The U.S. Department of Interior’s Bureau of Reclamation, Lower Colorado Region (Reclamation) is preparing an environmental impact statement (EIS) for the Navajo Generating Station-Kayenta Mine Complex Project (NGS-KMC Project). The proposed project involves various Federal approvals that would facilitate continued operation of the Navajo Generating Station (NGS) from December 23, 2019 through 2044, and continued operation of the Kayenta Mine and support facilities (collectively called the Kayenta Mine Complex, or KMC) to supply coal to the NGS for this operational period. The EIS will consider several project alternatives that are likely to produce different effects on the Navajo (N) aquifer; the N aquifer is the principal water resource in the Black Mesa area used by the Navajo Nation, Hopi Tribe, and Peabody Western Coal Company (PWCC).
The N aquifer is composed of three hydraulically connected formations—the Navajo Sandstone, the Kayenta Formation, and the Lukachukai Member of the Wingate Sandstone—that function as a single aquifer. The N aquifer is confined under most of Black Mesa, and the overlying stratigraphy limits recharge to this part of the aquifer. The N aquifer is unconfined in areas surrounding Black Mesa, and most recharge occurs where the Navajo Sandstone is exposed in the area near Shonto, Arizona. Overlying the N aquifer is the D aquifer, which includes the Dakota Sandstone, Morrison Formation, Entrada Sandstone, and Carmel Formation. The aquifer is named for the Dakota Sandstone, which is the primary water-bearing unit.
The NGS is located near Page, Arizona on the Navajo Nation. The KMC, which delivers coal to NGS by way of a dedicated electric railroad, is located approximately 83 miles southeast of NGS (about 125 miles northeast of Flagstaff, Arizona). The Kayenta Mine permit area is located on about 44,073 acres of land leased within the boundaries of the Hopi and Navajo Indian Reservations. KMC has been conducting mining and reclamation operations within the Kayenta Mine permit boundary since 1973.
The KMC part of the proposed project requires approval by the Office of Surface Mining (OSM) of a significant revision of the mine’s permit to operate in accordance with the Surface Mine Control and Reclamation Act (Public Law 95-87, 91 Stat. 445 [30 U.S.C. 1201 et seq.]). The revision will identify coal resource areas that may be used to continue extracting coal at the present rate of approximately 8.2 million tons per year. The Kayenta Mine Complex uses water pumped from the D and N aquifers beneath PWCC’s leasehold to support mining and reclamation activities. Prior to 2006, water from the PWCC well field also was used to transport coal by way of a coal-slurry pipeline to the now-closed Mohave Generating Station. Water usage at the leasehold was approximately 4,100 acre-feet per year (acre-ft/yr) during the period the pipeline was in use, and declined to an average 1,255 acre-ft/yr from 2006 to 2011. The Probable Hydrologic Consequences (PHC) section of the mining and reclamation permit must be modified to project the consequences of extended water use by the mine for the duration of the KMC part of the project, including a post-mining reclamation period.
Since 1971, the U.S. Geological Survey (USGS) has conducted the Black Mesa Monitoring Program, which consists of monitoring water levels and water quality in the N aquifer, compiling information on water use by PWCC and tribal communities, maintaining several stream-gaging stations, measuring discharge at selected springs, conducting special studies, and reporting findings. These data are useful in evaluating the effects on the N aquifer from PWCC and community pumping, and the effects of variable precipitation.
The EIS will assess the impacts of continued pumping on the N aquifer, including changes in storage, water quality, and effects on spring and baseflow discharge, by proposed mining through 2044, and during the reclamation process to 2057.
Several groundwater models exist for the area and Reclamation concluded it would conduct a peer review of the groundwater flow model that will be used to assess the direct, reasonably foreseeable indirect, and cumulative effects of future groundwater withdrawals on the D and N aquifers in the Black Mesa area. Reclamation made this determination because of the level of controversy around the effects of continued water use and the comments received from the 2014 draft EIS scoping meetings. Reclamation requested assistance from the USGS in evaluating existing groundwater flow models of the Black Mesa Basin that can be used to predict the effects of different project alternatives on the D and N aquifers.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161088","productDescription":"vi, 23 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-076168","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":321807,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1088/ofr20161088.pdf","text":"Report","size":"3.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1088"},{"id":321806,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1088/coverthb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Black Mesa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -111.4453125,\n 35.545635932499415\n ],\n [\n -111.4453125,\n 36.84446074079564\n ],\n [\n -109.6490478515625,\n 36.84446074079564\n ],\n [\n -109.6490478515625,\n 35.545635932499415\n ],\n [\n -111.4453125,\n 35.545635932499415\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Arizona Water Science Center
U.S. Geological Survey
520 N. Park Avenue
Tucson, AZ 85719
http://az.water.usgs.gov/
Solar power represents an important and rapidly expanding component of the renewable energy portfolio of the United States (Lovich and Ennen, 2011; Hernandez and others, 2014). Understanding the impacts of renewable energy development on wildlife is a priority for the U.S. Fish and Wildlife Service (FWS) in compliance with Department of Interior Order No. 3285 (U.S. Department of the Interior, 2009) to “develop best management practices for renewable energy and transmission projects on the public lands to ensure the most environmentally responsible development and delivery of renewable energy.” Recent studies examining effects of renewable energy development on mortality of migratory birds have primarily focused on wind energy (California Energy Commission and California Department of Fish and Game, 2007), and in 2012 the FWS published guidance for addressing wildlife conservation concerns at all stages of land-based wind energy development (U.S. Fish and Wildlife Service, 2012). As yet, no similar guidelines exist for solar development, and no published studies have directly addressed the methodology needed to accurately estimate mortality of birds and bats at solar facilities. In the absence of such guidelines, ad hoc methodologies applied to solar energy projects may lead to estimates of wildlife mortality rates that are insufficiently accurate and precise to meaningfully inform conversations regarding unintended consequences of this energy source and management decisions to mitigate impacts. Although significant advances in monitoring protocols for wind facilities have been made in recent years, there remains a need to provide consistent guidance and study design to quantify mortality of bats, and resident and migrating birds at solar power facilities (Walston and others, 2015).
In this document, we suggest methods for mortality monitoring at solar facilities that are based on current methods used at wind power facilities but adapted for the unique conditions encountered at solar facilities. In particular, unlike at wind-power facilities, the unimpeded access to almost all areas within the facilities, the typically flat terrain, and general absence of thick vegetation allow distance-sampling techniques (Buckland and others, 2001, 2004) to be exploited to advantage at industrial solar sites. These protocols build on the work of Nicolai and others (2011), and as our understanding and techniques for monitoring improve, the methods may be further modified to incorporate improvements in the future. We present case studies based on monitoring methods currently implemented at different utility-scale solar facilities to illustrate how distance-sampling techniques may improve overall detectability without substantially increasing costs. Every facility is unique, and the protocols presented may be adapted based on specific monitoring objectives and conditions at each site.
We provide guidance for designing monitoring programs whose objective it is to estimate the total number of bird and bat fatalities occurring at a facility over an extended period of time. We address spatial variation in causes of mortality, as well as potential sources of imperfect detection, for example, animals falling in or moving to unsearched areas, carcasses removed by predators, and carcasses missed by searchers. We suggest methods to estimate and account for each source of imperfect detection. This document focuses on monitoring design only and does not discuss approaches for estimating mortality from collected data. The development of statistically sound estimators relevant to the solar context is a current topic of research, although there are already strong foundations for estimation with distance-sampling methods in similar open, arid environments (Anderson and others, 2001; Freilich and others, 2005). Nonetheless, if protocols described in this document are followed, the resulting data will be adequate and sufficient for estimating mortality using newly formulated estimators.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161087","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Huso, Manuela, Dietsch, Thomas, and Nicolai, Chris, 2016, Mortality monitoring design for utility-scale solar power facilities: U.S. Geological Survey Open-File Report 2016-1087, 44 p., https://dx.doi.org/10.3133/ofr20161087.","productDescription":"vi, 44 p.","numberOfPages":"54","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-073911","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":321633,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1087/ofr20161087.pdf","text":"Report","size":"2.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1087 Report PDF"},{"id":321632,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1087/coverthb.jpg"}],"contact":"Director, Forest and Rangeland Ecosystem Science Center
U.S. Geological Survey
777 NW 9th St., Suite 400
Corvallis, Oregon 97330
http://fresc.usgs.gov/
Efforts to improve fish passage have resulted in the replacement of six culverts in Crystal Springs Creek in Portland, Oregon. Two more culverts are scheduled to be replaced at Glenwood Street and Bybee Boulevard (Glenwood/Bybee project) in 2016. Recently acquired data have allowed for a more comprehensive understanding of the hydrology of the creek and the topography of the watershed. To evaluate the impact of the culvert replacements and recent hydrologic data, a Hydrologic Engineering Center-River Analysis System hydraulic model was developed to estimate water-surface elevations during high-flow events. Longitudinal surface-water profiles were modeled to evaluate current conditions and future conditions using the design plans for the culverts to be installed in 2016. Additional profiles were created to compare with the results from the most recent flood model approved by the Federal Emergency Management Agency for Crystal Springs Creek and to evaluate model sensitivity.
Model simulation results show that water-surface elevations during high-flow events will be lower than estimates from previous models, primarily due to lower estimates of streamflow associated with the 0.01 and 0.002 annual exceedance probability (AEP) events. Additionally, recent culvert replacements have resulted in less ponding behind crossings. Similarly, model simulation results show that the proposed replacement culverts at Glenwood Street and Bybee Boulevard will result in lower water-surface elevations during high-flow events upstream of the proposed project. Wider culverts will allow more water to pass through crossings, resulting in slightly higher water-surface elevations downstream of the project during high-flows than water-surface elevations that would occur under current conditions. For the 0.01 AEP event, the water-surface elevations downstream of the Glenwood/Bybee project will be an average of 0.05 ft and a maximum of 0.07 ft higher than current conditions. Similarly, for the 0.002 AEP event, the water-surface elevations will be an average of 0.04 ft and a maximum of 0.19 ft higher than current conditions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161079","collaboration":"Prepared in cooperation with the City of Portland Bureau of Environmental Services","usgsCitation":"Stonewall, Adam, and Hess, Glen, 2016, Evaluation of flood inundation in Crystal Springs Creek, Portland, Oregon: U.S. Geological Survey Open-File Report 2016-1079, 33 p., https://dx.doi.org/10.3133/ofr20161079.","productDescription":"Report: iv, 33 p.; Plate: 24.00 x 36.00 inches","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-052885","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":321611,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1079/ofr20161079.pdf","text":"Report","size":"10 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1079 Report PDF"},{"id":321612,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2016/1079/ofr20161079_plate1.pdf","text":"Plate 1","size":"9.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1079 Plate 1 PDF"},{"id":321610,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1079/coverthb.jpg"}],"country":"United States","state":"Oregon","city":"Portland","otherGeospatial":"Crystal Springs Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.62,\n 45.45\n ],\n [\n -122.62,\n 45.5\n ],\n [\n -122.65,\n 45.5\n ],\n [\n -122.65,\n 45.45\n ],\n [\n -122.62,\n 45.45\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
http://or.water.usgs.gov
During 2015, the U.S. Geological Survey, in cooperation with the U.S. Department of Energy, collected groundwater samples from 31 wells at or near the Idaho Nuclear Technology and Engineering Center (INTEC) at the Idaho National Laboratory for purgeable organic compounds (POCs). The samples were collected and analyzed for the purpose of evaluating whether purge water from wells located inside an areal polygon established downgradient of the INTEC must be treated as a Resource Conservation and Recovery Act listed waste.
POC concentrations in water samples from 29 of 31 wells completed in the eastern Snake River Plain aquifer were greater than their detection limit, determined from detection and quantitation calculation software, for at least one to four POCs. Of the 29 wells with concentrations greater than their detection limits, only 20 had concentrations greater than the laboratory reporting limit as calculated with detection and quantitation calculation software. None of the concentrations exceeded any maximum contaminant levels established for public drinking water supplies. Most commonly detected compounds were 1,1,1-trichoroethane, 1,1-dichloroethene, and trichloroethene.
","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161083","collaboration":"DOE/ID-22238Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702
http://id.water.usgs.gov
Topock Marsh is a large wetland adjacent to the Colorado River and the main feature of Havasu National Wildlife Refuge (Havasu NWR) in southern Arizona. In 2010, the U.S. Fish and Wildlife Service (FWS) and Bureau of Reclamation began a project to improve water management capabilities at Topock Marsh and protect habitats and species. Initial construction required a drawdown, which caused below-average inflows and water depths in 2010–11. U.S. Geological Survey Fort Collins Science Center (FORT) scientists collected an assemblage of biotic, abiotic, and hydrologic data from Topock Marsh during the drawdown and immediately after, thus obtaining valuable information needed by FWS.
Building upon that work, FORT developed a decision support system (DSS) to better understand ecosystem health and function of Topock Marsh under various hydrologic conditions. The DSS was developed using a spatially explicit geographic information system package of historical data, habitat indices, and analytical tools to synthesize outputs for hydrologic time periods. Deliverables include high-resolution orthorectified imagery of Topock Marsh; a DSS tool that can be used by Havasu NWR to compare habitat availability associated with three hydrologic scenarios (dry, average, wet years); and this final report which details study results. This project, therefore, has addressed critical FWS management questions by integrating ecologic and hydrologic information into a DSS framework. This DSS will assist refuge management to make better informed decisions about refuge operations and better understand the ecological results of those decisions by providing tools to identify the effects of water operations on species-specific habitat and ecological processes. While this approach was developed to help FWS use the best available science to determine more effective water management strategies at Havasu NWR, technologies used in this study could be applied elsewhere within the region.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161065","collaboration":"In cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Holmquist-Johnson, Chris; Hanson, Leanne; Daniels, Joan; Talbert, Colin; and Haegele, Jeanette, 2016, Development of a decision support tool for water and resource management using biotic, abiotic, and hydrological assessments of Topock Marsh, Arizona: U.S. Geological Survey Open-File Report 2016–1065, 121 p., https://dx.doi.org/10.3133/ofr20161065.","productDescription":"viii, 121 p.","numberOfPages":"130","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-070577","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":321529,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1065/ofr20161065.pdf","text":"Report","size":"55.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1065"},{"id":321528,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1065/coverthb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Topock Marsh","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.57572937011719,\n 34.75233231513255\n ],\n [\n -114.57572937011719,\n 34.85015678001124\n ],\n [\n -114.46826934814453,\n 34.85015678001124\n ],\n [\n -114.46826934814453,\n 34.75233231513255\n ],\n [\n -114.57572937011719,\n 34.75233231513255\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Center Director, USGS Fort Collins Science Center
2150 Centre Ave., Bldg. C
Box 25046, MS-939
Fort Collins, CO 80526-8118
The Airborne Lidar Processing System (ALPS) analyzes Experimental Advanced Airborne Research Lidar (EAARL) data—digitized laser-return waveforms, position, and attitude data—to derive point clouds of target surfaces. A full-waveform airborne lidar system, the EAARL seamlessly and simultaneously collects mixed environment data, including submerged, sub-aerial bare earth, and vegetation-covered topographies.
ALPS uses three waveform target-detection algorithms to determine target positions within a given waveform: centroid analysis, leading edge detection, and bottom detection using water-column backscatter modeling. The centroid analysis algorithm detects opaque hard surfaces. The leading edge algorithm detects topography beneath vegetation and shallow, submerged topography. The bottom detection algorithm uses water-column backscatter modeling for deeper submerged topography in turbid water.
The report describes slant range calculations and explains how ALPS uses laser range and orientation measurements to project measurement points into the Universal Transverse Mercator coordinate system. Parameters used for coordinate transformations in ALPS are described, as are Interactive Data Language-based methods for gridding EAARL point cloud data to derive digital elevation models. Noise reduction in point clouds through use of a random consensus filter is explained, and detailed pseudocode, mathematical equations, and Yorick source code accompany the report.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161046","usgsCitation":"Nagle, David B., and Wright, C. Wayne, 2016, Algorithms used in the Airborne Lidar Processing System (ALPS):\nU.S. Geological Survey Open-File Report, 2016–1046, 45 p., https://dx.doi.org/10.3133/ofr20161046.","productDescription":"x, 45 p.","numberOfPages":"56","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-063528","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":321007,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1046/ofr20161046.pdf","text":"Report","size":"1.51 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1046"},{"id":321006,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1046/coverthb.jpg"}],"contact":"Director, St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
(727) 502–8000
http://coastal.er.usgs.gov/
Successful adaptive management hinges largely upon integrating new and improved sources of information as they become available. As a timely example of this tenet, we updated a management decision support tool that was previously developed for greater sage-grouse (Centrocercus urophasianus, hereinafter referred to as “sage-grouse”) populations in Nevada and California. Specifically, recently developed spatially explicit habitat maps derived from empirical data played a key role in the conservation of this species facing listing under the Endangered Species Act. This report provides an updated process for mapping relative habitat suitability and management categories for sage-grouse in Nevada and northeastern California (Coates and others, 2014, 2016). These updates include: (1) adding radio and GPS telemetry locations from sage-grouse monitored at multiple sites during 2014 to the original location dataset beginning in 1998; (2) integrating output from high resolution maps (1–2 m2) of sagebrush and pinyon-juniper cover as covariates in resource selection models; (3) modifying the spatial extent of the analyses to match newly available vegetation layers; (4) explicit modeling of relative habitat suitability during three seasons (spring, summer, winter) that corresponded to critical life history periods for sage-grouse (breeding, brood-rearing, over-wintering); (5) accounting for differences in habitat availability between more mesic sagebrush steppe communities in the northern part of the study area and drier Great Basin sagebrush in more southerly regions by categorizing continuous region-wide surfaces of habitat suitability index (HSI) with independent locations falling within two hydrological zones; (6) integrating the three seasonal maps into a composite map of annual relative habitat suitability; (7) deriving updated land management categories based on previously determined cut-points for intersections of habitat suitability and an updated index of sage-grouse abundance and space-use (AUI); and (8) masking urban footprints and major roadways out of the final map products.
Seasonal habitat maps were generated based on model-averaged resource selection functions (RSF) derived for 10 project areas (813 sage-grouse; 14,085 locations) during the spring season, 10 during the summer season (591 sage-grouse, 11,743 locations), and 7 during the winter season (288 sage-grouse, 4,862 locations). RSF surfaces were transformed to HSIs and averaged in a GIS framework for every pixel for each season. Validation analyses of categorized HSI surfaces using a suite of independent datasets resulted in an agreement of 93–97 percent for habitat versus non-habitat on an annual basis. Spring and summer maps validated similarly well at 94–97 percent, while winter maps validated slightly less accurately at 87–93 percent.
We then provide an updated example of how space use models can be integrated with habitat models to help inform conservation planning. We used updated lek count data to calculate a composite abundance and space use index (AUI) that comprised the combination of probabilistic breeding density with a non-linear probability of occurrence relative to distance to nearest lek. The AUI was then classified into two categories of use (high and low-to-no) and intersected with the HSI categories to create potential management prioritization scenarios based on information about sage-grouse occupancy coupled with habitat suitability. Compared to Coates and others (2014, 2016), the amount of area classified as habitat across the region increased by 6.5 percent (approximately 1,700,000 acres). For management categories, core increased by 7.2 percent (approximately 865,000 acres), priority increased by 9.6 percent (approximately 855,000 acres), and general increased by 9.2 percent (approximately 768,000 acres), while non-habitat decreased (that is, classified non-habitat occurring outside of areas of concentrated use) by 11.9 percent (approximately 2,500,000 acres). Importantly, seasonal and annual maps represent habitat for all age and sex classes of sage-grouse (that is, sample sizes of marked grouse were insufficient to only construct models for reproductive females). This revised sage-grouse habitat mapping product helps improve adaptive application of conservation planning tools based on intersections of spatially explicit habitat suitability, abundance, and space use indices.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161080","collaboration":"Prepared in cooperation with the State of Nevada Sagebrush Ecosystem Program, Bureau of Land Management, Nevada Department of Wildlife, California Department of Fish and Wildlife, and Idaho State University","usgsCitation":"Coates, P.S., Casazza, M.L., Brussee B.E., Ricca, M.A., Gustafson, K.B., Sanchez-Chopitea, E., Mauch, K., Niell, L., Gardner, S., Espinosa, S., and Delehanty, D.J., 2016, Spatially explicit modeling of annual and seasonal habitat for greater sage-grouse (Centrocercus urophasianus) in Nevada and Northeastern California—An updated decision-support tool for management: U.S. Geological Survey Open-File Report 2016-1080, 160 p., https://dx.doi.org/10.3133/ofr20161080.","productDescription":"Report: viii, 160 p.; Dataset","numberOfPages":"172","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-072897","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":322138,"rank":3,"type":{"id":28,"text":"Dataset"},"url":"https://dx.doi.org/10.5066/F7CC0XRV","text":"USGS data release - Spatially Explicit Modeling of Annual and Seasonal Habitat for Greater Sage-Grouse (Centrocercus urophasianus) in Nevada and Northeastern California - an Updated Decision-Support Tool for Management"},{"id":321471,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1080/coverthb.jpg"},{"id":321472,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1080/ofr20161080.pdf","text":"Report","size":"20 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1080 Report PDF"}],"country":"United States","state":"California, Nevada","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.87158203125,\n 37.50972584293751\n ],\n [\n -120.87158203125,\n 41.96765920367816\n ],\n [\n -114.06005859375,\n 41.96765920367816\n ],\n [\n -114.06005859375,\n 37.50972584293751\n ],\n [\n -120.87158203125,\n 37.50972584293751\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
http://werc.usgs.gov/
The U.S. Geological Survey (USGS) has developed a dynamic food-web simulation model to provide decision support for Bureau of Reclamation (Reclamation) river restoration projects in the Methow River, Washington. This modeling effort was done to contribute to Reasonable and Prudent Alternative actions 56 and 57of the 2014 Federal Columbia River Power System Biological Opinion (FCRPS BO), which calls for exploration of modeling as a means to help evaluate Endangered Species Act (ESA)-listed fish response to river restoration efforts. In the Methow River, these species of concern include Upper Columbia River (UCR) spring Chinook salmon (Oncorhynchus tshawytscha) and UCR summer steelhead (Oncorhynchus mykiss). Additionally, the Independent Scientific Advisory Board (ISAB) for the Columbia River has identified the need for modeling (Independent Scientific Advisory Board, 2011a)—including models that incorporate food-web dynamics (Independent Scientific Advisory Board, 2011b)—to better understand how restoration and management strategies might enhance salmon and steelhead populations.
\nDynamic food-web models, even relatively simple ones, can be valuable tools for exploring responses to river restoration. Although these models have rarely been applied to rivers and streams (but see Mcintire and Colby, 1978; Power and others, 1995), they are commonly used for management decisions in terrestrial and ocean ecosystems (Christensen and Pauly, 1993; Evans and others, 2013). One of the main strengths of these models is that they are rooted in the fundamental laws of thermodynamics (that is, mass balance). Moreover, these models can be easily adapted to different contexts by adding or subtracting different species from the web and by mechanistically linking the dynamics of web members to local environmental conditions, such as water temperature, stream discharge, and channel hydraulics (Power and others, 1995; Doyle, 2006). Alternative management actions can then be evaluated by changing these environmental conditions to simulate potential outcomes following restoration.
\nIn this report, we outline the structure of a stream food-web model constructed to explore how alternative river restoration strategies may affect stream fish populations. We have termed this model the “Aquatic Trophic Productivity model” (ATP). We present the model structure, followed by three case study applications of the model to segments of the Methow River watershed in northern Washington. For two case studies (middle Methow River and lower Twisp River floodplain), we ran a series of simulations to explore how food-web dynamics respond to four distinctly different, but applied, strategies in the Methow River watershed: (1) reconnection of floodplain aquatic habitats, (2) riparian vegetation planting, (3) nutrient augmentation (that is, salmon carcass addition), and (4) enhancement of habitat suitability for fish. For the third case study, we conducted simulations to explore the potential fish and food-web response to habitat improvements conducted in 2012 at the Whitefish Island Side Channel, located in the middle Methow River.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161075","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Benjamin, J.R., and Bellmore, J.R., 2016, Aquatic trophic productivity model: A decision support model for river restoration planning in the Methow River, Washington: U.S. Geological Survey Open-File Report 2016‒1075, 85 p., https://dx.doi.org/10.3133/ofr20161075.","productDescription":"vi, 85 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-071770","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":321408,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1075/coverthb.jpg"},{"id":321409,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1075/ofr20161075.pdf","text":"Report","size":"3.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1075 Report PDF"}],"country":"United States","state":"Washington","otherGeospatial":"Methow River","contact":"Director, Forest and Rangeland Ecosystem Science Center
U.S. Geological Survey
777 NW 9th St., Suite 400
Corvallis, Oregon 97330
http://fresc.usgs.gov/
During summer 2014, lake level, streamflow, and water temperature in and around Crystal Springs Lake in Portland, Oregon, were measured by the U.S. Geological Survey and the City of Portland Bureau of Environmental Services to better understand the effect of the lake on Crystal Springs Creek and Johnson Creek downstream. Johnson Creek is listed as an impaired water body for temperature by the Oregon Department of Environmental Quality (ODEQ), as required by section 303(d) of the Clean Water Act. A temperature total maximum daily load applies to all streams in the Johnson Creek watershed, including Crystal Springs Creek. Summer water temperatures downstream of Crystal Springs Lake and the Golf Pond regularly exceed the ODEQ numeric criterion of 64.4 °F (18.0 °C) for salmonid rearing and migration. To better understand temperature contributions of this system, the U.S. Geological Survey developed two-dimensional hydrodynamic water temperature models of Crystal Springs Lake and the Golf Pond. Model grids were developed to closely resemble the bathymetry of the lake and pond using data from a 2014 survey. The calibrated models simulated surface water elevations to within 0.06 foot (0.02 meter) and outflow water temperature to within 1.08 °F (0.60 °C). Streamflow, water temperature, and lake elevation data collected during summer 2014 supplied the boundary and reference conditions for the model. Measured discrepancies between outflow and inflow from the lake, assumed to be mostly from unknown and diffuse springs under the lake, accounted for about 46 percent of the total inflow to the lake.
\nModel simulations (scenarios) were run with lower water surface elevations in Crystal Springs Lake and increased shading to the lake to assess the relative effect the lake and pond characteristics have on water temperature. The Golf Pond was unaltered in all scenarios. The models estimated that lower lake elevations would result in cooler water downstream of the Golf Pond and shorter residence times in the lake. Increased shading to the lake would also provide substantial cooling. Most management scenarios resulted in a decrease in 7-day average of daily maximum values by about 2.0– 4.7 °F (1.1 –2.6 °C) for outflow from Crystal Springs Lake during the period of interest. Outflows from the Golf Pond showed a net temperature reduction of 0.5–2.7 °F (0.3–1.5 °C) compared to measured values in 2014 because of solar heating and downstream warming in the Golf Pond resulting from mixing with inflow from Reed Lake.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161076","collaboration":"Prepared in cooperation with City of Portland Bureau of Environmental Services","usgsCitation":"Buccola, N.L., and Stonewall, A.J., 2016, Development of a CE-QUAL-W2 temperature model for Crystal Springs Lake, Portland, Oregon: U.S. Geological Survey Open-File Report 2016‒1076, 26 p.,\nhttps://dx.doi.org/10.3133/ofr20161076.","productDescription":"Report: vi, 26 p.; Tables 1-9","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-060388","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":321392,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2016/1076/ofr20161076_tables1-9.xlsx","text":"Tables 1-9","size":"63 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2016-1076 Tables 1-9"},{"id":321390,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1076/coverthb.jpg"},{"id":321391,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1076/ofr20161076.pdf","text":"Report","size":"1.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1076"}],"country":"United States","state":"Oregon","city":"Portland","otherGeospatial":"Crystal Springs Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.63982295989989,\n 45.47522429601816\n ],\n [\n -122.63982295989989,\n 45.48085140521857\n ],\n [\n -122.63482332229613,\n 45.48085140521857\n ],\n [\n -122.63482332229613,\n 45.47522429601816\n ],\n [\n -122.63982295989989,\n 45.47522429601816\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
http://or.water.usgs.gov
The coral reef in Faga‘alu Bay, Tutuila, American Samoa, has suffered numerous natural and anthropogenic stresses. Areas once dominated by live coral are now mostly rubble surfaces covered with turf or macroalgae. In an effort to improve the health and resilience of the coral reef system, the U.S. Coral Reef Task Force selected Faga‘alu Bay as a priority study area. To support these efforts, the U.S. Geological Survey mapped nearly 1 km2 of seafloor to depths of about 60 m. Unconsolidated sediment (predominantly sand) constitutes slightly greater than 50 percent of the seafloor in the mapped area; reef and other hardbottom potentially available for coral recruitment constitute nearly 50 percent of the mapped area. Of this potentially available hardbottom, only slightly greater than 37 percent is covered with at least 10 percent coral, which is fairly evenly distributed between the reef flat, fore reef, and offshore bank/shelf.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161077","usgsCitation":"Cochran, S.A., Gibbs, A.E., D’Antonio, N.L., and Storlazzi, C.D., 2016, Benthic habitat map of U.S. Coral Reef Task Force Faga‘alu Bay priority study area, Tutuila, American Samoa: U.S. Geological Survey Open-File Report 2016–1077, 32 p., https://dx.doi.org/10.3133/ofr20161077.","productDescription":"Report: v, 32 p.; Metadata; Spatial Data","numberOfPages":"41","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-072636","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":321386,"rank":4,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1077/coverthb2.jpg"},{"id":321350,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1077/ofr20161077.pdf","text":"Report","size":"16.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1077"},{"id":321366,"rank":3,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/2016/1077/ofr20161077_metadata.html","text":"Metadata","size":"65 KB","linkFileType":{"id":5,"text":"html"},"description":"OFR 2016-1077 Metadata"},{"id":321367,"rank":2,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2016/1077/ofr20161077_gis_data.zip","text":"Polygon shapefile of benthic habitats and associated files","size":"256 KB","linkFileType":{"id":6,"text":"zip"},"description":"OFR 2016-1077 GIS data"}],"country":"United States","state":"American Samoa","otherGeospatial":"Faga'alu Bay, Tutuila","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -170.69046020507812,\n -14.277026769167454\n ],\n [\n -170.76547622680664,\n -14.332417680244378\n ],\n [\n -170.74419021606442,\n -14.367674440539975\n ],\n [\n -170.69578170776367,\n -14.326097485980599\n ],\n [\n -170.66900253295898,\n -14.288006232490893\n ],\n [\n -170.69046020507812,\n -14.277026769167454\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information, Pacific Coastal and Marine Science Center
U.S. Geological Survey
Pacific Science Center
2885 Mission St.
Santa Cruz, CA 95060
http://walrus.wr.usgs.gov/
The original National Aeronautics and Space Administration (NASA) Experimental Advanced Airborne Research Lidar (EAARL) was extensively modified to increase the spatial sampling density and to improve performance in water ranging from 3 to 44 meters (m). The new (EAARL-B) sensor features a higher spatial density that was achieved by optically splitting each laser pulse into three pulses spatially separated by 1.6 m along the flight track and 2.0 m across the flight track, on the water surface when flown at a nominal altitude of 300 m (984 feet). The sample spacing can be optionally increased to 1.0 m across the flight track. Improved depth capability was achieved by increasing the total peak laser power by a factor of 10 and by designing a new “deep-water” receiver, which is optimized to exclusively receive refracted and scattered light from deeper water (15–44 m).
\nTwo different clear-water flight missions were conducted over the U.S. Navy's South Florida Testing Facility (SFTF) to determine the EAARL-B calibration coefficients. The SFTF is an established lidar calibration range located in the coastal waters southeast of Fort Lauderdale, Florida. We used 23 selected polygons at 23 distinct depths to compare a reference dataset from this site to determine EAARL-B calibration constants over the depth range of 6.5 to 34 m.
\nWe also conducted a near-simultaneous single-beam jet-ski-based sonar survey of selected transects ranging from 1 to 33 m depth in the same area. The near-concurrent jet ski data were used to evaluate the EAARL-B performance over the depth range from 0.9 to 10 m. The more timely jet ski data were necessary because the primary reference dataset was 9 years old, and areas shallower than 6.5 m are dominated by shifting sand. We determined the jet ski data were not useful as a calibration reference in water deeper than 10 m due to large uncertainty in the vertical measurement introduced by the lack of any sensor orientation data, that is, for pitch, roll, and heading to correct the measured slant range to a vertical measurement.
\nThe resulting calibrated EAARL-B data were then analyzed and compared with the original reference dataset, the jet-ski-based dataset from the same Fort Lauderdale site, as well as the depth-accuracy requirements of the International Hydrographic Organization (IHO). We do not claim to meet all of the IHO requirements and standards. The IHO minimum depth-accuracy requirements were used as a reference only and we do not address the other IHO requirements such as “ Full Seafloor Search”. Our results show good agreement between the calibrated EAARL-B data and all reference datasets, with results that are within the 95 percent depth accuracy of the IHO Order 1 (a and b) depth-accuracy requirements.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161048","usgsCitation":"Wright, C.W., Kranenburg, C.J., Troche, R.J., Mitchell, R.W., and, Nagle, D.B., 2016, Depth calibration of the experimental advanced airborne research lidar, EAARL-B: U.S. Geological Survey Open-File Report 2016–1048, 23 p., https://dx.doi.org/10.3133/ofr20161048.","productDescription":"Report: vi, 22 p.; Data Release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-061552","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":320937,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1048/coverthb.jpg"},{"id":320951,"rank":3,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://dx.doi.org/10.5066/F79S1P4S","text":"Data Release"},{"id":320938,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1048/ofr20161048.pdf","text":"Report","size":"1.98 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1048"}],"contact":"Director, St. Petersburg Coastal and Marine Science Center
600 4th Street South
St. Petersburg, FL 33701
(727) 502-8000
http://coastal.er.usgs.gov/
Industrial practices at the Naval Industrial Reserve Ordnance Plant, in Fridley, Minnesota, caused soil and groundwater contamination. Some volatile organic compounds from the plant might have discharged to the Mississippi River, forced by the natural hydraulic gradient in the surficial aquifer system. The U.S. Environmental Protection Agency included the Naval Industrial Reserve Ordnance Plant on the Superfund National Priorities List in 1989.
\nThis report describes a preliminary characterization of trichloroethene transport in the surficial and Cambrian-Ordovician aquifer systems at the Naval Industrial Reserve Ordnance Plant. The characterization first involved simulation of 2001 conditions using a model, followed by an application of this 2001 simulator to 2011 conditions.
\nThe U.S. Geological Survey, in cooperation with the U.S. Department of the Navy, used a steady-state, uniform-density groundwater flow model to simulate measured potentiometric heads in aquifer systems on August 20, 2001, and a single-phase, conservative, non-reactive, miscible transport model to simulate trichloroethene concentrations in aquifer systems measured in 2001. The U.S. Department of the Navy furnished trichloroethene source areas and trichloroethene source area concentrations to the U.S. Geological Survey for this model simulation. Furnished delineations were postulated and informed by data collected from 1995 to 2011. The groundwater flow simulation of August 20, 2001, was superior to the trichloroethene transport simulation at replicating measurements; simulated potentiometric heads matched 90 percent of measured potentiometric heads on August 20, within 2 feet at selected locations whereas simulated trichloroethene concentration contours of 3, 10, 100, 1000, and 10,000 micrograms per liter (µg/L) correctly bounded 52 percent of measured concentrations in 2001 at selected locations. The degree to which the simulated trichloroethene plume does not match trichloroethene measurements in the surficial aquifer system during the 2001 simulation may suggest that furnished trichloroethene source areas and trichloroethene source area concentrations did not accurately represent all trichloroethene sources in the hydrogeologic system.
\nDuring the model simulation of 2001, trichloroethene discharged to the Mississippi River. A simulated 900-foot-long zone of benthic trichloroethene discharge flux existed in the shallow flow zone, across which simulated trichloroethene discharged from the surficial aquifer system to the Mississippi River at simulated trichloroethene concentrations that ranged from 3 µg/L to more than 100 µg/L. The Mississippi River was not sampled for volatile organic compounds in Fridley, Minn., from 1999 to 2016 (the publication of this report). Trichloroethene concentrations were measured in wells close to the Mississippi River in the surficial aquifer system on the downgradient side of the Naval Industrial Reserve Ordnance Plant groundwater flow field; for example, at well MS–43 in the shallow flow zone of the surficial aquifer system 280 feet east of the Mississippi River between December 1999 and August 2012, trichloroethene concentrations ranged from 130 to 220 µg/L. The 220-µg/L maximum concentration was reached in March 2003 and October 2006. The August 2012 concentration was 140 µg/L.
\nThe August 20, 2001, groundwater flow model simulator and the 2001 trichloroethene transport simulator were applied to a groundwater extraction and treatment system that existed in 2011. Furnished trichloroethene source areas and concentrations in the 2001 simulator were replaced with different, furnished, hypothetical source areas and concentrations. Forcing in 2001 was replaced with forcing in 2011. No trichloroethene concentrations greater than 3 µg/L were simulated as discharging to the Mississippi River during applications of the 2001 simulator to the 2011 groundwater extraction and treatment system. These applications were not intended to represent historical conditions. Differences between furnished and actual trichloroethene sources may explain differences between measurements and simulation results for the 2001 trichloroethene transport simulator. Causes of differences between furnished and actual trichloroethene sources may cause differences between hypothetical application results and the performance of the actual U.S. Department of the Navy groundwater extraction and treatment system at the Naval Industrial Reserve Ordnance Plant. Other limitations may also cause differences between application results and performance.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161066","collaboration":"Prepared in cooperation with the U.S. Department of the Navy, Naval Facilities Engineering Command","usgsCitation":"King, J.N., and Davis, J.H., 2016, Preliminary investigation of groundwater flow and trichloroethene transport in the surficial aquifer system, Naval Industrial Reserve Ordnance Plant, Fridley, Minnesota: U.S. Geological Survey Open File Report 2016–1066, 120 p., https://dx.doi.org/10.3133/ofr20161066.","productDescription":"Report: x, 120 p.; Metadata","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-039553","costCenters":[{"id":269,"text":"FLWSC-Ft. Lauderdale","active":true,"usgs":true}],"links":[{"id":321042,"rank":3,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://dx.doi.org/10.5066/F798853M","text":"Data Release","linkFileType":{"id":5,"text":"html"},"description":"OFR 2016-1066"},{"id":321040,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1066/coverthb.jpg"},{"id":321041,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1066/ofr20161066.pdf","text":"Report","size":"12,1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1066"}],"country":"United States","state":"Minnesota","city":"Fridley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.38172912597656,\n 45.09582203415993\n ],\n [\n -93.34877014160155,\n 45.03228854011639\n ],\n [\n -93.27735900878906,\n 45.02986219868277\n ],\n [\n -92.96905517578125,\n 45.180584858570136\n ],\n [\n -93.043212890625,\n 45.25652199219273\n ],\n [\n -93.38172912597656,\n 45.09582203415993\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Minnesota Water Science Center
U.S. Geological Survey
2280 Woodale Drive
Mounds View, MN 55112
(763) 783-3100
http://mn.water.usgs.gov/
The software program, QRev computes the discharge from moving-boat acoustic Doppler current profiler measurements using data collected with any of the Teledyne RD Instrument or SonTek bottom tracking acoustic Doppler current profilers. The computation of discharge is independent of the manufacturer of the acoustic Doppler current profiler because QRev applies consistent algorithms independent of the data source. In addition, QRev automates filtering and quality checking of the collected data and provides feedback to the user of potential quality issues with the measurement. Various statistics and characteristics of the measurement, in addition to a simple uncertainty assessment are provided to the user to assist them in properly rating the measurement. QRev saves an extensible markup language file that can be imported into databases or electronic field notes software. The user interacts with QRev through a tablet-friendly graphical user interface. This report is the manual for version 2.8 of QRev.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161052","usgsCitation":"Mueller, D.S., 2016, QRev—Software for computation and quality assurance of acoustic Doppler current profiler moving-boat streamflow measurements—User’s manual for version 2.8: U.S. Geological Survey Open-File Report 2016–1052, 50 p., https://dx.doi.org/10.3133/ofr20161052. ","productDescription":"vii, 50 p.","numberOfPages":"59","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-073112","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":321055,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1052/ofr20161052.pdf","text":"Report","size":"3.29 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1052"},{"id":321054,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1052/coverthb.jpg"},{"id":324156,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://dx.doi.org/10.3133/ofr20161068","text":"Open-File Report 2016–1068 - ","description":"OFR 2016-1052","linkHelpText":"QRev—Software for Computation and Quality Assurance of Acoustic Doppler Current Profiler Moving-Boat Streamflow Measurements—Technical Manual for Version 2.8 "}],"contact":"Chief, USGS Office of Surface Water
415 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
(703) 648-5301
Or visit the Office of Surface Water Web site at: http://water.usgs.gov/osw/
","tableOfContents":"Streamflow and concentrations of sodium and chloride estimated from records of specific conductance were used to calculate loads of sodium and chloride during water year (WY) 2014 (October 1, 2013, through September 30, 2014) for tributaries to the Scituate Reservoir, Rhode Island. Streamflow and water-quality data used in the study were collected by the U.S. Geological Survey and the Providence Water Supply Board in the cooperative study. Streamflow was measured or estimated by the U.S. Geological Survey following standard methods at 23 streamgages; 14 of these streamgages are equipped with instrumentation capable of continuously monitoring water level, specific conductance, and water temperature. Water-quality samples were collected at 37 sampling stations by the Providence Water Supply Board and at 14 continuous-record streamgages by the U.S. Geological Survey during WY 2014 as part of a long-term sampling program; all stations are in the Scituate Reservoir drainage area. Water-quality data collected by the Providence Water Supply Board are summarized by using values of central tendency and are used, in combination with measured (or estimated) streamflows, to calculate loads and yields (loads per unit area) of selected water-quality constituents for WY 2014.
The largest tributary to the reservoir (the Ponaganset River, which was monitored by the U.S. Geological Survey) contributed a mean streamflow of 23 cubic feet per second to the reservoir during WY 2014. For the same time period, annual mean streamflows measured (or estimated) for the other monitoring stations in this study ranged from about 0.35 to about 14 cubic feet per second. Together, tributaries (equipped with instrumentation capable of continuously monitoring specific conductance) transported about 1,200,000 kilograms of sodium and 2,100,000 kilograms of chloride to the Scituate Reservoir during WY 2014; sodium and chloride yields for the tributaries ranged from 7,700 to 45,000 kilograms per year per square mile and from 12,000 to 75,000 kilograms per year per square mile, respectively.
At the stations where water-quality samples were collected by the Providence Water Supply Board, the median of the median chloride concentrations was 24 milligrams per liter, median nitrite concentration was 0.002 milligrams per liter as nitrogen (N), median nitrate concentration was 0.01 milligrams per liter as N, median orthophosphate concentration was 0.07 milligrams per liter as phosphate, and median concentrations of total coliform bacteria and Escherichia coli were 320 and 20 colony forming units per 100 milliliters, respectively. The medians of the median daily loads (and yields) of chloride, nitrite, nitrate, orthophosphate, and total coliform and Escherichia coli bacteria were 62 kilograms per day (42 kilograms per day per square mile), 19 grams per day (6.1 grams per day per square mile), 79 grams per day (36 grams per day per square mile), 380 grams per day (150 grams per day per square mile), 13,000 million colony forming units per day (8,300 million colony forming units per day per square mile), and 1,000 million colony forming units per day (470 million colony forming units per day per square mile), respectively.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161051","collaboration":"Prepared in cooperation with the Providence Water Supply Board","usgsCitation":"Smith, K.P., 2016, Streamflow, water quality, and constituent loads and yields, Scituate Reservoir drainage area, Rhode Island, water year 2014: U.S. Geological Survey Open-File Report 2016–1051, 31 p., https://dx.doi.org/10.3133/ofr20161051.","productDescription":"Report: v, 31 p.; Appendix 1","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-069938","costCenters":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"links":[{"id":320747,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1051/ofr20161051.pdf","text":"Report","size":"11.1 (MB)","linkFileType":{"id":1,"text":"pdf"},"description":"OF 2016-1051"},{"id":320748,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1051/ofr20161051_appendix1.xlsx","text":"Appendix 1","linkFileType":{"id":3,"text":"xlsx"},"description":"Appendix 1","linkHelpText":"Appendix 1. Water-quality data collected by the Providence Water Supply Board at 37 monitoring stations in the Scituate Reservoir drainage area, Rhode Island, water year 2014. Excel (30 KB)"},{"id":320746,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1051/coverthb.jpg"}],"country":"United States","state":"Rhode Island","otherGeospatial":"Scituate Reservoir","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.7572021484375,\n 41.738784653087464\n ],\n [\n -71.7572021484375,\n 41.90304362629451\n ],\n [\n -71.55567169189453,\n 41.90304362629451\n ],\n [\n -71.55567169189453,\n 41.738784653087464\n ],\n [\n -71.7572021484375,\n 41.738784653087464\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
or visit our Web site at:
http://newengland.water.usgs.gov
In 2011, the U.S. Environmental Protection Agency (EPA) introduced emissions standards, known as Mercury and Air Toxics Standards (MATS), for a range of toxic constituents from coal-fired utility power stations and other combustion sources. This report presents the findings of an expert panel convened in September 2014 to assess the role of the U.S. Geological Survey (USGS) in new coal investigations that would be useful to stakeholders under MATS. Panel input is provided as summaries of responses to a questionnaire distributed to participants. The panel suggests that the USGS continue its work on trace elements in coal and include more information about delivered coals and boiler feed coals, in comparison to previous USGS compilations that emphasized sampling representative of coals in the ground. To be useful under multipollutant regulatory standards, investigation of a range of constituents in addition to mercury would be necessary. These include other toxic metals proposed for regulation, such as arsenic, nickel, cadmium, and chromium, as well as the halogens chlorine and fluorine, which upon emission form harmful acid gases. Halogen determinations are also important because they influence mercury speciation in flue gas, which allows the effectiveness of mercury controls to be assessed and predicted. The panel suggests that the Illinois Basin and the Powder River Basin should have the highest priority for new coal quality investigations in the near term by the USGS, on the basis of current economic conditions and overall economic importance, respectively. As a starting point for new investigations, brief summaries of the distribution of mercury in each coal basin, and their potential for further investigation, are presented.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161033","usgsCitation":"Kolker, Allan, 2016, Mercury in U.S. coal—Priorities for new U.S. Geological Survey studies: U.S. Geological Survey Open-File Report 2016–1033, 21 p., https://dx.doi.org/10.3133/ofr20161033. ","productDescription":"v, 21 p.","numberOfPages":"27","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-066372","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":321001,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1033/coverthb.jpg"},{"id":321002,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1033/ofr20161033.pdf","text":"Report","size":"1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1033"}],"contact":"Director, Eastern Energy Resources Science Center
U.S. Geological Survey
956 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
Telephone: 703-648-6401
http://energy.usgs.gov/GeneralInfo/
ScienceCenters/Eastern.aspx
The 20th century climate for the Southeastern United States and surrounding areas as simulated by global climate models used in the Coupled Model Intercomparison Project Phase 5 (CMIP5) was evaluated. A suite of statistics that characterize various aspects of the regional climate was calculated from both model simulations and observation-based datasets. CMIP5 global climate models were ranked by their ability to reproduce the observed climate. Differences in the performance of the models between regions of the United States (the Southeastern and Northwestern United States) warrant a regional-scale assessment of CMIP5 models.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161047","usgsCitation":"Rupp, D.E., 2016, An evaluation of 20th century climate for the Southeastern United States as simulated by Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models: U.S. Geological Survey Open-File Report 2016–1047, 32 p., https://dx.doi.org/10.3133/ofr20161047.","productDescription":"iv, 32 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-072786","costCenters":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"links":[{"id":320989,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1047/coverthb.jpg"},{"id":320990,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1047/ofr20161047.pdf","text":"Report","size":"4.55 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1047"}],"country":"United 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U.S. Department of the Interior
North Carolina State University, Campus Box 7617
Raleigh, NC 27695
(919) 515-2229
https://www.doi.gov/csc/southeast/
The Storm 3 is a browser-based data logger manufactured by WaterLOG/Xylem Incorporated that operates over a temperature range of −40 to 60 degrees Celsius (°C). A Storm logger with no built-in telemetry (Storm3-00) and a logger with built-in cellular modem (Storm3-03) were evaluated by the U.S. Geological Survey (USGS) Hydrologic Instrumentation Facility (HIF) for conformance to the manufacturer’s specifications with bench tests, for recording data over the device’s operating temperature range with temperature chamber tests, and for field performance with an outdoor deployment test.
\nThe procedures followed and the results obtained from the testing are described in this publication. The device met most of the manufacturer’s stated specifications. An exception was power consumption, which was about 10 percent above the manufacturer’s specifications. It was also observed that enabling WiFi doubles the Storm 3’s power consumption. In addition, several logging errors were made by two units during deployment testing, but it could not be determined whether these errors were the fault of the Storm or of an attached sensor.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161054","usgsCitation":"Kunkle, G.A., 2016, Evaluation of the Storm 3 data logger manufactured by Waterlog/Xylem Incorporated—Results of Bench, Temperature, and Field Deployment Testing: U.S. Geological Survey Open-File Report 2016–1054, 9 p., https://dx.doi.org/10.3133/ofr20161054.","productDescription":"iii, 9 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-069059","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":320970,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1054/ofr20161054.pdf","text":"Report","size":"373 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1054"},{"id":320969,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1054/coverthb.jpg","description":"OFR 2016-1054"}],"contact":"Chief, Hydrologic Instrumentation Facility
U.S. Geological Survey
Building 2101
Stennis Space Center, MS 39529
http://water.usgs.gov/hif/
U.S. Fish and Wildlife Service (USFWS) staff in the Pacific Southwest Region and at the Hopper Mountain National Wildlife Refuge Complex requested technical assistance to improve their global positioning system (GPS) data acquisition, management, and archive in support of the California Condor Recovery Program. The USFWS deployed and maintained GPS units on individual Gymnogyps californianus (California condor) in support of long-term research and daily operational monitoring and management of California condors. The U.S. Geological Survey (USGS) obtained funding through the Science Support Program to provide coordination among project participants, provide GPS Global System for Mobile Communication (GSM) transmitters for testing, and compare GSM/GPS with existing Argos satellite GPS technology. The USFWS staff worked with private companies to design, develop, and fit condors with GSM/GPS transmitters. The Movebank organization, an online database of animal tracking data, coordinated with each of these companies to automatically stream their GPS data into Movebank servers and coordinated with USFWS to improve Movebank software for managing transmitter data, including proofing/error checking of incoming GPS data. The USGS arranged to pull raw GPS data from Movebank into the USGS California Condor Management and Analysis Portal (CCMAP) (https://my.usgs.gov/ccmap) for production and dissemination of a daily map of condor movements including various automated alerts. Further, the USGS developed an automatic archiving system for pulling raw and proofed Movebank data into USGS ScienceBase to comply with the Federal Information Security Management Act of 2002. This improved data management system requires minimal manual intervention resulting in more efficient data flow from GPS data capture to archive status. As a result of the project’s success, Pinnacles National Park and the Ventana Wildlife Society California condor programs became partners and adopted the same workflow, tracking, and data archive system. This GPS tracking data management model and workflow should be applicable and beneficial to other wildlife tracking programs.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161030","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service, Region 8","usgsCitation":"Waltermire, R.G., Emmerich, C.U., Mendenhall, L.C., Bohrer, Gil, Weinzierl, R.P., McGann, A.J., Lineback, P.K., Kern, T.J., and Douglas, D.C., 2016, Improve wildlife species tracking—Implementing an enhanced global positioning system data management system for California condors: U.S. Geological Survey Open-File Report 2016–1030, 46 p., https://dx.doi.org/10.3133/ofr20161030.","productDescription":"vi, 46 p.","numberOfPages":"52","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-066019","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":320820,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1030/ofr20161030.pdf","text":"Report","size":"5.79 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1032"},{"id":320819,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1030/coverthb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.29980468749999,\n 37.07271048132946\n ],\n [\n -122.1240234375,\n 36.86204269508728\n ],\n [\n -121.79443359375,\n 36.87962060502676\n ],\n [\n -121.88232421875,\n 36.686041276581925\n ],\n [\n -122.05810546875,\n 36.63316209558658\n ],\n [\n -121.9482421875,\n 36.2265501474709\n ],\n [\n -121.53076171875,\n 35.871246850027966\n ],\n [\n -121.201171875,\n 35.60371874069731\n ],\n [\n -120.9814453125,\n 35.31736632923788\n ],\n [\n -120.95947265624999,\n 35.137879119634185\n ],\n [\n -120.76171875,\n 35.10193405724606\n ],\n [\n -120.65185546875,\n 34.66935854524543\n ],\n [\n -120.80566406250001,\n 34.52466147177172\n ],\n [\n -120.25634765624999,\n 34.34343606848294\n ],\n [\n -119.94873046875,\n 34.379712580462204\n ],\n [\n -119.59716796875,\n 34.34343606848294\n ],\n [\n -119.2236328125,\n 34.21634468843465\n ],\n [\n -118.91601562499999,\n 33.88865750124075\n ],\n [\n -118.5205078125,\n 33.88865750124075\n ],\n [\n -118.19091796875,\n 33.63291573870476\n ],\n [\n -117.83935546874999,\n 33.486435450999885\n ],\n [\n -117.6416015625,\n 33.87041555094183\n ],\n [\n -116.23535156249999,\n 34.03445260967645\n ],\n [\n -116.25732421875,\n 35.7286770448517\n ],\n [\n -116.89453125,\n 35.60371874069731\n ],\n [\n -117.22412109375,\n 36.38591277287651\n ],\n [\n -117.97119140625,\n 37.212831514455964\n ],\n [\n -118.47656249999999,\n 37.35269280367274\n ],\n [\n -118.95996093749999,\n 37.09023980307208\n ],\n [\n -119.77294921874999,\n 37.19533058280065\n ],\n [\n -120.34423828125,\n 37.28279464911045\n ],\n [\n -121.06933593749999,\n 37.23032838760387\n ],\n [\n -121.31103515625,\n 37.45741810262938\n ],\n [\n -121.55273437499999,\n 37.24782120155428\n ],\n [\n -121.9482421875,\n 37.125286284966805\n ],\n [\n -122.29980468749999,\n 37.07271048132946\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Center Director, USGS Fort Collins Science Center
2150 Centre Ave., Bldg. C
Fort Collins, CO 80526-8118
Much has been written about the age and formation of Death Valley, but that is one—if not the last—chapter in the fascinating geologic history of this area. Igneous and sedimentary rocks in the Greenwater Range, one mountain range east of Death Valley, tell an earlier story that overlaps with the formation of Death Valley proper. This early story has been told by scientists who have studied these rocks for many years and continue to do so. This field guide was prepared for the first Death Valley Natural History Conference and provides an overview of the geology of the Greenwater Range and the early history (10–0 Ma) of Death Valley.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161064","usgsCitation":"Calzia, J.P., Rämö, O.T., Jachens, Robert, Smith, Eugene, and Knott, Jeffrey, 2016, Geology of the Greenwater Range, and the dawn of Death Valley, California—Field guide for the Death Valley Natural History Conference, 2013: U.S. Geological Survey Open-File Report 2016–1064, 32 p., https://dx.doi.org/10.3133/ofr20161064.","productDescription":"iv, 32 p.","numberOfPages":"37","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-073504","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":320772,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1064/ofr20161064.pdf","text":"Report","size":"5.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1064 Report PDF"},{"id":320771,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1064/coverthb.jpg"}],"country":"United States","state":"California, Nevada","otherGeospatial":"Death Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.10052490234375,\n 36.07241230197147\n ],\n [\n -117.10052490234375,\n 36.59127365634205\n ],\n [\n -116.27517700195312,\n 36.59127365634205\n ],\n [\n -116.27517700195312,\n 36.07241230197147\n ],\n [\n -117.10052490234375,\n 36.07241230197147\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"GMEG staff, Geology, Minerals, Energy, & Geophysics Science Center—
Menlo Park, California
U.S. Geological Survey
345 Middlefield Road
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http://geomaps.wr.usgs.gov/gmeg/
Stable isotope delta values (δ18O and δ2H) of precipitation can vary with elevation, and quantification of the precipitation elevation gradient can be used to predict recharge elevation within a watershed. Precipitation samples were analyzed for stable isotope delta values between 2003 and 2014 from the Verde River watershed of north-central Arizona. Results indicate a significant decrease in summer isotopic values overtime at 3,100-, 4,100-, 6,100-, 7,100-, and 8,100-feet elevation. The updated local meteoric water line for the area is δ2H = 7.11 δ18O + 3.40. Equations to predict stable isotopic values based on elevation were updated from previous publications in Blasch and others (2006), Blasch and Bryson (2007), and Bryson and others (2007). New equations were separated for samples from the Camp Verde to Flagstaff transect and the Prescott to Chino Valley transect. For the Camp Verde to Flagstaff transect, the new equations for winter precipitation are δ18O = -0.0004z − 8.87 and δ2H = -0.0029z − 59.8 (where z represents elevation in feet) and the summer precipitation equations were not statistically significant. For the Prescott to Chino Valley transect, the new equations for summer precipitation are δ18O = -0.0005z − 3.22 and δ2H = -0.0022z − 27.9; the winter precipitation equations were not statistically significant and, notably, stable isotope values were similar across all elevations. Interpretation of elevation of recharge contributing to surface and groundwaters in the Verde River watershed using the updated equations for the Camp Verde to Flagstaff transect will give lower elevation values compared with interpretations presented in the previous studies. For waters in the Prescott and Chino Valley area, more information is needed to understand local controls on stable isotope values related to elevation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161053","collaboration":"Prepared in cooperation with Yavapai County Water Advisory Committee and Arizona Department of Water Resources","usgsCitation":"Beisner, K.R., Paretti, N.V., and Tucci, R.S., 2016, Analysis of stable isotope ratios (δ18O and δ2H) in precipitation of the Verde River watershed, Arizona, 2003 through 2014: U.S. Geological Survey Open-File Report 2016–1053, 11 p., https://dx.doi.org/10.3133/ofr20161053.","productDescription":"Report: iv, 9 p.; Stable Isotope Data","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-070405","costCenters":[{"id":128,"text":"Arizona Water Science Center","active":true,"usgs":true}],"links":[{"id":320392,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1053/ofr20161053.pdf","text":"Report","size":"10.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1053"},{"id":320393,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2016/1053/ofr20161053_appendix_tables.xlsx","text":"Stable Isotope Data","size":"31.1 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2016-1053"},{"id":320391,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1053/coverthbr.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Verde River Watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.6,\n 34.4\n ],\n [\n -112.6,\n 35.3\n ],\n [\n -111.3,\n 35.3\n ],\n [\n -111.3,\n 34.4\n ],\n [\n -112.6,\n 34.4\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Arizona Water Science Center
520 N. Park Avenue
Tucson, AZ 85719
(520) 670-6671
http://az.water.usgs.gov/
Many barrier islands in the United States are eroding and losing elevation substantively because of storm surge, waves, and sea-level changes. This is particularly true for the deltaic barrier system in Louisiana. Breton Island is near the mouth of the Mississippi River at the southern end of the Chandeleur barrier island chain in southeast Louisiana. This report expands on previous geomorphic studies of Breton Island by incorporating additional historic and recent datasets. Multiple analyses focus on longand short-term shoreline change, as well as episodic events and anthropogenic modification. Analyses periods include long term (1869–2014), long-term historic (1869–1950), post-Mississippi River-Gulf Outlet (1950–2014), pre/post-Hurricane Katrina (2004–5), and recent (2005–14). In addition to shoreline change, barrier island geomorphology is evaluated using island area, elevation, and sediment volume change. In the long term (1869–2014), Breton Island was affected by landward transgression, island narrowing, and elevation loss. Major storm events exacerbated the long-term trends. In the recent period (2005–14), Breton Island eroded at a slower rate than in the long-term and gained area and total sediment volume. The recent accretion is likely because of the lack of major storms since Hurricane Katrina in 2005.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161039","usgsCitation":"Terrano, J.F., Flocks, J.G., and Smith, K.E.L., 2016, Analysis of shoreline and geomorphic change for Breton Island, Louisiana, from 1869 to 2014: U.S. Geological Survey Open-File Report 2016–1039, 34 p.,\nhttps://dx.doi.org/10.3133/ofr20161039.","productDescription":"Report: viii, 34 p.; Data Releases","numberOfPages":"43","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-070444","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":320056,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1039/coverthb.jpg"},{"id":320057,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1039/ofr20161039.pdf","text":"Report","size":"3.69 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016–1039"},{"id":324797,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F70G3H6G","text":"USGS data release - Topobathymetric Lidar Survey of Breton and Gosier Islands, Louisiana, January 16 and 18, 2014"},{"id":324798,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7XS5SGM","text":"USGS data release - A GIS Compilation of Vector Shorelines and Associated Shoreline Change Data for Breton Island, Louisiana: 1869–2014"}],"country":"United States","state":"Louisiana","otherGeospatial":"Breton Island, Breton National Wildlife Refuge, Chandeleur barrier island chain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.17087554931639,\n 29.50729642400116\n ],\n [\n -89.17757034301758,\n 29.506698839472033\n ],\n [\n -89.18306350708008,\n 29.503262659979747\n ],\n [\n -89.18684005737305,\n 29.49579230227246\n ],\n [\n -89.18478012084961,\n 29.493849919009545\n ],\n [\n -89.1840934753418,\n 29.492206334848714\n ],\n [\n -89.17928695678711,\n 29.492804004901785\n ],\n [\n -89.17671203613281,\n 29.49235575269256\n ],\n [\n -89.17722702026367,\n 29.48862024048175\n ],\n [\n -89.18169021606444,\n 29.483390291999466\n ],\n [\n -89.18254852294922,\n 29.477861195816843\n ],\n [\n -89.1789436340332,\n 29.473676814427723\n ],\n [\n -89.1734504699707,\n 29.473527369040777\n ],\n [\n -89.16847229003906,\n 29.478907264175373\n ],\n [\n -89.1650390625,\n 29.48742484748479\n ],\n [\n -89.16435241699219,\n 29.497585238377603\n ],\n [\n -89.16521072387695,\n 29.501918036260868\n ],\n [\n -89.1653823852539,\n 29.506101251415647\n ],\n [\n -89.16778564453125,\n 29.508043399702284\n ],\n [\n -89.17087554931639,\n 29.50729642400116\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
In 2013, Landsat 8 began adding high quality, global, moderate-resolution imagery to the more than 40-year archive of Landsat imagery. To assess the potential effects of the availability of Landsat 8 imagery on users and their work, the U.S. Geological Survey (USGS) Land Remote Sensing Program (LRS) initiated a survey of Landsat users. The objectives of the survey were to
\n1. Characterize various Landsat user groups, such as United States (U.S.) and international users and Landsat 8 and non-Landsat 8 users;
2. Identify any differences among user groups in uses and preferences;
3. Measure the importance of and satisfaction with Landsat 8 attributes;
4. Assess the importance to users of the frequency of usable imagery; and
5. Determine any challenges in using Landsat 8.
The online survey was sent to 51,617 Landsat users registered with USGS in May 2014. Almost 13,000 people responded to the survey for a response rate of 25 percent (n = 12,966). Current Landsat users (users who had used Landsat in their work in the year prior to the survey) composed 89 percent of the sample (n = 11,549) and past Landsat users composed 11 percent (n = 1,417). The results reported here apply to current Landsat users registered with the USGS Earth Resources Observation and Science (EROS) Center.
\nUsers from 161 countries responded to the survey. Of those, 19 percent were citizens or permanent residents of the United States and 81 percent resided in other countries. More than 70 percent of current users had used Landsat 8 in the year prior to the survey. The majority of Landsat 8 users (65 percent) were established users who used Landsat imagery regularly both before and after Landsat 8 imagery became available. The average current Landsat user was male, 36 years old, and highly educated, with 9 years of experience using satellite imagery or geographic information system (GIS) software. Landsat 8 users had, on average, two more years of experience than non-Landsat 8 users. Users were employed predominantly by academic institutions (65 percent), followed by private businesses (13 percent), Federal governments (10 percent), State and local governments (6 percent), and nonprofit organizations (6 percent).
\nOf the Landsat imagery obtained in the past year by current users, on average 31 percent came from a Landsat 8 sensor. An equivalent amount came from the Landsat 7 ETM+ sensor (33 percent); slightly less came from Landsats 4 and 5 TM sensors (27 percent). Much less came from Landsats 1 through 5 MSS sensors (5 percent). Overall, more than a third of users’ work used Landsat imagery (38 percent). Of this work, on average, 37 percent of the work was operational. Landsat 8 users considered a greater proportion of their work operational than non-Landsat 8 users (39 percent compared with 29 percent). Environmental sciences and management were the most commonly selected primary applications (selected by 42 percent of users). Land use/land cover (23 percent) was the second most commonly selected primary application, followed by education (12 percent), agriculture (9 percent), and planning and development (6 percent).
\nLandsat 8 users were asked to rank the importance of certain attributes in determining whether to use Landsat 8 imagery in their work. The archive was ranked most important, followed by cost, spatial resolution, extent of coverage, data quality, and frequency of revisit. Users were asked how satisfied they were with these same attributes as they currently apply to Landsat 8 imagery. On average, users were most satisfied with lack of cost, extent of coverage, data quality, and the archive, but they were satisfied with all attributes.
\nUsers were asked how often they needed Landsat imagery to meet various requirements for their primary application. The survey question specifically asked how often users needed usable imagery, which differs from how often they would like the Landsat satellites to acquire an image. Users were asked to identify their needed frequency of usable imagery for the following levels:
\n1. Threshold level—the minimum frequency of usable imagery needed to be of any value to their primary application.
2. Breakthrough level—the frequency of usable imagery that would result in a significant improvement for their primary application of the imagery.
3. Target level—the frequency of usable imagery that would only provide a limited additional increase in the expected performance for their primary application.
To meet the threshold level, three-quarters of users needed usable imagery every 17 days or less frequently. At the breakthrough level, two-thirds of users (64 percent) needed a usable image every 5–16 days. The current constellation of two satellites (Landsat 7 and 8) is capable of meeting the threshold and breakthrough needs of most users at least some of the time, but a single satellite would be highly unlikely to do so. Two-fifths of users (40 percent) felt that usable imagery provided every 4 days or more frequently would meet their target level which the current Landsat constellation cannot provide. Landsat 8 users were significantly more likely than non-Landsat 8 users to need usable imagery more frequently to meet their target levels. Additionally, U.S. Landsat 8 users were significantly more likely than other Landsat users to need usable imagery more frequently in order meet both their breakthrough and target levels.
\nTo explore the effect of the availability of Landsat 8 imagery on Landsat imagery use in general, established users (those who had consistently used Landsat imagery both before and after Landsat 8 imagery became available) using Landsat 8 imagery were asked about changes in the amount of Landsat imagery they used. The majority of established users using Landsat 8 imagery (60 percent) reported an average increase of 51 percent in the number of scenes obtained after Landsat 8 imagery became available. Landsat 8 users were asked if they had encountered challenges in using Landsat 8 whereas non-Landsat 8 users were asked if such challenges had played a role in why they were not using Landsat 8 imagery. Although many users did not encounter challenges when using or trying to use Landsat 8 data, slightly less than 30 percent did encounter issues with processing the data to a usable point. The most common issue reported was not being able to create or have access to a surface reflectance corrected product. Other challenges were related to the file sizes of images being too large to download, store, or analyze. There were no statistically significant differences between Landsat 8 and non-Landsat 8 users in terms of challenges encountered when using or trying to use the imagery, which indicates that users were not unduly discouraged by the challenges they may have encountered. When asked about potential consequences of not using Landsat 8, more than half of the non-Landsat 8 users did not report detrimental effects on their work from not using the imagery. Of those who did report detrimental effects, decreased quality of work, decreased scope of work, and increased time spent on work were the most common.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161032","usgsCitation":"Miller, H.M., 2016, Users and uses of Landsat 8 satellite imagery—2014 survey results: U.S. Geological Survey Open-File Report 2016–1032, 27 p., https://dx.doi/org/10.3133/ofr20161032.","productDescription":"vi, 27 p.","numberOfPages":"33","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-069774","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":320059,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1032/ofr20161032.pdf","text":"Report","size":"2.37 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1032"},{"id":320058,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1032/coverthb.jpg"}],"contact":"Center Director, USGS Fort Collins Science Center
2150 Centre Ave., Bldg. C
Box 25046, MS-939
Fort Collins, CO 80526-8118
An analysis of total-dissolved-gas (TDG) and water-temperature data collected at eight fixed monitoring stations on the lower Columbia River in Oregon and Washington in water year 2015 indicated the following:
\nDirector, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
http://or.water.usgs.gov
As part of a cooperative effort among the U.S. Geological Survey (USGS), the U.S. Department of Energy, and the U.S. Department of the Interior Bureau of Ocean Energy Management, two grids of two-dimensional multichannel seismic reflection data were acquired in the Gulf of Mexico over lease blocks Green Canyon 955 and Walker Ridge 313 between April 18 and May 3, 2013. The purpose of the data acquisition was to fill knowledge gaps in an ongoing study of known gas hydrate accumulations in the area. These data were initially processed onboard the recording ship R/V Pelican for more quality control during the recording. The data were subsequently processed in detail by the U.S. Geological Survey in Denver, Colorado, in two phases. The first phase was to create a “kinematic” dataset that removed extensive noise present in the data but did not preserve relative amplitudes. The second phase was to create a true relative amplitude dataset that included noise removal and “wavelet” deconvolution that preserved the amplitude information. This report describes the processing techniques used to create both datasets.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161037","collaboration":"Performed in cooperation with the U.S. Department of Energy and the U.S. Department of the Interior Bureau of Ocean Energy Management","usgsCitation":"Miller, J.J., Agena, W.F., Haines, S.S., and Hart, P.E., 2016, Processing of multichannel seismic reflection data acquired in 2013 for seismic investigations of gas hydrates in the Gulf of Mexico: U.S. Geological Survey Open-File Report 2016‒1037, 32 p., https://dx.doi.org/10.3133/ofr20161037.","productDescription":"vi, 32 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-067340","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":319934,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1037/coverthb.jpg"},{"id":319936,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1037/ofr20161037.pdf","text":"Report","size":"30.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1037"}],"otherGeospatial":"Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96,\n 26\n ],\n [\n -96,\n 30.5\n ],\n [\n -89.7,\n 30.5\n ],\n [\n -89.7,\n 26\n ],\n [\n -96,\n 26\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Energy Resources Science Center
U.S. Geological Survey
Box 25046, MS-939
Denver Federal Center
Denver, CO 80225-0046
Technically recoverable undiscovered hydrocarbon resources in continuous accumulations are present in Upper Devonian and Lower Mississippian strata in the Appalachian Basin Petroleum Province. The province includes parts of New York, Pennsylvania, Ohio, Maryland, West Virginia, Virginia, Kentucky, Tennessee, Georgia, and Alabama. The Upper Devonian and Lower Mississippian strata are part of the previously defined Devonian Shale-Middle and Upper Paleozoic Total Petroleum System (TPS) that extends from New York to Tennessee. This publication presents a revision to the extent of the Devonian Shale-Middle and Upper Paleozoic TPS. The most significant modification to the maximum extent of the Devonian Shale-Middle and Upper Paleozoic TPS is to the south and southwest, adding areas in Tennessee, Georgia, Alabama, and Mississippi where Devonian strata, including potential petroleum source rocks, are present in the subsurface up to the outcrop. The Middle to Upper Devonian Chattanooga Shale extends from southeastern Kentucky to Alabama and eastern Mississippi. Production from Devonian shale has been established in the Appalachian fold and thrust belt of northeastern Alabama. Exploratory drilling has encountered Middle to Upper Devonian strata containing organic-rich shale in west-central Alabama. The areas added to the TPS are located in the Valley and Ridge, Interior Low Plateaus, and Appalachian Plateaus physiographic provinces, including the portion of the Appalachian fold and thrust belt buried beneath Cretaceous and younger sediments that were deposited on the U.S. Gulf Coastal Plain.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20161018","usgsCitation":"Enomoto, C.B., Rouse, W.A., Trippi, M.H., and Higley, D.K., 2016, Revisions to the original extent of the Devonian Shale-Middle and Upper Paleozoic Total Petroleum System: U.S. Geological Survey Open-File Report 2016–1018, 6 p., https://dx.doi.org/10.3133/ofr20161018.","productDescription":"Report: iv, 6 p.; Shapefiles; Metadata Files","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-068927","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":319798,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2016/1018/ofr20161018.pdf","text":"Report","size":"432 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2016-1018"},{"id":319797,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2016/1018/coverthb.jpg"},{"id":319922,"rank":3,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2016/1018/ofr20161018_tps506704-metadata.zip","text":"Shapefiles and Metadata Files","size":"1.18 MB","linkFileType":{"id":6,"text":"zip"},"description":"OFR 2016-1018"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.76220703125,\n 42.779275360241904\n ],\n [\n -78.79394531249999,\n 42.90816007196054\n ],\n [\n -81.5185546875,\n 42.48830197960227\n ],\n [\n -83.232421875,\n 41.623655390686395\n ],\n [\n -84.00146484374999,\n 38.71980474264239\n ],\n [\n -86.17675781249999,\n 36.63316209558658\n ],\n [\n -88.330078125,\n 34.90395296559004\n ],\n [\n -89.67041015625,\n 33.08233672856376\n ],\n [\n -86.396484375,\n 32.76880048488168\n ],\n [\n -81.05712890625,\n 36.58024660149866\n ],\n [\n -77.47558593749999,\n 39.30029918615029\n ],\n [\n -74.35546875,\n 41.1455697310095\n ],\n [\n -73.76220703125,\n 42.779275360241904\n ]\n ]\n ]\n }\n }\n ]\n}","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/