Ambystoma barbouri (streamside salamanders) are stream-breeding mole salamanders that rely on seasonally intermittent, fishless streams for egg and larval development but are primarily fossorial as adults. Climate-driven changes are likely to alter streamflow duration, peak, and seasonality within the range of A. barbouri, reducing reproductive habitat and larval survival. Although future changes in precipitation volume within the geographic range of A. barbouri are uncertain, in the next 90 years, increasing temperatures will likely increase potential evapotranspiration. Decreasing ratio of precipitation to potential evapotranspiration will likely shorten flow duration for intermittent streams, potentially causing earlier stream dry downs before larval metamorphosis. Increased temperatures may also shorten developmental periods buffering A. barbouri larvae from the effects of increased stream no-flow days. Additionally, precipitation in the future will increasingly fall in heavy rainfall events. Heavy rain and subsequent flooding during early larval stages may displace A. barbouri larvae from fishless pools into downstream reaches with vertebrate predators that can reduce survival. Finally, agriculture and urban land cover may amplify the stresses of climate change on A. barbouri, altering reproductive habitat and reducing survival of larval, juvenile, and adult life stages.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211104C","usgsCitation":"Lyons, M.P., LeDee, O.E., and Boyles, R., 2023, Potential effects of climate change on Ambystoma barbouri (streamside salamander): U.S. Geological Survey Open-File Report 2021–1104–C, 14 p., https://doi.org/10.3133/ofr20211104C.","productDescription":"Report: vi, 14 p.; Data Release","numberOfPages":"24","onlineOnly":"Y","ipdsId":"IP-138888","costCenters":[{"id":65882,"text":"Midwest Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":415229,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20211104C/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":415166,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F798865X","linkHelpText":"U.S. Geological Survey—Gap Analysis Project species range maps CONUS_2001"},{"id":415165,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1104/c/images"},{"id":415164,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1104/c/ofr20211104C.XML"},{"id":415163,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1104/c/ofr20211104c.pdf","text":"Report","size":"1.57 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021–1104–C"},{"id":415162,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1104/c/coverthb.jpg"}],"country":"United States","state":"Illinois, Indiana, Kentucky, Ohio, Tennessee, West Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -88.77637660661436,\n 37.29693429192959\n ],\n [\n -88.77637660661436,\n 36.81080154311158\n ],\n [\n -88.117170430842,\n 36.81080154311158\n ],\n [\n -88.117170430842,\n 37.29693429192959\n ],\n [\n -88.77637660661436,\n 37.29693429192959\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -86.87385719670998,\n 36.41563025729535\n ],\n [\n -86.87385719670998,\n 35.033754255529374\n ],\n [\n -85.60551113699587,\n 35.033754255529374\n ],\n [\n -85.60551113699587,\n 36.41563025729535\n ],\n [\n -86.87385719670998,\n 36.41563025729535\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -82.70166692228476,\n 38.46265353132972\n ],\n [\n -82.70166692228476,\n 37.89197947744543\n ],\n [\n -82.06749389242742,\n 37.89197947744543\n ],\n [\n -82.06749389242742,\n 38.46265353132972\n ],\n [\n -82.70166692228476,\n 38.46265353132972\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -82.22603714989201,\n 39.184248376047606\n ],\n [\n -83.62789332115464,\n 39.35866418136621\n ],\n [\n -84.06180118368843,\n 39.860090114776256\n ],\n [\n -84.02007927382951,\n 40.032813749497734\n ],\n [\n -85.0297494924173,\n 39.712611372960964\n ],\n [\n -85.78908825185144,\n 39.0353297194157\n ],\n [\n -86.43160566367993,\n 38.38420573496376\n ],\n [\n -86.36485060790544,\n 37.746963993740465\n ],\n [\n -84.23703320509641,\n 37.48919160202678\n ],\n [\n -83.66961523101361,\n 38.04328175226868\n ],\n [\n -82.55981242876403,\n 38.808111070451616\n ],\n [\n -82.22603714989201,\n 39.184248376047606\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
Bathymetric change analyses document historical patterns of sediment deposition and erosion, providing valuable insight into the sediment dynamics of coastal systems, including pathways of sediment and sediment-bound contaminants. In 2014 and 2015, the Office for Coastal Management, in partnership with the National Oceanic and Atmospheric Administration (NOAA) Office of Coastal Management, provided funding for new bathymetric surveys of large portions of San Francisco Bay. A total of 93 bathymetric surveys were conducted during this 2-year period, using a combination of interferometric sidescan and multibeam sonar systems. These data, along with recent NOAA, U.S. Geological Survey (USGS), U.S. Army Corps of Engineers, and private contractor surveys collected from 1999 to 2020 (hereinafter referred to as 2010s), were used to create the most comprehensive bathymetric digital elevation models (DEMs) of San Francisco Bay since the 1980s. Comparing DEMs created from these 2010s surveys with USGS DEMs created from NOAA’s 1971–1990 (hereinafter referred to as 1980s) surveys provides information on the quantities and patterns of erosion and deposition in San Francisco Bay during the 9 to 47 years between surveys. This analysis reveals that in the areas surveyed in both the 1980s and 2010s, the bay floor lost about 34 million cubic meters of sediment since the 1980s. Results from this study can be used to assess how San Francisco Bay has responded to changes in the system, such as sea-level rise and variation in sediment supply from the Sacramento-San Joaquin Delta and local tributaries, and supports the creation of a new, system-wide sediment budget. This report provides data on the quantities and patterns of sediment volume change in San Francisco Bay for ecosystem managers that are pertinent to various sediment-related issues, including restoration of tidal marshes, exposure of legacy contaminated sediment, and strategies for the beneficial use of dredged sediment.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231031","collaboration":"Prepared in cooperation with the Regional Monitoring Program for Water Quality in San Francisco Bay","usgsCitation":"Fregoso, T.A., Foxgrover, A.C., and Jaffe, B.E., 2023, Sediment deposition, erosion, and bathymetric change in San Francisco Bay, California, 1971–1990 and 1999–2020 (ver. 1.1, June 2024): U.S. Geological Survey Open-File Report 2023–1031, 19 p., https://doi.org/ 10.3133/ ofr20231031.","productDescription":"Report: vi, 19 p.; Data Release","numberOfPages":"19","onlineOnly":"Y","ipdsId":"IP-135389","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":435389,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1332UUW","text":"USGS data release","linkHelpText":"Bathymetric change analysis in San Francisco Bay, California, from 1971 to 2020"},{"id":430608,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2023/1031/versionHist.txt","size":"10.7 KB","linkFileType":{"id":2,"text":"txt"}},{"id":415025,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1031/images"},{"id":415024,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1031/ofr20231031.pdf","text":"Report","size":"15.5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":415023,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1031/coverthb2.jpg"},{"id":499186,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114619.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"California","county":"San Francisco Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.84417858005195,\n 38.240616044555935\n ],\n [\n -122.84417858005195,\n 37.276937922454465\n ],\n [\n -121.28479077260828,\n 37.276937922454465\n ],\n [\n -121.28479077260828,\n 38.240616044555935\n ],\n [\n -122.84417858005195,\n 38.240616044555935\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Version 1.0: March 31, 2023; Version 1.1: June 28, 2024","contact":"Pacific Coastal and Marine Science Center
U.S. Geological Survey
2885 Mission St.
Santa Cruz, CA 95060
Eugeoclinal metasedimentary and metavolcanic rocks in the Lane Mountain area, California, are considered part of the El Paso terrane, which is commonly thought to have been displaced several hundred kilometers (km) southeastward from its place of origin during late Paleozoic truncation of the North American continental margin. Uranium-lead dating of detrital zircons from this area was undertaken to limit the depositional ages of these nearly non-fossiliferous metamorphic rocks. Analysis of detrital zircons from 17 metasedimentary rock samples yielded a composite age distribution that ranges from Archean to Jurassic and has significant peaks at ~2,800 2,400 mega-annum (Ma), 2,100–1,600 Ma, and ~300–200 Ma. The Proterozoic and Archean ages indicate derivation from continental sources in ancestral North America, whereas the late Paleozoic and Mesozoic ages are interpreted as derived from a magmatic arc that began to develop along the continental margin in Permian to Triassic time.
The 17 detrital zircon samples are from quartzitic and conglomeratic rocks of the Carbide, Williams Well, and Noble Well formations, which were informally named by T.H. McCulloh in 1960. The zircon data indicate that the oldest rocks in the Carbide formation are quartzites likely correlative with the Ordovician Eureka Quartzite of the Cordilleran miogeocline. These rocks lie structurally above the rest of the Carbide formation, different units of which yielded zircons that indicate maximum depositional ages ranging from middle Paleozoic to Late Triassic. Zircons from the Williams Well and Noble Well formations indicate maximum depositional ages of late Paleozoic and Early Jurassic, respectively. The Noble Well formation is interpreted to correlate with the lithologically similar, Early Jurassic, Fairview Valley Formation of the Black and Quartzite Mountain areas some 60 km to the southwest.
The above interpretations depend on the presumption that the detrital zircons in these samples did not undergo extreme, postdepositional lead loss, which would result in misleadingly young ages. Although such lead loss is considered unlikely for these samples, further work could test the validity of this interpretation.
Zircons from six additional samples were also analyzed: (1) a quartzite from which all the zircons are interpreted to have formed by Late Jurassic metamorphism; (2) three samples interpreted as albitized igneous rocks of Middle Permian age; and (3) two samples interpreted as fine-grained monzonite to diorite of Late Jurassic age. Both sets of igneous rocks were initially thought to be metasedimentary but were reinterpreted as igneous largely on the basis of the zircon data.
Based on the interpretations presented here, this study demonstrates that the depositional, magmatic, and deformational history of the El Paso terrane was longer and more complex than previously thought and will require reevaluation of existing tectonic models involving this terrane.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221115","usgsCitation":"Stone, P., Cecil, M.R., Brown, H.J., and Vazquez, J.A., 2023, Geochronologic and geochemical data from metasedimentary and associated rocks in the Lane Mountain area, San Bernardino County, California: U.S. Geological Survey Open-File Report 2022–1115, 34 p., https://doi.org/10.3133/ofr20221115.","productDescription":"Report: vi, 34 p.; Data Release","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-126391","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":414958,"rank":7,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2022/1115/ofr20221115_table5.pdf","text":"Table 5","size":"1 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- SHRIMP-RG U-Pb zircon data for samples analyzed for this report, Lane Mountain area."},{"id":414957,"rank":6,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2022/1115/ofr20221115_table4.pdf","text":"Table 4","size":"3 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- LA-SF-ICPMS U-Pb zircon data for samples analyzed for this report, Lane Mountain area."},{"id":414900,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1115/covrthb.jpg"},{"id":414901,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1115/ofr20221115.pdf","text":"Report","size":"7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Open-File Report 2022–1115"},{"id":414902,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20211094","text":"Open-File Report 2021-1094","description":"Stone, P., Brown, H.J., Cecil, M.R., Fleck, R.J., Vazquez, J.A., and Fitzpatrick, J.A., 2021, Geochronologic, isotopic, and geochemical data from pre-Cretaceous plutonic rocks in the Lane Mountain area, San Bernardino County, California: U.S. Geological Survey Open-File Report 2021–1094, 74 p., https://doi.org/10.3133/ofr20211094.","linkHelpText":"- Geochronologic, Isotopic, and Geochemical Data from Pre- Cretaceous Plutonic Rocks in the Lane Mountain Area, San Bernardino County, California"},{"id":414903,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20191070","text":"Open-File Report 2019-1070","description":"Stone, P., Brown, H.J., Cecil, M.R., Fleck, R.J., Vazquez, J.A., Fitzpatrick, J.A., and Rosario, J., 2019, Geochronologic, isotopic, and geochemical data from igneous rocks in the Lane Mountain area, San Bernardino County, California: U.S. Geological Survey Open-File Report 2019–1070, 34 p., https://doi.org/10.3133/ofr20191070.","linkHelpText":"- Geochronologic, Isotopic, and Geochemical Data from Igneous Rocks in the Lane Mountain Area, San Bernardino County, California"},{"id":499724,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114618.htm","linkFileType":{"id":5,"text":"html"}},{"id":414899,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9G6YNEF","text":"Tabular geochronologic and geochemical data from metasedimentary and associated rocks in the Lane Mountain area, San Bernardino County, California","description":"Stone, P., Cecil, M.R., and Vazquez, J.A., 2023, Tabular geochronologic and geochemical data from metasedimentary and associated rocks in the Lane Mountain area, San Bernardino County, California: U.S. Geological Survey data release, https://doi.org/10.5066/P9G6YNEF."}],"country":"United States","state":"California","county":"San Bernardino County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -116.50673206071878,\n 34.67301889093439\n ],\n [\n -116.50673206071878,\n 35.322960316934655\n ],\n [\n -117.53351206069043,\n 35.322960316934655\n ],\n [\n -117.53351206069043,\n 34.67301889093439\n ],\n [\n -116.50673206071878,\n 34.67301889093439\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Contact Information,
Geology, Minerals, Energy, & Geophysics Science Center
Menlo Park, California
U.S. Geological Survey
Building 19, 350 N. Akron Rd.
P.O. Box 158
Moffett Field, CA 94035
Phytoplankton are an important and limiting food source in the Sacramento-San Joaquin Delta and San Francisco Bay. The decline of phytoplankton biomass is one potential factor in the decline of the protected Hypomesus transpacificus (delta smelt) and other pelagic organisms. The bivalves Corbicula fluminea and Potamocorbula amurensis (hereafter C. fluminea and P. amurensis, respectively) have been shown to control phytoplankton biomass in several locations throughout the San Francisco Bay and the Sacramento-San Joaquin Delta; therefore, knowledge of their distribution and population dynamics are of great interest.
Here, we describe the distribution and dynamics of bivalve biomass using samples collected by the California Department of Water Resources (DWR) as part of the benthic monitoring program in 2019. One element of DWR’s and the Bureau of Reclamation’s Environmental Monitoring Program—the Generalized Random Tessellation Stratified (GRTS) program—examines the spatial and temporal extent of C. fluminea and P. amurensis control on phytoplankton. Historically, the GRTS program sampled 175 benthic stations (50 stations that are monitored every year and 125 randomly selected new stations that are changed yearly) throughout the Sacramento-San Joaquin Delta and northern San Francisco Bay (San Pablo and Suisun Bays) during one week in May and October. In 2019, only the 50 annually replicated stations were sampled.
Corbicula fluminea and P. amurensis biomass and grazing rates had similar trends; therefore, the conclusions regarding biomass are applied to grazing rate data as well. Corbicula fluminea biomass decreased from May to October, whereas P. amurensis average biomass (reported increased from May (1 g ash-free-dry-tissue mass/square meter (g AFDM/m2) to October (2 g AFDM/m2). Although C. fluminea’s average biomass was lower in October (10 gAFDM/m2) than in May (20 gAFDM/m2), the highest single biomass value was also observed in October (300 gAFDM/m2). In both May and October, most stations that recorded high C. fluminea biomass values were located in the deep water (≥3 m of depth between the surface of the water and the surface of the substrate on the bottom) and were sampled in either rivers or sloughs. A relation between depth and biomass was not observed for P. amurensis.
Both C. fluminea and P. amurensis recruitment (recruits are considered animals ≤2.5mm in length in this study and recruitment is the process of recruits successfully settled to the bottom) increased from May to October. The total number of C. fluminea recruits more than doubled from May to October, whereas P. amurensis total recruitment increased by 8-fold during the same period. Most P. amurensis recruits in May can be attributed to one station, whereas the recruits in October were found at 14 stations. A relation between number of recruits and station depth was not evident for either C. fluminea or P. amurensis.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221102","collaboration":"Prepared in cooperation with California Department of Water Resources","usgsCitation":"Zierdt Smith, E.L., Shrader, K.H., Thompson, J.K., Parchaso, F., Gehrts, K., and Wells, E., 2023, Bivalve effects on the food web supporting delta smelt—A spatially intensive study of bivalve recruitment, biomass, and grazing rate patterns with varying freshwater outflow in 2019: U.S. Geological Survey Open-File Report 2022–1102, 15 p., https://doi.org/10.3133/ofr20221102.","productDescription":"Report: vi, 15 p.; Data Release","numberOfPages":"15","onlineOnly":"Y","ipdsId":"IP-120563","costCenters":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"links":[{"id":414835,"rank":1,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93BAY64","description":"Zierdt Smith, E.L., Shrader, K.H., Parchaso, F., and Thompson, J.K., 2021, A spatially and temporally intensive sampling study of benthic community and bivalve metrics in the Sacramento-San Joaquin Delta (ver. 2.0, May 2021): U.S. Geological Survey data release, https://doi.org/10.5066/P93BAY64.","linkHelpText":"A spatially and temporally intensive sampling study of benthic community and bivalve metrics in the Sacramento-San Joaquin Delta (ver. 2.0, May 2021)"},{"id":414837,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1102/covrthb.jpg"},{"id":414838,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1102/ofr20221102.pdf","text":"Report","size":"7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Open-File Report 2022–1102"},{"id":415721,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20221101","text":"Open-File Report 2022-1101","linkHelpText":"- Bivalve Effects on the Food Web Supporting Delta Smelt—A One-Year Study of Bivalve Recruitment, Biomass, and Grazing Rate Patterns with Varying Freshwater Outflow"},{"id":499721,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114617.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.32432978338892,\n 37.803391256717845\n ],\n [\n -121.87545670853471,\n 37.791400721304846\n ],\n [\n -121.29205898127825,\n 37.80121221377027\n ],\n [\n -121.31951299197254,\n 38.399657702215876\n ],\n [\n -122.30511197590273,\n 38.40180916920502\n ],\n [\n -122.32432978338892,\n 37.803391256717845\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director,
Water Resources, Earth System Processes Division
U.S. Geological Survey
411 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
The Chesapeake Bay Program (CBP) has operated a geographic information system (GIS) program since the early 1990s to address the established and growing need for and use of geospatial data, maps, and analysis within the CBP Partnership. This report is intended to detail the standard operating procedures of the CBP GIS program and address the quality assurance, quality control, and other technical activities that CBP will implement to ensure the commitment of the CBP GIS Team to performance standards (U.S. Environmental Protection Agency, 2003). The report is intended as an update to the 2011 Quality Assurance Project Plan (QAPP). For specialized tasks or analytical projects beyond the scope of this QAPP, a separate specialized QAPP with details on quality control, assurance procedures, and the geospatial methods associated with all aspects of the project may be required.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231007","collaboration":"Prepared in cooperation with the University of Maryland Center for Environmental Science","usgsCitation":"Wolf, J., Ahmed, L., Claggett, P., Fitch, A., Irani, F., McDonald, S., Strong, D., Thompson, R., and Wei, Z., 2023, Geospatial standard operating procedures of the Chesapeake Bay Program: U.S. Geological Survey Open-File Report 2023–1007, 22 p., https://doi.org/10.3133/ofr20231007.","productDescription":"vi; 22 p.","numberOfPages":"22","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-116901","costCenters":[{"id":242,"text":"Eastern Geographic Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":37759,"text":"VA/WV Water Science Center","active":true,"usgs":true}],"links":[{"id":414217,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1007/coverthb.jpg"},{"id":414218,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1007/ofr20231007.pdf","text":"Report","size":"1.08 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1007"},{"id":414219,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231007/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2023-1007"},{"id":414220,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1007/ofr20231007.XML"},{"id":414221,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1007/images/"}],"contact":"Director, Lower Mississippi-Gulf Water Science Center
U.S. Geological Survey
640 Grassmere Park Drive
Nashville, TN 37211
For more than 25 years, the U.S. Geological Survey (USGS) has used the remote-sensing capabilities of United States National Imagery Systems (USNIS) to obtain high-resolution electro-optical imagery to monitor Earth’s response to global environmental change. A major focus has been monitoring sea ice behavior in the Arctic Ocean and its marginal seas. In 1997 and 1998, under the direction of the Global Fiducials Program (GFP), USNIS imagery was collected during the Surface Heat Budget of the Arctic Ocean (SHEBA) Project. In 1999, collection of USNIS imagery of six static sea ice sites in the Arctic Ocean and its marginal seas began, and the imagery was archived in the USGS-hosted Global Fiducials Library (GFL). The static sites were imaged through 2014, creating time series of geographically referenced images which scientists have used to study seasonal changes in Arctic ice over the same locations for extended time periods. In early 2009, the Central Intelligence Agency’s MEDEA Program requested that the USGS use USNIS imagery to track movements of sea ice floes during an entire Arctic summer (April through September). The goal was to improve researchers’ understanding of seasonal changes in Arctic sea ice. In order to track and repeatedly capture imagery of the same ice as it drifted across the Arctic Ocean, the USGS developed a methodology and a series of protocols to use data from telemetering drift buoys deployed at locations across the Arctic Ocean by the International Arctic Buoy Programme (IABP) to track the drift of targeted ice masses for periods that exceeded a year. Resulting time series of sea ice imagery, captured while monitoring 38 individual buoys, were archived in the GFL. In 2013 and 2014, in support of the Seasonal Ice Zone Reconnaissance Surveys (SIZRS) Program led by the University of Washington, Seattle, Washington, the USGS requested the collection of USNIS imagery of selected sites in the Beaufort and Chukchi Seas located at every degree of latitude between 70º and 80º N. along a north-south transect. This was done to track and understand the interplay among the ice, atmosphere, and ocean and what it contributes to the rapid decline in summer ice extent that has occurred in recent years. Under the auspices of the GFP, thousands of sea ice images have been collected. Many of those that pass a quality and cloud-cover screening are archived in the GFL. Of these, more than 1,750 sea ice images have been publicly released, following an editing and processing procedure that produces high-resolution degraded images, known as “literal imagery-derived products” or LIDPs. These LIDPs have been approved for free, unrestricted public distribution and scientific analysis. The LIDPs can be downloaded from the USGS Global Fiducials Library Data Access Portal (USGS GFLDAP) at https://www.usgs.gov/global-fiducials-library-data-access-portal. In addition, nonliteral imagery-derived products (nonliteral IDPs), such as metadata, maps, charts, and graphs, have also been released.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231008","usgsCitation":"Molnia, B.F., and Wilson, E.M., 2023, Documenting Arctic sea ice dynamics with Global Fiducials Program imagery: U.S. Geological Survey Open-File Report 2023–1008, 32 p., https://doi.org/10.3133/ofr20231008.","productDescription":"viii, 32 p.","numberOfPages":"32","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-129958","costCenters":[{"id":36171,"text":"National Civil Applications Center","active":true,"usgs":true}],"links":[{"id":499733,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114471.htm","linkFileType":{"id":5,"text":"html"}},{"id":413704,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1008/images/"},{"id":413703,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1008/ofr20231008.XML"},{"id":413702,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231008/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2023-1008"},{"id":413701,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1008/ofr20231008.pdf","text":"Report","size":"37.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1008"},{"id":413700,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1008/coverthb.jpg"}],"contact":"Director, National Civil Applications Center
U.S. Geological Survey
12201 Sunrise Valley Drive, MS 562
Reston, VA 20192
Email: cac@usgs.gov
The U.S. Geological Survey Earth Resources Observation and Science Calibration and Validation (Cal/Val) Center of Excellence (ECCOE) focuses on improving the accuracy, precision, calibration, and product quality of remote-sensing data, leveraging years of multiscale optical system geometric and radiometric calibration and characterization experience. The ECCOE Landsat Cal/Val Team continually monitors the geometric and radiometric performance of active Landsat missions and makes calibration adjustments, as needed, to maintain data quality at the highest level.
This report provides observed geometric and radiometric analysis results for Landsats 7–8 for quarter 3 (July–September) of 2022. All data used to compile the Cal/Val analysis results presented in this report are freely available from the U.S. Geological Survey EarthExplorer website: https://earthexplorer.usgs.gov.
One specific activity that the ECCOE Landsat Cal/Val Team closely monitored was the lowering of the Landsat 7 orbit. On April 6, 2022, the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) sensor was placed into standby mode, and a series of spacecraft burns was completed through the month of April to lower the satellite’s orbit by 8 kilometers. Imaging resumed at a lower orbit of 697 kilometers on May 5, 2022, extending the science mission to allow for essential data acquisition during the 2022 Northern Hemisphere fire and growing season. Additional information about the Landsat 7 orbit lowering is here: https://www.usgs.gov/centers/eros/news/landsat-7-lowered-standard-landsat-orbit#:~:text=The%20satellite's%20primary%20science%20mission%20has%20ended&text=On%20April%206%2C%202022%2C%20the,satellite's%20orbit%20by%208%20kilometers.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231013","usgsCitation":"Haque, M.O., Rengarajan, R., Lubke, M., Hasan, M.N., Shrestha, A., Tuli, F.T., Shaw, J.L., Denevan, A., Franks, S.,\nMicijevic, E., Choate, M.J., Anderson, C., Thome, K., Kaita, E., Barsi, J., Levy, R., and Miller, J., 2023, ECCOE Landsat\nquarterly Calibration and Validation report—Quarter 3, 2022: U.S. Geological Survey Open-File Report 2023–1013, 38 p., https://doi.org/10.3133/ofr20231013.","productDescription":"Report: vii, 38 p.; Dataset","numberOfPages":"50","onlineOnly":"Y","ipdsId":"IP-146519","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":413661,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1013/images"},{"id":413659,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1013/coverthb.jpg"},{"id":413663,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1013/ofr20231013.XML","text":"Report","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2022-1013"},{"id":413662,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://earthexplorer.usgs.gov","text":"USGS database","linkHelpText":"—EarthExplorer"},{"id":413660,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1013/ofr20231013.pdf","text":"Report","size":"3.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1013"}],"contact":"Director, Earth Resources Observation and Science Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
Condit Dam was removed from river kilometer (rkm) 5.3 of the White Salmon River, Washington, in 2011 and 2012 after blocking upstream passage of anadromous fish for nearly 100 years. The dam removal opened habitat upstream and improved habitat downstream with addition of cobble and gravel to a reach depauperate of spawning and rearing habitat. We assessed juvenile anadromous salmonid abundance and distribution in the subbasin from 2016 through 2021 to evaluate the efficacy of natural recolonization. We sampled for outmigrant smolts and other life-history stages at a rotary screw trap at rkm 2.3 and for juvenile abundance at sites in Buck and Rattlesnake Creeks, two primary tributaries upstream from the former dam location.
We estimated smolt abundance of steelhead (Oncorhynchus mykiss) and coho salmon (O. kisutch) at the screw-trap site during most years of the study. High flow and missed trapping days in 2017 precluded estimates, and the trap was not fished during 2020 because of the onset of the COVID-19 pandemic. Steelhead smolt-abundance estimates ranged from 3,581 to 5,851 fish; coho salmon smolt-abundance estimates ranged from 1,093 to 1,773 fish, although in 2021, only 2 coho salmon smolt were captured and no estimate was made.
Other species and life stages also were captured in the screw trap. Steelhead and coho salmon fry and parr, and Chinook salmon (O. tshawytscha) fry were captured, indicating the presence and likely use of improved habitat downstream from the former dam site by multiple life stages and spawning success upstream from the screw-trap site. Chinook salmon fry were captured, indicating spawning success upstream from the screw-trap site. Fry numbers varied greatly by day and year. Yearly variation in Chinook and coho salmon fry numbers may have been influenced by high flows following spawning causing redd scour and egg-to-fry mortality. Three bull trout (Salvelinus confluentus) were caught in the screw trap, one in June 2018, one in June 2019, and one in June 2021. All three bull trout showed smolt characteristics and were tagged with passive integrated transponders (PITs). The bull trout captured in June 2018 was detected at Bonneville Dam Corner Collector several days later, indicating likely anadromy. We also captured lamprey in the screw trap: 44 during 2018, 31 during 2019, and 11 during 2021; we believe most were adult brook lamprey (Lampetra richardsoni), although some could have been Pacific lamprey (Entosphenus tridentatus) macropthalmia.
We confirmed the presence of juvenile steelhead (through smolt origin data) and coho salmon in Mill, Buck, and Rattlesnake Creeks, which are all upstream from the former site of Condit Dam. Juvenile salmonid abundance sampling at a site in Buck Creek during 2016–20 indicated the presence of juvenile coho salmon in all years except 2020. Total salmonid abundance (steelhead and coho salmon combined) at the Buck Creek site each year exceeded abundance in sampling prior to dam removal in 2009 and 2010. Juvenile salmonid abundance sampling in Rattlesnake Creek during 2016–20 indicated the presence of juvenile coho salmon in 2017, 2018, and 2019. Total juvenile salmonid abundance at the Rattlesnake Creek site was highly variable, sometimes exceeding and sometimes less than abundance prior to dam removal during 2001–05. During the period covered by this report, adult salmonid returns to the Columbia River were decreasing, largely because of marine survival. The extent to which this basin-wide decrease affected adult returns and juvenile populations in the White Salmon River subbasin is not known.
Despite a period of poor marine survival, PIT-tagged smolt and juvenile steelhead and coho salmon from the screw trap and tributaries returned to Bonneville Dam. Smolt-to-adult return rates from the screw trap to Bonneville Dam were similar to those in other nearby rivers during this period. However, data are still incomplete for some years and sample sizes were low. Future tagging and monitoring would be beneficial to track this valuable metric.
Genetic samples from steelhead smolt and parr collected at the screw trap and some main-stem electrofishing during 2016 were analyzed for Genetic Stock Identification (GSI) by CRITFC. Preliminary data showed that White Salmon River fish were the most common at about 42 percent, with 19 percent typing to Hood River, Oregon stock, and about 26 percent typing to Skamania stock, a common hatchery stock in the area. Winter and summer runs were represented in the samples.
Juvenile salmonid sampling in the White Salmon River, Washington, following removal of Condit Dam, demonstrated that anadromous salmonids are using newly opened habitat upstream from the former dam site and improved lower river habitat. Steelhead and coho salmon smolts are being produced upstream from the former dam site, and some have returned to Bonneville Dam as adults. Chinook salmon spawning upstream from our smolt trap site are producing fry. These results are encouraging for success of the strictly natural recolonization strategy. However, declines in anadromous runs to the larger Columbia River Basin also likely have affected the White Salmon runs and our data may not reflect full capacity of the White Salmon River subbasin juvenile production. Continued abundance, distribution, and GSI monitoring will help to track the evolution of anadromous fish in the White Salmon River under a natural recolonization strategy.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221117","collaboration":"Prepared in cooperation with Yakama Nation Fisheries and Mid-Columbia Fisheries Enhancement Group","usgsCitation":"Jezorek, I.G., and Hardiman, J.M., 2023, Juvenile salmonid monitoring to assess natural recolonization following removal of Condit Dam on the White Salmon River, Washington, 2016–21: U.S. Geological Survey Open-File Report 2022–1117, 23 p., https://doi.org/10.3133/ofr20221117.","productDescription":"vi, 23 p.","onlineOnly":"Y","ipdsId":"IP-137364","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":413140,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1117/coverthb.jpg"},{"id":413143,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1117/images"},{"id":413142,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221117/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2022-1117"},{"id":413141,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1117/ofr20221117.pdf","text":"Report","size":"1.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1117"},{"id":499726,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114378.htm","linkFileType":{"id":5,"text":"html"}},{"id":413144,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1117/ofr20221117.XML"}],"country":"United States","state":"Washington","otherGeospatial":"White Salmon River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.78283038944755,\n 46.100301136884156\n ],\n [\n -121.78283038944755,\n 45.67990372212273\n ],\n [\n -121.22276550358751,\n 45.67990372212273\n ],\n [\n -121.22276550358751,\n 46.100301136884156\n ],\n [\n -121.78283038944755,\n 46.100301136884156\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
Terrestrial sediment discharging from watersheds off West Maui, Hawaiʻi, has been documented as a primary stressor to local coral reefs, causing coral reef health to decline. The U.S. Geological Survey acquired and analyzed physical oceanographic and sedimentologic field data off the coast of West Maui to calibrate and validate physics-based, numerical hydrodynamic and sediment transport models of the study area developed by Deltares. These models simulated terrestrial sediment transport and dispersal from West Maui watersheds into coastal waters and how terrestrial sediment affects nearby coral reefs under different oceanographic forcing and watershed restoration scenarios.
Wave energy and near-bed turbidity are positively correlated in the field observations, illustrating a process not captured by the model simulations in which sediment already deposited on the seabed is resuspended by wave action and subsequently transported by prevailing currents. In the model simulations, large waves during flood events led to a decrease in suspended-sediment concentrations. Notably, however, the model results only consider sediment entering coastal waters from five stream sources and do not simulate sediment already present on the seabed.
The model simulations project that the Honokeana and Māhinahina coral reefs would experience the greatest reduction in sediment impacts from theoretical watershed restoration. Additionally, when large waves coincide with flood events, post-storm sedimentation generally decreases in the nearshore region, but increases in the region offshore of the reefs. The measured and modeled sediment dynamics demonstrate a demarcation between the coral reefs sheltered within embayments (Honolua reef) or behind points (Wahikuli reef) and those along the relatively open coastline between Kapalua and Kāʻanapali (Kapalua, Honokeana, Māhinahina, and Honokōwai reefs). The sheltered sites are affected by terrestrial sediment from single stream mouths, where most sediment is delivered within hours of a flood (rain) event. Once this sediment enters the nearshore, it settles out and remains within the reef area for a prolonged period owing to a lack of wave or current-driven bed shear stress. Thus, the primary effect of sediment on the reefs within these sheltered areas is sedimentation. In contrast, coral reefs along the unsheltered (or “open”) section of coastline (between Kapalua and Kāʻanapali) are more exposed to waves and terrestrial sediment from multiple stream sources. At these reefs, fine-grained terrestrial sediment can rarely settle but instead remains in suspension. Thus, even long after a flood event has occurred, these sites chronically experience light attenuation from suspended sediment.
These analyses underscore the importance of understanding how coastal ocean waves and circulation can lead to different sediment dynamics and stressors for coral reefs along the same region of the West Maui coastline. These differing factors indicate that the most effective watershed restoration and mitigation strategies may vary among the different coral reefs and streams. An important next step is to determine how the science of this study can support management goals for these coral reefs: what are target reductions of sedimentation, suspended-sediment concentrations, or the resulting light attenuation? Then, using the coupled hydrodynamic-sediment model, we can examine which watershed restoration scenarios in each stream will best achieve those targets.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221121","collaboration":"Prepared in cooperation with the Deltares Impacts of Extreme Weather Strategic Research Program","programNote":"Coastal and the Marine Hazards and Resources Program","usgsCitation":"Storlazzi, C.D., Cheriton, O.M., Cronin, K.M., van der Heijden, L.H., Winter, G., Rosenberger, K.J., Logan, J.B., and McCall, R.T., 2023, Observations of coastal circulation, waves, and sediment transport along West Maui, Hawaiʻi (November 2017–March 2018), and modeling effects of potential watershed restoration on decreasing sediment loads to adjacent coral reefs: U.S. Geological Survey Open-File Report 2022–1121, 73 p., https://doi.org/10.3133/ofr20221121.","productDescription":"Report: ix, 73 p.; 2 Data Releases","onlineOnly":"Y","ipdsId":"IP-138761","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":412766,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P914LMK2","text":"USGS data release","description":"USGS data release","linkHelpText":"Model parameter input files to compare effects of stream discharge scenarios on sediment deposition and concentrations around coral reefs off west Maui, Hawaii"},{"id":412765,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9DK9O60","text":"USGS data release","description":"USGS data release","linkHelpText":"Time series data of oceanographic conditions from West Maui, Hawaii, 2017-2018 Coral Reef Circulation and Sediment Dynamics Experiment"},{"id":412764,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1121/ofr20221121.pdf","text":"Report","size":"17.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1121"},{"id":412763,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1121/coverthb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"West Maui","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -156.72475140864907,\n 20.922050876041368\n ],\n [\n -156.5888533113449,\n 20.922050876041368\n ],\n [\n -156.5888533113449,\n 21.0514971765583\n ],\n [\n -156.72475140864907,\n 21.0514971765583\n ],\n [\n -156.72475140864907,\n 20.922050876041368\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Center Director, Pacific Coastal and Marine Science Center
U.S. Geological Survey
2885 Mission Street
Santa Cruz, CA 95060
The U.S. Geological Survey (USGS) provides reliable science, data, information, and models (hereafter collectively referred to as “information”) to describe and understand the Earth. This information is used to minimize loss of life and property from natural disasters; manage water, biological, energy, and mineral resources; and enhance and protect quality of life. USGS science informs public and private decisions, operations, and risk management in all major United States economic sectors, as defined by the Bureau of Economic Analysis, and provides critical information for natural resource and natural hazard management and stewardship decisions. Understanding the value of scientific information supports applications of USGS science in land- and water-management decisions, and better informs the public about the return on investment of USGS programs. USGS economists, social scientists, and physical scientists are engaged in collaborative efforts to advance methods to estimate the value of information (VOI) produced by the USGS. These efforts involve collaborating with an international community to develop and refine estimation methods, establish best practices to determine VOI, develop a study repository, and conduct projects to assess the VOI of specific information products and their application. This report focuses on economic valuation conducted by USGS specifically, although the methodology has much broader applicability within the U.S. government, academia, and beyond. Noneconomic valuation techniques for assessing the VOI also exist but are not addressed in this report.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20231011","usgsCitation":"Pindilli, E., Chiavacci, S., and Straub, C., 2023, The value of scientific information—An overview: U.S. Geological Survey Open-File Report 2023–1011, 5 p., https://doi.org/10.3133/ofr20231011.","productDescription":"iii, 5 p.","numberOfPages":"5","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-146764","costCenters":[{"id":554,"text":"Science and Decisions Center","active":true,"usgs":true}],"links":[{"id":412985,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20231011/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2023-1011"},{"id":412987,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1011/ofr20231011.XML"},{"id":412950,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1011/ofr20231011.pdf","text":"Report","size":"1.73 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1011"},{"id":412949,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1011/coverthb.jpg"},{"id":412986,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1011/images/"}],"contact":"Science and Decisions Center
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
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 nine needs (hereinafter, “Needs”) identified under the Sagebrush and Sage-Grouse topic in the Plan. The topic outlined research Needs broadly focused on understanding sagebrush rangelands and population dynamics important for the conservation and management of sage-grouse and other sagebrush-reliant wildlife species. 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 (in other words, addressed poorly) in the literature through 2020. Our searches resulted in the inclusion of 333 science products that at least partially addressed a Need identified in the Sagebrush and Sage-Grouse topic. The Needs that were well and partially addressed included:
Needs addressed poorly included:
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/ofr20231010","collaboration":"Prepared in cooperation with Bureau of Land Management and the U.S. Fish and Wildlife Service","usgsCitation":"Holloran, M.J., Anthony, C.R., 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—Sagebrush and sage-grouse topic, 2015–20: U.S. Geological Survey Open-File Report 2023–1010, 49 p., https://doi.org/10.3133/ofr20231010.","productDescription":"v, 49 p.","onlineOnly":"Y","ipdsId":"IP-141294","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":412990,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1010/ofr20231010.pdf","text":"Report","size":"5.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1010"},{"id":412989,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1010/coverthb.jpg"},{"id":412992,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1010/images"},{"id":412993,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1010/ofr20231010.XML"},{"id":413029,"rank":6,"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":413030,"rank":7,"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":499736,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114938.htm","linkFileType":{"id":5,"text":"html"}},{"id":418555,"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":413028,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20231003","text":"OFR 2023-1003 —","description":"Related work","linkHelpText":"Integrated rangeland fire management strategy actionable science plan completion assessment—Invasives topic, 2015–20"}],"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, Fort Collins Science Center
2150 Centre Avenue, Bldg C
Fort Collins, CO 80526
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 eight needs (hereinafter known as “Needs”) identified under the Fire topic in the Plan, defined as any non-structure fire that occurs in vegetation or natural fuels, including wildfires and prescribed fires. The topic outlined research Needs broadly focused on understanding the mechanisms and management of threats posed to the maintenance of large, contiguous sagebrush rangelands by fire. 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 (in other words., addressed poorly) in the literature through 2020. Our searches resulted in the inclusion of 156 science products that at least partially addressed a Need identified in the Fire topic. The Needs that were well and partially addressed included:
Needs addressed poorly included:
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/ofr20231009","collaboration":"Prepared in cooperation with Bureau of Land Management and the U.S. Fish and Wildlife Service","usgsCitation":"Holloran, M.J., Anthony, C.R., 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—Fire topic, 2015–20: U.S. Geological Survey Open-File Report 2023–1009, 31 p., https://doi.org/10.3133/ofr20231009.","productDescription":"vi, 31 p.","onlineOnly":"Y","ipdsId":"IP-141295","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":418552,"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":413027,"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":413026,"rank":6,"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":413025,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20231003","text":"OFR 2023-1003 —","description":"Related work","linkHelpText":"Integrated rangeland fire management strategy actionable science plan completion assessment—Invasives topic, 2015–20"},{"id":413017,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1009/ofr20231009.XML"},{"id":413016,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1009/images"},{"id":413014,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1009/ofr20231009.pdf","text":"Report","size":"5.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1009"},{"id":413013,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1009/coverthb.jpg"},{"id":418557,"rank":9,"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":499734,"rank":10,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114345.htm","linkFileType":{"id":5,"text":"html"}}],"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, Fort Collins Science Center
2150 Centre Avenue, Bldg C
Fort Collins, CO 80526
Loss and degradation of sagebrush rangelands due to an accelerated invasive annual grass-wildfire cycle and other stressors are substantial 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 10 needs (hereinafter “Needs”) identified under the Restoration topic in the Plan. The topic outlined research Needs for improving restoration success in degraded sagebrush rangelands. 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 371 science products that at least partially addressed a Need identified in the Restoration topic. The Needs that were well and partially addressed included:
Needs that were not addressed well included:
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/ofr20231004","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—Restoration topic, 2015–20: U.S. Geological Survey Open-File Report 2023–1004, 44 p., https://doi.org/10.3133/ofr20231004.","productDescription":"iv, 44 p.","onlineOnly":"Y","ipdsId":"IP-141195","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":413023,"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":413022,"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":412634,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2023/1004/images"},{"id":412632,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2023/1004/ofr20231004.pdf","text":"Report","size":"4.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2023-1004"},{"id":412635,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2023/1004/ofr20231004.XML"},{"id":412826,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20231003","text":"OFR 2023-1003 —","description":"Related work","linkHelpText":"Integrated rangeland fire management strategy actionable science plan completion assessment—Invasives topic, 2015–20"},{"id":412631,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2023/1004/coverthb.jpg"},{"id":499731,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_114344.htm","linkFileType":{"id":5,"text":"html"}},{"id":418551,"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"}],"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
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