Landsat satellites have been operating since 1972, providing a continuous global record of the Earth’s land surface. The imagery is currently available at no cost through the U.S. Geological Survey (USGS). A previous USGS study estimated that Landsat imagery provided users an annual benefit of $2.19 billion in 2011, with U.S. users accounting for $1.79 billion of those benefits. That study, published in 2013, surveyed users in 2012 about Landsat imagery they retrieved in 2011. But since then, many changes have altered the demand for and supply of remotely sensed imagery and have made the analysis complex. This report updates these estimates, surveying users in 2018 about Landsat images they retrieved in 2017. The report discusses changes in the value per scene in 2017 when compared to 2011 and analyzes the potential consequences of charging fees. Landsat imagery has been available at no cost to the public since 2008, resulting in the distribution of millions of scenes each subsequent year. In addition, tens of thousands of Landsat users have registered with the USGS to access the data. Considering the number of Landsat data users worldwide and the broad range of Landsat data applications, it is difficult to quantify the cascading benefits to society provided by Landsat imagery. The value of Landsat imagery to these users was demonstrated by the substantial aggregated annual economic benefit from the imagery. Landsat imagery provided domestic and international users an estimated $3.45 billion in benefits in 2017 compared to $2.19 billion in 2011, with U.S. users accounting for $2.06 billion of those benefits. Much of the societal value of Landsat stems from the free and open data policy that allows users to access as much imagery as is necessary for their analysis at no cost. Charging even small fees would result in a loss of users and, most likely, a steep decline in the amount of imagery downloaded. It is reasonable that more than 50 percent of users will decline to pay. The consequences of charging for Landsat imagery would be felt by downstream users as well, through increased prices for value-added products as well as more intangible effects, such as reduced monitoring of environmental hazards.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191112","usgsCitation":"Straub, C.L., Koontz, S.R., and Loomis, J.B., 2019, Economic valuation of Landsat imagery: U.S. Geological Survey Open-File Report 2019–1112, 13 p., https://doi.org/10.3133/ofr20191112.","productDescription":"iv, 13 p.","onlineOnly":"Y","ipdsId":"IP-110993","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":368280,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1112/coverthb.jpg"},{"id":368281,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1112/ofr20191112.pdf","text":"Report","size":"3.19 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1112"}],"contact":"Director, Fort Collins Science Center
U.S. Geological Survey
2150 Centre Ave., Building C
Fort Collins, CO 80526-8118
Letterkenny Army Depot in Chambersburg, Pennsylvania, built an Ammonium Perchlorate Rocket Motor Destruction (ARMD) facility in 2016. The ARMD Facility was designed to centralize rocket motor destruction and contain or capture all waste during the destruction process. Ideally, there would be no contaminant transport to air, soil, or water from the facility, but the Code of Federal Regulations requires that any hazardous waste disposal facility have an environmental monitoring program in place. In a study by the U.S. Geological Survey, in cooperation with the Letterkenny Army Depot, baseline characterization of constituents in groundwater, surface water, and soil was conducted from September to December 2016 to document site conditions prior to the beginning of operations at the facility in January 2017. Groundwater wells, surface water, and soils were sampled monthly during the baseline characterization period. No sediment transport from the site occurred on days when samples were collected from surface-water sites, so no sediment was collected from the retention basin at the facility during the baseline period. Data collected during the baseline period can be compared to data collected in future years to determine whether there is any contaminant transport from the ARMD Facility to the surrounding environment.
During the baseline characterization period, monthly samples were collected from 4 groundwater wells and 9 soil sites near the ARMD Facility. The only surface-water site sampled monthly during the baseline period was upgradient from the facility. There was no streamflow at surface-water sites downgradient from the facility on days when surface-water samples were collected during the baseline characterization period.
Groundwater results for the four wells sampled near the ARMD Facility during the baseline period did not show any major water-quality issues. Mean specific conductance (SC) and pH in groundwater ranged from 220 to 771 microsiemens per centimeter at 25 degrees Celsius (μS/cm) and 6.45 to 6.98, respectively. No constituents in groundwater samples exceeded any U.S. Environmental Protection Agency (EPA) Maximum Contaminant Level (MCL). Dissolved iron (Fe) was the only groundwater constituent that exceeded a Secondary Maximum Contaminant Level (SMCL) established by the EPA. The SMCL for Fe is 300 micrograms per liter (μg/L); samples from three wells had mean dissolved Fe concentrations ranging from 1,100 to 2,600 μg/L. The only volatile organic compounds (VOCs) detected in groundwater samples were bromomethane, acetone, and chloromethane. All VOC detections in groundwater samples were less than the Reporting Detection Levels (RDLs). These three compounds also were detected in blank samples submitted for groundwater samples. Perchlorate was not detected in any groundwater sample collected during the baseline period.
Surface-water data collected during the baseline period were strictly representative of a stream reach upgradient from the ARMD Facility. Stream discharge ranged from 0.03 to 0.08 cubic feet per second during sample collection. The mean SC and pH were 310 μS/cm and 7.6, respectively. No EPA established MCLs or SMCLs were exceeded for any constituents in samples collected from this upgradient stream. Some VOCs were detected in surface water at less than the RDLs. The VOCs detected in surface water were generally the same VOCs as those detected at less than the RDLs for groundwater. Perchlorate was detected in each sample collected from the stream; the mean concentration was 0.07 μg/L. All perchlorate results were less than the RDL of 0.2 μg/L.
Soil samples collected during the baseline period did not have any constituent concentrations that exceeded any medium-specific concentrations (MSC) or soil screening levels (SSL) established by either the Commonwealth of Pennsylvania or the EPA. The Commonwealth of Pennsylvania calculates MSCs based on either a function of acceptable concentrations in groundwater or based on health concerns if the soil is directly contacted. The EPA derives acceptable concentrations of constituents (SSLs) in soil based on standardized equations combining exposure information assumptions with EPA toxicity data. The EPA calculates SSLs for residential and industrial sites. Soil sites at the ARMD Facility were considered “industrial” for comparative purposes. There was at least one order of magnitude difference between any inorganic constituent concentration detected in soil and the MSC and (or) SSL for that constituent. Four VOCs were detected in soil samples collected during the baseline period. None of the VOCs detected in the soils were within three orders of magnitude of any established MSCs or SSLs. The VOCs detected in soil were dichloromethane (also known as methylene chloride), methyl tert-butyl ether (MTBE), tetrachloroethene, and acetone (only detected once). Dichloromethane was the only VOC detected at greater than the RDLs; concentrations in all soil samples were greater than the RDLs. Dichloromethane concentrations ranged from 1.9 to 50.1 micrograms per kilogram (μg/kg). MTBE was detected in 50 percent of samples collected but all results were less than the RDLs of 1.7 to 2.6 μg/kg. Tetrachloroethene was detected in 20 percent of soil samples collected, with a maximum estimated value of 1.5 μg/kg. Inorganic constituents with the highest concentrations in soil were Fe and aluminum (Al); mean Fe and Al concentrations ranged from 28,700 to 52,400 and 10,300 to 19,800 milligrams per kilogram (mg/kg), respectively. Data collected during the baseline period in 2016 can be compared to future data to determine whether concentrations in water and soils surrounding the facility have shown any changes that could be caused by the facility operation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191094","collaboration":"Prepared in Cooperation with the Letterkenny Army Depot","usgsCitation":"Galeone, D.G., 2019, Baseline environmental monitoring of groundwater, surface water, and soil at the Ammonium Perchlorate Rocket Motor Destruction Facility at the Letterkenny Army Depot, Chambersburg, Pennsylvania, 2016: U.S. Geological Survey Open-File Report 2019–1094, 32 p., https://doi.org/10.3133/ofr20191094.","productDescription":"Report: vii; 32 p.; Appendices 1-4","numberOfPages":"44","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-102807","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":437309,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P973YRPL","text":"USGS data release","linkHelpText":"Quality Control and Soil Quality Data in support of Baseline Environmental Monitoring at the Ammonium Perchlorate Rocket Motor Destruction (ARMD) Facility at the Letterkenny Army Depot, Chambersburg, Pennsylvania, 2016"},{"id":368210,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2019/1094/ofr20191094_appendix3.xlsx","text":"Appendix 3","size":"16.8 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2019-1094"},{"id":368211,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2019/1094/ofr20191094_appendix4.xlsx","text":"Appendix 4","size":"32.3 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2019-1094"},{"id":368208,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2019/1094/ofr20191094_appendix1.xlsx","text":"Appendix 1","size":"15.5 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2019-1094"},{"id":368212,"rank":7,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1094/ofr20191094.pdf","text":"Report","size":"20.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1094"},{"id":368107,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://www.sciencebase.gov/catalog/item/5be05a51e4b0b3fc5cf33502","text":"USGS data release","description":"OFR 2019-1094","linkHelpText":"Quality Control and Soil Quality Data in support of Baseline Environmental Monitoring at the Ammonium Perchlorate Rocket Motor Destruction (ARMD) Facility at the Letterkenny Army Depot, Chambersburg, Pennsylvania, 2016"},{"id":368209,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2019/1094/ofr20191094_appendix2.xlsx","text":"Appendix 2","size":"22.1 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2019-1094"},{"id":368190,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1094/coverthb.jpg"}],"country":"United States","state":"Pennsylvania ","county":"Franklin County","city":"Chambersburg","otherGeospatial":"Letterkenny Army Depot","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.71831512451172,\n 40.0013199623656\n ],\n [\n -77.67333984375,\n 40.0013199623656\n ],\n [\n -77.67333984375,\n 40.03471220877633\n ],\n [\n -77.71831512451172,\n 40.03471220877633\n ],\n [\n -77.71831512451172,\n 40.0013199623656\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Pennsylvania Water Science Center
U.S. Geological Survey
215 Limekiln Road
New Cumberland, PA 17070
Director,
Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
The Monte Blanco borate deposits are located along the southern margin of Death Valley’s Furnace Creek Wash, south of Twenty Mule Team Canyon road in California. Topographic and geologic mapping by S. Muessig and F.M. Byers, Jr., in 1954 documented these deposits’ geologic settings, geometries, mineralogies, and chemical characteristics. They estimated borate resources at the time to be in excess of 550,000 tons B2O3.
The borate bodies are composed of predominantly ulexite and colemanite. They lie beneath Monte Blanco itself and along a northwest-trending series of conspicuous, white hills and mounds formed by northeasterly dipping, fine-grained sedimentary beds and basaltic volcanic rocks of the Miocene and Pliocene Furnace Creek Formation.
Geologic data suggest that in Miocene and Pliocene time, fine-grained sediments, volcanic debris and flows, and volcanically associated, boron-rich fluids gradually filled a fairly flat playa-like environment. At times, thick beds of felty crystals of ulexite developed and were interlayered as lenses in a thick series of mudstones as is seen today at the Eagle Borax works. After burial, the exterior of the ulexite deposit was altered to massive colemanite by ground water, which produced the “shell” of colemanite that typically surrounds the presently outcropping ulexite bodies.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191111","usgsCitation":"Muessig, S.J., Pennell, W.M, Knott, J.R., and Calzia, J.P., 2019, Geology of the Monte Blanco borate deposits, Furnace Creek Wash, Death Valley, California: U.S. Geological Survey Open-File Report 2019–1111, 35, p., 2 plates, scales 1:2,400 and 1: 2,000, https://doi.org/10.3133/ofr20191111.","productDescription":"Report: v, 30 p.; 2 Plates: 28.00 x 29.75 and 18.11 x 24.96 inches","numberOfPages":"37","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-088268","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":368047,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1111/coverthb.jpg"},{"id":368050,"rank":4,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2019/1111/ofr20191111_plate2.pdf","text":"Plate 2","size":"3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Open-File Report 2019-1111"},{"id":368048,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1111/ofr20191111_pamphlet.pdf","text":"Report","size":"2.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Open-File Report 2019-1111"},{"id":368049,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2019/1111/ofr20191111_plate1.pdf","text":"Plate 1","size":"6.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Open-File Report 2019-1111"}],"country":"United States","state":"California","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 -117.76245117187499,\n 35.60818490437746\n ],\n [\n -116.06506347656251,\n 35.60818490437746\n ],\n [\n -116.06506347656251,\n 37.19095471582605\n ],\n [\n -117.76245117187499,\n 37.19095471582605\n ],\n [\n -117.76245117187499,\n 35.60818490437746\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Geology, Minerals, Energy, & Geophysics Science Center
Menlo Park, California
U.S. Geological Survey
345 Middlefield Road
Menlo Park, CA 94025-3591
Coastal droughts have a different dynamic than upland droughts, which are typically characterized by agricultural, hydrologic, meteorological, and (or) socioeconomic effects. Drought uniquely affects coastal ecosystems because of changes in the salinity conditions of estuarine creeks and rivers. The location of the freshwater-saltwater interface in surface-water bodies is an important factor in the ecological and socioeconomic dynamics of coastal communities. To address the data and information gap for characterizing coastal drought, the Coastal Salinity Index (CSI) was developed by using salinity data. The CSI uses a computational approach similar to the Standardized Precipitation Index. The CSI can be computed for unique time intervals (for example 1-, 6-, 12-, and 24-month intervals) to characterize short- and long-term drought (saline) conditions, as well as wet (high freshwater inflow) conditions.
To encourage the use of the CSI in current and future research endeavors, this investigation addressed three activities to enhance the use and application of the CSI. First, a software package was developed for the consistent computation of the CSI that includes preprocessing of salinity data, filling missing data, computing the CSI, post-processing, and generating the supporting metadata. This software package is available for download from the U.S. Geological Survey GitLab repository. Second, the CSI has been computed at sites along the southeastern Atlantic coast (Florida to North Carolina) and the Gulf of Mexico (Texas to Florida) to increase the opportunity for linking the CSI to ecological response data. Third, using telemetered salinity data, the real-time computation of the CSI has been prototyped and disseminated on the web.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191090","collaboration":"Prepared in cooperation with the National Integrated Drought Information System","usgsCitation":"Petkewich, M.D., Lackstrom, K., McCloskey, B.J., Rouen, L.F, and Conrads, P.A., 2019, Coastal Salinity Index along the southeastern Atlantic coast and the Gulf of Mexico, 1983 to 2018 (ver. 1.1, April 2023): U.S. Geological Survey\nOpen-File Report 2019–1090, 26 p., https://doi.org/10.3133/ofr20191090.","productDescription":"Report: vi, 26 p.; Appendix; Data Release","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-105920","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":499716,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109078.htm","linkFileType":{"id":5,"text":"html"}},{"id":415336,"rank":5,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2019/1090/versionHist.txt","size":"1 kB","linkFileType":{"id":2,"text":"txt"}},{"id":415335,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2019/1090/ofr20191090_appendix1.pdf","text":"Appendix 1","size":"1.68 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1090 Appendix 1","linkHelpText":"—Coastal Salinity Index User Guide"},{"id":415334,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1090/ofr20191090.pdf","text":"Report","size":"3.08 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1090"},{"id":367860,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1090/coverthb2.jpg"},{"id":367858,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MQLNL2","text":"USGS data release","linkHelpText":"Coastal Salinity Index for Monitoring Drought"}],"country":"United States","state":"Alabama, Florida, Georgia, Louisiana, Mississippi, North Carolina, Puerto Rico, South Carolina, Texas","otherGeospatial":"Gulf of Mexico Coast, South Atlantic Coast","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -67.5439453125,\n 17.45547257997284\n ],\n [\n -65.21484375,\n 17.45547257997284\n ],\n [\n -65.21484375,\n 18.95824648598139\n ],\n [\n -67.5439453125,\n 18.95824648598139\n ],\n [\n -67.5439453125,\n 17.45547257997284\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.61328125,\n 24.487148563173424\n ],\n [\n -75.0146484375,\n 24.487148563173424\n ],\n [\n -75.0146484375,\n 36.38591277287651\n ],\n [\n -98.61328125,\n 36.38591277287651\n ],\n [\n -98.61328125,\n 24.487148563173424\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: October 1, 2019; Version 1.1: April 6, 2023","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Stephenson Center, Suite 129
Columbia, SC 29210
The Anderson Ranch property (study area), located in Taos County, north-central New Mexico, was transferred from Chevron Mining, Inc. (CMI) to the Bureau of Land Management (BLM) as part of a Natural Resource Damage Assessment and Restoration (NRDAR) court-ordered settlement. The study area supports freshwater emergent wetlands and freshwater ponds. The settlement states that CMI will provide the land and a monetary settlement to support the restoration of the wetlands on the property. To best manage the study area, the BLM requires an understanding of potential effects of climate variability and groundwater withdrawals on the wetland function. This study, completed by the U.S. Geological Survey in cooperation with the BLM, provides an initial hydrologic characterization of the study area, which included literature review, collection of groundwater-level and aqueous-chemistry data, completion of a vegetation survey, and preliminary data analysis. The data compiled, collected, and analyzed as part of this study indicate that the wetlands within the study area are groundwater fed and that the water maintaining the wetlands is modern. Surface-water levels in the pond and groundwater levels in the surrounding wetland fluctuate seasonally. The hydraulic gradient in the study area is from northeast to southwest. Evapotranspiration is a main driver of water demand within the study area.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191100","collaboration":"Prepared in cooperation with the Bureau of Land Management","usgsCitation":"Galanter, A.E., Shephard, Z.M., and Herrera-Olivas, P., 2019, Anderson Ranch wetlands hydrologic characterization in Taos County, New Mexico: U.S. Geological Survey Open-File Report 2019–1100, 42 p., https://doi.org/10.3133/ofr20191100. ","productDescription":"iii, 42 p. ","numberOfPages":"46","onlineOnly":"Y","ipdsId":"IP-109765","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":367755,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1100/coverthb.jpg"},{"id":367756,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1100/ofr20191100.pdf","text":"Slide Presentation","size":"9.45 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019–1100"}],"country":"United States ","state":"New Mexico ","county":"Taos 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New Mexico Water Science Center
U.S. Geological Survey
6700 Edith Blvd. NE, Suite B
Albuquerque, NM 87113
The production of Klamath River fall Chinook salmon (Oncorhynchus tshawytscha) in northern California and southern Oregon is thought to be limited by poor survival during freshwater juvenile life stages, in part a result of Ceratonova shasta—a highly infectious disease that can lead to high fish mortality. Higher flushing river flows are thought to affect the concentration of C. shasta spores, and in turn, juvenile salmon infection and mortality. The Stream Salmonid Simulator (S3) model was built to simulate the spatiotemporal dynamics of the growth, movement, and survival of juvenile salmon from spawning through migration to the Pacific Ocean in response to river flow, habitat availability, water temperature, and C. shasta spore concentrations. The S3 model has been calibrated to juvenile fall Chinook salmon abundances at a trap site within the Klamath River, and was specifically designed to provide objective predictions of juvenile salmon abundance and survival in relation to proposed flow management alternatives and resulting fish infection and mortality by C. shasta. Infection by C. shasta in the Klamath River is location specific, occurring in a “disease zone” with high spore concentrations. The spatial extent of this disease zone (from river kilometer 289.6 to 212.9) has been incorporated in the S3 model for the Klamath River, enabling the assessment of disease effects on fish at specific spatial locations such as the trap sampling sites, and for fish that were or were not exposed to the disease zone as they emigrate the Klamath River to the Pacific Ocean.
Given the information gained from field observations on spore concentrations in relation to river flow, deliberations by resource managers resulted in the incorporation of springtime flushing flows in a Proposed Action (PA) scenario developed in part to lower spore concentrations within the disease zone. A Historical (HI) scenario based on the observed flows, temperatures, and spore concentrations from 2004 to 2016 was used to compare and contrast the potential benefits to juvenile salmon from PA flows in relation to the HI conditions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191099","collaboration":"Prepared in cooperation with the National Oceanic and Atmospheric Administration, National Marine Fisheries Service","usgsCitation":"Plumb, J.M., Perry, R.W., Som, N.A., Alexander, J., and Hetrick, N.J., 2019, Using the stream salmonid simulator (S3) to assess juvenile Chinook salmon (Oncorhynchus tshawytscha) production under historical and proposed action flows in the Klamath River, California: U.S. Geological Survey Open-File\nReport 2019-1099, 43 p., https://doi.org/10.3133/ofr20191099.","productDescription":"vi, 43 p.","onlineOnly":"Y","ipdsId":"IP-107092","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":367843,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1099/coverthb.jpg"},{"id":367844,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1099/ofr20191099.pdf","text":"Report","size":"3.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1099"}],"country":"United States","state":"California","otherGeospatial":"Klamath River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.5247802734375,\n 41.38917324986403\n ],\n [\n -122.23114013671875,\n 41.38917324986403\n ],\n [\n -122.23114013671875,\n 41.92475971933975\n ],\n [\n -123.5247802734375,\n 41.92475971933975\n ],\n [\n -123.5247802734375,\n 41.38917324986403\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016
In this report, we describe application of the Stream Salmonid Simulator (S3) to Chinook salmon (Oncorhynchus tshawytscha) in the Klamath River between Keno Dam in southern Oregon and the ocean in northern California. S3 is a deterministic life-stage-structured population model that tracks daily growth, movement, and survival of juvenile salmon. It can track different source populations or species, such as major tributary populations that enter a river like the Klamath River. A key theme of the model is that river flow affects habitat availability and capacity, which in turn drives density-dependent population dynamics. To explicitly link population dynamics to habitat quality and quantity, the river environment is constructed as a one-dimensional series of linked habitat units, each of which has an associated daily time series of discharge, water temperature, and useable habitat area or carrying capacity. In turn, the physical characteristics of each habitat unit and the number of fish occupying each unit affect survival and growth within each habitat unit and movement of fish among habitat units.
The physical template of the Klamath River was formed by classifying the river into 2,635 mesohabitat units composed of runs, riffles, and pools. This template enabled modeling of the unimpounded Klamath River between the Keno Dam (the uppermost of four dams) and Iron Gate Dam (the lowermost dam) to address dam-removal scenarios. However, in this report, our focus was on parameterizing and calibrating the model under existing conditions, which included 1,706 discrete habitat units over the 312-kilometer (km) section of river between Iron Gate Dam and the ocean. For each habitat unit, we developed a time series of daily flow, water temperature, and amount of available habitat (weighted usable habitat area [WUA]) for spawners, fry, and parr. WUA time series were constructed using habitat suitability criteria for Chinook salmon applied to eight two-dimensional (2-D) hydrodynamic models that represented the geomorphic variability in habitat across the Klamath River. Results from the 2-D models were then extrapolated to unmodeled habitat units by scaling WUA curves for changes in habitat unit length and width. These variables were then used to drive population dynamics such as egg development and survival and juvenile movement, growth, and survival.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191107","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service and the Bureau of Reclamation","usgsCitation":"Perry, R.W., Plumb, J.M., Jones, E.C., Som, N.A., Hardy, T.B., and Hetrick, N.J., 2019, Application of the Stream Salmonid Simulator (S3) to Klamath River fall Chinook salmon (Oncorhynchus tshawytscha), California—Parameterization and calibration: U.S. Geological Survey Open-File Report 2019–1107, 89 p., https://doi.org/10.3133/ofr20191107.","productDescription":"Report: viii, 89p.; Appendix 1","numberOfPages":"102","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-106890","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":367791,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1107/ofr20191107.pdf","text":"Report","size":"5.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1107"},{"id":367792,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2019/1107/ofr20191107_a1.pdf","text":"Appendix 1","size":"241 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1107 Appendix 1"},{"id":367790,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1107/coverthb.jpg"}],"country":"United States","state":"California, Oregon","otherGeospatial":"Keno Dam, Klamath River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.4091796875,\n 41.17038447781618\n ],\n [\n -120.66284179687498,\n 41.17038447781618\n ],\n [\n -120.66284179687498,\n 42.4234565179383\n ],\n [\n -124.4091796875,\n 42.4234565179383\n ],\n [\n -124.4091796875,\n 41.17038447781618\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016
In cooperation with the New Mexico County of Bernalillo, the U.S. Geological Survey characterized potential polychlorinated biphenyl (PCB) concentration and estimated loading into the Rio Grande from watersheds that are under the county’s jurisdiction. Water and sediment samples were collected in 2017–18 from six sites within four stormwater drainage basins in the Albuquerque, New Mexico, urbanized area for the analysis of PCB congeners and other water-quality constituents during dry and wet seasons. Also, the rainfall-runoff model Arid Lands Hydrologic Model (AHYMO) was used to estimate stormwater discharge at the two sample collection sites not affected by pump station operation. Along with the PCB analysis, the discharge data were used to estimate total PCB stormflow event loads for eight events in these urban Rio Grande tributaries. PCBs were detected in 34 of 36 water samples at concentrations as high as 65.8 nanograms per liter and in 12 of 13 sediment samples at concentrations as high as 163,000 nanograms per kilogram dry weight. Six of the 36 water samples exceeded the New Mexico surface-water quality standard for protection of wildlife habitat and aquatic life of 14 nanograms per liter for PCBs. None of the water samples exceeded the U.S. Environmental Protection Agency’s National Pollutant Discharge Elimination System permit level limit of 200 nanograms per liter for PCBs in stormwater systems discharging into the Rio Grande. PCB concentrations in water samples in this study were not linearly related to antecedent precipitation or measured water-quality parameters, but PCB concentrations had a statistically significant positive Kendall’s tau correlation with total suspended solids for water samples and with total organic carbon for sediment samples. The PCB congener profiles indicate that sources to stormwater drainage basins in Bernalillo County originate both from legacy sources, such as Aroclors (for example, in landfills and old building materials), and from current-use sources, such as yellow pigments (for example, in printed materials and packaging in urban litter or refuse). Total PCB stormflow event loads were calculated with average potential minimum and maximum event loads of 0.73 and 4.32 milligrams per storm event, respectively, at the Adobe Acres pump station site and 56.78 and 315.13 milligrams per storm event at the Sanchez Farms inflow at Albuquerque, N. Mex., site.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191106","collaboration":"Prepared in cooperation with Bernalillo County","usgsCitation":"Shephard, Z.M., Conn, K.E., Beisner, K.R., Jornigan, A.D., and Bryant, C.F., 2019, Characterization and load estimation of polychlorinated biphenyls (PCBs) from selected Rio Grande tributary stormwater channels in the Albuquerque urbanized area, New Mexico, 2017–18: U.S. Geological Survey Open-File Report 2019–1106, 48 p., https://doi.org/10.3133/of20191106.","productDescription":"x, 48 p.","numberOfPages":"61","onlineOnly":"Y","ipdsId":"IP-109136","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":367784,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1106/coverthb.jpg"},{"id":367785,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1106/ofr20191106.pdf","size":"4.96 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019–1106"}],"country":"United States","state":"New Mexico","city":"Albuquerque","otherGeospatial":"Rio Grande","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.8255615234375,\n 34.9371707067839\n ],\n [\n -106.48223876953125,\n 34.9371707067839\n ],\n [\n -106.48223876953125,\n 35.20579439829525\n ],\n [\n -106.8255615234375,\n 35.20579439829525\n ],\n [\n -106.8255615234375,\n 34.9371707067839\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Mexico Water Science Center
6700 Edith Blvd.
Albuquerque, NM 87113
Eastern Energy Resources Science Center
12201 Sunrise Valley Drive
956 National Center
Reston, VA 20192
Although streamflow is widely recognized as a controlling factor in stream health, empirical relations between indicators of anthropogenic modification of streamflow and ecological indicators have been elusive. The objective of this report is to build upon specific findings reported in recent publications by providing a library of empirical models that describe the relations between streamflow modification and indicators of biological integrity. Biological monitoring data from 812 streams and rivers across the United States were matched with sites where daily streamflow was also monitored by the U.S. Geological Survey. Of these sites, 118 were sampled by the U.S. Geological Survey along gradients of streamflow modification within 3 regional focus studies. The integrity of invertebrate and fish communities was expressed as a binary variable, “impaired” or “unimpaired,” signifying whether or not the composition and structure of the biological community was statistically reduced relative to regional reference sites. Streamflow modification at each gaged site was quantified with 509 streamflow statistics scaled to express the ratio of observed streamflow conditions to site-specific expected conditions in the absence of human influences on watershed hydrology. For each region, generalized additive modeling was used to examine relations between each indicator of streamflow modification and indicators of biological integrity (response variable). In every region examined, statistically defensible and ecologically realistic relations were found between indicators of streamflow modification and indicators of biological integrity. These findings can aid practitioners and managers seeking to (1) propose empirically based hypotheses about the specific components of streamflow regimes that are critical to aquatic communities, which can subsequently be explored in detail in a region or river basin of interest; and (2) predict biological responses to anthropogenic modification of specific components of the streamflow regime.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191088","usgsCitation":"Carlisle, D.M., Grantham, T.E., Eng, K., Wolock, D.M., 2019, Regional-scale associations between indicators of biological integrity and indicators of streamflow modification: U.S. Geological Survey Open-File Report 2019–1088, 10 p., https://doi.org/10.3133/ofr20191088.\n","productDescription":"iv, 10 p.","numberOfPages":"18","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-097828","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":367467,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9O2ZV0M","linkHelpText":"Regional-scale Model Predictions of the Relation Between Biological Integrity and Streamflow Modification"},{"id":367452,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1088/ofr20191088.pdf","text":"Report","size":"12.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1088"},{"id":367451,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1088/coverthb.jpg"}],"contact":"Director, USGS Kansas Water Science Center
1217 Biltmore Drive
Lawrence, KS 66049
785-842-9909
The National Park Service (NPS) and the Bureau of Land Management (BLM) are concerned about cumulative effects of groundwater development on groundwater-dependent resources managed by, and other groundwater resources of interest to, these agencies in Snake Valley and adjacent areas, Utah and Nevada. Of particular concern to the NPS and BLM are withdrawals from all existing approved, perfected, certified, permitted, and vested groundwater rights in Snake Valley totaling about 55,272 acre-feet per year (acre-ft/yr), and from several senior water-right applications filed by the Southern Nevada Water Authority (SNWA) totaling 50,680 acre-ft/yr.
An existing groundwater-flow model of the eastern Great Basin was used to investigate where potential drawdown and capture of natural discharge is likely to result from potential groundwater withdrawals from existing groundwater rights in Snake Valley, and from groundwater withdrawals proposed in several applications filed by the SNWA. To evaluate the potential effects of the existing and proposed SNWA groundwater withdrawals, 11 withdrawal scenarios were simulated. All scenarios were run as steady state to estimate the ultimate long-term effects of the simulated withdrawals. This assessment provides a general understanding of the relative susceptibility of the groundwater resources of interest to the NPS and BLM, and the groundwater system in general, to existing and future groundwater development in the study area.
At the NPS and BLM groundwater resource sites of interest, simulated drawdown resulting from withdrawals based on existing approved, perfected, certified, permitted, and vested groundwater rights within Snake Valley ranged between 0 and 159 feet (ft) without accounting for irrigation return flow, and between 0 and 123 ft with accounting for irrigation return flow. With the addition of proposed SNWA withdrawals of 35,000 acre-ft/yr (equal to the Unallocated Groundwater portion allotted to Nevada in a draft interstate agreement), simulated drawdowns at the NPS and BLM sites of interest increased to range between 0 and 2,074 ft without irrigation return flow, and between 0 and 2,002 ft with irrigation return flow. With the addition of the proposed SNWA withdrawals of an amount equal to the full application amounts (50,680 acre-ft/yr), simulated drawdowns at the NPS and BLM sites of interest increased to range between 1 and 3,119 ft without irrigation return flow, and between 1 and 3,044 ft with irrigation return flow.
At the NPS and BLM groundwater resource sites of interest, simulated capture of natural discharge resulting from withdrawals based on existing groundwater rights in Snake Valley, both with and without irrigation return flow, ranged between 0 and 100 percent; simulated capture of 100 percent occurred at four sites. With the addition of proposed SNWA withdrawals of an amount equal to the Unallocated Groundwater portion allotted to Nevada in the draft interstate agreement, simulated capture of 100 percent occurred at nine additional sites without irrigation return flow, and at eight additional sites with irrigation return flow. With the addition of the proposed SNWA withdrawals of an amount equal to the full application amounts, simulated capture of 100 percent occurred at 11 additional sites without irrigation return flow, and at 9 additional sites with irrigation return flow.
The large simulated drawdowns produced in the scenarios that include large portions or all of the proposed SNWA withdrawals indicate that the groundwater system may not be able to support the amount of withdrawals from the proposed points of diversion (PODs) in the current SNWA water-right applications. Therefore, four additional scenarios were simulated where the withdrawal rates at the SNWA PODs were constrained by not allowing drawdowns to be deeper than the assumed depth of the PODs (about 2,000 ft). In the constrained scenarios, total withdrawals at the SNWA PODs were reduced to about 48 percent of the Unallocated Groundwater portion allotted to Nevada (35,000 acre-ft/yr reduced to 16,817 acre-ft/yr or 16,914 acre-ft/yr, without or with irrigation return flow, respectively), and about 44 percent of the full application amounts (50,680 acre-ft/yr reduced to 22,048 acre-ft/yr or 22,165 acre-ft/yr, without or with irrigation return flow, respectively). This indicates that the SNWA may need to add more PODs, or PODs in different locations, in order to withdraw large portions or all of the groundwater that has been applied for.
At the NPS and BLM groundwater resource sites of interest, simulated drawdown resulting from the addition of the constrained SNWA withdrawals applied to the Unallocated Groundwater amount ranged between 0 and 290 ft without irrigation return flow, and between 0 and 252 ft with irrigation return flow. With the addition of the constrained SNWA withdrawals applied to the full application amounts, simulated drawdowns at the NPS and BLM sites of interest ranged between 0 and 358 ft without irrigation return flow, and between 0 and 313 ft with irrigation return flow.
At the NPS and BLM groundwater resource sites of interest, with the addition of the constrained SNWA withdrawals applied to the Unallocated Groundwater amount, simulated capture of 100 percent of the natural discharge occurred at five additional sites without irrigation return flow, and at two additional sites with irrigation return flow (in addition to the four captured from existing water rights both with and without irrigation return flow). With the addition of the constrained SNWA withdrawals applied to the full application amounts, simulated capture of 100 percent occurred at six additional sites both with and without irrigation return flow.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191083","collaboration":"Prepared in cooperation with the National Park Service and the Bureau of Land Management","usgsCitation":"Masbruch, M.D., 2019, Numerical model simulations of potential changes in water levels and capture of natural discharge from groundwater withdrawals in Snake Valley and adjacent areas, Utah and Nevada: U.S. Geological Survey Open-File Report 2019–1083, 49 p., https://doi.org/10.3133/ofr20191083.","productDescription":"Report: vi, 49 p.; Data Release","numberOfPages":"49","onlineOnly":"Y","ipdsId":"IP-103457","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":367115,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1083/coverthb_.jpg"},{"id":367116,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1083/ofr20191083.pdf","text":"Report","size":"4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1083"},{"id":367119,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LQDQGM","text":"Data Release","linkHelpText":"MODFLOW-2005 files for numerical model simulations of potential changes in water levels and capture of natural discharge from groundwater withdrawals in Snake Valley and adjacent areas, Utah and Nevada"}],"country":"United States","state":"Nevada, Utah","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.48828125000001,\n 35.53222622770337\n ],\n [\n -110.302734375,\n 39.36827914916014\n ],\n [\n -110.12695312499999,\n 40.97989806962013\n ],\n [\n -111.005859375,\n 42.68243539838623\n ],\n [\n -114.78515624999999,\n 41.244772343082076\n ],\n [\n -117.59765625,\n 37.64903402157866\n ],\n [\n -115.48828125000001,\n 35.53222622770337\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Utah Water Science Center
U.S. Geological Survey
2329 West Orton Circle
Salt Lake City, Utah 84119-2047
801-908-5000
At the request of the Bureau of Land Management (BLM), the U.S. Geological Survey (USGS) is releasing with this open-file report (OFR) a previously unpublished review and comparison of two numerical models for Tule Desert, Nevada. The original review was performed in spring 2013, and only minor editorial revisions were made in the current (2019) OFR for clarity and to reformat the original interagency correspondence to the USGS OFR template. No revisions have been made to the technical content of the original review for this OFR release. Report content presented in the purpose and scope statement, and all subsequent sections of the OFR, are original content submitted to BLM in May 2013. Model review and comparisons described in the following paragraphs are based on, in part, results of a long-term (more than 2 years) aquifer test mandated by Nevada State Engineer Order 1169. Additional information on Order 1169 and associated aquifer test results can be found at the State of Nevada Division of Water Resources website (State of Nevada, 2019).
Nevada Water Science Center
U.S. Geological Survey
2730 N. Deer Run Road
Carson City, Nevada 95819
A field study was conducted to estimate survival of juvenile Chinook salmon (Oncorhynchus tshawytscha) in Lookout Point Reservoir, Oregon, during 2018. The study consisted of releasing three groups of genetically-marked fish into the reservoir, and sampling them monthly. Juveniles were released during April 10–13 (116,708 fish), May 15–18 (31,911 fish), and June 19–20 (11,758 fish). Reservoir sampling began in May and occurred monthly through October, consisting of 5-day events where juvenile Chinook salmon were collected using electrofishing, shoreline traps, and gill nets. Data were analyzed using a staggered release-recovery model and a parentage-based tagging (PBT) N-mixture model. The staggered release-recovery model provided survival estimates from three periods: mid-April to mid-May (SSRRM1); mid-May to mid-June (SSRRM2); and mid-April to mid-June (SSRRM12). Multiple estimates of survival were possible for each period using different combinations of recovery data from the three groups of fish that were released. Survival probability estimates for SSRRM1 ranged from 0.98520 to 0.98954; estimates for SSRRM2 ranged from 0.09338 to 0.62142; and the estimate for cumulative survival from mid-April to mid-June (SSRRM12) were 0.75211. We suspect that issues with release groups in May (R2) and June (R3) led to biased survival results using the staggered release-recovery model. The PBT N-mixture model provided survival estimates from six periods: mid-April to mid-May (SNMIX1); mid-May to mid-June (SNMIX2), mid-June to mid-July (SNMIX3), mid-July to mid-August (SNMIX4), mid-August to mid-September (SNMIX5); and mid-September to mid-October (SNMIX6). Survival estimates from the PBT N-mixture model were lowest for SNMIX6 (0.41620) and highest for SNMIX1 (0.79587). These results differed from those in 2017 when monthly survival increased across months. This suggests that one or more factors could have affected juvenile Chinook salmon survival in Lookout Point Reservoir. One possible factor could be copepods (which were highly prevalent on juvenile Chinook salmon during summer 2018), but environmental factors such as reserveroir elevation, discharge at Lookout Point Dam, and fish distributions within the reservoir differed between study years. Two PBT N-mixture models provided cumulative survival estimates from mid-April to mid-October. Estimates from the two models were 0.061 and 0.039, which suggests that survival of subyearling Chinook salmon in Lookout Point Reservoir was very low in 2018. Additional research is recommended to better understand inter-annual variability of subyearling Chinook salmon in the reservoir and to gain insights into factors that affect their survival.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191097","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers and Oregon State University","usgsCitation":"Kock, T.J., Perry, R.W., Hansen, G.S., Haner, P.V., Pope, A.C., Plumb, J.M., Cogliati, K.M., and Hansen, A.C., 2019, Juvenile Chinook salmon (Oncorhynchus tshawytscha) survival in Lookout Point Reservoir, Oregon, 2018: U.S. Geological Survey Open-File Report 2019–1097, 41 p., https://doi.org/10.3133/ofr20191097.","productDescription":"vi, 41 p.","onlineOnly":"Y","ipdsId":"IP-108747","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":366974,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1097/coverthb.jpg"},{"id":366975,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1097/ofr20191097.pdf","text":"Report","size":"6.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1097"}],"country":"United States","state":"Oregon","otherGeospatial":"Lookout Point Reservoir, Middle Fork Willamette River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.8165054321289,\n 43.80009302166679\n ],\n [\n -122.55970001220705,\n 43.80009302166679\n ],\n [\n -122.55970001220705,\n 43.93919224634882\n ],\n [\n -122.8165054321289,\n 43.93919224634882\n ],\n [\n -122.8165054321289,\n 43.80009302166679\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016
Intermittent streams are important and productive for salmonid habitat. Rock Creek, in southeastern Washington, flows south to the Columbia River at river kilometer (rkm) 368 and is an intermittent stream of great significance to the Yakama Nation and to the Kah-miltpah (Rock Creek) Band in particular. Historically, native steelhead (anadromous form of rainbow trout [Oncorhynchus mykiss]) and bridgelip sucker (Catostomus columbianus) populations were used by the Kah-miltpah Band for sustenance, trade, and traditional practices. Anadromous salmonid populations currently present and being monitored in the Rock Creek subbasin include Coho (O. kisutch) salmon and steelhead. Resident rainbow trout are also present and monitored (rainbow trout and steelhead will be collectively referred to as O. mykiss throughout this report). Streamflow is a limiting habitat factor in this system, but despite this, steelhead and Coho salmon still successfully return to spawn, rear, out-migrate, and survive over-summer in many of the isolated pools.
We completed habitat surveys during 2015–17 to assess the perennial pools during low-flow conditions. The lower river sections (rkm 2–13) had proportionately more dry sections than the upper river sections (rkm 14–22) for all years surveyed and had higher variability among habitat types across years. The surveyed dry sections within the lower river ranged from 44 to 57 percent, with 2015 (a drought year) as the highest and 2017 the lowest. The percentage of pool habitat in the lower river was 21−24 percent, with 2015 as the lowest and 2016 and 2017 both at 24 percent. The upper river sections had a relatively high percentage of non-pool wet habitat (49−51 percent), followed by dry (33−36 percent) and pool habitat (17−18 percent). In Walaluuks Creek, the percentage of pool habitat was the most consistent across the years, ranging from 10 to 13 percent.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191092","collaboration":"Prepared in cooperation with the Yakama Nation Fisheries Program","usgsCitation":"Hardiman, J.M., and Harvey, Elaine, 2019, Fish and habitat assessment in Rock Creek, Klickitat County, Washington 2016–17: U.S. Geological Survey Open-File Report 2019-1092, 67 p., https://doi.org/10.3133/ofr20191092.","productDescription":"vi, 67 p.","onlineOnly":"Y","ipdsId":"IP-107346","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":366814,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1092/ofr20191092.pdf","text":"Report","size":"3.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1092"},{"id":366813,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1092/coverthb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Rock Creek, Walaluuks Creek","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 45.68891423419542\n ],\n [\n -120.30303955078124,\n 45.68891423419542\n ],\n [\n -120.30303955078124,\n 46.01699242164089\n ],\n [\n -120.87158203125,\n 46.01699242164089\n ],\n [\n -120.87158203125,\n 45.68891423419542\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016
This publication consists of two map sheets that display shallow geologic structure, along with sediment distribution and thickness, for an approximately 150-km-long offshore section of the northern California coast between Punta Gorda and Point Arena. Each map sheet includes three maps at scales of either 1:100,000 or 1:200,000, and together the sheets include 30 figures that contain representative high-resolution seismic-reflection profiles. The maps and seismic-reflection surveys cover most of the continental shelf in this region. In addition, the maps show the locations of the shelf break and the 3-nautical-mile limit of California’s State Waters.
The seismic-reflection data, which are the primary dataset used to develop the maps, were collected to support the California Seafloor Mapping Program, U.S. Geological Survey Offshore Geologic Hazards projects, and National Oceanic and Atmospheric Administration’s (NOAA’s) Ocean Explorer program. In addition to the two map sheets, this publication includes geographic information system data files of faults, sediment thicknesses, and depths-to-base of sediment
The map area includes the northernmost section of the right-lateral San Andreas Fault, which extends offshore from Point Arena in the south to Point Delgada in the north. The San Andreas Fault is the primary structure in the widely distributed plate boundary between the Pacific Plate and the Sierra Nevada–Great Valley Microplate, with estimates of cumulative right slip of as much as up to 450 km. South of Point Delgada, fault-related transtension has resulted in development of the Noyo Basin. North of Point Delgada, the San Andreas Fault transitions into a complex contractional zone in and (or) south of the King Range, including a possible nearshore fault that may connect with the Mattole Canyon Fault.
Quaternary sediments and bedrock underlie the shelf. On the seismic-reflection profiles, we digitally traced the thickness and depth of the uppermost seismic-stratigraphic unit, which is a focus of this publication. The upper contact of this unit is the seafloor; the lower contact is a transgressive surface of erosion, a commonly angular, wave-cut unconformity characterized by an upward change to lower amplitude, more diffuse reflections. On the basis of this lower contact, this stratigraphic unit is inferred to have been deposited on the shelf in the last about 21,000 years during the sea-level rise that followed the last major lowstand and the Last Glacial Maximum (LGM). Maps in this publication show both the thickness of this upper sediment unit and the depth to the base of the sediment unit. Within the map region, five different “domains” of post-LGM shelf sediment are delineated on the basis of sediment thickness and coastal geomorphology. Maximum sediment thickness (as much as 67 m) is found in the northern part of the region, along the steep south flank of the King Range. Minimum sediment thickness (areas of exposed bedrock) is found on fault-bounded uplifts, which include Tolo bank and Punta Gorda bank. Mean sediment thickness for the entire shelf in the map area between Punta Gorda and Point Arena is 8.9 m, and total sediment volume is 12,824×106 m3.
Contact Information
Pacific Coastal & Marine Science Center
U.S. Geological Survey
Pacific Science Center
2885 Mission St.
Santa Cruz, CA 95060
The U.S. Army Corps of Engineers, Jacksonville District, plans to deepen the St. Johns River channel in Jacksonville, Florida, from 40 to 47 feet along 13 miles of the river channel, beginning at the mouth of the river at the Atlantic Ocean, to accommodate larger, fully loaded cargo vessels. The U.S. Geological Survey, in cooperation with the U.S. Army Corps of Engineers, (1) installed continuous data collection stations to monitor discharge, salinity, and associated parameters at 23 sites prior to the commencement of dredging and (2) monitored stage and discharge at 13 sites and water temperature, specific conductance, and salinity at 16 sites; all parameters were monitored at some sites.
This is the second annual report by the U.S. Geological Survey on data collection for the Jacksonville Harbor deepening and contains information pertinent to the data collection sites during the 2017 water year, from October 2016 to September 2017. One data collection site on the St. Johns River below Shands Bridge was added to the network during this timeframe after the previously monitored location was damaged by Hurricane Matthew.
Discharge and salinity varied widely during the data collection period, reflecting the effects of Hurricane Matthew in October 2016 and Hurricane Irma in September 2017. The annual mean discharge at Trout River was greatest among the tributaries, followed by annual mean discharges at Durbin Creek, Ortega River, Julington Creek, Pottsburg Creek, Clapboard Creek, Cedar River, Broward River, and Dunn Creek. Among the tributary sites, annual mean salinity was highest at the site closest to the Atlantic Ocean, Clapboard Creek, and lowest at the site farthest from the ocean, Durbin Creek. Annual mean salinity data from the main-stem sites on the St. Johns River indicate that salinity decreased with distance upstream from the ocean, which is expected. Relative to salinity for the 2016 water year, annual mean salinity in the tributaries was higher for the 2017 water year at four monitoring locations, lower at four monitoring locations, and the same at one location. Of the three sites where salinity was calculated on the main stem in the 2016 water year, salinity was higher at one monitoring location in the 2017 water year and lower at two locations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191078","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Ryan, P.J., 2019, Continuous stream discharge, salinity, and associated data collected in the lower St. Johns River and its tributaries, Florida, 2017: U.S. Geological Survey Open-File Report 2019–1078, 35 p., https://doi.org/10.3133/ofr20191078.","productDescription":"viii, 35 p.","numberOfPages":"48","onlineOnly":"Y","ipdsId":"IP-106628","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":366770,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1078/ofr20191078.pdf","text":"Report","size":"11.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019–1078"},{"id":366769,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1078/coverthb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Lower St Johns River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.1502685546875,\n 29.156958511360703\n ],\n [\n -81.2109375,\n 29.156958511360703\n ],\n [\n -81.2109375,\n 30.500750980290693\n ],\n [\n -82.1502685546875,\n 30.500750980290693\n ],\n [\n -82.1502685546875,\n 29.156958511360703\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
The U.S. Geological Survey conducted a study using modern methods of molecular analysis aimed at attempting to identify the source(s) of fecal contamination that had been identified in previous studies conducted by the West Virginia Conservation Agency in the Elk Run watershed, Jefferson County, West Virginia. Water samples from multiple sites showing elevated fecal coliform counts were analyzed using molecular markers associated with general mammalian fecal contamination (AllBac), human Bacteroides (HF183), bovine Bacteroides (BoBac), and human polyomavirus (HPyV). Samples were also analyzed by quantitative polymerase chain reaction (qPCR) for human and bovine cytochrome b (mitochondrial DNA marker). A headwater site (Elk Branch at Shenandoah Junction) was found to be severely affected by both human and bovine contamination in May 2017. Although many of the molecular marker levels as well as Escherichia coli numbers had declined by a repeat sampling in June 2017, total coliform bacterial numbers remained high. Examination of the data indicated that this site had probably been affected by two separate contamination events, an influx of bovine contamination close to the time of the May sampling and a human contamination event that had occurred earlier. Samples from all sites contained bovine mitochondrial DNA, whereas only one revealed relatively high levels of human mitochondrial DNA. The Elk Run watershed appears to be widely affected by bovine influences with human influence episodically playing a role. Surface runoff caused by rain events exacerbates both.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191064","usgsCitation":"Schill, W.B., and Iwanowicz, D.D., 2019, Molecular identification of fecal contamination in the Elks Run watershed, Jefferson County, West Virginia, 2016–17: U.S. Geological Survey Open-File Report 2019–1064, 9 p., https://doi.org/10.3133/ofr20191064.","productDescription":"9 p.","onlineOnly":"Y","ipdsId":"IP-092227","costCenters":[{"id":365,"text":"Leetown Science Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":366675,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1064/ofr20191064.pdf","text":"Report","size":"6.53 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1064"},{"id":366674,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1064/coverthb.jpg"}],"country":"United States","state":"West Virginia","county":"Jefferson 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Eastern Ecological Science Center
U.S. Geological Survey
11649 Leetown Road
Kearneysville, WV 25430
Caged mussels used as biomonitors can provide insights about ambient contaminant assemblages and spatial patterns, sources of contaminants, and contaminant exposure risks for consumers of wild and farmed mussels. This study explored the potential role of ambient sediment in the uptake of polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), and potentially toxic inorganic elements by caged mussels and complements findings from a Puget Sound-wide stormwater-contaminant mussel-monitoring survey in Washington State. In summary, ambient sediment appeared to be related to mussel uptake of lead and possibly copper at all sites, PCBs at industrial sites, and PAHs at Liberty Bay, Eagle Harbor, and, to a lesser extent, Smith Cove. These findings indicate that resuspended bed sediment is one, but not the only, pathway that filter-feeding mussels are exposed to contaminants. Overall, PAHs, PCBs, arsenic, and potentially toxic metals were low in intertidal bed sediment at the nine sites measured in Puget Sound in February 2016 and signify a low risk of sediment-bound contaminant exposure to mussels at those locations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191087","usgsCitation":"Takesue, R.K., Campbell, P.L., and Conn, K.E., 2019, Polycyclic aromatic hydrocarbons, polychlorinated biphenyls, and metals in ambient sediment at mussel biomonitoring sites, Puget Sound, Washington: U.S. Geological Survey Open-File Report 2019–1087, 15 p., https://doi.org/10.3133/ofr20191087.","productDescription":"Report: vi, 15 p.","numberOfPages":"15","onlineOnly":"Y","ipdsId":"IP-102107","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":366767,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1087/ofr20191087.pdf","text":"Report","size":"10 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Open-File Report 2019-1087"},{"id":366766,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1087/coverthb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Puget Sound","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -125.3759765625,\n 47.03269459852135\n ],\n [\n -121.83837890625,\n 47.03269459852135\n ],\n [\n -121.83837890625,\n 48.98382212608503\n ],\n [\n -125.3759765625,\n 48.98382212608503\n ],\n [\n -125.3759765625,\n 47.03269459852135\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information
Pacific Coastal & Marine Science Center
U.S. Geological Survey
Pacific Science Center
2885 Mission St.
Santa Cruz, CA 95060
Data from a 4-year capture and transport program were used to assess translocation as a management strategy for two long-lived, federally endangered catostomids in the Upper Klamath Basin, Oregon. Lost River (Deltistes luxatus) and shortnose (Chasmistes brevirostris) suckers, two species endemic to the Klamath Basin, were translocated from Lake Ewauna to Upper Klamath Lake in each of 4 years (2014–2017) in an effort to augment existing spawning populations in Upper Klamath Lake. Lake Ewauna, downstream of Upper Klamath Lake and connected to it by the Link River, has small populations of Lost River and shortnose suckers. Upper Klamath Lake has the largest remaining population of Lost River suckers and one of the largest remaining populations of shortnose suckers. Adult suckers were captured in Lake Ewauna, tagged with passive integrated transponder (PIT) tags, and translocated to the Williamson River, a spawning tributary that flows into Upper Klamath Lake. We monitored initial success of translocation efforts with encounters from remote PIT tag antennas and physical recaptures.
A total of 659 suckers were translocated from Lake Ewauna to the Williamson River (40 in 2014, 384 in 2015, 172 in 2016, and 63 in 2017). All individuals that were translocated were assumed to be one of the endangered taxa, but recaptures indicated that some translocated suckers were misidentified and were instead Klamath largescale suckers (Catostomus snyderi), a non-listed species that is also endemic to the Upper Klamath Basin. Other recaptures of translocated individuals revealed conflicts in species identification between the two endangered taxa as well. Due to species identification conflicts, we analyzed translocated individuals by cohort (year of translocation) and sex only. Specifically, we documented encounters of translocated individuals at spawning locations and throughout the Upper Klamath Lake watershed, analyzed frequency of return to spawning sites, assessed fidelity to spawning sites, and monitored migration timing over three full years (2015, 2016, and 2017). Remote PIT tag antennas at 11 sites and 5 physical capture locations were part of a monitoring network to re-encounter translocated individuals. In contrast to other years of the study, high flows in the Williamson River in 2017 prevented the installation of a river-wide weir and upstream trap with associated PIT-tag antennas that routinely detect large numbers of tagged fish. As a result, re-encounter probabilities in 2017 were expected to be lower than 2015 and 2016.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191085","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Banet, N.V., and Hewitt, D.A., 2019, Monitoring of endangered Klamath Basin suckers translocated from Lake Ewauna to Upper Klamath Lake, Oregon, 2014−2017: U.S. Geological Survey Open-File Report 2019–1085, 40 p., https://doi.org/10.3133/ofr20191085.","productDescription":"v, 39 p.","onlineOnly":"Y","ipdsId":"IP-097743","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":366745,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1085/coverthb.jpg"},{"id":366746,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1085/ofr20191085.pdf","text":"Report","size":"2.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1085"}],"country":"United States","state":"Oregon","otherGeospatial":"Lake Ewauna, Upper Klamath Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.1240234375,\n 42.1613675328748\n ],\n [\n -121.74224853515625,\n 42.1613675328748\n ],\n [\n -121.74224853515625,\n 42.60970621339408\n ],\n [\n -122.1240234375,\n 42.60970621339408\n ],\n [\n -122.1240234375,\n 42.1613675328748\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016
Scenario planning is a useful tool for identifying key vulnerabilities of ecological systems to changing climates, informed by the potential outcomes for a set of divergent, plausible, and relevant climate scenarios. We evaluated potential vulnerabilities of grassland communities to changing climate in the Southern Great Plains (SGP) and the Landscape Conservation Design pilot area (LCD) for the U.S. Fish and Wildlife Service, Science Applications Program, Great Plains Landscape Conservation Cooperative. Four climate scenarios (warm-dry, warm-wet, hot-dry, and hot-wet) from atmospheric-ocean general circulation models were selected to represent a suite of plausible future climatic conditions. For each scenario, and for contemporary climatic conditions, we predicted the spatial patterns of relative productivity for indicator grass species using statistical models of relative above-ground net primary productivity (hereafter, productivity) based on temperature, precipitation, and soil texture (percent sand, silt, or clay).
Two indicator grass species were selected to represent each of four focal grassland communities: semi-desert grasslands, shortgrass prairie, mixed-grass prairie, and tallgrass prairie. Changes in spatial patterning of bioclimatic conditions conducive for each indicator species as predicted for each climate scenario relative to current land use were used to evaluate potential vulnerability and conservation opportunities for grassland communities. Specifically, the following questions were addressed for each focal grassland community: (1) Where is the productivity of each species predicted to increase, decrease, or remain stable relative to estimated contemporary productivity for the SGP and LCD pilot area, (2) where is the productivity of the two indicator species for each community predicted to increase, decrease, or remain stable, (3) which grassland communities are most vulnerable to changes in composition and vertical structure, (4) how do current land-use patterns contribute to potential vulnerabilities of grassland communities for the climate scenarios evaluated, and (5) how can managers use the vulnerabilities identified to evaluate conservation opportunities in the SGP and LCD?
Current land-use patterns, in combination with the potential effects of a changing climate, pose greater risks to mixed-grass and tallgrass prairies of the SGP compared to semi-desert grasslands and shortgrass prairie. For most climate scenarios evaluated, bioclimatic conditions conducive to the taller species were predicted to contract within some or all the current distribution of mixed-grass and tallgrass prairies within the SGP. An increase in precipitation, however, could potentially ameliorate the negative effects of increasing temperatures as evidenced by higher productivity for the hot-wet scenario compared to the other scenarios for the most vulnerable species. Compounding their greater vulnerability to increasing temperatures coupled with decreasing precipitation, the mixed-grass and tallgrass prairies have been greatly fragmented and converted, primarily by agriculture. In contrast, the climate scenarios evaluated are generally conducive to stable or increasing productivity of indicator species for semi-desert grasslands and shortgrass prairie. In addition, conversion and fragmentation of semi-desert grasslands and shortgrass prairie were relatively low. These results suggest that the synergistic effects of land use and changing climatic conditions could have the greatest effects on the composition and structure of mixed-grass and tallgrass prairies in the SGP. ScienceBase data release files that support this report are available at https://doi.org/10.5066/P9DGJHEP
(Manier and others, 2019).
Director, Fort Collins Science Center
U.S. Geological Survey
2150 Centre Ave., Building C
Fort Collins, CO 80526-8118
As part of a long-term cooperative program to monitor water quality within the Scituate Reservoir drainage area, the U.S. Geological Survey, in cooperation with the Providence Water Supply Board, collected streamflow and water-quality data at the Scituate Reservoir and tributaries. Streamflow and concentrations of chloride and sodium estimated from records of specific conductance were used to calculate loads of chloride and sodium during water year 2017 (October 1, 2016, through September 30, 2017) for tributaries to the Scituate Reservoir, Rhode Island. 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 by the Providence Water Supply Board at 36 sampling stations, which also include the 14 continuous-record streamgages maintained by the U.S. Geological Survey, during water year 2017 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 water year 2017.
The Ponaganset River, which is the largest tributary to the reservoir and was monitored by the U.S. Geological Survey, contributed a mean streamflow of 29 cubic feet per second to the reservoir during water year 2017. For the same period, annual mean streamflows measured (or estimated) for the other monitoring stations in this study ranged from about 0.44 to about 20 cubic feet per second. Together, tributaries equipped with instrumentation capable of continuously monitoring specific conductance transported about 3,100 metric tons of chloride and 1,900 metric tons of sodium to the Scituate Reservoir during water year 2017; chloride yields for the tributaries ranged from 16 to 140 metric tons per square mile, and sodium yields, from 10 to 80 metric tons per square mile.
At the stations where water-quality samples were collected by the Providence Water Supply Board, the medians of the median concentrations were 25.3 milligrams per liter for chloride, 0.002 milligram per liter as nitrogen for nitrite, 0.10 milligram per liter as nitrogen for nitrate, 0.05 milligram per liter as phosphate for orthophosphate, 1,200 colony forming units per 100 milliliters for total coliform bacteria, and 14 colony forming units per 100 milliliters for Escherichia coli (E. coli). The medians of the median daily loads of chloride, nitrite, nitrate, orthophosphate, total coliform, and E. coli bacteria were 230 kilograms per day, 17 grams per day, 860 grams per day, 690 grams per day, 84,000 million colony forming units per day, and 1,200 million colony forming units per day, respectively. The medians of the median yields of chloride, nitrite, nitrate, orthophosphate, total coliform, and E. coli bacteria were were 87 kilograms per day per square mile, 6.1 grams per day per square mile, 280 grams per day per square mile, 260 grams per day per square mile, 44,000 million colony forming units per day per square mile, and 655 million colony forming units per day per square mile, respectively.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191039","collaboration":"Prepared in cooperation with the Providence Water Supply Board, Rhode Island","usgsCitation":"Smith, K.P., 2019, Streamflow, water quality, and constituent loads and yields, Scituate Reservoir drainage area, Rhode Island, water year 2017: U.S. Geological Survey Open-File Report 2019–1039, 33 p., https://doi.org/10.3133/ofr20191039.","productDescription":"Report: v, 33 p.; Data Release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-102155","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"links":[{"id":365646,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9PPAKP6","text":"USGS data release","description":"USGS data release","linkHelpText":"Water-quality data from the Providence Water Supply Board for tributary streams to the Scituate Reservoir, water year 2017"},{"id":365582,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1039/coverthb.jpg"},{"id":365583,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1039/ofr20191039.pdf","text":"Report","size":"1.40 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1039"}],"country":"United States","state":"Rhode Island","otherGeospatial":"Scituate Reservoir Drainage Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -71.78878784179688,\n 41.72110557838152\n ],\n [\n -71.53610229492188,\n 41.72110557838152\n ],\n [\n -71.53610229492188,\n 41.97174336327968\n ],\n [\n -71.78878784179688,\n 41.97174336327968\n ],\n [\n -71.78878784179688,\n 41.72110557838152\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
331 Commerce Way, Suite 2
Pembroke, NH 03275
The U.S. Geological Survey assessed the effective solubilities of organic analytes at the BKK Class Ⅰ Landfill site, West Covina, California, in cooperation with the California Department of Toxic Substances Control, using available data for liquid samples collected within (in-waste) and below (sub-waste) the landfill in 2014–16. The primary purpose of the effective solubility calculations was to determine the likely presence or absence of dense non-aqueous phase liquids (DNAPLs), which is important for understanding the sources, persistence, and movement of the leachate contaminants. Percent effective solubility (a measure of the degree of deviation of a measured liquid concentration of a compound from the aqueous effective solubility) greater than 1 percent is the threshold that commonly has been used to infer the presence of DNAPLs or mixed DNAPLs in aqueous monitoring results. In the present study, however, thresholds higher than 1 percent were used because of elevated temperatures and concentrations of cosolvents in the liquid samples—thresholds of 10 percent or 100 percent, respectively, were used for liquid and solid (at 25 degrees Celsius) organic compounds for potential non-aqueous phase liquid presence.
Overall, the effective solubility calculations indicate the likely presence of DNAPLs or mixed DNAPLs in some samples for a range of compounds, including tetrachloroethene, trichloroethene, 1,1-dichloroethene, vinyl chloride, 1,2,4-trichlorobenzene, 1,4-dichlorobenzene, 1,2-dichlorobenzene, naphthalene, toluene, ethylbenzene, and xylenes. Samples with the highest calculated percent effective solubilities for chlorinated ethenes, ethanes, and benzenes were from a location where liquid in the waste prism is known to be in contact with the groundwater beneath the landfill. Trends in the effective solubilities for the chlorinated ethenes and ethanes were generally consistent between the in-waste and sub-waste samples, supporting a similar source composition for these liquids. Percent effective solubilities were less than 10 for the chlorinated ethanes in all the in-waste and sub-waste samples, indicating that DNAPL of these compounds is not present. Percent effective solubilities of chlorinated benzenes, ethylbenzene, and xylenes exceeded the 10-percent effective solubility threshold in more of the sub-waste samples than the in-waste liquid samples. Volatilization also may influence the patterns in the calculated effective solubilities but were not included in this study.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191080","collaboration":"Prepared in cooperation with the California Department of Toxic Substances Control","usgsCitation":"Lorah, M.M., Majcher, E.H., and Morel, C.J., 2019, Effective solubility assessment for organic analytes in liquid samples, BKK Class Ⅰ Landfill, West Covina, California, 2014–16: U.S. Geological Survey Open-File Report 2019–1080, 18 p., https://doi.org/10.3133/ofr20191080.","productDescription":"Report: v, 18p.; Tables","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-105175","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"links":[{"id":366110,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1080/ofr20191080.pdf","text":"Report","size":"8.58 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1080"},{"id":366109,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1080/coverthb.jpg"},{"id":366188,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2019/1080/ofr20191080_table1.xlsx","text":"Tables SI-1 through SI-11","size":"1.25 MB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"- Supplemental Information Worksheet - Mole Fraction and Effective Solubility Calculations"}],"country":"United States","state":"California","city":"West Covinia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.99917221069335,\n 34.064463311552615\n ],\n [\n -118.01462173461914,\n 34.04000041165585\n ],\n [\n -117.95145034790039,\n 34.03729768165777\n ],\n [\n -117.91471481323242,\n 34.03800893474363\n ],\n [\n -117.90956497192383,\n 34.04782361826847\n ],\n [\n -117.90939331054688,\n 34.0715732952909\n ],\n [\n -117.94235229492188,\n 34.07143110146331\n ],\n [\n -117.99917221069335,\n 34.064463311552615\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, MD-DE-DC Water Science Center
U.S. Geological Survey
5522 Research Park Drive
Baltimore, MD 21228
Director,
Utah Water Science Center
U.S. Geological Survey
2329 West Orton Circle
Salt Lake City, Utah 84119-2047
801-908-5000
The South Atlantic Water Science Center Strategic Science Planning Team has developed a unified strategic science plan to guide the science vision of the South Atlantic Water Science Center (SAWSC) in response to the merging of the Georgia, North Carolina, and South Carolina Water Science Centers. This plan proposes a path forward to keep SAWSC science activities relevant to the many diverse needs of stakeholders in the South Atlantic region (Georgia, North Carolina, and South Carolina) and considers the hydrologic setting and issues of the region. This plan advises the creation of five working groups to address five priority science topics for the period 2019–23 and beyond. The five priority science topics are (1) Foundational Data, (2) Effects of Land-Use Change, (3) Coastal Plain Science, (4) Water Availability, and (5) Hazards. From the goals laid forth in this plan for each priority science topic, the working groups plan to devise a set of strategic actions and milestones to be achieved by the SAWSC to provide valuable and relevant data, research, and assessments in the South Atlantic region. In this report, the “South Atlantic region” is used to describe the area encompassed by the States of North Carolina, South Carolina, and Georgia.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191068","usgsCitation":"Cuffney, T.F., Garcia, A.M., Horowitz, A.J., LaFontaine, J.H., Landmeyer, J.E., McKee, A.M., McSwain, K.B., Painter, J.A., Shelton, J.M., and Smith, C.A., 2019, South Atlantic Water Science Center strategic science plan—2019–23: U.S. Geological Survey Open-File Report 2019–1068, 31 p., https://doi.org/10.3133/ofr20191068.","productDescription":"v, 31 p.","onlineOnly":"Y","ipdsId":"IP-090584","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":365956,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1068/ofr20191068.pdf","text":"Report","size":"6.11 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1068"},{"id":365955,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1068/coverthb.jpg"}],"contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Stephenson Center, Suite 129
Columbia, SC 29210