusar copper-gold-silver-lead-zinc prospect area of western Afghanistan, located within the Dusar-Shaida copper and tin area of interest (AOI), Herat Province, Afghanistan.
Mineralization in the Dusar area is hosted within Early Jurassic to Early Cretaceous stratified volcanic and sedimentary rocks associated with numerous diabase and gabbro-diabase intrusive bodies and is generally near a major northeast-trending system of faults and quartz veins. Host rocks consist of quartz keratophyre and quartz-feldspar porphyry, with layers of schist, phyllite, and quartz-chlorite and chlorite-sericite slate; and limestone and shale, with schist and carbonate-chlorite and chlorite slate. Known mineralization includes an extensive quartz vein system, shown on the map as the “northern occurrence,” as well as the Dusar and Namak-sory gossan zones, interpreted to have formed from remnant pyrite mineralization. The veins of the northern occurrence and their altered host rocks are known to contain anomalous to economic concentrations of precious and base metals, with concentrations locally in excess of 2 parts per million gold, 100 parts per million silver, 5 percent copper, and 1 percent lead. These veins occur in swarms, and are hosted along structures that are approximately concordant with the plane of the metamorphic fabric. The veins consist mostly of quartz, with minor carbonate and sulfide minerals, and display weak alteration halos along their margins. The gossans are locally anomalous in these metals, but their size and extent makes them attractive exploration targets for potential massive sulfide mineralization.
The Dusar gossan zone is a massive, ochreous, and siliceous limonitic rock, approximately 2,200 meters long, 30 to 250 meters wide, and 2.0 to 7.2 meters thick. Drilling below the Dusar gossan intersected a siliceous, sericitic, and limonitic rock underlain by quartz keratophyre with abundant disseminated pyrite. Mineralized sections grade 0.06 weight percent copper and up to 0.05 weight percent zinc. The Namak-sory gossan zone contains a similar deposit with anomalous concentrations of copper, zinc, and gold.
The redrafted maps and cross sections reproduce the topology of rock units, contacts, and faults of the original Soviet maps and cross sections, and include minor modifications based on examination of the originals and observations made during two brief field visits by USGS staff in August, 2010, and June, 2013.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171126","collaboration":"Prepared in cooperation with the Afghan Geological Survey under the auspices of the U.S. Department of Defense","usgsCitation":"Tucker, R.D., Stettner, W.R., Masonic, L.M., and Bogdanow, A.K., comps., 2017, Geologic map of the Dusar area, Herat Province, Afghanistan; Modified from the 1973 original map compilations of V.I. Tarasenko and others: U.S. Geological Survey Open-File Report 2017–1126, 1 sheet, scales 1:50,000 and 1:10,000, https://doi.org/10.3133/ofr20171126.","productDescription":"57.56 x 39.83 inches","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-050066","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":346482,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1126/coverthb.jpg"},{"id":346483,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1126/ofr20171126.pdf","text":"Report","size":"786 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OF 2017-1126"}],"country":"Afghanistan","otherGeospatial":"Dusar Area, Herat Province","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 61.1,\n 33.5\n ],\n [\n 61.5,\n 33.5\n ],\n [\n 61.5,\n 34.020794936018724\n ],\n [\n 61.1,\n 34.020794936018724\n ],\n [\n 61.1,\n 33.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Office of International Programs
U.S. Geological Survey
917 National Center
Reston, VA 20192
The Southern Great Plains Rapid Ecoregional Assessment was conducted in partnership with the Bureau of Land Management (BLM) and the Great Plains Landscape Conservation Cooperative. The overall goal of the Rapid Ecoregional Assessments (REAs) is to compile and synthesize regional datasets to facilitate evaluation of the cumulative effects of change agents on priority ecological communities and species. In particular, the REAs identify and map the distribution of communities and wildlife habitats at broad spatial extents and provide assessments of ecological conditions. The REAs also identify where and to what degree ecological resources are currently at risk from change agents, such as development, fire, invasive species, and climate change. The REAs can help managers identify and prioritize potential areas for conservation or restoration, assess cumulative effects as required by the National Environmental Policy Act, and inform landscape-level planning and management decisions for multiple uses of public lands.
Management questions form the basis for the REA framework and were developed in conjunction with the BLM and other stakeholders. Conservation elements are communities and species that are of regional management concern. Core management questions relate to the key ecological attributes and change agents associated with each conservation element. Integrated management questions synthesize the results of the primary core management questions into overall landscape-level ranks for each conservation element.
The ecological communities evaluated as conservation elements are shortgrass, mixed-grass, and sand prairies; all grasslands; riparian and nonplaya wetlands; playa wetlands and saline lakes; and prairie streams and rivers. Species and species assemblages evaluated are the freshwater mussel assemblage, Arkansas River shiner (Notropis girardi), ferruginous hawk (Buteo regalis), lesser prairie chicken (Tympanuchus pallidicinctus), snowy plover (Charadrius nivosus), mountain plover (Charadrius montanus), long-billed curlew (Numenius americanus), interior least tern (Sternula antillarum athalassos), burrowing owl (Athene cunicularia hypugaea), black-tailed prairie dog (Cynomys ludovicianus), bat assemblage, swift fox (Vulpes velox), and mule deer (Odocoileus hemionus).
The Southern Great Plains REA is summarized in a series of three reports and associated datasets. The pre-assessment report (available online at https://pubs.usgs.gov/of/2015/1003/) summarizes the process used by the REA stakeholders to select management questions, conservation elements, and change agents. It also provides background information for each conservation element. Volume I of the Southern Great Plains REA report (this volume) addresses the ecological communities. Volume II will address the species and species assemblages. All source and derived datasets used to produce the maps and graphs for REAs are available online at the BLM Landscape Approach Data Portal (https://landscape.blm.gov/geoportal/catalog/REAs/REAs.page).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171100","collaboration":"Prepared in cooperation with the Bureau of Land Management and the Great Plains Landscape Conservation Cooperative","usgsCitation":"Reese, G.C., Burris, Lucy, Carr, N.B., Leinwand, I.I.F., and Melcher, C.P., 2017, Southern Great Plains Rapid Ecoregional assessment—Volume I. Ecological communities: U.S. Geological Survey Open-File Report 2017–1100, 126 p., https://doi.org/10.3133/ofr20171100.","productDescription":"xiii, 126 p.","numberOfPages":"144","onlineOnly":"N","ipdsId":"IP-080929","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":346770,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1100/coverthb.jpg"},{"id":346771,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1100/ofr20171100.pdf","text":"Report","size":"15.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1100"}],"country":"United States","state":"Colorado, Kansas, Nebraska, New Mexico, Oklahoma, Texas, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.14990234375,\n 30.939924331023445\n ],\n [\n -96.2841796875,\n 30.939924331023445\n ],\n [\n -96.2841796875,\n 43.08493742707592\n ],\n [\n -106.14990234375,\n 43.08493742707592\n ],\n [\n -106.14990234375,\n 30.939924331023445\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Fort Collins Science Center
U.S. Geological Survey
2150 Centre Ave., Building C
Fort Collins, CO 80526-8118
Most mortality of endangered Lost River (Deltistes luxatus) and shortnose (Chasmistes brevirostris) suckers in Upper Klamath Lake, Oregon, occurs within the first year of life. Juvenile suckers in Clear Lake Reservoir, California, survive longer and may even recruit to the spawning populations. In a previous (2013–2014) study, the health and condition of juvenile suckers and the dynamics of water quality between Upper Klamath Lake and Clear Lake Reservoir were compared. That study found that apparent signs of stress or exposure to irritants, such as peribiliary cuffing in liver tissue and mild inflammation and necrosis in gill tissues, were present in suckers from both lakes and were unlikely to be clues to the cause of differential mortality between lakes. Seasonal trends in energy storage as glycogen and triglycerides were also similar between lakes, indicating prey limitation was not a likely factor in differential mortality. To better understand the relationship between juvenile sucker health and water quality, we examined suckers collected in 2014–2015 from Upper Klamath Lake, where water quality can be dynamic and, at times, extreme.
While there were notable differences in water quality and fish health between years, we were not able to identify any specific water-quality-related causes for differential fish condition. Water quality was generally better in 2014 than in 2015. When considered together afflictions and abnormalities generally indicated healthier suckers in 2014 than 2015. Low dissolved-oxygen events (< 4 milligrams per liter) were less frequent and occurred earlier; high pH events (≥ 9.5) were less frequent and shorter in duration; large diel fluctuations in pH (≥ 1.4) were less frequent; water temperatures were warmer, particularly in July and September; and concentrations of microcystin in both large and small fractions of samples were lower in 2014 than in 2015. Total and therefore also un-ionized ammonia were low in 2014–2015 relative to concentrations known to affect suckers. Petechial hemorrhages of the skin, attached Lernaea spp. and eosinophilic hyaline droplets in the kidney tubules were less prevalent in 2014 than in 2015; however, hyperplastic and hypertrophic gill tissue and trichodinids on the gills were observed more frequently in 2014. There were more suckers with normal liver color and texture in 2014 than in 2015. The prevalence of suckers with liver inflammation was greater in 2014 and only observed in suckers collected after August 5, whereas liver inflammation occurred intermittently in 2015. Liver glycogen among suckers decreased in late-August 2014 and increased from early August to mid-September 2015. Lost River suckers had greater whole-body triglyceride content but a larger proportion with an absence of visceral fat observed in 2014 than in 2015. In contrast, shortnose suckers were similar between years in regard to both whole-body triglyceride and visceral fat. Black-spot-forming parasites (trematode metacercariae) were observed in a higher prevalence on shortnose suckers but not Lost River suckers in 2014 than in 2015. Opercular deformities were less prevalent in both species in 2014 than in 2015.
Neither gross nor histological examination revealed a high prevalence of abnormalities in suckers that clearly indicate a primary mechanism for juvenile mortality in Upper Klamath Lake. Histological abnormalities were almost always focal and minimal or mild except where associated with parasites. Mild to severe focal abnormalities associated with Lernaea sp. attachment sites and encysted digenean (trematode) metacercariae are unlikely to be associated with mortality. Severe and diffuse inflammation and hyperplasia of the gills associated with Ichthyobodo sp. on one Lost River sucker, may indicate a potential cause of mortality. High mortality may have primarily occurred outside our study period (for example, in spring or over winter), or was caused by a factor that could not be detected with our methods (for example, predation). Alternatively, abnormalities in a small percentage of passively captured suckers in Upper Klamath Lake may indicate health-related issues that were more prevalent in populations than in our samples. Temporary decreases in liver glycogen stores may also indicate periods of stress, which may eventually lead to mortality of young suckers.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171134","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Burdick, S.M., Conway, C.M., Elliott, D.G., Hoy, M.S., Dolan-Caret, Amari, and Ostberg, C.O., 2017, Health and condition of endangered young-of-the-year Lost River and shortnose suckers relative to water quality in Upper Klamath Lake, Oregon, 2014–2015: U.S. Geological Survey Open-File Report 2017-1134, 40 p., https://doi.org/10.3133/ofr20171134.","productDescription":"vi, 41 p.","onlineOnly":"Y","ipdsId":"IP-089897","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":347019,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1134/coverthb.jpg"},{"id":347020,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1134/ofr20171134.pdf","text":"Report","size":"2.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1134"}],"country":"United States","state":"Oregon","otherGeospatial":"Upper Klamath Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.06634521484374,\n 42.45892719924497\n ],\n [\n -122.08831787109375,\n 42.476148570254516\n ],\n [\n -122.08694458007812,\n 42.465005871175755\n ],\n [\n -122.07733154296875,\n 42.454874423427874\n ],\n [\n -122.07046508789062,\n 42.44271452226932\n ],\n [\n -122.04437255859375,\n 42.431565872579185\n ],\n [\n -122.03613281249999,\n 42.4234565179383\n ],\n [\n -122.04025268554688,\n 42.415346114253616\n ],\n [\n -122.03475952148436,\n 42.40317854182803\n ],\n [\n -122.01828002929686,\n 42.397093870535514\n ],\n [\n -122.00454711914061,\n 42.39912215986002\n ],\n [\n -122.00592041015626,\n 42.41737381352118\n ],\n [\n -121.99081420898439,\n 42.415346114253616\n ],\n [\n -121.97845458984375,\n 42.409262623071186\n ],\n [\n -121.97433471679689,\n 42.39912215986002\n ],\n [\n -121.97708129882812,\n 42.386951440524854\n ],\n [\n -121.96746826171875,\n 42.381879610913195\n ],\n [\n -121.96060180664062,\n 42.39405131362432\n ],\n [\n -121.95648193359374,\n 42.405206634470666\n ],\n [\n -121.96609497070312,\n 42.42447024463857\n ],\n [\n -121.96609497070312,\n 42.43257946814707\n ],\n [\n -121.95510864257811,\n 42.42649764886491\n ],\n [\n -121.94412231445314,\n 42.402164470921285\n ],\n [\n -121.93862915039061,\n 42.38390839192567\n ],\n [\n -121.91390991210938,\n 42.367676308265196\n ],\n [\n -121.89468383789061,\n 42.353469793490646\n ],\n [\n -121.91390991210938,\n 42.35245491952622\n ],\n [\n -121.937255859375,\n 42.34636533160187\n ],\n [\n -121.94137573242186,\n 42.33519955487233\n ],\n [\n -121.94137573242186,\n 42.31997030030749\n ],\n [\n -121.94000244140624,\n 42.309815415686664\n ],\n [\n -121.937255859375,\n 42.3016903282445\n ],\n [\n -121.93038940429688,\n 42.293564192170095\n ],\n [\n -121.93038940429688,\n 42.30270602152241\n ],\n [\n -121.92214965820311,\n 42.30676863078423\n ],\n [\n -121.90292358398438,\n 42.313877566161864\n ],\n [\n -121.88919067382812,\n 42.31793945446847\n ],\n [\n -121.88232421875,\n 42.3037216984154\n ],\n [\n -121.86721801757812,\n 42.27730877423709\n ],\n [\n -121.85348510742188,\n 42.26308184299127\n ],\n [\n -121.85073852539064,\n 42.249868245939325\n ],\n [\n -121.83425903320314,\n 42.239702056572334\n ],\n [\n -121.80679321289062,\n 42.235635122140614\n ],\n [\n -121.80953979492188,\n 42.247835139120575\n ],\n [\n -121.81365966796874,\n 42.26308184299127\n ],\n [\n -121.8218994140625,\n 42.274260416436455\n ],\n [\n -121.83425903320314,\n 42.28442103567813\n ],\n [\n -121.82876586914061,\n 42.3016903282445\n ],\n [\n -121.81365966796874,\n 42.29864315010169\n ],\n [\n -121.81915283203126,\n 42.31083097788358\n ],\n [\n -121.81777954101561,\n 42.32606244456202\n ],\n [\n -121.827392578125,\n 42.34129022434778\n ],\n [\n -121.82464599609375,\n 42.35854391749705\n ],\n [\n -121.81228637695312,\n 42.370720143531976\n ],\n [\n -121.80953979492188,\n 42.386951440524854\n ],\n [\n -121.83563232421875,\n 42.409262623071186\n ],\n [\n -121.85348510742188,\n 42.42142901536395\n ],\n [\n -121.86584472656251,\n 42.43359304732316\n ],\n [\n -121.86996459960938,\n 42.44271452226932\n ],\n [\n -121.88369750976562,\n 42.446768084936735\n ],\n [\n -121.8988037109375,\n 42.44879476791561\n ],\n [\n -121.904296875,\n 42.459940352216556\n ],\n [\n -121.91116333007811,\n 42.476148570254516\n ],\n [\n -121.91940307617188,\n 42.48019996901214\n ],\n [\n -121.93038940429688,\n 42.494377798972465\n ],\n [\n -121.94412231445314,\n 42.49842801732155\n ],\n [\n -121.94137573242186,\n 42.50450285299051\n ],\n [\n -121.95648193359374,\n 42.49842801732155\n ],\n [\n -121.95098876953125,\n 42.51057709842409\n ],\n [\n -121.937255859375,\n 42.521711682043765\n ],\n [\n -121.92901611328125,\n 42.532844281713125\n ],\n [\n -121.92214965820311,\n 42.57533232110996\n ],\n [\n -121.93588256835938,\n 42.57836607418331\n ],\n [\n -121.9482421875,\n 42.58847751848118\n ],\n [\n -121.96609497070312,\n 42.59151063198149\n ],\n [\n -121.98806762695311,\n 42.57634358853339\n ],\n [\n -121.98394775390625,\n 42.563195832927384\n ],\n [\n -121.97296142578124,\n 42.551056983385934\n ],\n [\n -121.98806762695311,\n 42.53891577257117\n ],\n [\n -121.9976806640625,\n 42.54802190204827\n ],\n [\n -122.00592041015626,\n 42.53891577257117\n ],\n [\n -122.01141357421875,\n 42.525760129656845\n ],\n [\n -122.0086669921875,\n 42.51462626746592\n ],\n [\n -121.99905395507812,\n 42.49235259142821\n ],\n [\n -122.01965332031249,\n 42.49336520339777\n ],\n [\n -122.04299926757812,\n 42.495390378152244\n ],\n [\n -122.05810546875,\n 42.48627657532139\n ],\n [\n -122.05810546875,\n 42.475135679579964\n ],\n [\n -122.06634521484374,\n 42.45892719924497\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115
Vertical one-dimensional shear wave velocity (VS) profiles are presented for strong-motion sites in Arizona for a suite of stations surrounding the Palo Verde Nuclear Generating Station. The purpose of the study is to determine the detailed site velocity profile, the average velocity in the upper 30 meters of the profile (VS30), the average velocity for the entire profile (VSZ), and the National Earthquake Hazards Reduction Program (NEHRP) site classification. The VS profiles are estimated using a non-invasive continuous-sine-wave method for gathering the dispersion characteristics of surface waves. Shear wave velocity profiles were inverted from the averaged dispersion curves using three independent methods for comparison, and the root-mean-square combined coefficient of variation (COV) of the dispersion and inversion calculations are estimated for each site.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161208","usgsCitation":"Kayen, R.E., Carkin, B.A., and Corbett, S.C., 2017, Seismic velocity site characterization of 10 Arizona strong-motion recording stations by spectral analysis of surface wave dispersion: U.S. Geological Survey Open-File Report 2016–1208, 32 p., https://doi.org/10.3133/ofr20161208.","productDescription":"32 p.","numberOfPages":"32","onlineOnly":"Y","ipdsId":"IP-060760","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":347018,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1208/ofr20161208.pdf","text":"Report","size":"4.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1208"},{"id":347017,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1208/coverthb_.jpg"}],"country":"United States","state":"Arizona","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114,\n 32.3\n ],\n [\n -111.5,\n 32.3\n ],\n [\n -111.5,\n 34.33\n ],\n [\n -114,\n 34.33\n ],\n [\n -114,\n 32.3\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Pacific Coastal and Marine Science Center
U.S. Geological Survey
Pacific Science Center
2885 Mission St.
Santa Cruz, CA 95060
During 2013, the U.S. Geological Survey (USGS) National Water-Quality Assessment Project (NAWQA), in collaboration with the USGS Columbia Environmental Research Center, the U.S. Environmental Protection Agency (EPA) National Rivers and Streams Assessment (NRSA), and the EPA Office of Pesticide Programs assessed stream quality across the Midwestern United States. This Midwest Stream Quality Assessment (MSQA) simultaneously characterized watershed and stream-reach water-quality stressors along with instream biological conditions, to better understand regional stressor-effects relations. The MSQA design focused on effects from the widespread agriculture in the region and urban development because of their importance as ecological stressors of particular concern to Midwest region resource managers.
A combined random stratified selection and a targeted selection based on land-use data were used to identify and select sites representing gradients in agricultural intensity across the region. During a 14-week period from May through August 2013, 100 sites were selected and sampled 12 times for contaminants, nutrients, and sediment. This 14-week water-quality “index” period culminated with an ecological survey of habitat, periphyton, benthic macroinvertebrates, and fish at all sites. Sediment was collected during the ecological survey for analysis of sediment chemistry and toxicity testing. Of the 100 sites, 50 were selected for the MSQA random stratified group from 154 NRSA sites planned for the region, and the other 50 MSQA sites were selected as targeted sites to more evenly cover agricultural and urban stressor gradients in the study area. Of the 50 targeted sites, 12 were in urbanized watersheds and 21 represented “good” biological conditions or “least disturbed” conditions. The remaining 17 targeted sites were selected to improve coverage of the agricultural intensity gradient or because of historical data collection to provide temporal context for the study.
This report provides a detailed description of the MSQA study components, including surveys of ecological conditions, routine water sampling, deployment of passive polar organic compound integrative samplers, and stream sediment sampling at all sites. Component studies that were completed to provide finer scale temporal data or more extensive analysis at selected sites, included continuous water-quality monitoring, daily pesticide sampling, laboratory and in-stream water toxicity testing efforts, and deployment of passive suspended-sediment samplers.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171073","collaboration":"National Water-Quality Program Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Garrett, J.D., Frey, J.W., Van Metre, P.C., Journey, C.A., Nakagaki, Naomi, Button, D.T., and Howell, L.H., 2017, Design and methods of the Midwest Stream Quality Assessment (MSQA), 2013: U.S. Geological Survey Open-File Report 2017–1073, 59 p., 4 app., https://doi.org/10.3133/ofr20171073.","productDescription":"Report: x, 57 p.; 4 Appendixes","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-075316","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"links":[{"id":346657,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1073/coverthb.jpg"},{"id":346658,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1073/ofr20171073.pdf","text":"Report","size":"19.5 MB","description":"OFR 2017-1073"},{"id":346660,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2017/1073/ofr20171073_appendix2_LabSchedules.xlsx","text":"Appendix 2","size":"80.6 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"Appendix 2","linkHelpText":"- Description of the Laboratory Analyses Used for Water, Periphyton, Sediment, Fish Tissue, and Passive Integrated Samples"},{"id":346659,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2017/1073/ofr20171073_appendix1_SiteDetails.xlsx","text":"Appendix 1","size":"149 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"Appendix 1","linkHelpText":"- Additional Site, Reach, and Watershed Characteristics of Selected Sites Assessed as Part of the U.S. Geological Survey (USGS) National Water-Quality Assessment (NAWQA) Midwest Stream Quality Assessment (MSQA) in 2013"},{"id":346661,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2017/1073/ofr20171073_appendix3_SampleCounts.xlsx","text":"Appendix 3","size":"50.5 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"Appendix 3","linkHelpText":"- Description of Quality Control Samples"},{"id":346662,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2017/1073/ofr20171073_appendix4_Workplan.xlsx","text":"Appendix 4","size":"27.5 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"Appendix 4","linkHelpText":"- Description of the Sampling Timelines, Matrix, Collection, and Processing for Water, Sediment, and Ecological Samples"}],"country":"United States","state":"Illinois, Indiana, Iowa, Kansas, Kentucky, Michigan, Minnesota, Missouri, Nebraska, Ohio, South Dakota, Wisconsin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.13037109375,\n 45.398449976304086\n ],\n [\n -96.85546875,\n 45.042478050891546\n ],\n [\n -97.1630859375,\n 44.402391829093915\n ],\n [\n -97.119140625,\n 43.78695837311561\n ],\n [\n -97.2509765625,\n 43.100982876188546\n ],\n [\n -97.6904296875,\n 42.87596410238256\n ],\n [\n -98.02001953125,\n 42.76314586689492\n ],\n [\n -99.36035156249999,\n 42.71473218539458\n ],\n [\n -100.04150390625,\n 42.45588764197166\n ],\n [\n -99.86572265625,\n 42.06560675405716\n ],\n [\n -98.89892578125,\n 41.672911819602085\n ],\n [\n -97.6904296875,\n 41.409775832009565\n ],\n [\n -97.119140625,\n 40.93011520598305\n ],\n [\n -96.8994140625,\n 40.39676430557203\n ],\n [\n -96.5478515625,\n 39.65645604812829\n ],\n [\n -96.1962890625,\n 39.095962936305476\n ],\n [\n -95.80078125,\n 38.90813299596705\n ],\n [\n -94.89990234375,\n 38.46219172306828\n ],\n [\n -93.49365234375,\n 38.44498466889473\n ],\n [\n -92.4169921875,\n 38.25543637637947\n ],\n [\n -91.58203125,\n 38.048091067457236\n ],\n [\n -90.4833984375,\n 37.50972584293751\n ],\n [\n -89.58251953125,\n 37.09023980307208\n ],\n [\n -89.14306640625,\n 36.756490329505176\n ],\n [\n -87.73681640625,\n 36.756490329505176\n ],\n [\n -86.824951171875,\n 36.79169061907076\n ],\n [\n -85.36376953125,\n 37.42252593456307\n ],\n [\n -83.07861328125,\n 38.324420427006544\n ],\n [\n -82.72705078125,\n 38.95940879245423\n ],\n [\n -81.9580078125,\n 39.62261494094297\n ],\n [\n -81.27685546875,\n 40.06125658140474\n ],\n [\n -80.9033203125,\n 40.697299008636755\n ],\n [\n -80.83740234375,\n 41.29431726315258\n ],\n [\n -81.03515625,\n 41.52502957323801\n ],\n [\n -82.08984375,\n 41.27780646738183\n ],\n [\n -83.12255859375,\n 41.21172151054787\n ],\n [\n -83.671875,\n 41.44272637767212\n ],\n [\n -83.935546875,\n 41.934976500546604\n ],\n [\n -83.56201171875,\n 42.68243539838623\n ],\n [\n -83.3203125,\n 43.11702412135048\n ],\n [\n -83.7158203125,\n 43.26120612479979\n ],\n [\n -84.462890625,\n 43.052833917627936\n ],\n [\n -85.14404296875,\n 42.69858589169842\n ],\n [\n -85.8251953125,\n 42.22851735620852\n ],\n [\n -86.3525390625,\n 41.86956082699455\n ],\n [\n -86.9677734375,\n 41.672911819602085\n ],\n [\n -87.36328125,\n 41.672911819602085\n ],\n [\n -87.6708984375,\n 42.08191667830631\n ],\n [\n -87.802734375,\n 42.35854391749705\n ],\n [\n -87.7587890625,\n 42.779275360241904\n ],\n [\n -87.78076171875,\n 43.100982876188546\n ],\n [\n -87.82470703125,\n 43.40504748787035\n ],\n [\n -87.69287109375,\n 43.739352079154706\n ],\n [\n -87.56103515625,\n 43.99281450048989\n ],\n [\n -87.42919921875,\n 44.22945656830167\n ],\n [\n -87.4072265625,\n 44.5435052132082\n ],\n [\n -87.2314453125,\n 44.69989765840318\n ],\n [\n -87.47314453125,\n 44.84029065139799\n ],\n [\n -87.890625,\n 44.715513732021336\n ],\n [\n -88.13232421875,\n 44.62175409623324\n ],\n [\n -88.65966796875,\n 44.55916341529182\n ],\n [\n -89.27490234375,\n 44.449467536006935\n ],\n [\n -89.4287109375,\n 44.35527821160296\n ],\n [\n -89.69238281249999,\n 44.05601169578525\n ],\n [\n -89.736328125,\n 43.54854811091286\n ],\n [\n -90.10986328125,\n 43.02071359427862\n ],\n [\n -90.3076171875,\n 42.4234565179383\n ],\n [\n -90.703125,\n 42.47209690919285\n ],\n [\n -91.2744140625,\n 42.65012181368022\n ],\n [\n -91.58203125,\n 43.08493742707592\n ],\n [\n -91.91162109375,\n 43.6599240747891\n ],\n [\n -92.57080078125,\n 44.19795903948531\n ],\n [\n -92.3291015625,\n 44.824708282300236\n ],\n [\n -91.69189453125,\n 45.22848059584359\n ],\n [\n -91.8017578125,\n 45.506346901083425\n ],\n [\n -92.94433593749999,\n 45.583289756006316\n ],\n [\n -94.94384765625,\n 45.583289756006316\n ],\n [\n -96.13037109375,\n 45.398449976304086\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, National Water Quality Program
U.S. Geological Survey
413 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
The In-Situ Aqua TROLL 400 (Aqua TROLL 400) was tested at the U.S. Geological Survey (USGS) Hydrologic Instrumentation Facility (HIF) against known standards over the Aqua TROLL 400’s operating temperature to verify the manufacturer’s stated accuracy specifications and the USGS recommendations for pH, dissolved oxygen (DO), and specific conductance (SC). The Aqua TROLL 400 manufacturer’s specifications are within the USGS recommendations for all parameters tested, except for DO, which is outside the USGS recommendation at DO concentrations of 8.0 milligrams per liter (mg/L) and higher. The Aqua TROLL 400 was compliant with Serial Digital Interface at 1200 baud (SDI-12) version 1.3. During laboratory testing of pH, the Aqua TROLL 400 sonde met the U.S. Geological Survey “National Field Manual for the Collection of Water-Quality Data” (NFM) recommendations for pH at all values tested, except at 4 degrees Celsius (°C) at pH 9.395 and pH 3.998. The Aqua TROLL 400 met the manufacturer specifications for pH at all values tested, except for pH buffers 3.998, 9.395, and 10.245 at 4 °C; pH 2.990 and 3.998 at 15 °C; and pH 3.040 at 40 °C. The Aqua TROLL 400 met the NFM recommendations at 93.7 percent of the SC values tested and met the manufacturer’s accuracy specifications at 56.3 percent of the SC values tested. During the laboratory testing for DO, the Aqua TROLL 400 met the manufacturer specifications, except at 5.55 mg/L, and met the NFM recommendations at all concentrations tested. An Aqua TROLL 400 was field tested at USGS Station 02492620, National Space Technology Laboratories (NSTL) Station, Mississippi, on the Pearl River for 6 weeks and showed good agreement with the well-maintained site sonde data for pH, DO, temperature, and SC.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171086","usgsCitation":"Tillman, E.F., 2017, HIF evaluation of In-Situ Aqua TROLL 400: U.S. Geological Survey Open-File Report, 2017–1086, 35 p., https://doi.org/10.3133/ofr20171086.","productDescription":"vi, 35 p.","numberOfPages":"41","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-076079","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":346630,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1086/coverthb.jpg"},{"id":346631,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1086/ofr20171086.pdf","text":"Report","size":"856 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1086"}],"contact":"Chief, Hydrologic Instrumentation Facility
U.S. Geological Survey
Building 2101
Stennis Space Center, MS 39529
The UJNR Panel on Earthquake Research promotes advanced research toward a more fundamental understanding of the earthquake process and hazard estimation. The Eleventh Joint meeting was extremely beneficial in furthering cooperation and deepening understanding of problems common to both Japan and the United States.
The meeting included productive exchanges of information on approaches to systematic observation and modeling of earthquake processes. Regarding the earthquake and tsunami of March 2011 off the Pacific coast of Tohoku and the 2016 Kumamoto earthquake sequence, the Panel recognizes that further efforts are necessary to achieve our common goal of reducing earthquake risk through close collaboration and focused discussions at the 12th UJNR meeting.
","conferenceTitle":"11th United States-Japan Natural Resources Panel for Earthquake Research","conferenceDate":"November 16-18, 2016","conferenceLocation":"Napa Valley, CA","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171133","usgsCitation":"Detweiler, S., and Pollitz, F., eds., 2017, Proceedings of the 11th United States-Japan natural resources panel for earthquake research, Napa Valley, California, November 16–18, 2016: U.S. Geological Survey Open-File Report 2017–1133, 147 p., https://doi.org/10.3133/ofr20171133.","productDescription":"vii, 147 p.","numberOfPages":"154","onlineOnly":"Y","ipdsId":"IP-084487","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":346852,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1133/ofr20171133.pdf","text":"Report","size":"9.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1133"},{"id":346851,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1133/coverthb.jpg"}],"contact":"USGS Earthquake Science Center
U.S. Geological Survey
345 Middlefield Road
Mail Stop 977
Menlo Park, CA 94025
To better assess the reservoir conditions influencing the induced seismicity hazard near a carbon dioxide sequestration demonstration site in Decatur, Ill., core samples from three deep drill holes were tested to determine a suite of physical properties including bulk density, porosity, permeability, Young’s modulus, Poisson’s ratio, and failure strength. Representative samples of the shale cap rock, the sandstone reservoir, and the Precambrian basement were selected for comparison. Physical properties were strongly dependent on lithology. Bulk density was inversely related to porosity, with the cap rock and basement samples being both least porous (<3 percent) and densest (~2.6 grams per cubic centimeter [g/cc]). Permeability was highest in the reservoir sandstones (10-15 to 10-18 meters squared [m2]) relative to the cap rock and basement rocks (<10-21 m2). Young’s modulus was distinctly higher in the basement rocks (45 to 80 gigapascal [GPa]) compared to the cap rock and sandstones (19 to 57 GPa). Poisson’s ratio for the sandstones varied widely (0.14 to 0.27), but the highest values were similar to the cap rock and basement rocks (0.24 to 0.28). These physical properties reflect the layered structure of the reservoir and adjacent rocks at the Decatur site. However, within the sandstone there is a great deal of lithologic variety, accounting for the large range in physical parameters for this geologic unit.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171094","usgsCitation":"Morrow, C.A., Kaven, J.O., Moore, D.E., and Lockner, D.A., 2017, Physical properties of sidewall cores from Decatur, Illinois: U.S. Geological Survey Open-File Report 2017–1094, 21 p., https://doi.org/10.3133/ofr20171094.","productDescription":"v, 21 p.","numberOfPages":"27","onlineOnly":"Y","ipdsId":"IP-085446","costCenters":[{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":346914,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1094/ofr2017_1094.pdf","text":"Report","size":"1.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1094"},{"id":346913,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1094/coverthb.jpg"}],"country":"United States","state":"Illinois","city":"Decatur","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.91,\n 39.87\n ],\n [\n -88.870,\n 39.87\n ],\n [\n -88.870,\n 39.9\n ],\n [\n -88.91,\n 39.9\n ],\n [\n -88.91,\n 39.87\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"USGS Earthquake Science Center
U.S. Geological Survey
345 Middlefield Road
Mail Stop 977
Menlo Park, CA 94025
The U.S. Geological Survey, working with the Montana Department of Environmental Quality and the British Columbia Ministry of the Environment and Climate Change Strategy, has developed a conceptual modeling framework that can be used to provide structured and scientifically based input to the Lake Koocanusa Monitoring and Research Working Group as they consider potential site-specific selenium criteria for Lake Koocanusa, a transboundary reservoir located in Montana and British Columbia. This report describes that modeling framework, provides an example of how it can be applied, and outlines possible next steps for implementing the framework.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171130","collaboration":"Prepared in cooperation with the Montana Department of Environmental Quality","usgsCitation":"Jenni, K.E., Naftz, D.L., and Presser, T.S., 2017, Conceptual modeling framework to support development of site-specific selenium criteria for Lake Koocanusa, Montana, U.S.A., and British Columbia, Canada: U.S. Geological Survey Open-File Report 2017–1130, 14 p., https://doi.org/10.3133/ofr20171130.","productDescription":"Report: iv, 14 p.; Data Release","numberOfPages":"22","onlineOnly":"N","ipdsId":"IP-091389","costCenters":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"links":[{"id":346538,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1130/coverthb.jpg"},{"id":346541,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.5066/F7ZP44C9","text":"USGS Data Release – ","description":"USGS Data Release","linkHelpText":"USGS Measurements of Dissolved and Suspended Particulate Material Selenium in Lake Koocanusa in the Vicinity of Libby Dam (MT), 2015–2016"},{"id":346539,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1130/ofr20171130.pdf","text":"Report","size":"11.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1130"}],"country":"Canada, United States","state":"British Columbia, Montana","otherGeospatial":" Lake Koocanusa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.98266601562499,\n 48.356249029540734\n ],\n [\n -114.8565673828125,\n 48.356249029540734\n ],\n [\n -114.8565673828125,\n 50.42601852427907\n ],\n [\n -115.98266601562499,\n 50.42601852427907\n ],\n [\n -115.98266601562499,\n 48.356249029540734\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Science and Decisions Center
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
The U.S. Geological Survey (USGS), in cooperation with the DuPage County Stormwater Management Department, maintains a database of hourly meteorological and hydrologic data for use in a near real-time streamflow simulation system. This system is used in the management and operation of reservoirs and other flood-control structures in the West Branch DuPage River watershed in DuPage County, Illinois. The majority of the precipitation data are collected from a tipping-bucket rain-gage network located in and near DuPage County. The other meteorological data (air temperature, dewpoint temperature, wind speed, and solar radiation) are collected at Argonne National Laboratory in Argonne, Ill. Potential evapotranspiration is computed from the meteorological data using the computer program LXPET (Lamoreux Potential Evapotranspiration). The hydrologic data (water-surface elevation [stage] and discharge) are collected at U.S.Geological Survey streamflow-gaging stations in and around DuPage County. These data are stored in a Watershed Data Management (WDM) database.
This report describes a version of the WDM database that is quality-assured and quality-controlled annually to ensure datasets are complete and accurate. This database is named WBDR13.WDM. It contains data from January 1, 2007, through September 30, 2013. Each precipitation dataset may have time periods of inaccurate data. This report describes the methods used to estimate the data for the periods of missing, erroneous, or snowfall-affected data and thereby improve the accuracy of these data. The other meteorological datasets are described in detail in Over and others (2010), and the hydrologic datasets in the database are fully described in the online USGS annual water data reports for Illinois (U.S. Geological Survey, 2016) and, therefore, are described in less detail than the precipitation datasets in this report.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171099","collaboration":"Prepared in cooperation with DuPage County Stormwater Management Department","usgsCitation":"Bera, Maitreyee, 2017, Watershed Data Management (WDM) database for West Branch DuPage River streamflow simulation, DuPage County, Illinois, January 1, 2007, through September 30, 2013: U.S. Geological Survey Open-File Report 2017–1099, 39 p., https://doi.org/10.3133/ofr20171099.","productDescription":"Report: v, 39 p.; Data Release","numberOfPages":"50","onlineOnly":"Y","ipdsId":"IP-078980","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":346557,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1099/ofr20171099.pdf","text":"Report","size":"1.16 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1099"},{"id":346556,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1099/coverthb.jpg"},{"id":346558,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F71Z42M0","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"Watershed Data Management (WDM) Database (WBDR13.WDM) for West Branch DuPage River Streamflow Simulation, DuPage County, Illinois, January 1, 2007, through September 30, 2013"}],"country":"United States","state":"Illinois","county":"DuPage County","otherGeospatial":"West Branch DuPage River Watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.28338623046875,\n 41.70214000452559\n ],\n [\n -87.99087524414062,\n 41.70214000452559\n ],\n [\n -87.99087524414062,\n 41.99726342796974\n ],\n [\n -88.28338623046875,\n 41.99726342796974\n ],\n [\n -88.28338623046875,\n 41.70214000452559\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Illinois Water Science Center
U.S. Geological Survey
405 North Goodwin Avenue
Urbana, IL 61801-2347
The consequence of a 1996 wildfire disturbance and a subsequent high-intensity summer convective rain storm (about 110 millimeters per hour) was the deposition of a sediment superslug in the Spring Creek basin (26.8 square kilometers) of the Front Range Mountains in Colorado. Spring Creek is a tributary to the South Platte River upstream from Strontia Springs Reservoir, which supplies domestic water for the cities of Denver and Aurora. Changes in a superslug were monitored over the course of 18 years (1996–2014) by repeat surveys at 18 channel cross sections spaced at nearly equal intervals along a 1,500-meter study reach and by a time series of photographs of each cross section. Surveys were not repeated at regular time intervals but after major changes caused by different geomorphic processes. The focus of this long-term study was to understand the evolution and internal alluvial architecture of chronostratigraphic units (defined as the volume of sediment deposited between two successive surveys), and the preservation or storage of these units in the superslug. The data are presented as a series of 18 narratives (one for each cross section) that summarize the changes, illustrate these changes with photographs, and provide a preservation plot showing the amount of each chronostratigraphic unit still remaining in June 2014.
The most significant hydrologic change after the wildfire was an exponential decrease in peak discharge of flash floods caused by summer convective rain storms. In response to these hydrologic changes, all 18 locations went through an aggradation phase, an incision phase, and finally a stabilization phase. However, the architecture of the chronostratigraphic units differs from cross section to cross section, and units are characterized by either a laminar, fragmented, or hybrid alluvial architecture. In response to the decrease in peak-flood discharge and the increase in hillslope and riparian vegetation, Spring Creek abandoned many of the nearly horizontal erosional and depositional surfaces and left a landscape consisting of a series of cut-and-fill terraces as a legacy of this wildfire disturbance.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171090","usgsCitation":"Moody, J.A., and Martin, D.A., 2017, Description of chronostratigraphic units preserved as channel deposits and geomorphic processes following a basin-scale disturbance by a wildfire in Colorado: U.S. Geological Survey Open-File Report 2017–1090, 73 p., https://doi.org/10.3133/ofr20171090.","productDescription":"vi, 73 p.","numberOfPages":"79","onlineOnly":"Y","ipdsId":"IP-081971","costCenters":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"links":[{"id":346458,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1090/coverthb.jpg"},{"id":346459,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1090/ofr20171090.pdf","text":"Report","size":"43.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1090"}],"country":"United States","state":"Colorado","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.0455322265625,\n 38.89958342598271\n ],\n [\n -104.600830078125,\n 38.89958342598271\n ],\n [\n -104.600830078125,\n 39.50827899034114\n ],\n [\n -106.0455322265625,\n 39.50827899034114\n ],\n [\n -106.0455322265625,\n 38.89958342598271\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Branch Chief, Hydrodynamics Branch
Earth System Processes Division
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401
During spring 2015, Nebraska Game and Parks Commission (NGPC) biologists noted that pallid sturgeon (Scaphirhynchus albus) were in poor condition during sampling associated with the Pallid Sturgeon Population Assessment Project and NGPC’s annual pallid sturgeon broodstock collection effort. These observations prompted concerns that reduced fish condition could compromise reproductive health and population growth of pallid sturgeon. There was a further concern that compromised condition could possibly be linked to U.S. Army Corps of Engineers management actions and increase jeopardy to the species. An evaluation request was made to the Missouri River Recovery Program and the Effects Analysis Team was chartered to evaluate the issue. Data on all Missouri River pallid sturgeon captures were requested and received from the National Pallid Sturgeon Database. All data were examined for completeness and accuracy; 12,053 records of captures between 200 millimeters fork length (mm FL) and 1,200 mm FL were accepted. We analyzed condition using (1) the condition formula (Kn) from Shuman and others (2011); (2) a second Kn formulation derived from the 12,053 records (hereafter referred to as “Alternative Kn”); and (3) an analysis of covariance (ANCOVA) approach that did not rely on a Kn formulation. The Kn data were analyzed using group (average annual Kn) and individual (percentage in low, normal, and robust conditions) approaches. Using the Shuman Kn formulation, annual mean Kn was fairly static from 2005 to 2011 (although always higher in the upper basin), declined from 2012 to 2015, then remained either static (lower basin) or increasing (upper basin) in 2016. Under the Alternative Kn formulation, the upper basin showed no decline in Kn, whereas the lower basin displayed the same trend as the Shuman Kn formulation. Using both formulations, the individual approach revealed a more complex situation; at the same times and locations that there are fish in poor condition, there are nearby fish in normal or robust condition. The ANCOVA approach revealed that fish condition at size changed between 400 and 600 mm and that some of the apparent trend in low condition was caused by differences in sample size across the size range of the population (that is, greater catch of intermediate-sized fish compared to large fish). We examined basin, year, origin (hatchery compared to wild), segment, and size class for effects on condition and concluded that, since 2012, there has been an increase in the percentage of pallid sturgeon in low condition. There are basin, year, and segment effects; origin and size class do not seem to have an effect. The lower basin, in particular segment 9 (Platte River to Kansas River), had a high percentage of low-condition fish. Within the segment, there were bend-level effects, but the bend effect was not spatially contiguous.
We concluded that existing data confirm concerns about declining fish condition, especially in the segments between Sioux City, Iowa, and Kansas City, Missouri. Although the evidence is strong that fish condition has been in decline from 2011 to 2015, additional analysis of individual fish histories may provide more confidence in this conclusion; such analysis was beyond the scope of this effort but is part of our recommendations. The most recent data in 2016 indicate that decline of condition may have leveled off; however, the length of record is insufficient to determine whether recent declines are within the background range of variation. We recommend that monitoring of fish condition should be increased and enhanced with additional health metrics. We also recommend that, should condition continue to decline, processes are deployed to bring low-condition adult fish into the hatchery to improve nutrition and condition. We could not determine the cause of declining fish condition with available data, but we compiled information on several dominant hypotheses in two main categories: inter- or intraspecific competition for resources and habitat conditions. Data are insufficient to indicate a specific causation or solution, and it is possible that multiple causes apply. We make recommendations for additional research that can be pursued to address uncertainties in trends in fish health as well as potential causes.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171121","collaboration":"Prepared in cooperation with the Missouri River Recovery Program","usgsCitation":"Randall, M.T., Colvin, M.E., Steffensen, K.D., Welker, T.L., Pierce, L.L., and Jacobson, R.B., 2017, Assessment of adult pallid sturgeon fish condition, Lower Missouri River—Application of new information to the Missouri River Recovery Program: U.S. Geological Survey Open-File Report 2017–1121, 103 p., https://doi.org/10.3133/ofr20171121. ","productDescription":"vi, 103 p.","numberOfPages":"111","onlineOnly":"N","ipdsId":"IP-082584","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":346492,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1121/coverthb.jpg"},{"id":346493,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1121/ofr20171121.pdf","text":"Report","size":"7.33 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1121"}],"country":"United States","otherGeospatial":"Missouri River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.34765625,\n 38.496593518947584\n ],\n [\n -90.10986328125,\n 38.496593518947584\n ],\n [\n -90.10986328125,\n 48.23930899024907\n ],\n [\n -106.34765625,\n 48.23930899024907\n ],\n [\n -106.34765625,\n 38.496593518947584\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Columbia Environmental Research Center
U.S. Geological Survey
4200 New Haven Road
Columbia, Missouri 65201
Streamflow statistics are needed by decision makers for many planning, management, and design activities. The U.S. Geological Survey (USGS) StreamStats Web application provides convenient access to streamflow statistics for many streamgages by accessing the underlying StreamStatsDB database. In 2016, non-interpretive streamflow statistics were compiled for streamgages located throughout the Nation and stored in StreamStatsDB for use with StreamStats and other applications. Two previously published USGS computer programs that were designed to help calculate streamflow statistics were updated to better support StreamStats as part of this effort. These programs are named “GNWISQ” (Get National Water Information System Streamflow (Q) files), updated to version 1.1.1, and “QSTATS” (Streamflow (Q) Statistics), updated to version 1.1.2.
Statistics for 20,438 streamgages that had 1 or more complete years of record during water years 1901 through 2015 were calculated from daily mean streamflow data; 19,415 of these streamgages were within the conterminous United States. About 89 percent of the 20,438 streamgages had 3 or more years of record, and about 65 percent had 10 or more years of record. Drainage areas of the 20,438 streamgages ranged from 0.01 to 1,144,500 square miles. The magnitude of annual average streamflow yields (streamflow per square mile) for these streamgages varied by almost six orders of magnitude, from 0.000029 to 34 cubic feet per second per square mile. About 64 percent of these streamgages did not have any zero-flow days during their available period of record. The 18,122 streamgages with 3 or more years of record were included in the StreamStatsDB compilation so they would be available via the StreamStats interface for user-selected streamgages. All the statistics are available in a USGS ScienceBase data release.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171108","collaboration":"Prepared in cooperation with the Federal Highway Administration Office of Project Development and Environmental Review","usgsCitation":"Granato G.E., Ries, K.G., III, and Steeves, P.A., 2017, Compilation of streamflow statistics calculated from daily mean streamflow data collected during water years 1901–2015 for selected U.S. Geological Survey streamgages: U.S. Geological Survey Open-File Report 2017–1108, 17 p., https://doi.org/10.3133/ofr20171108.","productDescription":"Report: vi, 17 p.; 4 Figures; Data Release","onlineOnly":"Y","ipdsId":"IP-077435","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":346453,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F71V5CFT","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"Streamflow statistics calculated from daily mean streamflow data collected during water years 1901–2015 for selected U.S. Geological Survey streamgages"},{"id":346446,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1108/coverthb.jpg"},{"id":346447,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1108/ofr20171108.pdf","text":"Report","size":"5.88 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1108"},{"id":346448,"rank":3,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/of/2017/1108/ofr20171108_fig3a_interactive.pdf","text":"Figure 3A","size":"4.56 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1108 - Figure 3A","linkHelpText":"—Streamgages by record length [layered pdf; view in Adobe Reader or Microsoft Internet Explorer]"},{"id":346449,"rank":4,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/of/2017/1108/ofr20171108_fig3b_interactive.pdf","text":"Figure 3B","size":"4.44 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1108 - Figure 3B","linkHelpText":"—Streamgages by drainage area [layered pdf; view in Adobe Reader or Microsoft Internet Explorer]"},{"id":346450,"rank":5,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/of/2017/1108/ofr20171108_fig3c_interactive.pdf","text":"Figure 3C","size":"4.14 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1108 - Figure 3C","linkHelpText":"—Streamgages by percentage of zero-flow days [layered pdf; view in Adobe Reader or Microsoft Internet Explorer]"},{"id":346451,"rank":6,"type":{"id":29,"text":"Figure"},"url":"https://pubs.usgs.gov/of/2017/1108/ofr20171108_fig3d_interactive.pdf","text":"Figure 3D","size":"4.18 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1108 - Figure 3D","linkHelpText":"—Streamgages by geometric mean of nonzero daily mean streamflow values [layered pdf; view in Adobe Reader or Microsoft Internet Explorer]"}],"country":"United States","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"MultiPolygon\",\"coordinates\":[[[[-75.867044,36.550754],[-75.536428,35.780118],[-75.723662,36.003139],[-75.85147,36.415785],[-76.019261,36.503506],[-75.793974,36.07171],[-75.922344,36.244122],[-75.904999,36.164188],[-76.184702,36.298166],[-76.064224,36.143775],[-76.447812,36.192514],[-76.298733,36.1012],[-76.514335,36.00564],[-76.676484,36.043612],[-76.693253,36.278357],[-76.7521,36.147328],[-76.667547,35.933509],[-76.024162,35.970891],[-76.04015,35.65131],[-75.947293,35.959835],[-75.80935,35.959308],[-75.71294,35.69849],[-75.775328,35.579335],[-75.895045,35.573152],[-76.149655,35.326411],[-76.485762,35.371375],[-76.586349,35.508957],[-76.471207,35.55742],[-76.634468,35.510332],[-76.580187,35.387113],[-77.023912,35.514802],[-76.467776,35.276951],[-76.60042,35.067867],[-76.801426,34.964369],[-76.982904,35.060607],[-76.762931,34.920374],[-76.463468,35.076411],[-76.395625,34.975179],[-76.288354,35.005726],[-76.524712,34.681964],[-76.604796,34.787482],[-76.673619,34.71491],[-76.523303,34.652271],[-76.038648,35.065045],[-76.535946,34.588577],[-76.726969,34.69669],[-77.169701,34.622023],[-77.740136,34.272546],[-77.970606,33.844517],[-78.276147,33.912364],[-78.772737,33.768511],[-79.084588,33.483669],[-79.18787,33.173712],[-79.359961,33.006672],[-79.55756,33.021269],[-79.576006,32.906235],[-79.999374,32.611851],[-80.472068,32.496964],[-80.455192,32.326458],[-80.858735,32.099581],[-80.862814,31.969346],[-81.203572,31.719448],[-81.133493,31.623348],[-81.260076,31.54828],[-81.177254,31.517074],[-81.288403,31.211065],[-81.493651,30.977528],[-81.403409,30.957914],[-81.447087,30.503679],[-81.163581,29.55529],[-80.525094,28.459454],[-80.606874,28.336484],[-80.566432,28.09563],[-80.031362,26.796339],[-80.127987,25.772245],[-80.154972,25.66549],[-80.197674,25.74437],[-80.296719,25.622195],[-80.31036,25.3731],[-80.418872,25.235532],[-81.079859,25.118797],[-81.352731,25.822015],[-81.527665,25.901531],[-81.68954,25.85271],[-81.868983,26.378648],[-82.105672,26.48393],[-82.181565,26.681712],[-82.093023,26.665614],[-82.063126,26.950214],[-82.175241,26.916867],[-82.147068,26.789803],[-82.259867,26.717398],[-82.745748,27.538834],[-82.65072,27.523115],[-82.393383,27.837519],[-82.478063,27.92768],[-82.47244,27.822559],[-82.553946,27.848462],[-82.553918,27.966998],[-82.678606,27.993715],[-82.720395,27.937199],[-82.566819,27.858002],[-82.733076,27.612972],[-82.846526,27.854301],[-82.654138,28.590837],[-82.804736,29.146624],[-83.053207,29.130839],[-83.686423,29.923735],[-84.000716,30.096209],[-84.256439,30.103791],[-84.358923,30.058224],[-84.349066,29.896812],[-85.344768,29.654793],[-85.413575,29.85294],[-85.353885,29.684765],[-85.302591,29.808094],[-85.405052,29.938487],[-86.2987,30.363049],[-86.750906,30.391881],[-88.028401,30.221132],[-87.755263,30.277292],[-88.008396,30.684956],[-88.136173,30.320729],[-88.841328,30.409598],[-89.291444,30.303296],[-89.335942,30.374016],[-89.461275,30.174745],[-89.857558,30.004439],[-89.660568,29.862909],[-89.481926,30.079128],[-89.372375,30.054729],[-89.433411,29.991205],[-89.368019,29.911491],[-89.218071,29.97275],[-89.322289,29.887333],[-89.236298,29.877081],[-89.383789,29.838928],[-89.271034,29.756355],[-89.651237,29.749479],[-89.485367,29.624357],[-89.688141,29.615055],[-89.700501,29.515967],[-89.508551,29.386168],[-89.189354,29.345061],[-89.000674,29.180091],[-89.41148,28.925011],[-89.354798,29.072543],[-89.482844,29.215053],[-89.850305,29.311768],[-89.849642,29.477996],[-90.01251,29.462775],[-90.009678,29.294785],[-90.096038,29.240673],[-89.949925,29.263154],[-90.174273,29.105301],[-90.348768,29.057817],[-90.234235,29.110268],[-90.271251,29.204639],[-90.332796,29.276956],[-90.472489,29.192688],[-90.510555,29.290925],[-90.803699,29.063709],[-90.637495,29.066608],[-90.839345,29.039167],[-90.961278,29.180817],[-91.278792,29.247776],[-91.33275,29.305816],[-91.221166,29.436421],[-91.531021,29.531543],[-91.553537,29.632766],[-91.648941,29.633635],[-91.632829,29.742576],[-91.88075,29.710839],[-91.889118,29.836023],[-92.149349,29.697052],[-91.712002,29.56474],[-91.782387,29.482882],[-92.046316,29.584362],[-92.61627,29.578729],[-93.267456,29.778113],[-94.056506,29.671163],[-94.778691,29.361483],[-94.495025,29.525031],[-94.779674,29.530533],[-94.735271,29.785433],[-94.893107,29.661336],[-94.965963,29.70033],[-95.018253,29.554885],[-94.909898,29.49691],[-94.893994,29.30817],[-95.16525,29.113566],[-94.72253,29.331446],[-95.38239,28.866348],[-96.378616,28.383909],[-95.978526,28.650594],[-96.228909,28.580873],[-96.222802,28.698431],[-96.487943,28.569677],[-96.648758,28.709627],[-96.403973,28.44245],[-96.672677,28.335579],[-96.775985,28.405809],[-96.800413,28.224128],[-96.934765,28.123873],[-97.037008,28.185528],[-97.214039,28.087494],[-97.022806,28.107588],[-97.186709,27.825453],[-97.379042,27.837867],[-97.253955,27.696696],[-97.401942,27.335574],[-97.532223,27.278577],[-97.501688,27.366618],[-97.639094,27.253131],[-97.42408,27.264073],[-97.563266,26.842188],[-97.295072,26.108342],[-97.216954,25.993838],[-97.152009,26.062108],[-97.145567,25.971132],[-97.422636,25.840378],[-97.649176,26.021499],[-98.197046,26.056153],[-98.807348,26.369421],[-99.085126,26.398782],[-99.268613,26.843213],[-99.446524,27.023008],[-99.512219,27.568094],[-99.841708,27.766464],[-99.931812,27.980967],[-100.293468,28.278475],[-100.333814,28.499252],[-100.797671,29.246943],[-101.254895,29.520342],[-101.415402,29.756561],[-102.315389,29.87992],[-102.386678,29.76688],[-102.670971,29.741954],[-102.866846,29.225015],[-103.115328,28.98527],[-103.28119,28.982138],[-104.507568,29.639624],[-104.924796,30.604832],[-106.207837,31.468188],[-106.451541,31.764808],[-108.208394,31.783599],[-108.208573,31.333395],[-111.074825,31.332239],[-114.813613,32.494277],[-114.719633,32.718763],[-117.124862,32.534156],[-117.469794,33.296417],[-118.132698,33.753217],[-118.411211,33.741985],[-118.519514,34.027509],[-119.130169,34.100102],[-119.559459,34.413395],[-120.471376,34.447846],[-120.637805,34.56622],[-120.644311,35.139616],[-120.856047,35.206487],[-120.884757,35.430196],[-121.284973,35.674109],[-121.503112,36.000299],[-121.888491,36.30281],[-121.978592,36.580488],[-121.814462,36.682858],[-121.862266,36.931552],[-122.105976,36.955951],[-122.405073,37.195791],[-122.514483,37.780829],[-122.398139,37.80563],[-122.378545,37.605592],[-122.111344,37.50758],[-122.430087,37.963115],[-122.273006,38.07438],[-122.489974,38.112014],[-122.438268,37.880974],[-122.505383,37.822128],[-122.882114,38.025273],[-123.024066,37.994878],[-122.977082,38.267902],[-123.725367,38.917438],[-123.851714,39.832041],[-124.363414,40.260974],[-124.408601,40.443201],[-124.137066,40.925732],[-124.063076,41.439579],[-124.147412,41.717955],[-124.255994,41.783014],[-124.214213,42.005939],[-124.410982,42.250547],[-124.401177,42.627192],[-124.552441,42.840568],[-124.233534,43.55713],[-124.067569,44.428582],[-123.927891,46.009564],[-124.024305,46.229256],[-123.854801,46.157342],[-123.547636,46.265595],[-124.080671,46.267239],[-124.068655,46.634879],[-124.026032,46.462978],[-123.943667,46.477197],[-123.960642,46.636364],[-123.84621,46.716795],[-124.092176,46.741624],[-124.138225,46.905534],[-123.86018,46.948556],[-124.122057,47.04165],[-124.180111,46.926357],[-124.425195,47.738434],[-124.672427,47.964414],[-124.733174,48.163393],[-124.65894,48.331057],[-124.731828,48.381157],[-123.981032,48.164761],[-123.332699,48.11297],[-123.133445,48.177276],[-122.877641,48.047025],[-122.833173,48.134406],[-122.760448,48.14324],[-122.766648,48.04429],[-122.68724,48.101662],[-122.718082,47.987739],[-122.610341,47.887343],[-122.811929,47.679861],[-122.820178,47.835904],[-123.15598,47.355745],[-122.549072,47.919072],[-122.470333,47.757109],[-122.554454,47.745704],[-122.479089,47.583654],[-122.547521,47.285344],[-122.611464,47.2181],[-122.697378,47.283969],[-122.632463,47.376394],[-122.725738,47.33047],[-122.641802,47.205013],[-122.711997,47.127681],[-122.832799,47.243412],[-122.803688,47.355071],[-122.863732,47.270221],[-122.858735,47.167955],[-122.67813,47.103866],[-122.547747,47.316403],[-122.4442,47.266723],[-122.324833,47.348521],[-122.421139,47.57602],[-122.339513,47.599113],[-122.429841,47.658919],[-122.224979,48.016626],[-122.395499,48.228551],[-122.479008,48.175703],[-122.358375,48.056133],[-122.512031,48.133931],[-122.530996,48.249821],[-122.371693,48.287839],[-122.712322,48.464143],[-122.471832,48.470724],[-122.534719,48.574246],[-122.425271,48.599522],[-122.535803,48.776128],[-122.673472,48.733082],[-122.821631,48.941369],[-122.75802,49.002357],[-95.153711,48.998903],[-95.15335,49.383079],[-94.957465,49.370186],[-94.816222,49.320987],[-94.645083,48.744143],[-93.840754,48.628548],[-93.794454,48.516021],[-92.954876,48.631493],[-92.634931,48.542873],[-92.712562,48.463013],[-92.456325,48.414204],[-92.369174,48.220268],[-92.26228,48.354933],[-92.055228,48.359213],[-91.567254,48.043719],[-90.88548,48.245784],[-90.751608,48.090968],[-89.489226,48.014528],[-90.86827,47.5569],[-92.094089,46.787839],[-91.961889,46.682539],[-90.855874,46.962232],[-90.750952,46.890293],[-90.951476,46.597033],[-90.73726,46.692267],[-90.436512,46.561748],[-88.972802,47.002096],[-88.418841,47.371058],[-87.929672,47.478743],[-87.710471,47.4062],[-87.957058,47.38726],[-88.227552,47.199938],[-88.443901,46.972251],[-88.462349,46.786711],[-88.142807,46.966302],[-88.175197,46.90458],[-87.681561,46.842392],[-87.352448,46.501324],[-87.008724,46.532723],[-86.850111,46.434114],[-86.698139,46.438624],[-86.678182,46.561039],[-86.586168,46.463324],[-86.161681,46.669475],[-84.989497,46.772403],[-85.015211,46.479712],[-84.551496,46.418522],[-84.128925,46.530119],[-84.097766,46.256512],[-84.251424,46.175888],[-83.873147,45.993426],[-83.765277,46.018363],[-83.815826,46.108529],[-83.581315,46.089613],[-83.510623,45.929324],[-84.376429,45.931962],[-84.656567,46.052654],[-84.746985,45.835597],[-85.01399,46.010774],[-85.499422,46.09692],[-85.697203,45.960158],[-86.278007,45.942057],[-86.616893,45.606796],[-86.718191,45.67732],[-86.541464,45.890234],[-86.78208,45.860195],[-86.964275,45.672761],[-87.031435,45.837238],[-87.600796,45.146842],[-87.630298,44.976865],[-87.837647,44.933091],[-88.005518,44.539216],[-87.756048,44.649117],[-87.609784,44.838514],[-87.384821,44.865532],[-87.238426,45.166492],[-86.970355,45.278455],[-87.467089,44.553557],[-87.512903,44.192808],[-87.735436,43.882219],[-87.702685,43.687596],[-87.911787,43.250406],[-87.766675,42.784896],[-87.828569,42.269922],[-87.42344,41.642835],[-87.066033,41.661845],[-86.616978,41.896625],[-86.297168,42.358207],[-86.208654,42.69209],[-86.254646,43.083409],[-86.540916,43.633158],[-86.43114,43.815569],[-86.514704,44.057672],[-86.26871,44.345324],[-86.254996,44.691935],[-85.551072,45.210742],[-85.652355,44.849092],[-85.593833,44.768651],[-85.475204,44.991053],[-85.576566,44.760208],[-85.3958,44.931018],[-85.371593,45.270834],[-84.91585,45.393115],[-85.115479,45.539406],[-84.942636,45.714292],[-85.014509,45.760329],[-84.726192,45.786905],[-84.215268,45.634767],[-84.095905,45.497298],[-83.488826,45.355872],[-83.265896,45.026844],[-83.454168,45.03188],[-83.274747,44.714893],[-83.332533,44.340464],[-83.53771,44.248171],[-83.58409,44.056748],[-83.877047,43.959351],[-83.909479,43.672622],[-83.666052,43.591292],[-83.26153,43.973525],[-82.967439,44.066138],[-82.746255,43.996037],[-82.643166,43.852468],[-82.412965,42.977041],[-82.518782,42.613888],[-82.686417,42.518597],[-82.630851,42.673341],[-82.813518,42.640833],[-82.894013,42.389437],[-83.096521,42.290138],[-83.133511,42.088143],[-83.455626,41.727445],[-82.934369,41.514353],[-82.834101,41.587587],[-82.499099,41.381541],[-82.011966,41.515639],[-81.738755,41.48855],[-81.288892,41.758945],[-80.329976,42.036168],[-79.148723,42.553672],[-78.851355,42.791758],[-79.074467,43.077855],[-79.070469,43.262454],[-78.370221,43.376505],[-77.760231,43.341161],[-77.551022,43.235763],[-76.958402,43.270005],[-76.235834,43.529256],[-76.28272,43.858601],[-76.125023,43.912773],[-76.360306,44.070907],[-76.312647,44.199044],[-74.992756,44.977449],[-71.502487,45.013367],[-71.443882,45.235462],[-71.296509,45.29919],[-71.13943,45.242958],[-71.01081,45.34725],[-70.857042,45.22916],[-70.795009,45.428145],[-70.634661,45.383608],[-70.688214,45.563981],[-70.259117,45.890755],[-70.292736,46.191599],[-70.057061,46.415036],[-69.997086,46.69523],[-69.22442,47.459686],[-69.043947,47.427634],[-69.050334,47.256621],[-68.902425,47.178839],[-68.329879,47.36023],[-67.955669,47.199542],[-67.789461,47.062544],[-67.750422,45.917898],[-67.817892,45.693705],[-67.429716,45.583773],[-67.489464,45.282653],[-67.345585,45.126392],[-67.157919,45.161004],[-66.950569,44.814539],[-67.293403,44.599265],[-67.308538,44.707454],[-67.405492,44.594236],[-67.551133,44.621938],[-67.568159,44.531117],[-67.839896,44.558771],[-67.855108,44.419434],[-68.049334,44.33073],[-68.117746,44.475038],[-68.261708,44.484062],[-68.173608,44.328397],[-68.317588,44.225101],[-68.430946,44.298624],[-68.3791,44.430049],[-68.565161,44.39907],[-68.525302,44.227554],[-68.827197,44.31216],[-68.783679,44.473879],[-68.927452,44.448039],[-69.100863,44.104529],[-69.031878,44.079036],[-69.214205,43.935583],[-69.398455,43.971804],[-69.838689,43.70514],[-69.884066,43.778035],[-70.041351,43.738053],[-70.009869,43.859315],[-70.190014,43.771866],[-70.196911,43.565146],[-70.361214,43.52919],[-70.810069,42.909549],[-70.778671,42.693622],[-70.594014,42.63503],[-70.871382,42.546404],[-71.01568,42.326019],[-70.722269,42.207959],[-70.63848,42.081579],[-70.710034,41.999544],[-70.552941,41.929641],[-70.471552,41.761563],[-70.024734,41.787364],[-70.095595,42.032832],[-70.245385,42.063733],[-70.058531,42.040363],[-69.935952,41.809422],[-69.998071,41.54365],[-70.007011,41.671579],[-70.351634,41.634687],[-70.948431,41.409193],[-70.658659,41.543385],[-70.623652,41.707398],[-70.718739,41.73574],[-71.19302,41.457931],[-71.240709,41.619225],[-71.24071,41.474872],[-71.337695,41.448902],[-71.19564,41.67509],[-71.350057,41.727835],[-71.449318,41.687401],[-71.483295,41.371722],[-72.916827,41.282033],[-73.643478,41.002171],[-73.781369,40.794907],[-73.485365,40.946397],[-72.585327,40.997587],[-72.278789,41.158722],[-72.317238,41.088659],[-72.10216,40.991509],[-71.856214,41.070598],[-73.23914,40.6251],[-73.934512,40.545175],[-74.024543,40.709436],[-74.186027,40.646076],[-74.261889,40.464706],[-73.978282,40.440208],[-74.096906,39.76303],[-74.864458,38.94041],[-74.971995,38.94037],[-74.887167,39.158825],[-75.136548,39.179425],[-75.536431,39.460559],[-75.509342,39.685313],[-75.587147,39.651012],[-75.402035,39.066885],[-75.089473,38.797198],[-75.048939,38.451263],[-75.195382,38.093582],[-75.514921,37.799149],[-75.906734,37.114193],[-76.018645,37.31782],[-75.663095,37.961195],[-75.892686,37.916848],[-75.812913,38.058932],[-75.843862,38.144599],[-75.958786,38.135572],[-75.848473,38.20934],[-75.970514,38.233668],[-75.973876,38.36585],[-76.032044,38.216684],[-76.258189,38.318373],[-76.33636,38.492235],[-76.147158,38.63684],[-76.238685,38.735434],[-76.347998,38.686234],[-76.271575,38.851771],[-76.19343,38.821787],[-76.203638,38.928382],[-76.376031,38.848777],[-76.311766,39.035257],[-76.164004,38.99953],[-76.145174,39.092824],[-76.231765,39.018518],[-76.274741,39.164961],[-76.170588,39.331954],[-76.002408,39.367501],[-75.970337,39.557637],[-76.096072,39.536912],[-76.060988,39.447775],[-76.281374,39.304531],[-76.341443,39.354217],[-76.425281,39.205708],[-76.535885,39.211008],[-76.394358,39.01216],[-76.557535,38.744687],[-76.321499,38.03805],[-76.920778,38.291529],[-77.016371,38.445572],[-77.250172,38.382781],[-77.263599,38.512344],[-77.12634,38.6177],[-77.246704,38.635217],[-77.279633,38.339444],[-77.043526,38.400548],[-76.962311,38.214075],[-76.613939,38.148587],[-76.236725,37.889174],[-76.339892,37.655966],[-76.28037,37.613715],[-76.36232,37.610368],[-76.784618,37.869569],[-76.542666,37.616857],[-76.300144,37.561734],[-76.360474,37.51924],[-76.265056,37.481365],[-76.275552,37.309964],[-76.415167,37.402133],[-76.349489,37.273963],[-76.50364,37.233856],[-76.292344,37.126615],[-76.304272,37.001378],[-76.428869,36.969947],[-76.649869,37.220914],[-76.802511,37.198308],[-76.685614,37.198851],[-76.662558,37.045748],[-76.469914,36.882898],[-76.297663,36.968147],[-75.996252,36.922047],[-75.867044,36.550754]],[[-77.038598,38.791513],[-76.910795,38.891712],[-77.040999,38.99511],[-77.1199,38.934311],[-77.038598,38.791513]]],[[[-88.124658,30.28364],[-88.075856,30.246139],[-88.313323,30.230024],[-88.124658,30.28364]]],[[[-120.248484,33.999329],[-120.043259,34.035806],[-119.97026,33.944359],[-120.121817,33.895712],[-120.248484,33.999329]]],[[[-119.789798,34.05726],[-119.52064,34.034262],[-119.758141,33.959212],[-119.923337,34.069361],[-119.789798,34.05726]]],[[[-118.524531,32.895488],[-118.605534,33.030999],[-118.353504,32.821962],[-118.524531,32.895488]]],[[[-118.500212,33.449592],[-118.305084,33.310323],[-118.465368,33.326056],[-118.60403,33.47654],[-118.500212,33.449592]]],[[[-81.582923,24.658732],[-81.425483,24.752989],[-81.298028,24.656774],[-81.81289,24.546468],[-81.582923,24.658732]]],[[[-84.777208,29.707398],[-84.696726,29.76993],[-85.097082,29.625215],[-84.777208,29.707398]]],[[[-85.156415,29.679628],[-85.077237,29.670862],[-85.222546,29.678039],[-85.156415,29.679628]]],[[[-82.255777,26.703437],[-82.166042,26.489679],[-82.013913,26.452058],[-82.177017,26.471558],[-82.255777,26.703437]]],[[[-80.250581,25.34193],[-80.659395,24.897433],[-80.174544,25.518406],[-80.250581,25.34193]]],[[[-88.865067,29.752714],[-88.944435,29.658806],[-88.8312,29.878839],[-88.881454,30.053202],[-88.865067,29.752714]]],[[[-70.59628,41.471905],[-70.451084,41.348161],[-70.838777,41.347209],[-70.59628,41.471905]]],[[[-70.092142,41.297741],[-70.049053,41.391702],[-69.960181,41.264546],[-70.275526,41.310464],[-70.092142,41.297741]]],[[[-68.453236,44.189998],[-68.384903,44.154955],[-68.502096,44.152388],[-68.453236,44.189998]]],[[[-68.680773,44.279242],[-68.605906,44.230772],[-68.675056,44.137131],[-68.680773,44.279242]]],[[[-68.785601,44.053503],[-68.944597,44.11284],[-68.825067,44.186338],[-68.785601,44.053503]]],[[[-68.942826,44.281073],[-68.868444,44.38144],[-68.95189,44.218719],[-68.942826,44.281073]]],[[[-88.684434,48.115785],[-88.418244,48.18037],[-88.968903,47.901675],[-88.899698,47.902445],[-89.255202,47.876102],[-88.684434,48.115785]]],[[[-84.612845,45.834528],[-84.35602,45.771895],[-84.484128,45.73071],[-84.612845,45.834528]]],[[[-85.566441,45.760222],[-85.487026,45.621211],[-85.561634,45.572213],[-85.630016,45.598166],[-85.566441,45.760222]]],[[[-88.710719,30.250799],[-88.562067,30.227476],[-88.771991,30.245523],[-88.710719,30.250799]]],[[[-75.753765,35.199612],[-75.529393,35.288272],[-75.533512,35.773577],[-75.458659,35.596597],[-75.52592,35.233839],[-76.013145,35.061855],[-75.753765,35.199612]]],[[[-74.144428,40.53516],[-74.254588,40.502303],[-74.1894,40.642121],[-74.075884,40.648101],[-74.144428,40.53516]]],[[[-97.240849,26.411504],[-97.387459,26.820789],[-97.361796,27.359988],[-96.879424,28.131402],[-96.403206,28.371475],[-96.966996,27.950531],[-97.30447,27.407734],[-97.370731,26.909706],[-97.154271,26.066841],[-97.240849,26.411504]]],[[[-122.519535,48.288314],[-122.668385,48.223967],[-122.54512,48.05255],[-122.376259,48.034457],[-122.380497,47.904023],[-122.770045,48.224395],[-122.664659,48.401508],[-122.519535,48.288314]]],[[[-122.474684,47.511068],[-122.373628,47.388718],[-122.51885,47.33332],[-122.474684,47.511068]]],[[[-122.800217,48.60169],[-122.803521,48.428748],[-122.874135,48.418196],[-123.203026,48.596178],[-122.987296,48.561895],[-123.048652,48.621002],[-122.894599,48.71503],[-122.743049,48.661991],[-122.800217,48.60169]]],[[[-90.572383,46.958835],[-90.508157,46.956836],[-90.654796,46.919249],[-90.572383,46.958835]]],[[[-90.757147,47.03372],[-90.544875,47.017383],[-90.671581,46.948973],[-90.757147,47.03372]]],[[[-86.880572,45.331467],[-86.943041,45.41525],[-86.810055,45.422619],[-86.880572,45.331467]]]]},\"properties\":{\"name\":\"Alabama\",\"nation\":\"USA \"}}]}\n","publicComments":"Groundwater and Streamflow Information Program","contact":"Office of Surface Water
U.S. Geological Survey
415 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
The Aggregate Water-Use Data System (AWUDS) is the database management system used to enter, store, and analyze state aggregate water-use data. It is part of the U.S. Geological Survey National Water Information System. AWUDS has a graphical user interface that facilitates data entry, revision, review, and approval. This document provides information on the basic functions of AWUDS and the steps for carrying out common tasks that are a part of compiling an aggregated dataset. Also included are explanations of terminology and descriptions of user-interface structure, procedures for using the AWUDS operations, and dataset-naming conventions. Information on water-use category definitions, data-collection methods, and data sources are found in the report “Guidelines for preparation of State water-use estimates,” available at https://pubs.er.usgs.gov/publication/ofr20171029.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171114","usgsCitation":"Nawyn, J.P., Sargent, B.P., Hoopes, B.C., Augenstein, T.W., Rowland, K.M., and Barber, N.L., 2017, User’s Manual for the National Water Information System of the U.S. Geological Survey: Aggregate Water-Use Data System, Version 3.2: U.S. Geological Survey Open-File Report 2017–1114, 29 p., https://doi.org/10.3133/ofr20171114.","productDescription":"iv, 29 p.","numberOfPages":"38","onlineOnly":"Y","ipdsId":"IP-088071","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":346324,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1114/coverthb.jpg"},{"id":346325,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1114/ofr20171114.pdf","text":"Report","size":".99 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1114"}],"contact":"Director, New Jersey Water Science Center
U.S. Geological Survey
3450 Princeton Pike, Suite 110
Lawrenceville, NJ 08648
or visit our website
https://nj.usgs.gov
Large rivers carry terrestrial sediment, contaminants, and other materials to the coastal zone where they can affect marine biogeochemical cycles and ecosystems. This U.S. Geological Survey study combined river and marine sediment geochemistry and organic contaminant analyses to identify riverborne sediment and associated contaminants at shoreline sites in Commencement Bay, Puget Sound, Washington, that could be used by adult forage fish and other marine organisms. Geochemical signatures distinguished the fine fraction (<0.063 millimeter, mm) of Puyallup River sediment—which originates from Mount Rainier, a Cascade volcano—from glacial fine sediment in lowland bluffs that supply sediment to beaches. In combination with activities of beryllium-7 (7Be), a short-lived radionuclide, geochemical signatures showed that winter 2013–14 sediment runoff from the Puyallup River was transported to and deposited along the north shore of Commencement Bay, then mixed downward into the sediment column. The three Commencement Bay sites at which organic contaminants were measured in surface sediment did not have measurable 7Be activities in that layer, so their contaminant assemblages were attributed to sources from previous years. Concentrations of organic contaminants (the most common of which were polycyclic aromatic hydrocarbons, polychlorinated biphenyls, and fecal sterols) were higher in the <0.063-mm fraction compared to the <2-mm fraction, in winter compared to summer, in river suspended sediment compared to river bar and bank sediment, and in marine sediment compared to river sediment. The geochemical property barium/aluminum (Ba/Al) showed that the median percentage of Puyallup River derived fine surface sediment along the shoreline of Commencement Bay was 77 percent. This finding, in combination with higher concentrations of organic contaminants in marine rather than river sediment, indicates that riverborne sediment-bound contaminants are retained in shallow marine habitats of Commencement Bay. The retention of earlier inputs complicates efforts to identify recent inputs and sources. Understanding modern sources and fates of riverborne sediment and contaminants and their potential ecological impacts will therefore require a suite of targeted geochemical studies in such marine depositional environments.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171124","usgsCitation":"Takesue, R.K., Conn, K.E., and Dinicola, R.S., 2017, Tracking riverborne sediment and contaminants in Commencement Bay, Washington, using geochemical signatures: U.S. Geological Survey Open-File Report 2017–1124, 31 p., https://doi.org/10.3133/ofr20171124.","productDescription":"vii, 31 p.","numberOfPages":"41","onlineOnly":"Y","ipdsId":"IP-086001","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":346256,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1124/coverthb.jpg"},{"id":346257,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1124/ofr20171124.pdf","text":"Report","size":"5.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1124"}],"country":"United States","state":"Washington","otherGeospatial":"Puyallup River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.46185302734375,\n 46.86582490125156\n ],\n [\n -121.60491943359375,\n 46.86582490125156\n ],\n [\n -121.60491943359375,\n 47.23262467463881\n ],\n [\n -122.46185302734375,\n 47.23262467463881\n ],\n [\n -122.46185302734375,\n 46.86582490125156\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Pacific Coastal and Marine Science Center
U.S. Geological Survey
Pacific Science Center
2885 Mission St.
Santa Cruz, CA 95060
Natural resource management is conducted in the context of multiple anthropogenic stressors and is further challenged owing to changing climate. Experiments to determine the effects of climate change on complex ecological systems are nearly impossible. However, using a simulation model to synthesize current understanding of key ecological processes through the life cycle of a fish population can provide a platform for exploring potential effects of and management responses to changing conditions. Potential climate-change scenarios can be imposed, responses can be observed, and the effectiveness of potential actions can be evaluated. This approach is limited owing to future conditions likely deviating in range and timing from conditions used to create the model so that the model is expected to become obsolete. In the meantime, however, the modeling process explicitly states assumptions, clarifies information gaps, and provides a means to better understand which relationships are robust and which are vulnerable to changing climate by observing whether and why model output diverges from actual observations through time. The purpose of the model described herein is to provide such a decision-support tool regarding coho (Oncorhynchus kisutch) salmon for the Sauk-Suiattle Indian Tribe of Washington State.
The Skagit coho salmon model is implemented in a system dynamics format and has three primary stocks—(1) predicted smolts, (2) realized smolts, and (3) escapement. “Predicted smolts” are the number of smolts expected based on the number of spawners in any year and the Ricker production curve. Pink salmon (Oncorhynchus gorbuscha) return to the Skagit River in odd years, and when they overlap with juvenile rearing coho salmon, coho smolt production is substantially higher than in non-pink years. Therefore, the model uses alternative Ricker equations to predict smolts depending on whether their juvenile year was a pink or non-pink year. The stock “realized smolts” is calculated based on the expected effect of streamflow conditions to alter the productivity predicted by the Ricker curve. Adverse conditions include scouring flow events that occur when redds are present; high-flow events during winter on juveniles, which can cause fish displacement and adverse water turbidity; and extremely low flows in summer. The stock “escapement” represents the fish remaining after accounting for ocean mortality and harvest. Ocean mortality has been linked with indices of ocean conditions, which are related to ocean biological productivity. Ocean survival also may have a density-dependent component such that lower survival is associated with higher numbers of smolts. The model allows the user to change certain model parameters and inputs, and choose among alternative predictors for certain modeled relations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171125","collaboration":"Prepared in cooperation with Sauk-Suiattle Indian Tribe","usgsCitation":"Woodward, Andrea, Kirby, Grant, and Morris, Scott, 2017, Skagit River coho salmon life history model—Users’ guide: U.S. Geological Survey Open-File Report 2017–1125, 57 p., https://doi.org/10.3133/ofr20171125.","productDescription":"vi, 57 p.","numberOfPages":"68","onlineOnly":"Y","ipdsId":"IP-081907","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":346300,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1125/ofr20171125.pdf","text":"Report","size":"3.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1125"},{"id":346299,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1125/coverthb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Skagit River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.5,\n 47.95314495015594\n ],\n [\n -120.75347900390624,\n 47.95314495015594\n ],\n [\n -120.75347900390624,\n 49\n ],\n [\n -122.5,\n 49\n ],\n [\n -122.5,\n 47.95314495015594\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Forest and Rangeland Ecosystem Science Center
U.S. Geological Survey
777 NW 9th St., Suite 400
Corvallis, Oregon 97330
Detecting populations of rare or cryptic species is essential for their conservation. For species like giant gartersnakes (Thamnophis gigas), conventional survey methods can be expensive and inefficient. These sampling difficulties might be overcome by modern techniques that detect deoxyribonucleic acid (DNA) shed by organisms into the environment (eDNA). We evaluated the efficacy of detecting giant gartersnake eDNA in water samples from the laboratory and at locations with known giant gartersnake populations in the Sacramento Valley of California, and failed to detect giant gartersnake DNA in most laboratory and all field samples. Aspects of giant gartersnake biology—such as highly keratinized skin and spending extensive time in the terrestrial environment, as well as hot, sunny, and turbid conditions in wetlands and canals of the Sacramento Valley—likely contributed to low detection probabilities. Although detection of eDNA shows promise under many conditions, further development is needed before sampling for eDNA is a viable option for detecting giant gartersnake populations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171123","collaboration":"Prepared in cooperation with the Central Valley Project—Bureau of Reclamation and U.S. Fish and Wildlife Service","usgsCitation":"Halstead, B.J., Wood, D.A, Bowen, Lizabeth, Waters, Shannon, Vandergast, A.G., Ersan, J.S.M., Skalos, S.M., and Casazza, M.L., 2017, An evaluation of the efficacy of using environmental DNA (eDNA) to detect giant gartersnakes (Thamnophis gigas): U.S. Geological Survey Open-File Report 2017-1123, 41 p., https://doi.org/10.3133/ofr20171123.","productDescription":"vi, 41 p.","numberOfPages":"52","onlineOnly":"Y","ipdsId":"IP-086792","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":346165,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1123/ofr20171123.pdf","text":"Report","size":"4.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1123"},{"id":346180,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1123/coverthb2.jpg"}],"country":"United States","state":"California","otherGeospatial":"Colusa National Wildlife Refuge, Natomas Basin","contact":"Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
The U.S. Geological Survey (USGS) recently conducted an assessment of the undiscovered, technically recoverable oil and gas potential of Tertiary strata underlying the onshore areas and State waters of the northern Gulf of Mexico coastal region. The assessment was based on a number of geologic elements including an evaluation of hydrocarbon source rocks, suitable reservoir rocks, and hydrocarbon traps in an Upper Jurassic-Cretaceous-Tertiary Composite Total Petroleum System defined for the region by the USGS. Five conventional assessment units (AUs) were defined for the Midway (Paleocene) and Wilcox (Paleocene-Eocene) Groups, and the Carrizo Sand of the Claiborne Group (Eocene) interval including: (1) the Wilcox Stable Shelf Oil and Gas AU; (2) the Wilcox Expanded Fault Zone Gas and Oil AU; (3) the Wilcox-Lobo Slide Block Gas AU; (4) the Wilcox Slope and Basin Floor Gas AU; and (5) the Wilcox Mississippi Embayment AU (not quantitatively assessed).
The USGS assessment of undiscovered oil and gas resources for the Midway-Wilcox-Carrizo interval resulted in estimated mean values of 110 million barrels of oil (MMBO), 36.9 trillion cubic feet of gas (TCFG), and 639 million barrels of natural gas liquids (MMBNGL) in the four assessed units. The undiscovered oil resources are almost evenly divided between fluvial-deltaic sandstone reservoirs within the Wilcox Stable Shelf (54 MMBO) AU and deltaic sandstone reservoirs of the Wilcox Expanded Fault Zone (52 MMBO) AU. Greater than 70 percent of the undiscovered gas and 66 percent of the natural gas liquids (NGL) are estimated to be in deep (13,000 to 30,000 feet), untested distal deltaic and slope sandstone reservoirs within the Wilcox Slope and Basin Floor Gas AU.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171111","usgsCitation":"Warwick, P.D., 2017, Geologic assessment of undiscovered conventional oil and gas resources in the lower Paleogene Midway and Wilcox Groups, and the Carrizo Sand of the Claiborne Group, of the northern Gulf Coast region: U.S. Geological Survey Open-File Report 2017–1111, 67 p., https://doi.org/10.3133/ofr20171111.","productDescription":"Report: vi, 60 p.; Appendixes 1-4","numberOfPages":"78","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-063993","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":410834,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/publication/ofr20171167","text":"Open-File Report 2017–1167","linkHelpText":"- Geologic Assessment of Undiscovered Gas Resources in Cretaceous–Tertiary Coal Beds of the U.S. Gulf of Mexico Coastal Plain"},{"id":346065,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2017/1111/ofr20171111_appendix2.pdf","text":"Appendix 2","size":"490 KB","linkHelpText":"- Input Data Form for the Wilcox Expanded Fault Zone Gas and Oil Assessment Unit (50470117)"},{"id":346063,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1111/ofr20171111.pdf","text":"Report","size":"14.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1111"},{"id":346062,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1111/coverthb.jpg"},{"id":346066,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2017/1111/ofr20171111_appendix3.pdf","text":"Appendix 3","size":"510 KB","linkHelpText":"- Input Data Form for the Wilcox-Lobo Slide Block Gas Assessment Unit (50470119)"},{"id":346067,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2017/1111/ofr20171111_appendix4.pdf","text":"Appendix 4","size":"396 KB","linkHelpText":"- Input Data Form for the Wilcox Slope and Basin Floor Gas Assessment Unit (50470118)"},{"id":346064,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2017/1111/ofr20171111_appendix1.pdf","text":"Appendix 1","size":"389 KB","linkHelpText":"- Input Data Form for the Wilcox Stable Shelf Oil and Gas Assessment Unit (50470116)"}],"country":"United States","otherGeospatial":"Gulf of Mexico","contact":"Director, Eastern Energy Resources Science Center
U.S. Geological Survey
Mail Stop 956
12201 Sunrise Valley Drive
Reston, VA 20192
http://energy.usgs.gov/
Groundwater provides more than 40 percent of California’s drinking water. To protect this vital resource, the State of California created the Groundwater Ambient Monitoring and Assessment (GAMA) Program. The GAMA Program’s Priority Basin Project assesses the quality of groundwater resources used for drinking water supply and increases public access to groundwater-quality information. In the Yuba River and Bear River Watersheds of the Sierra Nevada, many rural households rely on private wells for their drinking water supplies.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171115","collaboration":"Prepared in collaboration with California State Water Resources Control Board","usgsCitation":"Fram, M.S., Jasper, Monica, and Taylor, K.A., 2017, Groundwater Quality in the Yuba River and Bear River watersheds, Sierra Nevada, California: U.S. Geological Survey Open-File Report 2017–1115, 4 p., https://doi.org/10.3133/ofr20171115.","productDescription":"4 p.","numberOfPages":"4","ipdsId":"IP-087403","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":438208,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F73F4MS9","text":"USGS data release","linkHelpText":"Groundwater-Quality Data in the Yuba and Bear Watersheds Shallow Aquifer Study Unit, 2015-2016: Results from the California GAMA Priority Basin Project"},{"id":346137,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1115/ofr20171115.pdf","text":"Report","size":"3.75 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1115"},{"id":346136,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1115/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Bear River Watershed, Yuba River Watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.5,\n 39\n ],\n [\n -120.4167,\n 39\n ],\n [\n -120.4167,\n 39.75\n ],\n [\n -121.5,\n 39.75\n ],\n [\n -121.5,\n 39\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"California Water Science Center
California GAMA
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
Surface-water supplies are important sources of drinking water for residents in the Triangle area of North Carolina, which is located within the upper Cape Fear and Neuse River Basins. Since 1988, the U.S. Geological Survey and a consortium of local governments have tracked water-quality conditions and trends in several of the area’s water-supply lakes and streams. This report summarizes data collected through this cooperative effort, known as the Triangle Area Water Supply Monitoring Project, during October 2013 through September 2014 (water year 2014) and October 2014 through September 2015 (water year 2015). Major findings for this period include:
Director, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Stephenson Center, Suite 129
Columbia, SC 29210