Loss and degradation of sagebrush rangelands due to an accelerated invasive annual grass-wildfire cycle and other stressors are significant management, conservation, and economic issues in the western United States. These sagebrush rangelands comprise a unique biome spanning 11 states, support over 350 wildlife species, and provide important ecosystem services that include stabilizing the economies of western communities. Impacts to sagebrush ecosystem processes over large areas due to the annual grass-wildfire cycle necessitated the development of a coordinated, science-based strategy for improving efforts to achieve long-term protection, conservation, and restoration of sagebrush rangelands, which was framed in 2015 under the Integrated Rangeland Fire Management Strategy (IRFMS). Central to this effort was the development of an Actionable Science Plan (Plan) that identified 37 priority science needs (Needs) for informing the actions proposed under the 5 topics (Fire, Invasives, Restoration, Sagebrush and Sage-Grouse, Climate and Weather) that were part of the collective focus of the IRFMS. Notable keys to this effort were identification of the Needs co-produced by managers and researchers, and a focus on resulting science being “actionable.”
Substantial investments aimed at fulfilling the Needs identified in the Plan have been made since its release in 2016. While the state of the science has advanced considerably, the extent to which knowledge gaps remain relative to identified Needs is relatively unknown. Moreover, new Needs have likely emerged since the original strategy as results from actionable science reveal new questions and possible (yet untested) solutions. A quantifiable assessment of the progress made on the original science Needs can identify unresolved gaps and new information that can help inform prioritization of future research efforts.
This report details a systematic literature review that evaluated how well peer-reviewed journal articles and formal technical reports published between January 1, 2015, and December 31, 2020, addressed six needs (hereinafter “Needs”) identified under the Invasives topic in the Plan. The topic outlined research Needs related to the control of invasive plant species in sagebrush rangelands, with a special emphasis on invasive annual grasses. We established the level of progress towards addressing each Need following a standardized set of criteria, and developed summaries detailing how research objectives nested within Needs identified in the Plan (“Next Steps”) were either addressed well, partially addressed, or remain outstanding (that is, addressed poorly) in the literature through 2020. Our searches resulted in the inclusion of 198 science products that at least partially addressed a Need identified in the Invasives topic. The Needs that were well and partially addressed included:
Needs that were addressed poorly included (1) investigations of livestock grazing as a tool for managing invasive plants and (2) investigations of cheatgrass die-offs and identification and subsequent study of potential biocontrol agents associated with those die-offs. The information provided in this assessment will assist updating the Plan along with other science strategies.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231003","collaboration":"Prepared in cooperation with the Bureau of Land Management and the U.S. Fish and Wildlife Service","usgsCitation":"Anthony, C.R., Holloran, M.J., Ricca, M.A., Hanser, S.E., Phillips, S.L., Steblein, P.F., and Wiechman, L.A., 2023, Integrated rangeland fire management strategy actionable science plan completion assessment—Invasives topic, 2015–20: U.S. Geological Survey Open-File Report 2023–1003, 33 p., https://doi.org/10.3133/ofr20231003.","productDescription":"vii, 33 p.","onlineOnly":"Y","ipdsId":"IP-141649","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true},{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true},{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":413020,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20231009","text":"OFR 2023-1009 —","description":"Related work","linkHelpText":"Integrated rangeland fire management strategy actionable science plan completion assessment—Fire topic, 2015–20"},{"id":412640,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1003/ofr20231003.pdf"},{"id":412639,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1003/images"},{"id":412636,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1003/coverthb.jpg"},{"id":418550,"rank":8,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20231035","text":"OFR 2023-1035 —","description":"Related work","linkHelpText":"Integrated rangeland fire management strategy actionable science plan completion assessment— Climate and weather topic, 2015–20"},{"id":499730,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114343.htm","linkFileType":{"id":5,"text":"html"}},{"id":413021,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20231010","text":"OFR 2023-1010 —","description":"Related work","linkHelpText":"Integrated rangeland fire management strategy actionable science plan completion assessment—Sagebrush and sage-grouse topic, 2015–20"},{"id":412825,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20231004","text":"OFR 2023-1004 —","description":"Related work","linkHelpText":"Integrated rangeland fire management strategy actionable science plan completion assessment—Restoration topic, 2015–20"},{"id":412637,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1003/ofr20231003.pdf","text":"Report","size":"5.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1003"}],"country":"United States","otherGeospatial":"western United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -102.82114253002419,\n 48.983205061126796\n ],\n [\n -122.41445472125756,\n 48.983205061126796\n ],\n [\n -122.41445472125756,\n 34.5\n ],\n [\n -102.82114253002419,\n 34.5\n ],\n [\n -102.82114253002419,\n 48.983205061126796\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Forest and Rangeland Ecosystem Science Center
777 NW 9th Street, Suite 400
Corvallis, OR 97330
Remotely sensed surface temperature (ST) has been widely used to monitor and assess landscape thermal conditions, hydrologic modeling, and surface energy balance. Landsat thermal sensors have continuously measured the Earth surface thermal radiance since August 1982. The thermal radiance measurements are atmospherically compensated and converted to Landsat STs and delivered as part of the U.S. Geological Survey Landsat Collection 1 U.S. Analysis Ready Data; however, the low satellite revisit cycles combined with the presence of clouds and cloud shadows reduce the number of valid retrievals. This reduction can limit the ability to monitor annual or seasonal variations in the surface thermal budget. These factors reduce the ability to use the temperature data to fit time series for historical trend analysis to match background climate variations. In this study, we implemented an approach that uses linear harmonic least absolute shrinkage and selection operator regression models to fill gaps because of clouds, shadows, and coarse temporal resolution. The gap-filled data provide increased temporal density of Landsat ST records. The gap-filled Landsat ST, therefore, can allow for an improved monitoring of annual, seasonal, or even monthly landscape thermal conditions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231006","usgsCitation":"Xian, G., Shi, H., Arab, S., Mueller, C., Hussain, R., Sayler, K., and Howard, D., 2023, Improving temporal frequency of Landsat surface temperature products using the gap-filling algorithm: U.S. Geological Survey Open-File Report 2023–1006, 15 p., https://doi.org/10.3133/ofr20231006.","productDescription":"vi, 15 p.","numberOfPages":"26","onlineOnly":"Y","ipdsId":"IP-144337","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":412873,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1006/images"},{"id":412872,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1006/ofr20231006.XML","text":"Report","linkFileType":{"id":8,"text":"xml"}},{"id":412871,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1006/ofr20231006.pdf","text":"Report","size":"41.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023–1006"},{"id":412880,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/ofr20231006/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":412870,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1006/coverthb.jpg"},{"id":499732,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114340.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Georgia","city":"Atlanta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -84.9318883744094,\n 34.338976979151155\n ],\n [\n -84.9318883744094,\n 33.376859208686255\n ],\n [\n -83.70224614831253,\n 33.376859208686255\n ],\n [\n -83.70224614831253,\n 34.338976979151155\n ],\n [\n -84.9318883744094,\n 34.338976979151155\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Earth Resources Observation and Science Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
Water samples were collected from July through December 2016 from 9 production wells and 13 domestic wells in the Mohawk River Basin, and from 17 production wells and 17 domestic wells in the western New York River Basins. The samples were collected and processed by using standard U.S. Geological Survey methods and were analyzed for 320 physicochemical properties and constituents, including dissolved gases, major ions, nutrients, trace elements, pesticides, volatile organic compounds, radionuclides, and indicator bacteria, to characterize groundwater quality in the basins. Analytical results are provided in the companion U.S. Geological Survey data release titled “Groundwater Quality Data From the Mohawk and Western New York River Basins, New York, 2016.”
The Mohawk River Basin study area covers 3,500 square miles in New York. Of the 22 wells sampled in the Mohawk River Basin, 8 are completed in sand and gravel, and 14 are completed in bedrock aquifers. Most constituents in the samples from the Mohawk River Basin were present in concentrations below the maximum contaminant levels used in public supply drinking-water regulations by the New York State Department of Health and the U.S. Environmental Protection Agency. Values for some of the properties and concentrations of some constituents—pH, color, iron, manganese, aluminum, sodium, chloride, dissolved solids, radon-222, and heterotrophic plate count—sometimes equaled or exceeded primary, secondary, or proposed drinking-water standards.
The western New York River Basins study area covers 5,340 square miles in western New York and includes parts of the Lake Erie and Niagara River Basins, the western Lake Ontario Basin (between the Niagara River and Genesee River Basins), and the Allegheny River Basin. Of the 34 wells sampled in the western New York River Basins, 16 are completed in sand and gravel, and 18 are completed in bedrock aquifers. Most constituents in the samples from the western New York River Basins were present in concentrations below the maximum contaminant levels used in public supply drinking-water regulations by the New York State Department of Health and the U.S. Environmental Protection Agency. Values for some of the properties and concentrations of some constituents—color, chloride, sodium, dissolved solids, iron, manganese, aluminum, arsenic, barium, radon-222, methane, total coliform bacteria, fecal coliform bacteria, and Escherichia coli bacteria—sometimes equaled or exceeded primary, secondary, or proposed drinking-water standards.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221021","collaboration":"Prepared in cooperation with the New York State Department of Environmental Conservation","usgsCitation":"Gaige, D.L., Scott, T.-M., Reddy, J.E., and Keefe, M.R., 2023, Groundwater quality in the Mohawk and western New York River Basins, New York, 2016: U.S. Geological Survey Open-File Report 2022–1021, 38 p., https://doi.org/10.3133/ofr20221021.","productDescription":"Report: viii, 38 p.; Data Release","numberOfPages":"38","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-115618","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":412503,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YNH96T","text":"USGS data release","linkHelpText":"Groundwater quality data from the Mohawk and western New York River Basins, New York, 2016"},{"id":412502,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1021/images/"},{"id":412500,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/ofr20221021/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1021"},{"id":412499,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1021/ofr20221021.pdf","text":"Report","size":"19.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1021"},{"id":412498,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1021/coverthb.jpg"},{"id":412501,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1021/ofr20221021.XML"},{"id":499717,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114305.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"New York","otherGeospatial":"Mohawk and New York River basins","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -75.84977657608984,\n 43.556764188166994\n ],\n [\n -75.84977657608984,\n 41.81434325258104\n ],\n [\n -73.94567088326258,\n 41.81434325258104\n ],\n [\n -73.94567088326258,\n 43.556764188166994\n ],\n [\n -75.84977657608984,\n 43.556764188166994\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180–8349
The U.S. Army Corps of Engineers, Jacksonville District, is deepening the St. Johns River channel in Jacksonville, Florida, by 7 feet along 13 miles of the river channel beginning at the mouth of the river at the Atlantic Ocean, in order to accommodate larger, fully loaded cargo vessels. The U.S. Geological Survey, in cooperation with the U.S. Army Corps of Engineers, monitored stage, discharge, and (or) water temperature and salinity at 26 continuous data collection stations in the St. Johns River and its tributaries.
This is the sixth annual report by the U.S. Geological Survey on data collection for the Jacksonville Harbor deepening project. Prior reports in this series documented data collected from October 2015 to September 2020. This report contains information pertinent to data collection during the 2021 water year, from October 2020 to September 2021. There were no modifications this year to the previously installed monitoring network. Data at each station were compared for the length of the project and on a yearly basis to show the annual variability of discharge and salinity in the project area.
Discharge and salinity varied widely during the 2021 water year data collection period, which included above-average rainfall for four of the five counties in the study area. Total annual rainfall for all counties ranked third among the annual totals computed for the 6 years considered for this study. Annual mean discharge at Durbin Creek was highest among the tributaries, followed by Trout River, Clapboard Creek, Ortega River, Pottsburg Creek at U.S. 90, Julington Creek, Pottsburg Creek near South Jacksonville, Dunn Creek, Cedar River, and Broward River, whose annual mean discharge was lowest. Annual mean discharge at 7 of the 10 tributary monitoring sites was higher for the 2021 water year than for the 2020 water year, and the computed annual mean flow at Clapboard Creek was the highest over the 6 years considered for this study. The annual mean discharge for each of the main-stem sites was higher for the 2021 water year than for the 2020 water year and ranked second among the annual totals computed for the 6 years considered for this study.
Among the tributary sites, annual mean salinity was highest at Clapboard Creek, the site closest to the Atlantic Ocean, and was lowest at Durbin Creek, the site farthest from the ocean. 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 was expected. Relative to annual mean salinity calculated for the 2020 water year, annual mean salinity at all monitoring locations was lower for the 2021 water year except at the tributary site of Durbin Creek, which remained the same. The 2021 annual mean salinity at all sites ranked second lowest since the beginning of the study in 2016 except at Julington Creek and Racy Point, which tied for lowest, and Durbin Creek, which had the same value for each year.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221111","issn":"ISSN 2331-1258","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Ryan, P.J., 2023, Continuous stream discharge, salinity, and associated data collected in the lower St. Johns River and its tributaries, Florida, 2021: U.S. Geological Survey Open-File Report 2022–1111, 48 p., https://doi.org/10.3133/ofr20221111.","productDescription":"Report: x, 48 p.; Dataset","numberOfPages":"62","onlineOnly":"Y","ipdsId":"IP-139675","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":413532,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221111/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":412288,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1111/ofr20221111.XML","linkFileType":{"id":8,"text":"xml"}},{"id":412285,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1111/coverthb.jpg"},{"id":412286,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1111/ofr20221111.pdf","text":"Report","size":"16.3 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":412287,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1111/images"},{"id":412289,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS water data for the Nation—U.S. Geological Survey National Water Information System database"}],"country":"United States","state":"Florida","otherGeospatial":"St. Johns River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -82.31115628870195,\n 30.583300030597925\n ],\n [\n -82.31115628870195,\n 29.490035998849976\n ],\n [\n -81.03179238276725,\n 29.490035998849976\n ],\n [\n -81.03179238276725,\n 30.583300030597925\n ],\n [\n -82.31115628870195,\n 30.583300030597925\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
We conducted a field study during 2020–21 to describe habitat use patterns of juvenile Chinook salmon (Oncorhynchus tshawytscha) in the mainstem Willamette, McKenzie, and Santiam Rivers and to evaluate how habitat suitability criteria affected the predictive accuracy of a hydraulic habitat model. Two approaches were used to collect habitat use data: a stratified sampling design was used to ensure that a representative sample of available habitats was included in our sampling; and a targeted sampling design was used to collect additional data in habitat cells where juvenile Chinook salmon were observed. Habitat attributes and fish presence data were collected in habitat cells that were approximately 2 square meters during April, June, and July. A total of 632 cells were sampled during the study and included habitat located in the main channel (373 cells), side channels (228 cells), and in alcoves (31 cells). Juvenile Chinook salmon were observed in 42 percent of the cells located in the main channel, 38 percent of the cells located in side channels, and 7 percent of the cells located in alcoves. We used logistic regression to develop resource selection functions for April, June, and July, which produced probability-based predictions of habitat use for juvenile Chinook salmon based on water velocity and water depth. The resource selection functions revealed a habitat shift by juvenile Chinook salmon to locations with higher water velocities and greater water depths from April to July as juvenile Chinook salmon size increased. The resource selection functions that we developed are an important addition to habitat modeling in the Willamette River basin because they were developed from in-basin data, capture seasonal differences in habitat use, and facilitate probability-based estimates of habitat use for juvenile Chinook salmon. These advancements will improve habitat modeling efforts for juvenile Chinook salmon during spring and summer months within the Willamette River.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231001","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Hansen, G.S., Perry, R.W., Kock, T.J., White, J.S., Haner, P.V., Plumb, J.M., and Wallick, J.R., 2023, Assessment of habitat use by juvenile Chinook salmon (Oncorhynchus tshawytscha) in the Willamette River Basin, 2020–21: U.S. Geological Survey Open-File Report 2023–1001, 20 p., https://doi.org/10.3133/ofr20231001.","productDescription":"vii, 20 p.","onlineOnly":"Y","ipdsId":"IP-141847","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true},{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":412251,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1001/coverthb.jpg"},{"id":412252,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1001/ofr20231001.pdf","text":"Report","size":"5.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1001"},{"id":412254,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1001/images"},{"id":412255,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1001/ofr20231001.XML"}],"country":"United States","state":"Oregon","otherGeospatial":"Willamette River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -124.70681047535611,\n 46.26773381073258\n ],\n [\n -124.70681047535611,\n 42.583539358952294\n ],\n [\n -121.08286121390995,\n 42.583539358952294\n ],\n [\n -121.08286121390995,\n 46.26773381073258\n ],\n [\n -124.70681047535611,\n 46.26773381073258\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016
A three-dimensional numerical model of groundwater flow was developed and calibrated for the unconsolidated New Jersey Coastal Plain aquifers underlying Joint Base McGuire-Dix-Lakehurst (JBMDL) and vicinity, New Jersey, to evaluate groundwater flow pathways of per- and polyfluoroalkyl substances (PFAS) contamination associated with use of aqueous film forming foam (AFFF) at the base. The regional subsurface flow model spans an area of approximately 518 square miles around JBMDL and is based on a previously developed hydrogeologic framework of the area. Steady-state flow in the unconsolidated aquifers was simulated using the MODFLOW 6 groundwater flow model, which is able to account for hydrostratigraphic pinchouts and discontinuities in the Coastal Plain aquifers underlying JBMDL. To account for local patterns of fluid flow driving advective subsurface migration of PFAS, the grid was refined using quadtree meshes spanning 21 areas where historical AFFF use was identified, five off-site reconnaissance areas identified by AFCEC as areas in which the occurrence of PFAS is most likely to pose a potential danger to local drinking water supplies, and along streams that behave as drains in the base-flow-dominated Coastal Plain.
Following grid refinement, four physical processes known to govern subsurface flow were introduced to the model. These included effective precipitation recharge, discharge to streams and stream-connected wetlands, regional inflows and outflows along the model bottom, and withdrawals from wells, each of which were incorporated into the model as either external or internal boundary conditions. To account for effective precipitation recharge, a specified-flow boundary was assigned along the top of the model. Similarly, regional flows predicted using the modified U.S Geological Survey’s New Jersey Coastal Plain Regional Aquifer System Analysis model were treated as specified-flow boundary conditions along the bottom of the model. Base-flow losses were treated as drains along streams delineated using a 10-foot LiDAR dataset. Drains were also assigned to cells falling within stream-connected National Hydrologic Database wetlands. Finally, well-pumpage data mined from the New Jersey Water Transfer database were added to the model to account for extraction of groundwater through pumping from industrial-supply and drinking-water-supply wells. Along model edges established at groundwater divides, where the net flux of water across the boundary is equal to zero, natural no-flow boundary conditions were imposed.
The refined flow model was calibrated using the parameter-estimation (PEST) program, which adjusts model parameters by performing a gradient search over the sum-of-squared-error objective function until the parameter set that produces simulated water levels and base flows most closely matches 544 water levels and 20 estimated base flows and closely adheres to initial parameter estimates. Based on the analysis of calibration residuals, the model did not appear to be affected by significant model structural error.
The MODPATH particle-tracking algorithm was used to estimate advective transport paths of PFAS in the vicinity of JBMDL. Forward tracking was used to determine paths of PFAS away from AFFF source areas to streams, wetlands, pumping wells, and geographic areas that PFAS may contaminate. Additionally, reverse tracking was used to determine particle pathlines away from off-site PFAS reconnaissance areas, or areas within which all sources of PFAS might be advectively transported into subsurface drinking-water supplies, to locations at land surface that may indicate a source of PFAS.
The coupled and calibrated groundwater flow and particle-tracking transport model provide valuable tools for predicting the relative extent of PFAS contamination from onsite legacy source areas. The calibrated model also provides measures of water-level and base-flow observation influence that can help guide future data-collection efforts related to groundwater and surface water sampling for PFAS.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221112","collaboration":"Prepared in cooperation with the U.S. Air Force","usgsCitation":"Fiore, A.R., and Colarullo, S.J., 2023, Simulation of regional groundwater flow and advective transport of per- and polyfluoroalkyl substances, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey, 2018: U.S. Geological Survey Open-File Report 2022–1112, 41 p., 2 pls., https://doi.org/10.3133/ofr20221112.","productDescription":"Report: ix, 41 p.; 2 Plates: 35.00 x 45.00 inches and 45.00 x 30.00 inches; Data Release","numberOfPages":"41","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-129806","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":412124,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9EK4CZS","text":"USGS data release","linkHelpText":"MODFLOW6 and MODPATH7 used to simulate regional groundwater flow and advective transport of per- and polyfluoroalkyl substances, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey, 2018"},{"id":412125,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1112/ofr20221112.XML"},{"id":412123,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/ofr20221112/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1112"},{"id":412121,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1112/coverthb.jpg"},{"id":412126,"rank":6,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1112/images/"},{"id":412129,"rank":7,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2022/1112/ofr20221112_plate1.pdf","text":"Plate 1","size":"212 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Forward particle tracks from aqueous film-forming foam source areas 1 to 15 and reverse particle tracks from per- and polyfluoroalkyl substances reconnaissance areas 4 and 14, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey, 2018"},{"id":412122,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1112/ofr20221112.pdf","text":"Report","size":"7.96 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1112"},{"id":412130,"rank":8,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2022/1112/ofr20221112_plate2.pdf","text":"Plate 2","size":"200 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Forward particle tracks from aqueous film-forming foam source areas 16 to 21 and reverse particle tracks from per- and polyfluoroalkyl substances reconnaissance areas 16 to 19, Joint Base McGuire-Dix-Lakehurst and vicinity, New Jersey, 2018"},{"id":499723,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114286.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"New Jersey","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -74.77016941849112,\n 40.156458843115274\n ],\n [\n -74.77016941849112,\n 39.93505011875061\n ],\n [\n -74.17559168378837,\n 39.93505011875061\n ],\n [\n -74.17559168378837,\n 40.156458843115274\n ],\n [\n -74.77016941849112,\n 40.156458843115274\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, New Jersey Water Science Center
U.S. Geological Survey
3450 Princeton Pike, Suite 110
Lawrenceville, NJ 08648
In 2021, the U.S. Geological Survey will collect water-quality samples and environmental data from 3 sites in Koocanusa Reservoir and from 1 site in the Kootenai River. The transboundary Koocanusa Reservoir is in southeastern British Columbia, Canada, and northwestern Montana, United States, and was formed with the construction of Libby Dam on the Kootenai River 26 kilometers upstream from Libby, Montana. Two of the reservoir sites and the Kootenai River site, in the Libby Dam tailwater (the outflow of the reservoir flow into the Kootenai River), are equipped with automated, high-frequency ServoSipper water samplers. At the two reservoir sites, these samplers are mounted to pontoon platforms and automatically collect samples from multiple depths; a ServoSipper sampler was deployed at one site in 2019, and another ServoSipper sampler will be deployed at a second site in 2021. Discrete water-quality samples will be collected monthly at two depths at the river site and at two of the reservoir sites. The goal of this project is to collect multidepth, high-frequency vertical and temporal water-quality samples and data to understand the limnological and biological processes that control variations and trends in selenium concentrations and loads throughout Koocanusa Reservoir and in the Libby Dam tailwater at the southern end of the reservoir. This sampling and analysis plan documents the organization, sampling and data-collection scheme and design, pre- and post-collection processes, and quality-assurance and quality-control procedures.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221113","usgsCitation":"Caldwell Eldridge, S.L., Schaar, M.A., Reese, C.B., Bussell, A.M., and Chapin, T., 2023, Sampling and analysis plan for the Koocanusa Reservoir and upper Kootenai River, Montana, water-quality monitoring program, 2021: U.S. Geological Survey Open-File Report 2022–1113, 32 p., https://doi.org/10.3133/ofr20221113.","productDescription":"ix, 32 p.","numberOfPages":"46","onlineOnly":"Y","ipdsId":"IP-137190","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true},{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true}],"links":[{"id":412312,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1113/ofr20221113.XML"},{"id":412310,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1113/coverthb.jpg"},{"id":412311,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1113/ofr20221113.pdf","text":"Report","size":"1.39 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022–1113"},{"id":412313,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1113/images"},{"id":412323,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221113/full","text":"Report","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Montana","otherGeospatial":"Koocanusa Reservoir, Upper Kootenai River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.10472590374278,\n 49.02558777092872\n ],\n [\n -116.10472590374278,\n 47.62376452411149\n ],\n [\n -113.60090641401644,\n 47.62376452411149\n ],\n [\n -113.60090641401644,\n 49.02558777092872\n ],\n [\n -116.10472590374278,\n 49.02558777092872\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Wyoming-Montana Water Science Center
U.S. Geological Survey
3162 Bozeman Avenue
Helena, MT 59601
Groundwater is the primary source of drinking water in the Coachella Valley in the desert region of southern California. Although most people in Coachella Valley are served by public drinking-water systems, about 20,000 people rely on private domestic or small-system wells (referred to herein as domestic wells). Recently, the U.S. Geological Survey (USGS) found that 39 percent of the groundwater resources used by domestic wells in Coachella Valley contained arsenic, fluoride, or both constituents at concentrations greater than the maximum contaminant levels established for public drinking-water systems. Uranium, chromium, nitrate, and perchlorate were detected at moderate concentrations below maximum contaminant levels. Elevated (above background) perchlorate concentrations in some areas indicate that domestic wells may receive recharge from Colorado River water used for irrigation or aquifer replenishment. Moderate total dissolved solids (TDS) concentrations throughout the study area and the co-occurrence of high concentrations of TDS and perchlorate indicates that Colorado River water is a source of recharge in the southeastern Indio groundwater subbasin. Four volatile organic compounds were detected at low concentrations, and pesticides and per- and polyfluoroalkyl substances were not detected.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221122","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Soldavini, A.L., Harkness, J.S., Levy, Z.F., and Fram, M.S., 2023, Quality of groundwater used for domestic drinking-water supply in the Coachella Valley, 2020: U.S. Geological Survey Open-File Report 2022-1122, 6 p., https://doi.org/10.3133/ofr20221122.","productDescription":"Report: 6 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-127493","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":411823,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9UYXI95","text":"USGS data release","description":"USGS data release","linkHelpText":"Groundwater-quality data in the Coachella Valley Domestic Supply Aquifer Study Unit, 2020: Results from the California GAMA Priority Basin Project (ver. 2.0, May 2022)"},{"id":411820,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1122/coverthb.jpg"},{"id":411821,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1122/ofr20221122.pdf","text":"Report","size":"6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1122"},{"id":411824,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1122/images"},{"id":411825,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1122/ofr20221122.XML"},{"id":411822,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221122/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1122"},{"id":499728,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114228.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United 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U.S. Geological Survey
California Water Science Center
6000 J Street, Placer Hall
Sacramento, CA 95819
Telephone number: (916) 278-3000
Unit Chief State Water Resources Control Board Division of Water Quality
P.O. Box 2231, Sacramento, CA 95812
Telephone number: (916) 341-5779
Plecoptera (stoneflies) are an order of insects where most species rely on clean, fast-moving freshwater for an aquatic larval stage followed by a short terrestrial adult stage. Most species of Plecoptera seem to be restricted to specific stream types and thermal regimes. Climate-driven changes are likely to alter stream temperatures and flow, resulting in physiological stress, reduced reproductive success, and possibly latitudinal or elevational distribution shifts. This report focuses on climate projections and the resulting ecological effect for three species of Appalachian stoneflies: Remenus kirchneri, Acroneuria kosztarabi, and Tallaperla lobata. Although species-specific information is sparse for these three species, climate studies for other Plecoptera spp. are applicable. In the focal region, temperature is increasing and likely leading to increased stream temperatures. In response, Plecoptera spp. will likely experience physiological stress from increasing metabolic rates and energy demands concurrent with changing food quality and access. Warming temperatures and decreased larval energy stores are likely to contribute to lower adult body size and longevity, thus decreasing reproductive success. Whereas projected changes to precipitation and runoff are less certain, under drier future climate projections, decreased streamflow may further stress larval Plecoptera. Remenus kirchneri, A. kosztarabi, and T. lobata will likely retain stable permanent stream habitats for the analyzed future (2006–99). Changing climate is of particular concern for mountaintop species R. kirchneri and T. lobata because they may be unable to track shifts in suitable climate and habitat.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Effects of climate change on fish and wildlife species in the United States","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211104B","usgsCitation":"Lyons, M.P., Nikiel, C.A., LeDee, O.E., and Boyles, R., 2023, Potential effects of climate change on Appalachian stoneflies (Remenus kirchneri, Acroneuria kosztarabi, and Tallaperla lobata): U.S. Geological Survey Open-File Report 2021–1104–B, 41 p., https://doi.org/10.3133/ofr20211104B.","productDescription":"Report: viii, 41 p.; Data release","numberOfPages":"54","onlineOnly":"Y","ipdsId":"IP-141912","costCenters":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":411793,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9B2O22V","text":"USGS data release","linkHelpText":"CMIP5 MACAv2-METDATA monthly water balance model projections 1950–2099 for the contiguous United States"},{"id":411792,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1104/b/images"},{"id":411791,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1104/b/ofr20211104b.XML"},{"id":411790,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1104/b/ofr20211104b.pdf","text":"Report","size":"74.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021–1104–B"},{"id":411789,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1104/b/coverthb.jpg"}],"country":"United States","state":"North Carolina, Tennessee, Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -84.36021079719424,\n 35.42843231038343\n ],\n [\n -78.2983320325932,\n 35.42843231038343\n ],\n [\n -78.2983320325932,\n 38.58463308582091\n ],\n [\n -84.36021079719424,\n 38.58463308582091\n ],\n [\n -84.36021079719424,\n 35.42843231038343\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Midwest Climate Adaptation Science Center
U.S. Geological Survey
1954 Buford Avenue
St. Paul, MN 55108
The Federal Energy Regulatory Commission has been considering the approval to breach four dams on lower Klamath River in southern Oregon and northern California. Approval of this application would allow for Strikeouts indicate text deletion hereafter. decommissioning and dam removal, beginning as early as 2023. This action would affect Klamath River salmon (Oncorhynchus ssp.) populations, a critical food source for federally endangered Southern Resident Killer Whales (Orcinus orca). In the long run, reintroduction of salmon populations to the upper Klamath River Basin may increase salmon abundance available to Southern Resident Killer Whales, but in the near term, it is uncertain how changes in hatchery management and disease-caused mortality by the myxosporean parasite Ceratonova shasta will influence abundance of salmon populations entering the ocean. To assess this uncertainty, we used the Stream Salmonid Simulator (S3) to simulate population dynamics of juvenile Chinook salmon (Oncorhynchus tshawytscha) for nine different population sources that rear and migrate through the Klamath River.
S3 is a spatially explicit population model that runs on a daily time-step and simulates daily growth, survival, and movement of juvenile Chinook salmon from the time of spawning through ocean entry. The key features of this model relevant to this report include (1) a C. shasta disease submodel; (2) a temperature-dependent bioenergetics model that calculates daily growth rates; (3) size-dependent movement; (4) density-dependent dynamics that are influenced by the effect of flow on suitable habitat area; and (5) habitat, river flow, and water temperature specific to each scenario.
We constructed and ran four scenarios: two scenarios for dams in place (Dams In) and dams removed (Dams Out), and given these dam-removal conditions, a low- and high-spore scenario for C. shasta. Each scenario was run for nine water years representing a range of conditions from dry to wet. Previously published daily river flows and water temperatures for Dams In and Dams Out provided physical inputs for each scenario. Daily spore concentrations were simulated using a three-part mechanistic model that used river discharge, water temperature, and the prevalence of infection (POI) of hatchery-origin Chinook salmon juveniles with C. shasta in the previous year3. We constructed two spore scenarios for each Dams In and Dams Out scenario, a “Low Spore” scenario and a “High Spore” scenario resulting in four scenarios for comparison. Spore scenarios were established by setting the prior-year POI of hatchery fish to 0.15 and 0.75 in the estimation of spore concentrations. Hatchery releases under Dams Out differed from those under the current Dams In scenario. Hatchery releases under the Dams Out scenario were modified to emulate changes in hatchery production that would occur under Dams Out conditions. This included moving hatchery production and releases from Iron Gate Dam to a proposed hatchery at Fall Creek, which would be located about 11 kilometers (km) upstream of Iron Gate Dam. It is anticipated that the Fall Creek hatchery would produce fewer fish at smaller and larger sizes at different release timings. For salmon inputs, we used observed historical abundance of main-stem spawners from brood year 2009 and juvenile salmon entering from tributaries in water year 2010, which represented an average return year for the 2005–18 period. Main-stem spawning was allowed to shift upstream from Iron Gate Dam under the Dams Out scenario. We also included hatchery-origin fish as natural spawners that would have otherwise returned to Iron Gate Hatchery in the first 3 years following dam removal.
The S3 model simulated considerably higher total abundance for Dams Out relative to the respective Dams In scenarios, and higher abundance for the Low Spore scenario relative to the High Spore scenario. The difference in abundance between the four combinations of the dam-removal and spore scenarios varied among population groups. For main-stem natural production, juvenile abundance at ocean entry was 2–3 times higher for Dams Out scenarios than for Dams In scenarios, and juvenile abundance for High Spore scenarios was lower than that for the Dams Out Low Spores scenario. For hatchery releases, abundance at ocean entry was similar between Dams In and Dams Out scenarios for most water years, despite lower release sizes from Fall Creek Hatchery under Dams Out. For tributary populations, abundance for the High Spore scenarios was consistently lower than for the Low Spore scenarios, but differences between dam-removal scenarios varied among water years, with Dams Out scenarios having similar or higher abundance than Dams In scenarios, and dry water years having the largest difference between Dams In and Dams Out scenarios.
We determined that different factors affected the response of each population group. For main-stem natural production, survival from fry emergence to ocean entry was higher under Dams Out scenarios compared to Dams In scenarios because juveniles emerged later and tended to arrive at the ocean sooner and at larger sizes, causing the population to have less time-dependent in-river mortality. Owing to their late release timing, hatchery populations had high disease-caused mortality in Dams In and Dams Out High Spore scenarios. Furthermore, a high proportion of infected fish (those that would be expected to die at some future point) survived to the ocean. Iron Gate Hatchery fish had lower survival rates than releases from Fall Creek Hatchery because the last mid-June release group from the 2010 Iron Gate Hatchery release incurred nearly total mortality in most water years owing to water temperatures exceeding 24 degrees Celsius. Our analysis shows how the S3 model was able to track different populations and provide insights on how the differential response of each population combined to influence the simulated number of juvenile Chinook salmon arriving at the Pacific Ocean where they become available as a food source for Southern Resident Killer Whales.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221106","collaboration":"Prepared in cooperation with the National Marine Fisheries Service and the U.S. Fish and Wildlife Service","usgsCitation":"Perry, R.W., Plumb, J.M., Dodrill, M.J., Som, N.A., Robinson, H.E., and Hetrick, N.J., 2023, Simulating post-dam removal effects of hatchery operations and disease on juvenile Chinook salmon (Oncorhynchus tshawytscha) production in the Lower Klamath River, California: U.S. Geological Survey Open-File Report 2022–1106, 33 p., https://doi.org/10.3133/ofr20221106.","productDescription":"vii, 33 p.","onlineOnly":"Y","ipdsId":"IP-137471","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":410980,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1106/coverthb2.jpg"},{"id":410983,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1106/images"},{"id":410981,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1106/ofr20221106.pdf","text":"Report","size":"6.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1106"},{"id":499722,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114179.htm","linkFileType":{"id":5,"text":"html"}},{"id":410984,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1106/ofr20221106.XML"},{"id":410982,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221106/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1106"}],"country":"United States","state":"California","otherGeospatial":"Lower Klamath River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -124.36610471757332,\n 40.58470369882767\n ],\n [\n -120.32485220783963,\n 40.58470369882767\n ],\n [\n -120.32485220783963,\n 42.21557817118634\n ],\n [\n -124.36610471757332,\n 42.21557817118634\n ],\n [\n -124.36610471757332,\n 40.58470369882767\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016
More than 2 million Californians rely on groundwater from privately owned domestic wells for drinking-water supply. This report summarizes a water-quality survey of domestic and small-system drinking-water supply wells in the Modesto, Turlock, and Merced subbasins of the San Joaquin Valley where more than 78,000 residents are estimated to use privately owned domestic wells. Results indicate that inorganic and organic constituents in groundwater were respectively present above regulatory (maximum contaminant level, MCL) benchmarks for public drinking-water quality in 37 percent and 9 percent of the aquifer area used for domestic drinking-water supplies (herein, “domestic groundwater resources”).
The most prevalent inorganic constituents exceeding regulatory benchmarks were nitrate, uranium, and arsenic. The only organic constituents exceeding regulatory benchmarks were the fumigant constituents 1,2,3-trichloropropane (1,2,3-TCP) and 1,2-dibromo-3-chloropropane (DBCP), but the herbicides atrazine and simazine were detected at low concentrations below one-tenth of regulatory benchmarks in 30 percent of domestic groundwater resources. Total dissolved solids (TDS) and manganese exceeded aesthetic-based (secondary maximum contaminant level [SMCL]) benchmarks for drinking water in 3 percent and 13 percent of domestic groundwater resources, respectively. Per- and polyfluoroalkyl substances (PFAS) were detected in 23 percent of domestic groundwater resources, with 4 percent exceeding California state notification or response levels for specific compounds. Total coliform bacteria were detected in 20 percent of domestic groundwater resources.
Elevated concentrations of nitrate, uranium, TDS, and pesticides (fumigant constituents and herbicides) are related to agricultural land use and were typically present at shallow depths up to 75 meters below land surface. Agriculturally derived constituents were detected in wells screened below the Corcoran Clay Member of the Tulare Formation (herein, “Corcoran Clay”) in the southeastern part of the study area, where the Corcoran Clay tends to be shallower and thinner than in areas to the northwest. Nitrate, uranium, and TDS were most prevalent in the northwest part of the study area proximal to the valley trough where soils are poorly drained and agricultural land uses are predominantly grain, alfalfa, and dairy farms. Pesticides tended to occur in groundwater below coarse-grained surficial deposits and within a northwest to southeast trending band along the eastern extent of the Corcoran Clay that typically demarcates the western extent of well-drained soils associated with perennial orchard crops. Elevated concentrations of arsenic tended to occur west of this band in reducing groundwater but also sometimes co-occurred with elevated nitrate in oxic groundwater, most likely because of geochemical conditions in agriculturally affected groundwater that can enhance the mobility of arsenic from aquifer sediments.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221116","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","programNote":"GAMA Program","usgsCitation":"Levy, Z.F., Balkan, M., and Shelton, J.L., 2023, Quality of groundwater used for domestic supply in the Modesto, Turlock, and Merced Subbasins of the San Joaquin Valley, California: U.S. Geological Survey Open-File Report 2022-1116, 13 p., https://doi.org/10.3133/ofr20221116.","productDescription":"Report: 13 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-139668","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":411493,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P96R55KQ","text":"USGS data release","description":"USGS data release","linkHelpText":"Groundwater-quality data in the Modesto-Turlock-Merced Domestic-Supply Aquifer Study Unit, 2020-2021: Results from the California GAMA Priority Basin Project"},{"id":411490,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1116/coverthb.jpg"},{"id":411494,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1116/images"},{"id":411491,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1116/ofr20221116.pdf","text":"Report","size":"6.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1116"},{"id":411492,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221116/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1116"},{"id":411495,"rank":6,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1116/ofr20221116.XML"},{"id":499725,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114178.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"California","otherGeospatial":"San Joaquin Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.79107113798727,\n 38.18457756338151\n ],\n [\n -121.79107113798727,\n 37.036293717738104\n ],\n [\n -119.63866490997714,\n 37.036293717738104\n ],\n [\n -119.63866490997714,\n 38.18457756338151\n ],\n [\n -121.79107113798727,\n 38.18457756338151\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"GAMA Project Chief
U.S. Geological Survey
California Water Science Center
6000 J Street
Placer Hall, Sacramento, CA 95819
Telephone number: (916) 278-3000
GAMA Program Unit Chief State Water Resources Control Board Division of Water Quality
PO Box 2231
Sacramento, CA 95812
Telephone number: (916) 341-5855
This guide is intended to assist with characterizing injury to freshwater benthic macroinvertebrates (BMIs) in Natural Resource Damage Assessment and Restoration (NRDAR) cases. The contents are narrowly focused on insects, crustaceans, snails, and other invertebrate fauna that are typically considered part of BMI communities and are not intended to address studies of injury to larger benthic taxa such as freshwater mussels, crayfish, or benthic fishes or amphibians. Although some percentage of the community functions as predators, BMIs are predominantly primary consumers (for example, scrapers, shredders, and filterer/gatherer feeding groups) that play an essential role in converting carbon and nitrogen from plant tissues into animal biomass for higher-order consumers, especially in flowing waters. Aquatic contaminants can disrupt the quantity and quality of energy transferred (ecosystem function) by reducing invertebrate biomass and diversity. Additionally, the accumulation of toxic residues in invertebrate tissues may be a source of exposure leading to adverse effects in higher trophic levels. The goal of NRDAR BMI assessments is to establish direct linkages of contaminant exposure to injuries reflected by changes in community structure (for example, reduced density and taxa richness) or by effects at the individual population level (for example, survival, growth, and reproduction). BMIs are infrequently the U.S. Department of Interior (DOI)-managed resource in a NRDAR case, with managed resources more frequently including migratory birds, fish, or other insectivorous vertebrates. Therefore, it is critical to have clearly defined objectives for evaluating BMIs and an understanding of how invertebrate data relate to the quantification of injuries to the DOI-managed resource. This guide is intended to assist decisions on whether or not to proceed with BMI studies, use of existing information and data for screening purposes, and what types of studies can support a BMI-injury determination. This document is intended to provide general considerations and best practices for assessing BMIs. Relevant guidance and references are listed throughout the report as sources for specific methods and analysis.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221110","usgsCitation":"Soucek, D.J., Farag, A.M., Besser, J.M., and Steevens, J.A., 2023, Guide for benthic invertebrate studies in support of Natural Resource Damage Assessment and Restoration: U.S. Geological Survey Open-File Report 2022–1110, 11 p., https://doi.org/10.3133/ofr20221110.","productDescription":"iv, 11 p.","numberOfPages":"20","onlineOnly":"Y","ipdsId":"IP-139162","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":411372,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221110/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":411347,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1110/coverthb.jpg"},{"id":411348,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1110/ofr20221110.pdf","text":"Report","size":"1.37 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022–1110"},{"id":411349,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1110/ofr20221110.XML"},{"id":411350,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1110/images"}],"contact":"Director, Columbia Environmental Research Center
U.S. Geological Survey
4200 New Haven Road
Columbia, MO 65201
Establishing and enhancing pollinator habitat to support declining bee populations is a national goal within the United States. Pollinator habitat is often created through incentive-based conservation programs, and the inclusion of cost-effective forbs within the habitat design is a critical component of such programs. U.S. Geological Survey research from 2015 to 2019 identified forb species that (1) were preferred or highly visited by bees, (2) demonstrated high rates of establishment success, and (3) could be purchased at reduced cost. In this report, we enhance this past research by identifying common physical characteristics and functional traits of these cost-effective forbs so that land managers may have easy access to information on cost-effective forbs for new conservation plantings. This report highlights 22 forb species that were preferred and (or) highly visited by honey bees (Apis mellifera Linnaeus) or wild bees. Of the species evaluated for cost-effectiveness, most had less than average seed cost and greater than average apparent establishment rates. Several forb species were not considered cost effective because of bee avoidance, poor establishment, or high seed cost. Most forbs preferred or highly visited by bees were from the Asteraceae family and demonstrated a wide range of flower color. Forb species represented a range of wetland statuses from facultative wetland to upland, indicating that wetland and nonwetland habitat types represent areas where important floral resources for bees exist. Many forb species were in bloom from June to September, but our results showcase forb species that could be used in conservation projects seeking early- (June–July) or late-season (August–September) floral resources for pollinators.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221114","collaboration":"Prepared in cooperation with the Farm Service Agency, Natural Resources Conservation Service, and Honey Bee Health Coalition","usgsCitation":"Simanonok, S.C., and Otto, C.R.V., 2023, Identifying physical characteristics and functional traits of forbs preferred or highly visited by bees in the Prairie Pothole Region: U.S. Geological Survey Open-File Report 2022–1114, 10 p., https://doi.org/10.3133/ofr20221114.","productDescription":"Report: v, 10 p.; Data Release","numberOfPages":"20","onlineOnly":"Y","ipdsId":"IP-138617","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":411280,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1114/coverthb.jpg"},{"id":411284,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9O61BCB","text":"USGS data release","linkHelpText":"Dataset—Plant and bee transects in the Northern Great Plains, USA, 2015–2019"},{"id":411281,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1114/ofr20221114.pdf","text":"Report","size":"2.81 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022–1114"},{"id":411282,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1114/ofr20221114.XML"},{"id":411283,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1114/images"},{"id":411290,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221114/full","text":"Report"}],"country":"United States","otherGeospatial":"Prairie Pothole Region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -95.712890625,\n 43.58039085560784\n ],\n [\n -94.74609375,\n 41.50857729743935\n ],\n [\n -92.548828125,\n 41.77131167976407\n ],\n [\n -92.900390625,\n 43.32517767999296\n ],\n [\n -94.04296874999999,\n 45.460130637921004\n ],\n [\n -95.537109375,\n 48.45835188280866\n ],\n [\n -96.85546875,\n 49.61070993807422\n ],\n [\n -96.767578125,\n 50.401515322782366\n ],\n [\n -97.55859375,\n 51.069016659603896\n ],\n [\n -97.998046875,\n 50.51342652633956\n ],\n [\n -99.140625,\n 51.12421275782688\n ],\n [\n -99.931640625,\n 51.45400691005982\n ],\n [\n -102.216796875,\n 52.696361078274485\n ],\n [\n -104.501953125,\n 54.213861000644926\n ],\n [\n -107.22656249999999,\n 54.41892996865827\n ],\n [\n -111.533203125,\n 55.57834467218206\n ],\n [\n -114.78515624999999,\n 54.97761367069628\n ],\n [\n -115.13671875,\n 52.74959372674114\n ],\n [\n -115.13671875,\n 50.90303283111257\n ],\n [\n -113.90625,\n 49.095452162534826\n ],\n [\n -111.796875,\n 48.22467264956519\n ],\n [\n -110.56640625,\n 48.69096039092549\n ],\n [\n -109.16015624999999,\n 48.45835188280866\n ],\n [\n -107.40234375,\n 48.80686346108517\n ],\n [\n -105.380859375,\n 48.980216985374994\n ],\n [\n -101.77734374999999,\n 47.989921667414194\n ],\n [\n -100.986328125,\n 47.754097979680026\n ],\n [\n -100.37109375,\n 46.800059446787316\n ],\n [\n -100.546875,\n 45.460130637921004\n ],\n [\n -99.66796875,\n 43.96119063892024\n ],\n [\n -98.96484375,\n 43.45291889355465\n ],\n [\n -96.85546875,\n 42.8115217450979\n ],\n [\n -95.712890625,\n 43.58039085560784\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Northern Prairie Wildlife Research Center
U.S. Geological Survey
8711 37th Street Southeast
Jamestown, ND 58401
The U.S. Geological Survey performed subsurface and geophysical site characterization of the irrigated four-plex baseball field in the Langford Valley–Irwin Groundwater Subbasin, as part of a research study in cooperation with the U.S. Environmental Protection Agency, the Agricultural Research Service, and the Fort Irwin National Training Center, California. To help meet future demands, the Fort Irwin National Training Center is evaluating the efficacy of gravity-fed drywells to enhance storm-water recharge into the Langford Valley–Irwin Groundwater Subbasin by bypassing fine-grained, less permeable deposits between land surface and the water table. The amount, rate, and location of recharge beneath an irrigated baseball field in the groundwater basin at the Fort Irwin National Training Center is not well understood, so data were collected using physical and geophysical techniques to characterize subsurface materials, geologic controls, and the vertical movement of water through the unsaturated zone to the water table near the drywell at the Fort Irwin National Training Center. Based on the data collected and interpreted from these techniques, several fine-grained deposits were identified. Although these deposits appear to impede the downward movement of water through the unsaturated zone locally, they are not laterally continuous, and water appears to continue to move downward when it reaches the edges of the deposits. These data will help managers evaluate recharge at the site and determine if the use of gravity-fed drywells enhances recharge from surface runoff.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221118","issn":"2331-1258","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","programNote":"U.S. Environmental Protection Agency","usgsCitation":"Densmore, J.N., Dick, M.C., Groover, K.D., Ely, C.P., and Brown, A., 2022, Characterization of subsurface conditions and recharge at the irrigated four-plex baseball field, Fort Irwin National Training Center, California, 2018–20: U.S. Geological Survey Open File Report 2022-1118, 13 p., https://doi.org/10.3133/ofr20221118","productDescription":"13 p.","numberOfPages":"13","onlineOnly":"Y","ipdsId":"IP-129107","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":499727,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114180.htm","linkFileType":{"id":5,"text":"html"}},{"id":411259,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1118/ofr20221118.XML"},{"id":411257,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1118/images"},{"id":411255,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1118/coverthb.jpg"},{"id":411256,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1118/ofr20221118.pdf","text":"Report","size":"3.61 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"California","city":"Fort Irwin","otherGeospatial":"Fort Irwin National Training Center","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.69261791592291,\n 35.26487666931442\n ],\n [\n -116.69251062756216,\n 35.26470146901906\n ],\n [\n -116.69238188152951,\n 35.26459634865991\n ],\n [\n -116.69212438946424,\n 35.264447427917574\n ],\n [\n -116.69163086300526,\n 35.264359827352905\n ],\n [\n -116.69129826908738,\n 35.26422842632836\n ],\n [\n -116.69092275982544,\n 35.263983143846076\n ],\n [\n -116.68835856800732,\n 35.2661468601287\n ],\n [\n -116.6903755891864,\n 35.26772362102348\n ],\n [\n -116.69260718708664,\n 35.265822744364684\n ],\n [\n -116.69281103497185,\n 35.265752665110384\n ],\n [\n -116.69268228893922,\n 35.26531466839623\n ],\n [\n -116.69261791592291,\n 35.26487666931442\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, California Water Science Center
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
https://www.usgs.gov/centers/ca-water/
Contact Pubs Warehouse
https://pubs.er.usgs.gov/contact
Historical observations by the New York City Department of Environmental Protection (NYCDEP) indicate that the Rondout pressure tunnel has been leaking in the vicinity of the hamlet of High Falls, New York. In the 74 days from November 11, 2019, to January 23, 2020, NYCDEP shut down and partially dewatered the pressure tunnel for inspection and repairs. On November 5–7, 2019 (during normal tunnel operations), and on January 21–22, 2020 (when the tunnel was shut down), the U.S. Geological Survey used a network of 31 groundwater wells to collect water-level elevations and determine the potentiometric surface of the bedrock aquifer adjacent to the Rondout pressure tunnel. When the tunnel was fully pressurized during normal operations, water levels indicated a two-mile-long groundwater mound which trended northeastward, approximately along the regional strike of the bedrock units. The mound ranged in elevation from 250 to 300 feet (ft) above the North American Vertical Datum of 1988 and extended from 1,500 ft southwest of a suspected leak at the Rondout pressure tunnel to about 8,500 ft northeast of the possible leak. During the 74-day shutdown, during which the aqueduct was nonoperational, this groundwater mound decreased in magnitude and extent as it reverted to equilibrium conditions. This resulted in a flattening of the potentiometric surface, represented by two remnant groundwater plateaus.
Water-level differences were calculated for wells that may be affected by potential tunnel leakage to determine the influence on the local bedrock aquifer. The five largest water-level differences (77, 61, 49, 42, and 41 ft) occurred in wells that were generally aligned with the northeastward trend of regional bedrock strike; these wells may penetrate the karstic Helderberg Group bedrock unit. Near the suspected tunnel leak, the Helderberg Group overlies the Binnewater Sandstone and the High Falls Shale, both of which produced substantial groundwater inflows during the construction of the Rondout pressure tunnel. Water levels in wells penetrating the Shawangunk Formation just east of Rondout Creek, where the unit is in contact with the High Falls Shale, and in wells penetrating the Esopus Shale, which is adjacent to the Helderberg Group and northwest of the tunnel leak, may be affected by tunnel leakage. It is unclear if water levels in a well 9,000 ft northwest of the suspected tunnel leak are influenced by the tunnel leakage, by another source of artificial recharge, or by both. This well penetrates the Onondaga Limestone in the northwestern part of the study area. An unconsolidated aquifer composed of stratified gravel, sand, silt, and clay overlies the limestone bedrock in this part of study area―additional study is required to determine if this unconsolidated aquifer is affected by tunnel leakage.
Robert Francis Breault, Center Director
New York Water Science Center
U.S. Geological Survey
425 Jordan Road
Troy, NY 12180-8349
Cross-correlation waveforms of seismic noise in the Seattle basin, Washington, were analyzed to determine the group velocities of surface waves and constrain the shear-wave velocity (VS) for depths less than about 2 kilometers (km). Twenty broadband seismometers were deployed for about 3 weeks in three dense arrays separated by about 5 km, with minimum intra-array station spacing of about 0.5 km. Cross correlations of only 9 days of noise recordings produced Green’s functions at periods of 2 to 6 seconds (s) for sites about 5 km apart. Usable noise correlations for shorter periods of 0.5 to 1.0 s were found for sites within the arrays separated by 1 to 2 km. We bandpass filtered the inter- and intra-array cross-correlation waveforms to determine Love-wave group velocities at periods of 0.5 to 6 s for paths within the Seattle basin and at 3 to 5 s for paths crossing the southern edge of the basin. We developed a non-linear inversion program to determine VS profiles that fit the observed group velocities for paths in the basin. We found that these group velocities are well fit by a variety of VS profiles, each with a distinct jump in VS at depths ranging from 0.9 to 1.3 km. This jump in VS is inferred to represent the top of bedrock. The observed group velocities are not matched by models with the top of bedrock at 0.7-km depth or shallower. The group velocities are also fit by a model with no large jumps in VS in depths less than 2.4 km. The VS profile for the middle of the basin from Stephenson and others (2017), with a depth to bedrock of 0.9 km, also adequately fits the group velocity observations, if a velocity gradient is added from 0.05- to 0.1-km depth. The results indicate that short (3-week) deployments of seismometers to record seismic noise may provide useful constraints on the VS of sedimentary basins.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221108","collaboration":"Prepared in cooperation with the University of Washington","usgsCitation":"Frankel, A., and Bodin, P., 2022, Using seismic noise correlation to determine the shallow velocity structure of the Seattle basin, Washington: U.S. Geological Survey Open-File Report 2022–1108, 13 p., https://doi.org/10.3133/ofr20221108.","productDescription":"vi, 12 p.","onlineOnly":"Y","ipdsId":"IP-140830","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":501842,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114001.htm","linkFileType":{"id":5,"text":"html"}},{"id":410660,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1108/ofr20221108.XML"},{"id":410656,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1108/coverthb.jpg"},{"id":410657,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1108/ofr20221108.pdf","text":"Report","description":"OFR 2022-1108"},{"id":410658,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221108/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1108"},{"id":410659,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1108/images"}],"country":"United States","state":"Washington","city":"Seattle","otherGeospatial":"Seattle Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.45036951581977,\n 47.693059199440825\n ],\n [\n -122.45036951581977,\n 47.51906296781365\n ],\n [\n -122.22524539503297,\n 47.51906296781365\n ],\n [\n -122.22524539503297,\n 47.693059199440825\n ],\n [\n -122.45036951581977,\n 47.693059199440825\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Earthquake Science Center
U.S. Geological Survey
345 Middlefield Road, MS 977
Menlo Park, California 94025
The U.S. Geological Survey’s Grand Canyon Monitoring and Research Center, in coordination with the Glen Canyon Dam Adaptive Management Program, has monitored the geomorphic condition of select archaeological sites along the Colorado River in Grand Canyon using high-resolution terrestrial light detection and ranging (lidar) topographic surveys. Many of these sites are vulnerable to degradation by natural erosional processes. Regulation of the Colorado River by some operations of Glen Canyon Dam has been shown to affect archaeological resources by directly or indirectly causing degradation of site condition. Conversely, some specific operations of Glen Canyon Dam, such as controlled flood releases (termed high flow experiments), can potentially be used to slow or stop erosion at some degraded archaeological sites. Results of monitoring conducted with terrestrial lidar surveys from 2006 to 2010 have been synthesized in previous reports and publications. Here, we present and summarize results of monitoring conducted at 30 archaeological sites within 23 monitoring locations from 2010 to 2020. This report presents a sample of a much larger population of Colorado River archaeological sites in Grand Canyon that are being qualitatively monitored by the National Park Service (NPS). To ensure relevance to the NPS monitoring program, the quantitative high-resolution topographic monitoring presented in this report focused on sites binned by geomorphic context, using two previously published geomorphic classification frameworks to identify important changes in geomorphic condition within archaeological sites that can be related to operations of Glen Canyon Dam. We found that 22 archaeological sites changed within one or both of the previously determined geomorphic classifications, and changes at 21 of those 22 sites were interpreted as a transition to a more degraded geomorphic condition. The monitoring records contained within this report represent the foundation for future monitoring of these and other archaeological sites with high-resolution topographic surveys and change detection. These monitoring results provide benchmarks for managers of cultural resources along the Colorado River in Grand Canyon to assess significant changes to cultural resource integrity, aid in future risk management at these locations, and illustrate methods relevant for assessing geomorphic condition changes within other river valleys.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221097","usgsCitation":"Caster, J., Sankey, J.B., Fairley, H., and Kasprak, A., 2022, Terrestrial lidar monitoring of the effects of Glen Canyon Dam operations on the geomorphic condition of archaeological sites in Grand Canyon National Park, 2010–2020: U.S. Geological Survey Open-File Report 2022–1097, 100 p., https://doi.org/10.3133/ofr20221097.","productDescription":"xii, 100 p.","onlineOnly":"Y","ipdsId":"IP-112281","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":501838,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114000.htm","linkFileType":{"id":5,"text":"html"}},{"id":410864,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1097/ofr20221097.pdf","text":"Report","size":"60.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1097"},{"id":410863,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1097/coverthb.jpg"}],"country":"United States","state":"Arizona","otherGeospatial":"Grand Canyon National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -110.94729427966845,\n 36.935208423901784\n ],\n [\n -113.47307709825252,\n 36.935208423901784\n ],\n [\n -113.47307709825252,\n 35.500002816586004\n ],\n [\n -110.94729427966845,\n 35.500002816586004\n ],\n [\n -110.94729427966845,\n 36.935208423901784\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Southwest Biological Science Center
U.S. Geological Survey
2255 N. Gemini Drive
Flagstaff, AZ 86001
The U.S. Geological Survey (USGS) completed an assessment in 2007 of the undiscovered, technically recoverable, continuous gas potential of Cretaceous–Tertiary coal beds of the onshore areas and State waters of the northern Gulf of Mexico Coastal Plain. The assessment was based on geologic elements including hydrocarbon source rocks, availability of suitable reservoir rocks, and hydrocarbon accumulations in three coalbed gas total petroleum systems (TPSs) identified in the region: (1) the Olmos Coalbed Gas TPS (Upper Cretaceous), (2) the Wilcox Coalbed Gas TPS (Paleocene–Eocene), and (3) the Cretaceous-Tertiary Coalbed Gas TPS. Four continuous assessment units (AUs) were defined within these three TPSs: (1) the Cretaceous Olmos Coalbed Gas AU, (2) the Rio Escondido Basin Olmos Coalbed Gas AU, (3) the Wilcox Coalbed Gas AU, and (4) the Cretaceous-Tertiary Coalbed Gas AU, which was not quantitatively assessed and which includes all other Cretaceous and Tertiary coal beds that are not included in the other AUs.
This USGS assessment estimated a mean of 4.06 trillion cubic feet of undiscovered, technically recoverable, continuous coalbed gas resources in the four AUs that were assessed. Nearly all of the undiscovered continuous gas resources that were estimated (95 percent, or 3.86 trillion cubic feet of gas [TCFG]) were in the Wilcox Coalbed Gas AU. The continuous gas resources resided in coalbed reservoirs. Gas sourced from these coal beds may also occur as conventional accumulations in adjacent or interlayered sandstones that were not included in this assessment of continuous resources. The assessment was conducted via the established USGS methodology for continuous petroleum accumulations and reflects estimates of undiscovered resources based on vertical (nonhorizontal) drilling technology.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171167","usgsCitation":"Warwick, P.D., 2022, Geologic assessment of undiscovered gas resources in Cretaceous–Tertiary coal beds of the U.S. Gulf of Mexico Coastal Plain: U.S. Geological Survey Open-File Report 2017–1167, 52 p., https://doi.org/10.3133/ofr20171167.","productDescription":"Report: vi, 52 p.; 3 Appendixes","numberOfPages":"52","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-017257","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":501520,"rank":10,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113996.htm","linkFileType":{"id":5,"text":"html"}},{"id":410558,"rank":9,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.er.usgs.gov/publication/ofr20171111","text":"Open-File Report 2017–1111","linkHelpText":"- Geologic assessment of undiscovered conventional oil and gas resources in the Lower Paleogene Midway and Wilcox Groups, and the Carrizo Sand of the Claiborne Group, of the Northern Gulf coast region"},{"id":410555,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2017/1167/ofr20171167_appendix1.pdf","text":"Appendix 1","size":"165 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Input Data Form for the Cretaceous Olmos Coalbed Gas Assessment Unit (50470281)"},{"id":410985,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/ofr20171167/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2017-1167"},{"id":410553,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1167/ofr20171167.pdf","text":"Report","size":"15.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1167"},{"id":410552,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1167/coverthb.jpg"},{"id":409355,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2017/1167/ofr20171167.XML"},{"id":409356,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2017/1167/images/"},{"id":410556,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2017/1167/ofr20171167_appendix2.pdf","text":"Appendix 2","size":"161 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Input Data Form for the Rio Escondido Basin Olmos Coalbed Gas Assessment Unit (53000281)"},{"id":410557,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2017/1167/ofr20171167_appendix3.pdf","text":"Appendix 3","size":"168 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Input Data Form for the Wilcox Coalbed Gas Assessment Unit (50470381)"}],"country":"United States","otherGeospatial":"U.S. Gulf of Mexico Coastal Plain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -99.32775336731807,\n 26.212616580411137\n ],\n [\n -81.93279691237665,\n 26.212616580411137\n ],\n [\n -81.3178237043738,\n 38.82626189520937\n ],\n [\n -99.67916662903421,\n 38.491360932976605\n ],\n [\n -102.44654606504763,\n 38.43753817164347\n ],\n [\n -102.40261940733356,\n 36.63809827557699\n ],\n [\n -102.4904727227622,\n 31.785348237738653\n ],\n [\n -99.32775336731807,\n 26.212616580411137\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Program Coordinator, Energy Resources Program
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
Telephone: 703–648–6470
AskEnergyProgram@usgs.gov
The U.S. Geological Survey monitors a suite of intertidal black abalone sites at San Nicolas Island, California, in cooperation with the U.S. Navy, which owns the island. The nine rocky intertidal sites were established in 1980 to study the potential effect of translocated sea otters on the intertidal black abalone population at the island. The sites were monitored from 1981 to 1997, usually annually or biennially. Monitoring resumed in 2001 and has been completed annually since then. Since 2018, the work has been carried out by the U.S. Geological Survey Western Ecological Research Center. The study sites became particularly important, from a management perspective, after a virulent disease decimated black abalone populations throughout southern California beginning in the mid-1980s. The disease, withering syndrome, was first observed on San Nicolas Island in 1992 and during the next few years, it reduced the population there by more than 99 percent. The species was subsequently listed as endangered under the Endangered Species Act in 2009.
The subject of this report is the 2021 survey of the sites and how the measured population status compares to the long-term data (collected over several decades) at San Nicolas Island. During the last two decades, the total monitored black abalone population at the island has grown approximately ten-fold after the disease related decline, from about 200 to more than 2,000 abalone. Since it was first consistently measured in 2005, the mean distance between adjacent black abalone has decreased substantially from approximately 50 centimeters to less than 15 centimeters, indicating that abalone are close enough together at several of the sites to reproduce successfully. The 2021 counts were the first since 2016 to indicate a possible decline in the monitored population at San Nicolas Island. Although still more than ten times the population counted in 2001, counts on the transects dropped by 13.6 percent from the survey count in 2020. The most significant decline was the loss of 341 abalone, from the previous count of 547, on a transect that since 2002 had the highest count of all 44 transects. Between 2020 and 2021, there were increases and decreases at the sites and the transects at each site. Although the 2021 count was lower than the 2020 count, it was the second highest since 1997. Based on the number of small abalone counted, recruitment rates were similar to most years since 2008 and higher than the rates observed before the population declines resulting from withering syndrome.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221107","collaboration":"Prepared in cooperation with the U.S. Navy","programNote":"Ecosystems Mission Area—Species Management Research Program","usgsCitation":"Kenner, M.C., and Yee, J.L., 2022, Black Abalone surveys at Naval Base Ventura County, San Nicolas Island, California—2021, annual report: U.S. Geological Survey Open-File Report 2022–1107, 34 p., https://doi.org/10.3133/ofr20221107.","productDescription":"vii, 34 p.","onlineOnly":"Y","ipdsId":"IP-144353","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":410409,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1107/ofr20221107.XML"},{"id":410407,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221107/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1107"},{"id":410408,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1107/images"},{"id":410406,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1107/ofr20221107.pdf","text":"Report","size":"3.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1107"},{"id":410405,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1107/coverthb.jpg"}],"country":"United States","state":"California","county":"Ventura County","otherGeospatial":"San Nicolas Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -119.59425743862556,\n 33.2937160305206\n ],\n [\n -119.59425743862556,\n 33.20294676390226\n ],\n [\n -119.4170269925379,\n 33.20294676390226\n ],\n [\n -119.4170269925379,\n 33.2937160305206\n ],\n [\n -119.59425743862556,\n 33.2937160305206\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
This study evaluated carbon dioxide (CO2) injected into water as a possible behavioral stimulant to enhance capture and removal of invasive red swamp crayfish (RSC, Procambarus clarkii [Girard, 1852]) from a retention pond in southeastern Michigan. Objectives of this study were (1) to determine if target CO2 concentrations were attainable within the infested pond and (2) to determine if CO2 treatment was effective to push RSC either towards shorelines or onto dry land, where they could be collected and removed. Carbon dioxide was applied directly into one treatment pond (about [~]2,500 cubic meters) in Novi, Michigan. Two nearby ponds in Livonia, Mich., were used as untreated control ponds. Crayfish removal efficiency was evaluated in all ponds using baited traps and shoreline surveys. Results showed that the CO2 treatment pond reached its target concentration of greater than (>) 200 milligrams per liter (mg/L) of CO2, a benchmark determined from previous laboratory studies, approximately 11 hours after injection started, and maintained concentrations between 200 and 351 mg/L of CO2 for about 2.5 days. During treatment, some emergent crayfish were observed near influent culverts around the pond, which possibly brought about a behavioral response. However, the number of individuals and crayfish observations were minimal and infrequent. Crayfish continued to be removed throughout CO2 treatment with baited traps and perimeter surveys, but differences in catch rates between the treatment and control ponds were not apparent and confounded by a temporal decline in catch rates across all ponds. Overall, this study demonstrated that open-water treatment applications with CO2 are possible, but its effectiveness to enhance RSC removal was unclear because of the limited crayfish observations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221105","collaboration":"Prepared in cooperation with Michigan Department of Natural Resources, Michigan State University, and Auburn University","programNote":"Biological Threats and Invasive Species Research Program","usgsCitation":"Smerud, J., Rivera, J., Johnson, T., Tix, J., Fredricks, K., Barbour, M., Herbst, S., Thomas, S., Nathan, L., Roth, B., Smith, K., Allert, A., Stoeckel, J., and Cupp, A., 2022, Field application of carbon dioxide as a behavioral control method for invasive red swamp crayfish (Procambarus clarkii) in southeastern Michigan water retention ponds: U.S. Geological Survey Open-File Report 2022–1105, 12 p., https://doi.org/10.3133/ofr20221105.","productDescription":"Report: vii, 12 p.; Data Release","numberOfPages":"24","onlineOnly":"Y","ipdsId":"IP-138063","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":501841,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113941.htm","linkFileType":{"id":5,"text":"html"}},{"id":410370,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221105/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":410273,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P99OUHMV","text":"USGS data release","linkHelpText":"Water quality and atmospheric carbon dioxide data for field application of carbon dioxide during summer 2018 as a behavioral control method for invasive red swamp crayfish (Procambarus clarkii) in southeastern Michigan water retention ponds"},{"id":410272,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1105/images"},{"id":410271,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1105/ofr20221105.XML"},{"id":410270,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1105/ofr20221105.pdf","text":"Report","size":"1.08 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022–1105"},{"id":410269,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1105/coverthb.jpg"}],"country":"United States","state":"Michigan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -83.44162797914937,\n 42.44723847720684\n ],\n [\n -83.44162797914937,\n 42.42580674596837\n ],\n [\n -83.3843952063379,\n 42.42580674596837\n ],\n [\n -83.3843952063379,\n 42.44723847720684\n ],\n [\n -83.44162797914937,\n 42.44723847720684\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Upper Midwest Environmental Sciences Center
U.S. Geological Survey
2630 Fanta Reed Road
La Crosse, WI 54603
The Sand Resources Project was established through collaborative agreements between the U.S. Geological Survey (USGS), the Bureau of Ocean Energy Management (BOEM), and the California Ocean Protection Council (OPC) with the purpose of evaluating sand and gravel resources in Federal and California State Waters for potential use in future beach-nourishment projects. Project partners worked in collaboration with California Coastal Sediment Management Workgroup (CSMW) members to define priority study areas for this work based on the potential for finding sand within the broader region and the needs for this sand as shown by beach erosion areas of concern in the adjacent littoral cells. The final study areas were defined to be (1) the San Francisco Littoral Cell, (2) the Oceanside Littoral Cell, and (3) the Silver Strand Littoral Cell.
A two-stage approach was used to assess the study areas. The initial stage was a synthesis of the existing geophysical and sediment-sampling data in each area. This allowed for evaluations of the data availability, data gaps, and general patterns of sediment thickness and grain size. This synthesis was published in a separate USGS open-file report (Warrick and others, 2022). The findings from this assessment were used to refine study area boundaries and develop sampling plans for stage two of the project.
Stage two of the project is the collection, processing, and synthesis of new data, including high-resolution geophysical surveys and sediment cores—this report addresses the second stage. The work focuses on two of the study areas—the San Francisco and the Oceanside Littoral Cells, where several research cruises have been conducted. A more limited, exploratory approach was used for the Silver Strand Littoral Cell, owing to the lack of existing high-resolution bathymetric data for this study area. The data collected provide new information about the three study areas, including sediment thickness, grain-size distributions, and total organic carbon.
Sediment in all three study areas of the Sand Resources Study was suitable for beach nourishment, as reflected by their grain-size distributions and sediment thicknesses. For example, sandy sediment in the San Francisco Littoral Cell study area was on and immediately outside of the ebb-tidal bar of the San Francisco Bay, a landform that has a strong influence on grain-size patterns of the region. The presence of thick sediment deposits in this area was interpreted to be a function of tectonics, which has caused physical features that include a graben north of the Golden Gate whose deposits were thicker and siltier than the remaining area. Sandy sediment on the inner and outer parts of the continental shelf in the Oceanside Littoral Cell may be useful for nourishment, whereas the midshelf between these areas was dominated by silty sediment. Sediment in the Silver Strand Littoral Cell, which was only sampled selectively, had the greatest potential for beach nourishment because of the greater prevalence of beach-comparable grain sizes, especially in the more distal and deeper areas where medium sands were found.
The Sand Resources Project did identify several sandy regions of the continental shelf that are deeper than dredging technologies currently (2022) available in the United States, which are generally limited to 30 meters (m) water depth or less. Although sandy sediment exists in all three study areas at water depths of 30 m or less, additional sediment supplies—most of which are in Federal Waters—are present in deeper settings, especially for the Oceanside and Silver Strand Littoral Cell study areas. Although the Silver Strand Littoral Cell study area was found to be considerably replete in sand resources, these conclusions are based on a limited sampling exercise across that study area. Thus, it may be beneficial to complete a more thorough characterization of the sediment resources in the Silver Strand Littoral Cell study area if it is determined that a need for sandy coastal sediment exists in this region.
As a result of the Sand Resources Project, several areas of sand resources in Federal and California State Waters were found where they were previously unknown. As such, this project may provide important data for future coastal-management decisions in California, and it should provide a model for future investigations of sediment resources in other regions of the State.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221095","collaboration":"Prepared in cooperation with the Bureau of Ocean Energy Management and the State of California Ocean Protection Council","usgsCitation":"Warrick, J.A., Conrad, J.E., Papesh, A., Lorenson, T., and Sliter, R.W., 2022, Assessment of significant sand resources in Federal and California State Waters of the San Francisco, Oceanside, and Silver Strand littoral cell study areas along the continental shelf of California: U.S. Geological Survey Open-File Report 2022–1095, 104 p., https://doi.org/10.3133/ofr20221095.","productDescription":"Report: viii, 104 p.; 3 Data Releases","onlineOnly":"Y","ipdsId":"IP-130530","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":501837,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113943.htm","linkFileType":{"id":5,"text":"html"}},{"id":410366,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9UELSBU","text":"USGS data release","description":"USGS data release","linkHelpText":"Geophysical and sampling data collected offshore Oceanside, southern California during field activity 2017-686-FA from 2017-10-23 to 2017-10-31"},{"id":410365,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9690BEK","text":"USGS data release","description":"USGS data release","linkHelpText":"Geophysical and core sample data collected offshore Oceanside to San Diego, southern California, during field activity 2018-638-FA from 2018-05-21 to 2018-05-26"},{"id":410364,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LBG9H5","text":"USGS data release","description":"USGS data release","linkHelpText":"Geophysical and core sample data collected offshore San Francisco, California, during field activity 2019-649-FA from 2019-10-11 to 2019-10-18"},{"id":410367,"rank":3,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20221094","text":"OFR 2022-1094 —","linkHelpText":"Compilation of existing data for sand resource studies in Federal and California State Waters of the San Francisco, Oceanside, and Silver Strand littoral cell study areas along the continental shelf of California—Strategy for field studies and sand resource assessment"},{"id":410363,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1095/ofr20221095.pdf","text":"Report","size":"12.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1095"},{"id":410362,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1095/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"San Francisco, Oceanside, and Silver Strand littoral cell study areas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.32845828309286,\n 37.818674364541195\n ],\n [\n -123.23587958971336,\n 37.818674364541195\n ],\n [\n -123.23587958971336,\n 36.79251013661299\n ],\n [\n -122.32845828309286,\n 36.79251013661299\n ],\n [\n -122.32845828309286,\n 37.818674364541195\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.13365815618306,\n 32.493660702226535\n ],\n [\n -117.13365815618306,\n 32.93175821350262\n ],\n [\n -117.80008333663935,\n 32.93175821350262\n ],\n [\n -117.80008333663935,\n 32.493660702226535\n ],\n [\n -117.13365815618306,\n 32.493660702226535\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -118.26754558635474,\n 33.52924818029179\n ],\n [\n -118.26754558635474,\n 33.1318551432673\n ],\n [\n -117.66427888472828,\n 33.1318551432673\n ],\n [\n -117.66427888472828,\n 33.52924818029179\n ],\n [\n -118.26754558635474,\n 33.52924818029179\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Pacific Coastal and Marine Science Center
U.S. Geological Survey
2885 Mission St
Santa Cruz, CA 95060
The Sand Resources Project was established through collaborative agreements between the U.S. Geological Survey (USGS), the Bureau of Ocean Energy Management (BOEM), and the California Ocean Protection Council (OPC) with the purpose of evaluating sand and gravel resources in Federal and California State Waters for potential use in future beach-nourishment projects. Project partners worked in collaboration with California Coastal Sediment Management Workgroup (CSMW) members to define priority study areas for this work based on the potential for finding sand within the broader region and the needs for this sand as shown by beach erosion areas of concern in the adjacent littoral cells. The final study areas were defined to be (1) the San Francisco Littoral Cell, (2) the Oceanside Littoral Cell, and (3) the Silver Strand Littoral Cell.
A two-stage approach was used to assess the study areas. This report addresses the initial stage, which is a synthesis of the existing geophysical and sediment-sampling data in each area. This allowed for evaluations of the data availability, data gaps, and general patterns of sediment thickness and grain size. This report provides a description of the methods and results of this synthesis. The findings from this work were used to refine study area boundaries and develop sampling plans for stage two of the project.
Stage two of the project, the results of which will be published separately, will be the collection, processing, and synthesis of new data, including high-resolution geophysical surveys and sediment cores within the three study areas. The data collected will provide new information about the three study areas including sediment thickness, grain-size distributions, and total organic carbon. The description and results of stage two of the work is included in another USGS report (Warrick and others, 2022).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221094","collaboration":"Prepared in cooperation with the Bureau of Ocean Energy Management and the State of California Ocean Protection Council","usgsCitation":"Warrick, J.A., Conrad, J.E., Papesh, A., Lorenson, T., and Sliter, R.W., 2022, Compilation of existing data for sand resource studies in Federal and California State Waters of the San Francisco, Oceanside, and Silver Strand littoral cell study areas along the continental shelf of California—Strategy for field studies and sand resource assessment: U.S. Geological Survey Open-File Report 2022–1094, 21 p., https://doi.org/10.3133/ofr20221094.","productDescription":"vii, 21 p.","onlineOnly":"Y","ipdsId":"IP-142746","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":410369,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1094/ofr20221094.pdf","text":"Report","size":"6.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1094"},{"id":410368,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1094/coverthb.jpg"},{"id":501836,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113942.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"California","otherGeospatial":"San Francisco, Oceanside, and Silver Strand littoral cell study areas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.32845828309286,\n 37.818674364541195\n ],\n [\n -123.23587958971336,\n 37.818674364541195\n ],\n [\n -123.23587958971336,\n 36.79251013661299\n ],\n [\n -122.32845828309286,\n 36.79251013661299\n ],\n [\n -122.32845828309286,\n 37.818674364541195\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.13365815618306,\n 32.493660702226535\n ],\n [\n -117.13365815618306,\n 32.93175821350262\n ],\n [\n -117.80008333663935,\n 32.93175821350262\n ],\n [\n -117.80008333663935,\n 32.493660702226535\n ],\n [\n -117.13365815618306,\n 32.493660702226535\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -118.26754558635474,\n 33.52924818029179\n ],\n [\n -118.26754558635474,\n 33.1318551432673\n ],\n [\n -117.66427888472828,\n 33.1318551432673\n ],\n [\n -117.66427888472828,\n 33.52924818029179\n ],\n [\n -118.26754558635474,\n 33.52924818029179\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Pacific Coastal and Marine Science Center
U.S. Geological Survey
2885 Mission St
Santa Cruz, CA 95060
A cascading set of hazards to coastal environments is intimately tied to sediment transport and includes the flooding and erosion of shorelines and habitats that support communities, industry, infrastructure, and ecosystem functions (for example, habitats critical to fisheries). This report summarizes modeling and measurement data used to evaluate the sediment budget of the Nisqually River Delta, the vulnerability of the largest estuary restoration project in Puget Sound at the Billy Frank Jr. Nisqually National Wildlife Refuge, and the role of coastal hydrodynamics and potential restoration alternatives for recovering sediment delivery to its marshes. The 2009 Brown’s Farm Restoration achieved many goals toward recovering salmon habitat, but the understanding of the delta and restoration area sediment budgets remain poorly quantified. Specifically, quantitative estimates of the amount of sediment delivered to the delta and restored marsh areas, which had subsided in response to historical diking and draining for grazing, were identified as important information needs. Forecasts of potential outcomes of proposed adaptive distributary channel restoration actions were also prioritized to inform potential solutions. These estimates can be used to evaluate whether sufficient sediment is available for marsh recovery downstream from Alder Lake, which traps about 90 percent the Nisqually River sediment load that could reach the delta. Additionally, quantitative sediment information was identified to help prioritize opportunities to recover and maintain the area marshes and guide ecosystem restoration investments across the delta to reduce the vulnerability of the system to drowning under projected sea level rise.
A coupled, numerical hydrodynamic-sediment transport model and measurements of the sediment load just upstream from the delta were used to evaluate the (1) availability of sediment for marsh recovery, (2) sediment transport dynamics across the estuary, and (3) potential outcomes of distributary reconnection alternatives under existing and projected conditions of streamflow and sea level. Modeling and measurements indicated that the volume of fluvial sediment load reaching and accumulating in the restoration area ranges from 7 to 32 percent and identified that restoration alternatives could recover about an additional 10–12 percent under current and projected sea-level rise by the year 2100. At these rates of sediment delivery, 85–200+ years may be necessary to fill for marsh vegetation development and maintenance. The model also reveals the sensitivity of sediment transport and accumulation to sediment properties, hydrodynamics, and wave conditions. The low sediment accumulation results in large part because of the role of waves in directing sediment transport offshore and challenges of restoring geomorphic processes suited to maintaining habitat structure where opportunity exists or least conflicts with land use. The findings therefore have implications for siting, phasing, and implementing strategies to route and retain sediment. This study shows that opportunities to recover sediment higher in the tidal prism, where a greater hydraulic gradient and gravity could promote progradation and greater sediment retention, may be more effective than alternatives lower in the tidal prism implemented to date and assessed in this study. Furthermore, the modeling indicates that distributary channel restoration also may provide additional benefits to society by reducing flood stage, and therefore, flood hazards surrounding the delta.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221088","collaboration":"Prepared in cooperation with Nisqually Indian Tribe, U.S. Fish and Wildlife Service, Billy Frank Jr. Nisqually National Wildlife Refuge, and Washington Department of Fish and Wildlife Estuary and Salmon Restoration Program","usgsCitation":"Grossman, E.E., Crosby, S.C., Stevens, A.W., Nowacki, D.J., vanAredonk, N.R., and Curran, C.A., 2022, Assessment of vulnerabilities and opportunities to restore marsh sediment supply at Nisqually River Delta, west-central Washington: U.S. Geological Survey Open-File Report 2022–1088, 50 p., https://doi.org/10.3133/ofr20221088.","productDescription":"Report: ix, 50 p.; 2 Data Releases","onlineOnly":"Y","ipdsId":"IP-121432","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":410185,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7GF0SG7","text":"USGS data release","description":"USGS data release","linkHelpText":"Stage, water velocity and water quality data collected in the Lower Nisqually River, McAllister Creek and tidal channels of the Nisqually River Delta, Thurston County, Washington, February 11, 2016 to September 18, 2017 (ver. 1.1, December, 2019)"},{"id":410186,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P95N6CIT","text":"USGS data release","description":"USGS data release","linkHelpText":"Topobathymetric Model of Puget Sound, Washington, 1887 to 2017"},{"id":410184,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1088/ofr20221088.pdf","text":"Report","size":"32.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1088"},{"id":410183,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1088/coverthb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Nisqually River Delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -123.12450821055306,\n 47.12862354087443\n ],\n [\n -123.12450821055306,\n 45.666890715537136\n ],\n [\n -121.49348505325844,\n 45.666890715537136\n ],\n [\n -121.49348505325844,\n 47.12862354087443\n ],\n [\n -123.12450821055306,\n 47.12862354087443\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Pacific Coastal and Marine Science Center
U.S. Geological Survey
2885 Mission St.
Santa Cruz, CA 95060
The U.S. Geological Survey (USGS) completed a verification study of selected commercially available phosphorus analyzers for their applicability to scientific surface-water applications. In this study, the analyzers were the Hach EZ7800 TOPHO, Hach Phosphax sc, Sea-Bird Scientific HydroCycle-PO4, and the YSI Inc. Alyza IQ PO4. Verification tests included laboratory trials comparing analyzer results to known standards with several known concentrations of dissolved organic matter and waste production estimates. Field trials were completed at the Vermilion River near Danville, Illinois (U.S. Geological Survey station 03339000), where analyzer-measured concentrations were compared against discrete samples across a wide range of environmental conditions from November 2020 to August 2021. Data coverage was closely tracked for analyzer malfunctions and operator errors that caused missing data. Laboratory and field trials indicated that each analyzer is a viable option for scientific surface-water studies depending on environmental conditions. Because of the complexity of the analyzers, a substantial time investiture was required to get maximum data coverage including considerable site infrastructure investments and well-trained technicians. Data coverage was closely related to each analyzer’s ability to handle elevated turbidity levels.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221100","collaboration":"Prepared in cooperation with the Next Generation Water Observing System","programNote":"Groundwater and Streamflow Information Program","usgsCitation":"Peake, C.S., 2022, Verification of multiple phosphorus analyzers for use in surface-water applications: U.S. Geological Survey Open-File Report 2022–1100, 23 p., https://doi.org/10.3133/ofr20221100.","productDescription":"Report: viii, 23 p.; Dataset","numberOfPages":"36","onlineOnly":"Y","ipdsId":"IP-139337","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":410009,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221100/full","text":"Report"},{"id":409997,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1100/ofr20221100.XML"},{"id":409995,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1100/coverthb.jpg"},{"id":501839,"rank":7,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113882.htm","linkFileType":{"id":5,"text":"html"}},{"id":409998,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1100/images"},{"id":409996,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1100/ofr20221100.pdf","text":"Report","size":"1.42 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022–1100"},{"id":409999,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"}],"country":"United States","state":"Illinois, Indiana","otherGeospatial":"Vermilion River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -87.41449158849616,\n 39.979211528524246\n ],\n [\n -87.41449158849616,\n 40.79889755055865\n ],\n [\n -88.38087805821512,\n 40.79889755055865\n ],\n [\n -88.38087805821512,\n 39.979211528524246\n ],\n [\n -87.41449158849616,\n 39.979211528524246\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
405 North Goodwin
Urbana, IL 61801
This study used the complete set of continuous water-quality (WQ) data and discrete measurements of total ammonia collected by the U.S. Geological Survey from 2005 to 2019 at the four core sites in Upper Klamath Lake, Oregon, to examine relations between variables and extreme conditions that may be harmful for endemic Lost River suckers (Deltistes luxatus) and shortnose suckers (Chasmistes brevirostris). Several graphical and tabular approaches were used to compare variables, sites, and years to better understand the factors contributing to and timing of extreme WQ in the lake. Extreme WQ thresholds were defined as the 1st or 99th percentiles of the daily average dataset of water temperature, pH, and dissolved oxygen (DO) concentration, and the weekly estimated un-ionized ammonia (NH3) from 2005 to 2019. Extreme WQ days were defined as those when at least 12 hours of measurements exceeded the extreme WQ threshold. The core site at Mid-Trench, which was also the deepest measurement site with a full-pool depth of 15 meters and at which water-quality sondes were deployed at the top and bottom of the water column, had the most extreme conditions of high water temperature, low DO, and high NH3. The upper sonde at Mid-Trench represented 40 percent of all days of extremely high water temperature (days with at least 12 hours exceeding 24.38 degrees Celsius) in the lake and 71 percent of all weekly estimates of extremely high NH3 (greater than 264 micrograms per liter) in the lake. The lower sonde at Mid-Trench represented 85 percent of all days of extremely low DO (days with at least 12 hours of DO concentrations less than 1.76 milligrams per liter) in the lake. In each of the study years, poor water quality at Mid-Trench, as represented by several metrics, lasted for multiple days. The shallowest site at the Williamson River outlet represented 54 percent of all days of extremely high pH (days with at least 12 hours of pH measurements exceeding 10.04) in the lake. The seasonality of extreme WQ during the summer sampling period (limited to June through September) was evaluated and most days of extremely high water temperature (83 percent) and extremely high pH (54 percent) occurred in July, whereas most days of extremely low DO (57 percent) and extremely high NH3 (57 percent) occurred in August. The years with the most days of extreme WQ accumulated for all variables (high water temperature, low DO, high pH, and high NH3) were 2012–15 and 2017, which all occurred in the latter half of the study period. The years with the fewest accumulated days of extreme WQ were 2010 and 2011.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221080","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Wherry, S.A., 2022, Summary of extreme water-quality conditions in Upper Klamath Lake, Oregon, 2005–19: U.S. Geological Survey Open-File Report 2022–1080, 29 p., https://doi.org/10.3133/ofr20221080.","productDescription":"vii, 29 p.","onlineOnly":"Y","ipdsId":"IP-128098","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":501831,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_113883.htm","linkFileType":{"id":5,"text":"html"}},{"id":410005,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1080/ofr20221080.XML"},{"id":410002,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1080/ofr20221080.pdf","text":"Report","size":"6.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1080"},{"id":410001,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1080/coverthb.jpg"},{"id":410004,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1080/images"},{"id":410003,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/ofr20221080/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1080"}],"country":"United States","state":"Oregon","otherGeospatial":"Upper Klamath Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.11865576927013,\n 42.623699726465674\n ],\n [\n -122.11865576927013,\n 42.185824493728575\n ],\n [\n -121.73017939010751,\n 42.185824493728575\n ],\n [\n -121.73017939010751,\n 42.623699726465674\n ],\n [\n -122.11865576927013,\n 42.623699726465674\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201