The first author, Gary S. Fuis, conducted this mapping in the summer of 1967 in partial fulfillment of the entry requirements into the Ph.D program of the Division of Geological and Planetary Sciences of the California Institute of Technology, Pasadena, Calif. The area mapped lies wholly within the Fort Rock Ranch, a private ranch spanning ~50 square miles in Mohave and Yavapai Counties, Arizona. Access to the ranch is limited, and it is uncertain whether a detailed geologic map of the Aquarius Mountains can be recreated today. Therefore, we are making this map available to the public in this Open-File Report.
The original mapping was compiled on an enlarged single aerial photograph at an approximate scale of 1:15,600. The second author, J. Luke Blair, photogrammetrically rectified the original map and added modern topography, which was not available at the time the original map was completed. Modern roads and drainages were also added, including I–40, built after the original map was completed. Both authors reformatted the original map using current USGS geologic map standards.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221016","usgsCitation":"Fuis, G.S, and Blair, J.L., 2022, Preliminary geologic map of early Miocene felsic eruptive centers in the Aquarius Mountains, west-central Arizona: U.S. Geological Survey Open-File Report 2022-1016, scale 1:15,000, https://doi.org/10.3133/ofr20221016.","productDescription":"1 Sheet: 65.39 × 42.11 inches","numberOfPages":"1","onlineOnly":"Y","ipdsId":"IP-123374","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":501761,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112843.htm","linkFileType":{"id":5,"text":"html"}},{"id":397987,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1016/covrthb.jpg"},{"id":397988,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2022/1016/ofr20221016_sheet.pdf","size":"26 MB","linkFileType":{"id":1,"text":"pdf"}}],"scale":"15000","country":"United States","state":"Arizona","otherGeospatial":"Aquarius Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -113.73046875,\n 34.86001735420488\n ],\n [\n -113.10,\n 34.86001735420488\n ],\n [\n -113.10,\n 35.3\n ],\n [\n -113.73046875,\n 35.3\n ],\n [\n -113.73046875,\n 34.86001735420488\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information, Menlo Park, Calif.
Office—Earthquake Science Center
U.S. Geological Survey
345 Middlefield Road, MS 977
Menlo Park, CA 94025
The U.S. Geological Survey (USGS) calculated discharge at 13 water control structures in Florida using theoretical equations and uncalibrated coefficients gathered from previous studies and typical textbook values for selected flow regimes and structure types. These discharges were compared to the real-time discharges calculated and published by the USGS from October 1, 2007, to September 30, 2019, using traditional methods and coefficients verified by direct discharge measurements. The theoretical and USGS-calculated daily mean discharges were compared at each structure for different flow regimes covering the entire range of discharges that occurred over the study period except those less than 10 cubic feet per second to avoid large percentage errors for small actual differences in discharge. The discharges were also not compared if (1) any alterations were made to the USGS discharge to account for factors such as debris or construction, (2) any values were missing throughout the day, (3) the flow regime changed during the day, or (4) the USGS discharge was estimated. The structures compared include a mixture of vertical lift and radial gates with free and submerged conditions for orifice and weir flow.
The study totals showed that the average absolute difference for all structures was 18.7 percent. Average percent differences ranged from −26.5 to 28.6 percent, and 4 of the 13 structures had average differences within 10 percent.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221011","usgsCitation":"Ryan, P.J., and Hazelbaker, C.L., 2022, Comparison of computed flow through manually operated water control structures in Florida using theoretical versus calibrated coefficients: U.S. Geological Survey Open-File Report 2022–1011, 25 p., https://doi.org/10.3133/ofr20221011.","productDescription":"Report: vii, 25 p.; Data Release; Dataset","numberOfPages":"38","onlineOnly":"Y","ipdsId":"IP-129610","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":501757,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112754.htm","linkFileType":{"id":5,"text":"html"}},{"id":397688,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1011/coverthb.jpg"},{"id":397689,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1011/ofr20221011.pdf","text":"Report","size":"3.35 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1011"},{"id":397691,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1011/ofr20221011.XML"},{"id":397692,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1011/images"},{"id":397693,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9MHF0GD","text":"USGS data release","linkHelpText":"Data for the comparison of computed flow through manually operated water control structures in Florida using theoretical versus calibrated coefficients"},{"id":397695,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":397885,"rank":7,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221011/full","text":"Report","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.9248046875,\n 28.70986084394286\n ],\n [\n -83.1884765625,\n 28.110748760633534\n ],\n [\n -82.33154296875,\n 26.03704188651584\n ],\n [\n -81.23291015625,\n 25.443274612305746\n ],\n [\n -80.13427734374999,\n 25.383735254706842\n ],\n [\n -79.73876953125,\n 26.725986812271756\n ],\n [\n -80.22216796875,\n 28.323724553546015\n ],\n [\n -81.03515625,\n 29.496987596535742\n ],\n [\n -83.38623046875,\n 29.49698759653577\n ],\n [\n -82.9248046875,\n 28.70986084394286\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Caribbean-Florida Water Science Center
U.S. Geological Survey
4446 Pet Lane, Suite 108
Lutz, FL 33559
Monitoring discharge in the Chicago Sanitary and Ship Canal is critical for the accounting done by the U.S. Army Corps of Engineers of the diversion of water from Lake Michigan to the Mississippi River Basin by the State of Illinois. The primary streamgage used for this discharge monitoring, the Chicago Sanitary and Ship Canal near Lemont, Illinois (U.S. Geological Survey station 05536890), is operated by the U.S. Geological Survey as an index-velocity station and at the time of this study (water years 2006–16) had two continuous velocity meters (an acoustic Doppler velocity meter and an acoustic velocity meter) and a water-level sensor, among other instruments. Discharge is computed at the streamgage using an index-velocity rating developed by linear regression of the velocity meter values fitted to discharges intermittently measured with an acoustic Doppler current profiler. In this study, the uncertainties of the velocity meters and stage sensors were estimated using a type B (judgment-based) approach, and measured discharge uncertainties were taken from those provided by a common acoustic Doppler current profiler data processing software tool, QRev. The velocity meter uncertainties, expressed as standard deviations, were estimated to be about 2.5 percent of velocity except near zero, where they exceeded that fraction, whereas for the acoustic Doppler current profiler uncertainties, when converted to mean channel velocity, 2.5 percent of velocity was determined to be a lower bound. The estimated velocity meter and measured discharge uncertainties were compared to index-velocity ratings developed from regression analyses of two types: (1) those that allow specification of measurement uncertainties and (2) ordinary least squares (OLS) regression, which does not. Based on the linearity of the index-velocity rating and the approximate agreement of the distributions of the fitting and prediction velocities, the assumptions required for unbiased prediction by OLS regression were determined to be approximately satisfied. From the regression residuals, it was determined that the estimated measurement uncertainties are too small, too similar between acoustic velocity meter and acoustic Doppler velocity meter velocities, and possibly too strongly dependent on velocity. Large, non-Gaussian OLS regression residuals also were observed. The uncertainty of annual mean discharge computed using the different regressions also was considered and was determined to be strongly dependent on the assumed measurement uncertainty. Because the assumptions required for OLS regression to give unbiased and variance-maintaining predictions were determined to be approximately satisfied, the results of discharge computation using the index-velocity rating based on OLS regression were deemed to be reliable. These results indicate about 0.8-percent uncertainty in the computed discharge as measured by the coefficient of variation at the annual time scale when using the acoustic Doppler velocity meter and 1.2-percent uncertainty with the acoustic velocity meter. It may be possible to improve the accuracy of the computed discharge and its uncertainty by further examining the measurement uncertainties and addressing differences in the distributions of the velocities used in fitting the index-velocity ratings and those used in prediction. Although the index-velocity ratings and computed discharges presented in this study are similar to those used in computing the published discharge at the study streamgage, the values presented in this report are not intended to replace the published discharge.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221007","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Chicago District","usgsCitation":"Over, T.M., Muste, M., Duncker, J.J., Tsai, H., Jackson, P.R., Johnson, K.K., Engel, F.L., and Prater, C.D., 2022, Uncertainty analysis of index-velocity meters and discharge computations at the Chicago Sanitary and Ship Canal near Lemont, Illinois, water years 2006–16: U.S. Geological Survey Open-File Report 2022–1007, 35 p., https://doi.org/10.3133/ofr20221007.","productDescription":"Report: viii, 35 p.; Appendix; Data Release; Dataset","numberOfPages":"48","onlineOnly":"Y","ipdsId":"IP-125889","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":501754,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112755.htm","linkFileType":{"id":5,"text":"html"}},{"id":397713,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7X63K41","text":"USGS data release","linkHelpText":"Discharge measurements at U.S. Geological Survey streamgage 05536890 Chicago Sanitary and Ship Canal near Lemont, Illinois, 2005–2013"},{"id":397709,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2022/1007/ofr20221007_appendix2.pdf","text":"Appendix 2","size":"7.03 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1007 appendix 2","linkHelpText":"—Slides"},{"id":397714,"rank":7,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":397708,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1007/ofr20221007.pdf","text":"Report","size":"13.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1007"},{"id":397712,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1007/images"},{"id":397711,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1007/ofr20221007.XML"},{"id":397707,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1007/coverthb.jpg"}],"country":"United States","state":"Illinois","city":"Lemont","otherGeospatial":"Chicago Sanitary and Ship Canal","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.06846618652344,\n 41.66573093599398\n ],\n [\n -88.04718017578125,\n 41.64469659784919\n ],\n [\n -87.86796569824217,\n 41.699063978799174\n ],\n [\n -87.75672912597656,\n 41.789744876718984\n ],\n [\n -87.7979278564453,\n 41.83068856472101\n ],\n [\n -87.92701721191406,\n 41.75645886225854\n ],\n [\n -88.06709289550781,\n 41.6908605241911\n ],\n [\n -88.06846618652344,\n 41.66573093599398\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
405 North Goodwin Ave.
Urbana, IL 61801
The U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) 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), 2021. All data used to compile the Cal/Val analysis results presented in this report are freely available from the USGS EarthExplorer website: https://earthexplorer.usgs.gov.
One specific activity that the Cal/Val Team continued to closely monitor this quarter was the Landsat 8 Thermal Infrared Sensor (TIRS) response degradation, which has been observed since the two November 2020 safehold events. Detailed analysis results characterizing this degradation have been included in this report. Additional information about the safehold events is here: https://www.usgs.gov/core-science-systems/nli/landsat/november-19-2020-landsat-8-data-availability-update-recent-safehold.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221025","usgsCitation":"Micijevic, E., Rengarajan, R., Haque, M.O., Lubke, M., Tuli, F.T.Z., Shaw, J.L., Hasan, N., Denevan, A., Franks, S., Choate, M.J., Anderson, C., Markham, B., Thome, K., Kaita, E., Barsi, J., Levy, R., and Ong, L., 2022, ECCOE Landsat quarterly Calibration and Validation report—Quarter 3, 2021: U.S. Geological Survey Open-File Report 2022–1025, 38 p., https://doi.org/10.3133/ofr20221025.","productDescription":"Report: vii, 38 p.; Dataset","numberOfPages":"50","onlineOnly":"Y","ipdsId":"IP-134677","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":397609,"rank":6,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221025/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":397606,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://earthexplorer.usgs.gov","text":"U.S. Geological Survey database","linkHelpText":"—EarthExplorer"},{"id":397605,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1025/images"},{"id":397604,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1025/ofr20221025.XML"},{"id":397603,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1025/ofr20221025.pdf","text":"Report","size":"2.32 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1025"},{"id":397602,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1025/coverthb.jpg"}],"contact":"Director, Earth Resources Observation and Science Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
This study is part of the Coastal Protection and Restoration Authority (CPRA) Louisiana Barrier Island Comprehensive Monitoring (BICM) program. The goal of the BICM program is to provide long-term data on the barrier islands of Louisiana for monitoring change and assisting in coastal management. The BICM program uses historical data and acquires new data to map and monitor shoreline position, sediment properties, topography, bathymetry, and habitat. Since 2006, the U.S. Geological Survey (USGS) has collected geophysical and sedimentologic data across the Breton National Wildlife Refuge (BNWR) through the BICM program and collaborative USGS projects such as the Barrier Island Evolution Research project (under CPRA contract number 2000339324, BICM2–Chandeleurs TopoBathy DEM), which builds upon the previous BICM physical assessment of the BNWR outlined in a separate report. This project uses topographic and bathymetric data from three periods (1917–1922, 2006–2007, and 2013–2015) to develop digital elevation models (DEMs), measure elevation change, and calculate sediment budgets for the barrier island system. The sediment budget analysis, derived from the volumetric change between the three periods, is necessary for understanding sediment transport dynamics along barrier islands and providing information for effective coastal management. This report describes the methods used to acquire, process, and produce these products.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221020","collaboration":"Prepared in cooperation with the Coastal Protection and Restoration Authority of Louisiana","programNote":"Louisiana Barrier Island Comprehensive Monitoring Program 2015–2020","usgsCitation":"Flocks, J.G., Forde, A.S., and Bernier, J.C., 2022, Chandeleur Islands to Breton Island bathymetric and topographic datasets and operational sediment budget development—Methodology and analysis report: U.S. Geological Survey Open-File Report 2022–1020, 48 p., https://doi.org/10.3133/ofr20221020.","productDescription":"ix, 48 p.","numberOfPages":"48","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-122915","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":397352,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/ofr20231020/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":397307,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1020/coverthb.jpg"},{"id":397308,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1020/ofr20221020.pdf","text":"Report","size":"47.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1020"},{"id":397309,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1020/images/"},{"id":397310,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1020/ofr20221020.XML"},{"id":501765,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112713.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Louisiana","otherGeospatial":"Breton Island, Breton National Wildlife Refuge, Chandeleur Islands, Curlew Shoals, Grand Gosier Shoals, Gulf of Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.22477722167967,\n 29.351656186711196\n ],\n [\n -88.83064270019531,\n 29.438999582891338\n ],\n [\n -88.61228942871094,\n 29.685070141332993\n ],\n [\n -88.59992980957031,\n 29.956124387148986\n ],\n [\n -88.72833251953125,\n 30.19439868711761\n ],\n [\n -89.09431457519531,\n 30.064934211006477\n ],\n [\n -89.00230407714844,\n 29.854341876042557\n ],\n [\n -89.14306640625,\n 29.664189403696138\n ],\n [\n -89.36073303222656,\n 29.467101009006807\n ],\n [\n -89.22477722167967,\n 29.351656186711196\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
Data were collected at two monitoring sites along the Little Arkansas River in south-central Kansas that bracket most of the easternmost part of the Equus Beds aquifer. The data were used as part of the city of Wichita’s aquifer storage and recovery project to evaluate source water quality. The U.S. Geological Survey, in cooperation with the City of Wichita, has continued to monitor the water quality of these sites through 2019 to update previously published regression-based models using continuously measured physicochemical properties and discretely sampled water-quality constituents of interest. The purpose of this report is to provide an update of the previously published linear regression models that have been used to continuously compute estimates of water-quality constituent concentrations or densities at these two sites. Water-quality constituent model updates include those for dissolved and suspended solids, suspended-sediment concentration, hardness, alkalinity, primary ions (bicarbonate, calcium, sodium, chloride, and sulfate), nutrients (total Kjeldahl nitrogen and total phosphorus), total organic carbon, indicator bacteria (Escherichia coli and fecal coliform bacteria), a trace element (arsenic), and a pesticide (atrazine).
Regression analyses were used to develop surrogate models that related continuously measured physicochemical properties, streamflow, and seasonal components to discretely sampled water-quality constituent concentrations or densities. Specific conductance was an explanatory variable for dissolved solids, primary ions, and atrazine. Turbidity was an explanatory variable for total suspended solids and sediment, nutrients, total organic carbon, and indicator bacteria. Streamflow and water temperature were explanatory variables for dissolved arsenic. Seasonal components were included as explanatory variables for atrazine models. The amount of variance explained by most of the updated models was within 5 percent of previously published models.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221010","collaboration":"Prepared in cooperation with the City of Wichita, Kansas","usgsCitation":"Stone, M.L., and Klager, B.J., 2022, Documentation of models describing relations between continuous real-time and discrete water-quality constituents in the Little Arkansas River, south-central Kansas, 1998–2019: U.S. Geological Survey Open-File Report 2022–1010, 34 p., https://doi.org/10.3133/ofr20221010.","productDescription":"Report: vii, 34 p.; 2 Appendixes; Dataset","numberOfPages":"46","onlineOnly":"Y","ipdsId":"IP-126572","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":397345,"rank":8,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/ofr20221010/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":397333,"rank":7,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":397331,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2022/1010/ofr20221010_appendix1.zip","text":"Appendix 1","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"—Model Archive Summaries for the Little Arkansas River at Highway 50 near Halstead, Kansas (Halstead Site; U.S. Geological Survey Station Number 07143672)"},{"id":501756,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112715.htm","linkFileType":{"id":5,"text":"html"}},{"id":397330,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1010/images"},{"id":397332,"rank":6,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/of/2022/1010/ofr20221010_appendix2.zip","text":"Appendix 2","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"—Model Archive Summaries for the Little Arkansas River near Sedgwick, Kansas (Sedgwick Site; U.S. Geological Survey Station Number 07144100)"},{"id":397329,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1010/ofr20221010.XML"},{"id":397328,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1010/ofr20221010.pdf","text":"Report","size":"1.82 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1010"},{"id":397327,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1010/coverthb.jpg"}],"country":"United States","state":"Kansas","otherGeospatial":"Little Arkansas River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.1667,\n 37.714244967649265\n ],\n [\n -97.1667,\n 37.714244967649265\n ],\n [\n -97.1667,\n 38.533333\n ],\n [\n -98.1667,\n 38.533333\n ],\n [\n -98.1667,\n 37.714244967649265\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Kansas Water Science Center
U.S. Geological Survey
1217 Biltmore Drive
Lawrence, KS 66049
The Cherry Hill 7.5-minute quadrangle straddles the Coastal Plain and Piedmont Provinces along the Tidewater Fall Line. Rocks of the eastern Piedmont Roanoke Rapids terrane crop out in the western part of the quadrangle and consist of greenschist- to amphibolite-facies Neoproterozoic felsic to intermediate metavolcanic rocks, some of which contain flattened quartz phenocrysts and are locally isoclinally folded; greenstone that locally preserves primary layering; and intrusive metadiorite and metagabbro, much of which has been altered to amphibolite. Most of these rocks are strongly foliated and jointed. Greenschist-facies metasiltstone that preserves primary bedding also occurs locally in the Roanoke Rapids terrane. Neoproterozoic mica schist, middle Paleozoic foliated metagranite, and late Paleozoic massive and porphyritic granite crop out in the eastern part of the quadrangle and are part of the Dinwiddie terrane and the late Paleozoic De Witt pluton. Upper greenschist- to lower amphibolite-facies mica schist consists of stringers and boudins of vein quartz and contains porphyroclasts of staurolite that preserve an earlier foliation as inclusion trails. Porphyroblasts of garnet, staurolite, and kyanite also occur locally. Foliation in granites of the De Witt pluton may be magmatic. Separating the Dinwiddie terrane from the Roanoke Rapids terrane are greenschist-facies, highly strained granitic mylonite and bodies of less deformed granite within the Nottoway River fault zone, which is a strand of the eastern Piedmont fault system. Paleozoic pegmatite dikes and quartz veins cross-cut rocks of the Dinwiddie terrane, and quartz veins and Jurassic diabase dikes cross-cut rocks of the Roanoke Rapids terrane.
Sand and gravel deposits of the Atlantic Coastal Plain overlie Piedmont rocks. Two units assigned to the upper part of the Neogene Chesapeake Group occur at elevations up to 295 feet (90 meters) above sea level atop the Richmond plain in the central part of the quadrangle. Two units of the Quaternary Bacons Castle Formation occupy the Essex plain and Norge uplands at elevations up to 180 feet (55 meters) above sea level in the eastern part of the quadrangle. In the western part of the quadrangle, multiple levels of terrace deposits are the fluvial equivalent of estuarine to marine units of the Atlantic Coastal Plain to the east. Holocene alluvium occurs along creeks and the Nottoway River. Quaternary colluvial deposits occur locally. Numerous Carolina bays pock the landscape of the Richmond and Essex plains, and three abandoned channelways represent former locations of Sappony Creek, one of the major drainages of the quadrangle.
Brittle faults juxtapose Piedmont basement rocks against Neogene sediments of the upper part of the Chesapeake Group. These Cenozoic faults were first uncovered in mine excavations in the late 1990s; new mapping indicates that many of these faults are reactivated silicified cataclasite zones that occur throughout the Piedmont basement rocks. Silicified cataclasites and associated quartz veins are typically mineralized with iron and iron sulfide minerals. The quadrangle was the focus of extensive mining for heavy minerals, including ilmenite and zircon, in upland Atlantic Coastal Plain deposits beginning in the mid-1990s. Other mineral resources, including precious metals, clay for structural brick, crushed stone, and building stone for millstones, have also been prospected or quarried in the quadrangle.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211106","usgsCitation":"Carter, M.W., Karst, A.T., Berquist, C.R., Jr., Schindler, J.S., Weems, R.E., Weinmann, B.R., and Crider, E.A., Jr., 2022, Preliminary geologic map of the Cherry Hill quadrangle, Dinwiddie, Sussex, and Greensville Counties, Virginia: U.S. Geological Survey Open-File Report 2021–1106, 1 sheet, scale 1:24,000, https://doi.org/10.3133/ofr20211106.","productDescription":"1 Sheet: 40.00 x 54.01 inches; Data Release","numberOfPages":"1","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-118811","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":391751,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1106/coverthb.jpg"},{"id":394115,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P910X7BJ","text":"USGS data release","linkHelpText":"Database for the Preliminary Geologic Map of the Cherry Hill Quadrangle, Dinwiddie, Sussex, and Greensville Counties, Virginia"},{"id":391752,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1106/ofr20211106.pdf","text":"Report","size":"10.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1106"},{"id":501531,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112547.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Virginia","county":"Dinwiddie County, Sussex County, Greensville County","otherGeospatial":"Cherry Hill quadrangle","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.625,\n 36.875\n ],\n [\n -77.50,\n 36.875\n ],\n [\n -77.50,\n 37.00\n ],\n [\n -77.625,\n 37.00\n ],\n [\n -77.625,\n 36.875\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Florence Bascom Geoscience Center
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
Releases of water from Flaming Gorge Dam together with climate-related variations in runoff determine the streamflow regime of the Green River, which affects the physical characteristics of the channel and riparian ecosystem of the Green River corridor in Canyonlands National Park. The dam has decreased peak streamflows and raised base streamflows, resulting in vegetation encroachment and channel narrowing and simplification, which could be detrimental to endangered fish habitats over time. Operations of Flaming Gorge Dam are in part determined by flow recommendations provided by the Upper Colorado River Basin Endangered Fish Recovery Program that are designed to benefit native fish and disadvantage nonnative fish. These recommendations alone may not be sufficient to prevent channel narrowing and simplification. Increases in base flows may contribute to channel narrowing and simplification by increasing the water available to riparian vegetation and reducing the water volume available for increasing peak-flow magnitude or duration This report describes how proposed revisions to these flow recommendations would affect the physical characteristics of the Green River corridor in Canyonlands National Park, with a focus on riparian vegetation and channel width.
Hydrologic conditions for the Green River downstream from Flaming Gorge Dam are classified by the U.S. Department of the Interior Bureau of Reclamation as dry, moderately dry, average, moderately wet, or wet. The flow recommendations for peak-flow magnitude and duration in wet years are consistent with geomorphic objectives and historical post-dam flows. In moderately wet years, although the recommended peaks may be sufficient to prevent narrowing over the short term, these peaks are lower than historical post-dam peak flows for moderately wet years and could therefore allow reduction in the occasional large peaks necessary to maintain sediment mobility and channel complexity. For average and drier years, the recommendations allow, but do not require, peak-flow magnitude and durations that are likely to achieve geomorphic objectives.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221019","collaboration":"Prepared in cooperation with Canyonlands National Park","usgsCitation":"Grams, P.E., Friedman, J.M., Dean, D.J., and Topping, D.J., 2022, The effects of requested flows for native fish on sediment dynamics, geomorphology, and riparian vegetation for the Green River in Canyonlands National Park, Utah: U.S. Geological Survey Open-File Report 2022–1019, 20 p., https://doi.org/10.3133/ofr20221019.","productDescription":"vi, 20 p.","numberOfPages":"20","onlineOnly":"Y","ipdsId":"IP-126163","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":501764,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112531.htm","linkFileType":{"id":5,"text":"html"}},{"id":396864,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1019/ofr20221019.pdf","text":"Report","size":"5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":396863,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1019/covrthb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"Green River, Canyonlands National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.4730224609375,\n 38.19502155795575\n ],\n [\n -109.64630126953125,\n 38.19502155795575\n ],\n [\n -109.64630126953125,\n 39.1833042481843\n ],\n [\n -110.4730224609375,\n 39.1833042481843\n ],\n [\n -110.4730224609375,\n 38.19502155795575\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"The goal of the Louisiana Barrier Island Comprehensive Monitoring (BICM) program is to provide long-term data on coastal Louisiana for monitoring change and assisting in coastal management. This study (carried out under Coastal Protection and Restoration Authority contract number 2000339324, BICM2—Chenier TopoBathy DEM) builds upon the previous BICM physical assessment of the Chenier Plain region using bathymetric data from three periods (1930, 2007, and 2017) to develop digital elevation models for historical and current periods. In addition to bathymetric datasets, the study includes light detection and ranging elevation measurements along the coastline to produce elevation datasets for the 2007 and 2017 periods. This report describes the methods used to acquire, process, and produce these products.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221014","collaboration":"Prepared in cooperation with Coastal Protection and Restoration Authority of Louisiana","programNote":"Louisiana Barrier Island Comprehensive Monitoring Program 2015–2020","usgsCitation":"Flocks, J.G., Forde, A.S., and Bernier, J.C., 2022, Chenier Plain region bathymetric and topographic datasets: Methodology report: U.S. Geological Survey Open-File Report 2022–1014, 21 p., https://doi.org/10.3133/ofr20221014.","productDescription":"vii, 21 p.","numberOfPages":"21","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-122902","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":501759,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112530.htm","linkFileType":{"id":5,"text":"html"}},{"id":396683,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1014/ofr20221014.pdf","text":"Report","size":"6.62 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1014"},{"id":396682,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1014/coverthb.jpg"},{"id":396685,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1014/images/"},{"id":396684,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1014/ofr20221014.XML"},{"id":396704,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20221014/full","text":"Report","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Louisiana","otherGeospatial":"Chenier Plain","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.85620117187499,\n 29.439597566602902\n ],\n [\n -92.1258544921875,\n 29.439597566602902\n ],\n [\n -92.1258544921875,\n 29.8\n ],\n [\n -93.85620117187499,\n 29.8\n ],\n [\n -93.85620117187499,\n 29.439597566602902\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
The Floyd River and Little Sioux River Basins in northwestern Iowa flooded on June 21–July 1, 2018, after sustained rainfall on June 14–27, 2018. Within the Floyd River Basin, rainfall totals from June 14 to 21 preceding flooding were 3.01 inches (in.) at Le Mars, 4.50 in. at Orange City, and 7.44 in. at Sheldon. Within the Little Sioux River Basin, rainfall amounts for the 2-week period from June 14 to 27 preceding flooding were 11.29 in. at Lake Park, 12.95 in. at Milford, 5.56 in. at Spencer, 7.71 in. at Sioux Rapids, and 6.13 in. at Cherokee. Flooding in the Floyd River Basin resulted in a recorded maximum peak discharge of 14,300 cubic feet per second (ft3/s; annual exceedance probability [AEP] estimate between 4 and 10 percent) at the U.S. Geological Survey (USGS) streamgage Floyd River at Alton, Iowa (06600100), and a recorded maximum peak discharge of 9,180 ft3/s (AEP estimate greater than 10 percent) at the USGS streamgage Floyd River at James, Iowa (06600500). Flooding in the Little Sioux River Basin resulted in a recorded maximum peak discharge of 16,300 ft3/s (AEP estimate between 4 and 10 percent) at the USGS streamgage Little Sioux River at Linn Grove, Iowa (06605850), and maximum peak discharges of 18,700 ft3/s (AEP estimate greater than 10 percent) and 20,000 ft3/s (AEP estimate greater than 10 percent) were recorded at the USGS streamgages Little Sioux River at Correctionville, Iowa (06606600), and Little Sioux River near Turin, Iowa (06607500), respectively. High-water mark elevations were surveyed at 19 locations along the Floyd River and 22 locations along the Little Sioux River to develop 2 flood profiles: a 52.5-mile profile along the Floyd River from State Highway 3 at Le Mars to U.S. Highway 18 at Sheldon that includes the USGS streamgage Floyd River at Alton and a 101-mile profile along the Little Sioux River from U.S. Highway 59 at Cherokee to U.S. Highway 18 north of Spencer that includes the USGS streamgage Little Sioux River at Linn Grove.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221015","collaboration":"Prepared in cooperation with the Iowa Department of Transportation and the Iowa Highway Research Board (Project HR–140)","usgsCitation":"O’Shea, P.S., Wilson, J.L., Vegrzyn, J.C., and Barnes, K.K., 2022, Floods of June 21–July 1, 2018, in the Floyd River and Little Sioux River Basins, northwestern Iowa: U.S. Geological Survey Open-File Report 2022–1015, 35 p., https://doi.org/10.3133/ofr20221015.","productDescription":"Report: ix, 35 p.; 2 Data Releases; Dataset","numberOfPages":"48","onlineOnly":"N","ipdsId":"IP-111461","costCenters":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":396505,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1015/coverthb.jpg"},{"id":396510,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9V8NO0H","text":"USGS data release","linkHelpText":"Peak-flow frequency analysis for seven selected U.S. Geological Survey streamgages in the Floyd and Little Sioux River Basins, Iowa, based on data through water year 2019"},{"id":396508,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1015/images"},{"id":396507,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1015/ofr20221015.XML","size":"189 kB","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2022–1015 XML"},{"id":396506,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1015/ofr20221015.pdf","text":"Report","size":"9.39 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022–1015"},{"id":501760,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112527.htm","linkFileType":{"id":5,"text":"html"}},{"id":396512,"rank":7,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"—USGS water data for the Nation"},{"id":396511,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9W7VP64","text":"USGS data release","linkHelpText":"Peak-flow frequency analysis for three selected streamgages in the Cedar and Little Sioux River Basins, Iowa, based on data through water year 2019"}],"country":"United States","state":"Iowa","otherGeospatial":"Floyd River and Little Sioux River Basins","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.6192626953125,\n 42.407234661551875\n ],\n [\n -95.701904296875,\n 42.407234661551875\n ],\n [\n -95.701904296875,\n 43.5326204268101\n ],\n [\n -96.6192626953125,\n 43.5326204268101\n ],\n [\n -96.6192626953125,\n 42.407234661551875\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
400 South Clinton Street, Suite 269
Iowa City, IA 52240
On December 23, 2021, groundwater levels were measured in selected wells in the Hālawa area, O‘ahu, Hawai‘i, constituting a synoptic groundwater-level survey (shortened herein to “synoptic survey”) of the area. Groundwater levels were measured mainly from 9:00 a.m. to 12:00 p.m. (times listed in Hawai‘i standard time) and provide a snapshot of groundwater levels during the survey period. Following a reported fuel release that affected groundwater quality in the Red Hill area, several production wells were shut down in the weeks prior to the synoptic survey. These wells include the Red Hill Shaft (shut down on November 28, 2021) and the Hālawa Shaft (shut down on December 3, 2021, except for weekly, short-duration operations for water-quality sampling). Groundwater levels measured in wells during the synoptic survey ranged from 16.34 to 19.77 feet above mean sea level.
The groundwater levels collected during the multiagency synoptic survey contain uncertainty because of several potential sources of error associated with (1) the accuracy of the measuring tapes used, (2) the accuracy of the measuring-point altitude at the top of each well, (3) well plumbness and alignment, (4) human error, and (5) changing conditions during the survey period. Because of these potential sources of error, comparability of groundwater-level measurements may be affected. Some of the sources of uncertainty can be addressed and lead to improved accuracy and comparability of the groundwater levels. For example, uncertainty associated with the measuring-point altitudes can be addressed by resurveying measuring-point altitudes to a common vertical datum using consistent surveying methods.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221018","collaboration":"Prepared in cooperation with the U.S. Navy","usgsCitation":"Nakama, R.K., Mitchell, J.N., and Oki, D.S., 2022, December 23, 2021, Red Hill synoptic groundwater-level survey, Hālawa area, O‘ahu, Hawai‘i: U.S. Geological Survey Open-File Report 2022–1018, 10 p., https://doi.org/10.3133/ofr20221018.","productDescription":"Report: v, 10 p.; Data Release","numberOfPages":"10","onlineOnly":"Y","ipdsId":"IP-137125","costCenters":[{"id":525,"text":"Pacific Islands Water Science Center","active":true,"usgs":true}],"links":[{"id":396393,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1018/covrthb.jpg"},{"id":396394,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1018/ofr20221018.pdf","text":"Report","size":"8 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":401563,"rank":4,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20221048","text":"Open-File Report 2022-1048","description":"Nakama, R.K., Mitchell, J.N., and Oki, D.S., 2022, January 18, 2022, Red Hill synoptic groundwater-level survey, Hālawa area, O‘ahu, Hawai‘i: U.S. Geological Survey Open-File Report 2022–1048, 11 p., https://doi.org/10.3133/ofr20221048.","linkHelpText":"- January 18, 2022, Red Hill Synoptic Groundwater-Level Survey, Hālawa Area, O‘ahu, Hawai‘i"},{"id":396395,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS water data for the nation","description":"U.S. Geological Survey, 2022, USGS water data for the nation: U.S. Geological Survey National Water Information database, https://doi.org/10.5066/F7P55KJN"},{"id":501763,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112526.htm","linkFileType":{"id":5,"text":"html"}},{"id":404438,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20221069","text":"Open-File Report 2022-1069","description":"Nakama, R.K., Mitchell, J.N., and Oki, D.S., 2022, Groundwater-level monitoring from January 17 to March 3, 2022, Hālawa area, O‘ahu, Hawai‘i: U.S. Geological Survey Open-File Report 2022–1069, 29 p., https://doi.org/10.3133/ofr20221069.","linkHelpText":"- Groundwater-Level Monitoring from January 17 to March 3, 2022, Hālawa Area, O‘ahu, Hawai‘i"}],"country":"United States","state":"Hawaii","otherGeospatial":"O‘ahu, Hālawa area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -157.95867919921875,\n 21.332873489271286\n ],\n [\n -157.86117553710938,\n 21.332873489271286\n ],\n [\n -157.86117553710938,\n 21.410883719938866\n ],\n [\n -157.95867919921875,\n 21.410883719938866\n ],\n [\n -157.95867919921875,\n 21.332873489271286\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Pacific Islands Water Science Center
U.S. Geological Survey
Inouye Regional Center
1845 Wasp Blvd., B176
Honolulu, HI 96818
The Blythe 30' x 60' quadrangle in southeastern California and southwestern Arizona displays complex geology that includes Mesozoic contractional deformation, metamorphism, and magmatism in addition to Cenozoic extensional deformation and magmatism. Previous geologic map compilations predate recent geologic mapping efforts that have contributed new insights into the stratigraphy and structure of this quadrangle. This new map, compiled in collaboration with the Arizona Geological Survey, incorporates these recent mapping efforts to provide an updated depiction of the quadrangle’s geologic framework. The scope of this map is limited to bedrock units of Miocene and older age because younger deposits have not been mapped in enough detail across the quadrangle to support a systematic compilation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211097","collaboration":"Prepared in Cooperation with the Arizona Geological Survey","usgsCitation":"Stone, P., Spencer, J.E., and Beard, L.S., comps., 2022, Preliminary bedrock geologic map of the Blythe 30' x 60' quadrangle, California and Arizona: U.S. Geological Survey Open-File Report 2021–1097, 1 sheet, scale 1:100,000, 10-p. pamphlet, https://doi.org/10.3133/ofr20211097.","productDescription":"Report: iv, 10 p., 1 Sheet; 50.42 x 33.06: Data Release","numberOfPages":"10","additionalOnlineFiles":"Y","ipdsId":"IP-100416","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":396064,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YUU64Z","description":"Stone, P., Spencer, J.E., and Beard, L.S., 2022, Digital data for the preliminary bedrock geologic map of the Blythe 30’ x 60’ quadrangle, California and Arizona: U.S. Geological Survey data release, https://doi.org/10.5066/P9YUU64Z.","linkHelpText":"Digital data for the preliminary bedrock geologic map of the Blythe 30’ x 60’ quadrangle, California and Arizona"},{"id":501529,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112445.htm","linkFileType":{"id":5,"text":"html"}},{"id":396063,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2021/1097/ofr20211097_sheet.pdf","size":"20 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":396062,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1097/ofr20211097_pamphlet.pdf","text":"Pamphlet","size":"3 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":396061,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1097/covrthb.jpg"}],"country":"United States","state":"Arizona, California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115.00,\n 33.30\n ],\n [\n -114.00,\n 33.30\n ],\n [\n -114.00,\n 34.00\n ],\n [\n -115.00,\n 34.00\n ],\n [\n -115.00,\n 33.30\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information,
Geology, Minerals, Energy, & Geophysics Science Center
Menlo Park, California
U.S. Geological Survey
345 Middlefield Road
Menlo Park, CA 94025-3591
Surveys and monitoring for the endangered Least Bell’s Vireo (Vireo bellii pusillus; vireo) were done at the San Luis Rey Flood Risk Management Project Area (Project Area) in the city of Oceanside, San Diego County, California, between April 4 and August 4, 2021. We completed four protocol surveys during the breeding season, supplemented by weekly territory monitoring visits. We identified a total of 122 territorial male vireos; 111 were confirmed as paired and 8 were confirmed as single males. For the remaining three territories, we were unable to confirm pair status. Five transient vireos were detected in 2021. The vireo population in the Project Area decreased by 24 percent from 2020 to 2021. Vireo populations decreased across San Diego County, with a 14-percent decrease documented at Marine Corps Base Camp Pendleton (MCBCP); a 5-percent decrease on the Otay River; a 6-percent decrease on the middle San Luis Rey River; and a 44-percent decrease at Marine Corps Air Station (although this decrease was likely exaggerated by large-scale vegetation clearing that occurred prior to the 2021 breeding season).
We used an index of treatment (Treatment Index) to evaluate the impact of on-going vegetation clearing on the Project Area vireo population. The Treatment Index measures the cumulative effect of vegetation treatment within a territory (since 2005) by using the percent area treated weighted by the number of years since treatment. We found that the Treatment Index for unoccupied habitat was more than two times that of occupied habitat, indicating that vireos selected less treated habitat in which to settle.
We monitored vireo nests at three general site types: (1) within the flood channel where exotic and native vegetation removal has occurred regularly (Channel), (2) three sites next to the flood channel where limited exotic and native vegetation removal has occurred (Off-channel), and (3) three sites that have been actively restored by planting native vegetation (Restoration). Nesting activity was monitored in 85 territories, 8 of which were occupied by single males. Of the completed nests, 39 percent were successful, and nest success did not differ among the three sites. Clutch size was greater in the Channel than the Off-channel sites, and the proportion of hatchlings that fledged was greater in Off-channel sites than Channel and Restoration sites. There were no other nest-level differences detected among site types, nor were there any differences in territory-level measures of productivity (young fledged per pair, double-brooding) among the sites. Overall, breeding success and productivity were slightly lower in 2021 than in 2020, with 66 percent of pairs fledgling at least one young and pairs fledging an average of 1.9±1.7 young.
To investigate if the cumulative years of treatment had an impact on vireo reproductive effort, we looked at the effects of the Treatment Index on reproductive parameters. Results from generalized linear models indicated that treatment did not have an effect on vireo nesting effort or the number of vireo fledglings per pair produced in 2021. Similarly, our analysis of nest survival for 2021 revealed no effect of Treatment Index on daily survival rate.
Analysis of vegetation data collected at vireo nests from 2006 to 2021 did not indicate an effect of vegetation at the nest on daily survival rate. We also found no differences in nest-placement characteristics among site types or successful/unsuccessful nests.
Red/arroyo willow (Salix laevigata or Salix lasiolepis) was the species most commonly selected for nesting by vireos in all three site types. Black willow (Salix gooddingii) and mule fat (Baccharis salicifolia) also were commonly used. Vireos used a wider variety of species for nesting in Channel and Off-channel sites (seven and eight species, respectively) compared with Restoration sites (three species).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221012","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Los Angeles District","programNote":"Ecosystems Mission Area—Species Management Research Program","usgsCitation":"Houston, Alexandra , Allen, L.D., Pottinger, R.E., and Kus, B.E., 2022, Least Bell's Vireos and Southwestern Willow Flycatchers at the San Luis Rey flood risk management project area in San Diego County, California: Breeding activities and habitat use—2021 Annual report: U.S. Geological Survey Open-File Report 2022–1012, 79 p., https://doi.org/10.3133/ofr20221012.","productDescription":"viii, 79 p.","numberOfPages":"79","onlineOnly":"Y","ipdsId":"IP-135579","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":396128,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1012/covrthb.jpg"},{"id":396129,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1012/ofr20221012.pdf","text":"Report","size":"7 Mb"},{"id":396130,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1012/ofr20221012.xml"},{"id":396131,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1012/images"}],"country":"United States","state":"California","county":"San Diego County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.41500854492188,\n 33.19301824551205\n ],\n [\n -117.17056274414064,\n 33.19301824551205\n ],\n [\n -117.17056274414064,\n 33.288350918671775\n ],\n [\n -117.41500854492188,\n 33.288350918671775\n ],\n [\n -117.41500854492188,\n 33.19301824551205\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
The snail kite (Rostrhamus sociabilis plumbeus), an endangered, wetland-dependent raptor, is highly sensitive to changes in hydrology. Climate-driven changes in water level will likely affect snail kite populations—altering reproductive success and survival rates. Identifying the mechanisms mediating the direct and indirect effects of climate on snail kite populations and the range of future climate conditions is important to the conservation of this species. When water levels are low, snail kite nest initiation and nest success decrease owing to decreased availability of their primary prey applesnails (Pomacea spp.), unstable nesting sites, and increased predator access. Dry events also lead to decreased adult and juvenile survival. In the next 80 years, temperatures and potential evapotranspiration are projected to increase in central and southern Florida. Although future precipitation volume is more uncertain, increased temperatures and evaporative loss may lead to increased frequency, duration, and severity of low-water events. Additionally, rapidly rising water levels have adverse effects on snail kite reproductive success—destroying nests, preventing access to apple snails, and reducing apple snail productivity. Finally, it is likely that future climate will favor more frequent dry conditions and extreme heavy rainfall events, both of which are directly linked to decreased reproductive success and survival. The potential effects of climate change may be buffered by the availability of alternative prey (non-native applesnails) that are more tolerant of anticipated conditions. In highly controlled southern Florida waterbodies, regional water-management decisions may buffer or exacerbate waterbody accession and recession rates.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211104A","usgsCitation":"Lyons, M.P., LeDee, O.E., and Boyles, R., 2021, Potential effects of climate change on snail kites (Rostrhamus sociabilis plumbeus) in Florida: U.S. Geological Survey Open-File Report 2021–1104–A, 12 p., https://doi.org/10.3133/ofr20211104A.","productDescription":"vi, 12 p.","numberOfPages":"22","onlineOnly":"Y","ipdsId":"IP-131203","costCenters":[{"id":565,"text":"Southeast Climate Science Center","active":true,"usgs":true}],"links":[{"id":393183,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1104/a/images"},{"id":393182,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1104/a/ofr20211104A.XML","size":"75.8 kB","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2021–1104 XML"},{"id":393181,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1104/a/ofr20211104A.pdf","text":"Report","size":"5.56 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021–1104"},{"id":393180,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1104/a/coverthb3.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Everglades National Park, Lake Okeechobee, Kissimmee Chain of Lakes","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.0791015625,\n 25.64152637306577\n ],\n [\n -80.408935546875,\n 25.64152637306577\n ],\n [\n -80.408935546875,\n 26.204734267107604\n ],\n [\n -81.0791015625,\n 26.204734267107604\n ],\n [\n -81.0791015625,\n 25.64152637306577\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.287841796875,\n 26.598351182358293\n ],\n [\n -80.496826171875,\n 26.598351182358293\n ],\n [\n -80.496826171875,\n 27.293689224852407\n ],\n [\n -81.287841796875,\n 27.293689224852407\n ],\n [\n -81.287841796875,\n 26.598351182358293\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.73553466796874,\n 27.761329874505204\n ],\n [\n -80.96649169921874,\n 27.761329874505204\n ],\n [\n -80.96649169921874,\n 28.497660832963447\n ],\n [\n -81.73553466796874,\n 28.497660832963447\n ],\n [\n -81.73553466796874,\n 27.761329874505204\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Midwest Climate Adaptation Science Center
U.S. Geological Survey
1954 Buford Avenue
St Paul, MN 55108
This U.S. Geological Survey Open-File Report provides brief syntheses of the direct and indirect effects of climate change to priority species and ecosystems in the United States. Each chapter focuses on changes in climate and related effects to the life cycle, interspecific interactions, and habitats of a fish or wildlife species of conservation concern. These reports are independent species-specific summaries of relevant literature, current and historic climate conditions, and future climate projections.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211104","costCenters":[],"links":[{"id":395662,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1104/coverthb.jpg"}],"contact":"Director, Midwest Climate Adaptation Science Center
U.S. Geological Survey
1954 Buford Avenue
St Paul, MN 55108
Integrating recent scientific knowledge into management decisions supports effective natural resource management and can lead to better resource outcomes. However, finding and accessing scientific knowledge can be time consuming and costly. To assist in this process, the U.S. Geological Survey (USGS) is creating a series of annotated bibliographies on topics of management concern for western lands. Previously published reports introduced a methodology for preparing annotated bibliographies to facilitate the integration of recent, peer-reviewed science into resource management decisions. Therefore, relevant text from those efforts is reproduced here to frame the presentation. Sagebrush ecosystems throughout North America face management challenges including habitat loss and fragmentation. Brachylagus idahoensis (pygmy rabbits) are a sagebrush-obligate species that has experienced population declines and range contraction in recent decades. A disjunct population of pygmy rabbits in the Columbia Basin in Washington was listed as federally endangered in 2003. Due to their specialized habitat requirements and low dispersal ability, pygmy rabbits are a high priority for managers throughout their range. We compiled and summarized peer-reviewed journal articles, data products, and formal technical reports (such as U.S. Forest Service General Technical Reports and U.S. Geological Survey Open-File Reports) on pygmy rabbits published between January 1, 1990 and December 31, 2020. We first conducted a structured search of three reference databases and three government databases using the phrase “pygmy rabbit” or “Brachylagus idahoensis.” We refined the initial list of products by removing (1) duplicates, (2) products not written in English, (3) publications that were not focused on North America, (4) publications that were not published as research, data products, or scientific review articles in peer-reviewed journals or as formal technical reports, and (5) products for which pygmy rabbits were not a research focus or for which the study did not present new data or findings about pygmy rabbits. We summarized each product using a consistent structure (background, objectives, methods, location, findings, and implications) and identified the management topics (for example, captive breeding, habitat characteristics, and population estimates) addressed by each product. We also noted which publications included new publicly available geospatial data. The review process for this annotated bibliography included an initial internal colleague review of each summary, requesting input on each summary from an author of the original publication, and a formal peer review. Our initial searches resulted in 2,285 total products, of which 105 met our criteria for inclusion. Sensitive/rare wildlife, behavior or demographics, site-scale habitat characteristics, habitat selection, and effects distances or spatial scale were the management topics most commonly addressed. The online version of this bibliography, Science for Resource Managers, will be searchable by topic, location, and year; it will include links to each original publication, where available. The studies compiled and summarized here may inform planning and management actions that seek to maintain and restore sagebrush landscapes and associated native species across the western United States.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221003","usgsCitation":"Kleist, N.J., Willems, J.S., Bencin, H.L., Foster, A.C., McCall, L.E., Meineke, J.K., Poor, E.E., and Carter, S.K., 2022, Annotated bibliography of scientific research on pygmy rabbits published from 1990 to 2020: U.S. Geological Survey Open-File Report 2022–1003, 75 p., https://doi.org/10.3133/ofr20221003.","productDescription":"viii, 75 p.","onlineOnly":"Y","ipdsId":"IP-127323","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":395704,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1003/coverthb.jpg"},{"id":395705,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1003/ofr20221003.pdf","text":"Report","size":"1.24 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022-1003"}],"contact":"Director, Fort Collins Science Center
U.S. Geological Survey
2150 Centre Ave., Bldg. C
Fort Collins, CO 80526-8118
A Decree of the Supreme Court of the United States, entered June 7, 1954, established the position of Delaware River Master within the U.S. Geological Survey. In addition, the Decree authorizes diversion of water from the Delaware River Basin and requires compensating releases from certain reservoirs, owned by New York City, to be made under the supervision and direction of the River Master. The Decree stipulates that the River Master will furnish reports to the Court, not less frequently than annually. This report is the 59th annual report of the River Master of the Delaware River. It covers the 2012 River Master report year, the period from December 1, 2011 to November 30, 2012.
During the report year, precipitation in the upper Delaware River Basin was 43.35 inches or 97 percent of the long-term average. Combined storage in the Pepacton, Cannonsville, and Neversink Reservoirs remained high through late May, declined from then until mid-September, decreasing below 80 percent of combined capacity in late August, increased in late October, and decreased slightly in November 2012. Delaware River Master operations during the year were conducted as stipulated by the Decree and the Flexible Flow Management Program.
Diversions from the Delaware River Basin by New York City and New Jersey were in full compliance with the Decree. Reservoir releases were made as directed by the River Master at rates designed to meet the flow objective for the Delaware River at Montague, New Jersey, on 52 days during the report year. Interim Excess Release Quantity and conservation releases, designed to relieve thermal stress and protect the fishery and aquatic habitat in the tailwaters of the reservoirs, were also made during the report year. An agreement was signed on October 25, 2012, to increase discharge mitigation releases from the Neversink Reservoir due to potential impacts from Hurricane Sandy.
The quality of water in the Delaware River estuary between Trenton, New Jersey, and Reedy Island Jetty, Delaware, was monitored at various locations. Data on water temperature, specific conductance, dissolved oxygen, and pH were collected continuously by electronic instruments at four sites.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211095","usgsCitation":"DiFrenna, V.J., Andrews, W.J., Russell, K.L., Norris, J.M., and Mason, R.R., Jr., 2022, Report of the River Master of the Delaware River for the period December 1, 2011–November 30, 2012: U.S. Geological Survey Open-File Report 2021–1095, 101 p., https://doi.org/10.3133/ofr20211095.","productDescription":"x, 101 p.","numberOfPages":"101","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-123829","costCenters":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true},{"id":516,"text":"Oklahoma Water Science Center","active":true,"usgs":true}],"links":[{"id":395538,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1095/coverthb.jpg"},{"id":395539,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1095/ofr20211095.pdf","text":"Report","size":"4.69 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1095"},{"id":501528,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112444.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"New Jersey, New York, Pennsylvania","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.66259765625,\n 39.67337039176558\n ],\n [\n -73.65234375,\n 39.67337039176558\n ],\n [\n -73.65234375,\n 42.52069952914966\n ],\n [\n -76.66259765625,\n 42.52069952914966\n ],\n [\n -76.66259765625,\n 39.67337039176558\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Delaware River Master
Office of the Delaware River Master
U.S. Geological Survey
120 Route 209 South
Milford, PA 18337
This report addresses system characterization of Planet’s SuperDove and is part of a series of system characterization reports produced and delivered by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence. These reports present and detail the methodology and procedures for characterization; present technical and operational information about the specific sensing system being evaluated; and provide a summary of test measurements, data retention practices, data analysis results, and conclusions.
Since 2013, Planet has launched more than 360 Dove 3U CubeSats, where U stands for 10-centimeter (cm) x 10-cm x 10-cm stowed dimensions, each weighing about 5.8 kilograms. Since 2015, all Dove satellites have had four-band imagers with about a 3-meter (m) pixel ground sample distance. Since 2016, all Doves have been launched into Sun-synchronous orbits varying from 474 to 524 kilometers, with inclinations between 97 and 98 degrees. The Dove series satellites do not have orbit maintenance capabilities; thus, their orbits decay slowly over time, contributing to shorter lifetimes of about 3 years. More information on Planet satellites and sensors is available in the “2020 Joint Agency Commercial Imagery Evaluation—Remote Sensing Satellite Compendium” and from the manufacturer at https://www.planet.com/.
The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team completed data analyses to characterize the geometric (interior and exterior), radiometric, and spatial performances. Results of these analyses indicate that SuperDove has a band-to-band geometric performance in the range of −1.701 m (−0.567 pixel) to 1.173 m (0.391 pixel) in easting and −4.950 m (−1.650 pixels) to 6.051 m (2.017 pixels) in northing, an image-to-image geometric performance of −1.17 m (−0.39 pixel) to 23.45 m (7.82 pixels) in easting and −10.61 m (−3.54 pixels) to −4.43 m (−1.48 pixels) in northing offset in comparison to Sentinel-2, a radiometric performance in the range of −0.043 to 0.020 in offset and 0.812 to 1.246 in slope, and a spatial performance in the range of 3.59 to 3.70 pixels for full width at half maximum, with a modulation transfer function at a Nyquist frequency in the range of 0.005 to 0.008.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211030F","usgsCitation":"Kim, M., Park, S., Anderson, C., and Stensaas, G.L., 2022, System characterization report on Planet’s SuperDove, chap. F of Ramaseri Chandra, S.N., comp., System characterization of Earth observation sensors: U.S. Geological Survey Open-File Report 2021–1030, 19 p., https://doi.org/10.3133/ofr20211030F.","productDescription":"iv, 19 p.","numberOfPages":"28","onlineOnly":"Y","ipdsId":"IP-126679","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":395388,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1030/f/Images"},{"id":395385,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1030/f/coverthb.jpg"},{"id":395387,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1030/f/ofr20211030f.XML","size":"67.7 kB","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2021–1030–F XML"},{"id":395386,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1030/f/ofr20211030f.pdf","text":"Report","size":"16.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021–1030–F"}],"contact":"Director, Earth Resources Observation and Science (EROS) Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
Climate change presents new and ongoing challenges to natural resource management. To confront these challenges effectively, managers need to develop proactive adaptation strategies to prepare for and deal with the effects of climate change. We engaged managers and biologists from several midwestern U.S. Fish and Wildlife Service field stations to understand recent and future climate change effects, identify adaptation barriers and opportunities, and pilot an approach for integrating adaptation thinking into management planning. To start, three structured discussions informed our understanding of how managers currently deal with climate change effects, the strategies being implemented to cope, and the barriers that limit climate change adaptation efforts. We used these insights to develop a multiday virtual workshop geared toward identifying potential adaptation strategies for managed wetlands. First, we developed a conceptual model to visualize how management actions are used to meet habitat objectives within wetland management systems. Next, we discussed how climate change may affect management actions and objectives; we used this understanding of potential effects to spatially assess vulnerability of managed wetlands to climate change. Using a scenario planning approach, we incorporated multiple potential future conditions and identified effects and adaptation strategies that could be considered for each scenario. As a result, several adaptation strategies for managed wetlands under dry and wet future scenarios were identified that can be applied when developing site-specific adaptation plans. Based on our piloted approach, we determined it would be important to have an adaptation team composed of scientists and managers to facilitate discussions, develop appropriate scenarios, and identify realistic adaptation options. We document the tools, findings, and adaptation thinking process taken to enhance adaptation efforts of managed wetlands. The adaptation thinking process can be applied to advance adaptation efforts in other habitats, ecosystems, and site-specific land management.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211103","usgsCitation":"Delaney, J.T., Bouska, K.L., and Eash, J.D., 2021, Climate Change Adaptation Thinking for Managed Wetlands: U.S. Geological Survey Open-File Report 2021–1103, 25 p., https://doi.org/10.3133/ofr20211103.","productDescription":"Report: vi, 25 p.; 3 Data Releases","numberOfPages":"34","onlineOnly":"Y","ipdsId":"IP-128227","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":394943,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9AL7GZM","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"Watershed-based Midwest Climate Change Vulnerability Assessment Tool"},{"id":394942,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9AL7GZM","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"R code: Scripts used to analyze data for the Midwest Climate Change Vulnerability Assessment"},{"id":394941,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9AL7GZM","text":"USGS Data Release","description":"USGS Data Release","linkHelpText":"Model inputs: Midwest climate change vulnerability assessment for the U.S. Fish and Wildlife Service"},{"id":394938,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1103/ofr20211103.pdf","text":"Report","size":"44.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021–1103"},{"id":394937,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1103/coverthb.jpg"},{"id":501530,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112325.htm","linkFileType":{"id":5,"text":"html"}},{"id":394940,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1103/images"},{"id":394939,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1103/ofr20211103.XML","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2021–1103 XML"}],"contact":"Director, Upper Midwest Environmental Sciences Center
U.S. Geological Survey
2630 Fanta Reed Road
La Crosse, WI 54602
Structured decision making is a systematic, transparent process for improving the quality of complex decisions by identifying measurable management objectives and feasible management actions; predicting the potential consequences of management actions relative to the stated objectives; and selecting a course of action that maximizes the total benefit achieved and balances tradeoffs among objectives. The U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service, applied an existing, regional framework for structured decision making to develop a prototype tool for optimizing tidal marsh management decisions at the Petit Manan National Wildlife Refuge of the Maine Coastal Islands National Wildlife Refuge Complex in Maine. Refuge biologists, refuge managers, and research scientists identified multiple potential management actions to improve the ecological integrity of two marsh management units within the refuge complex, totaling about 47 hectares, and estimated the outcomes of each action in terms of performance metrics associated with each management objective. Value functions previously developed at the regional level were used to transform metric scores to a common utility scale, and utilities were summed to produce a single score representing the total management benefit that could be accrued from each potential management action. Constrained optimization was used to identify the set of management actions, one per marsh management unit, that could maximize total management benefits at different cost constraints at the refuge scale. Results indicated that, for the objectives and actions considered here, total management benefits may increase consistently up to $9,545, and may continue to increase at a lower rate with further expenditures. Potential management actions in optimal portfolios at total costs less than or equal to $9,545 included removing dikes to restore tidal flow in the Gouldsboro Bay management unit and installing runnels to improve surface-water drainage in the Sawyers Marsh management unit. The potential management benefits were derived from expected increases in the numbers of tidal marsh obligate breeding birds and density of spiders (as an indicator of trophic health), reduced duration of flooding, and increased capacity of marsh elevation to keep pace with sea-level rise. The prototype presented here does not resolve management decisions; rather, it provides a framework for decision making at the Maine Coastal Islands National Wildlife Refuge Complex that can be updated for implementation as new data and information become available. Insights from this process may also be useful to inform future habitat management planning at the refuge complex.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211123","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Neckles, H.A., Lyons, J.E., Nagel, J.L., Adamowicz, S.C., Mikula, T., and Williams, S., 2022, Optimization of salt marsh management at the Petit Manan National Wildlife Refuge of the Maine Coastal Islands National Wildlife Refuge Complex, Maine, through use of structured decision making: U.S. Geological Survey Open-File Report 2021–1123, 27 p., https://doi.org/10.3133/ofr20211123.","productDescription":"Report: vi, 27 p.; Database","numberOfPages":"27","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-135555","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true},{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":501535,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112158.htm","linkFileType":{"id":5,"text":"html"}},{"id":394950,"rank":5,"type":{"id":9,"text":"Database"},"url":"https://ecos.fws.gov/ServCat/Reference/Profile/121918","text":"U.S. Fish and Wildlife Service database","linkHelpText":"- Salt marsh integrity and Hurricane Sandy vegetation, bird and nekton data"},{"id":394949,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1123/images/"},{"id":394948,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1123/ofr20211123.XML"},{"id":394947,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1123/ofr20211123.pdf","text":"Report","size":"3.08 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1123"},{"id":394946,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1123/coverthb.jpg"}],"country":"United States","state":"Maine","otherGeospatial":"Petit Manan National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -68.0438232421875,\n 44.36902359940364\n ],\n [\n -67.64556884765625,\n 44.36902359940364\n ],\n [\n -67.64556884765625,\n 44.570415145955515\n ],\n [\n -68.0438232421875,\n 44.570415145955515\n ],\n [\n -68.0438232421875,\n 44.36902359940364\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
11649 Leetown Road
Kearneysville, WV 25430
The Southcentral Alaska (SCAK) sea otter (Enhydra lutris) stock is the northernmost stock of sea otters, a keystone predator known for structuring nearshore marine ecosystems. We conducted aerial surveys within the range of the SCAK sea otter stock to provide recent estimates of sea otter abundance and distribution. We defined three survey regions: (1) Eastern Cook Inlet (2017), (2) Outer Kenai Peninsula (2019), and (3) Prince William Sound (2014 and 2017). Combined, the three regional estimates yielded an overall abundance estimate of 21,617 sea otters (standard error [SE] = 2,190) with an average density of 1.96 sea otters per square kilometer (km2; SE = 0.55). Sea otters were distributed unevenly across the survey regions and densities varied from 0.52 sea otters/km2 (SE = 0.18) in the deep rock-walled glacial fjords along parts of the Outer Kenai Peninsula to nearly 20 sea otters/km2 (SE = 6.70) in shallow soft-bottom communities such as those in Orca Inlet and Kachemak Bay. These survey results represent the best available contemporary information concerning the distribution, density, and abundance of sea otters across the range of the SCAK stock. Survey data files have been standardized and formatted in data releases associated with this report so that they can be queried and displayed with standard geographic information system and database management software. In addition to providing contemporary information on sea otter populations, this report details how an observer-based aerial survey method has been applied in Alaska over 2 decades.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211122","collaboration":"Prepared in cooperation with U.S. Fish and Wildlife Service","usgsCitation":"Esslinger, G.G., Robinson, B.H., Monson, D.H., Taylor, R.L., Esler, D., Weitzman, B.P., and Garlich-Miller, J., 2021, Abundance and distribution of sea otters (Enhydra lutris) in the southcentral Alaska stock, 2014, 2017, and 2019: U.S. Geological Survey Open-File Report 2021–1122, 19 p., https://doi.org/10.3133/ofr20211122.","productDescription":"Report: iv, 19 p.; 4 Data Releases","numberOfPages":"19","onlineOnly":"Y","ipdsId":"IP-125417","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":394901,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9TTJVBC","linkHelpText":"Sea otter aerial survey data from the outer Kenai Peninsula, Alaska, 2019"},{"id":394902,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9KNKOG1","linkHelpText":"Sea otter aerial survey data from western Prince William Sound, Alaska, 2017"},{"id":394904,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/p9OG6SR5","linkHelpText":"Sea otter aerial survey data from northern and eastern Prince William Sound, Alaska, 2014"},{"id":394903,"rank":5,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Q4DA3T","linkHelpText":"Sea otter aerial survey data from lower Cook Inlet, Alaska, 2017"},{"id":435988,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9OG6SR5","text":"USGS data release","linkHelpText":"Sea Otter Aerial Survey Data from Northern and Eastern Prince William Sound, Alaska, 2014"},{"id":394895,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1122/covrthb.jpg"},{"id":394896,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1122/ofr20211122.pdf","text":"Report","size":"26 MB","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -155.3466796875,\n 57.868131763328826\n ],\n [\n -143.0419921875,\n 57.868131763328826\n ],\n [\n -143.0419921875,\n 61.80428390136847\n ],\n [\n -155.3466796875,\n 61.80428390136847\n ],\n [\n -155.3466796875,\n 57.868131763328826\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Alaska Science Center
U.S. Geological Survey
4210 University Drive
Anchorage, Alaska 99508
The West Napa Fault has previously been mapped as extending ~45 kilometers (km) from northern Vallejo to southern Saint Helena, California, dominantly running along the western edge of Napa Valley. A zone of fault strands (some previously unmapped) along a ~15-km section of the fault ruptured during the 2014 magnitude 6.0 South Napa earthquake, illustrating the need for further investigation of this little-studied structure. Based on light detection and ranging (lidar) topography and field examination, the fault zone likely extends an additional 10 km or more northward past Saint Helena. In this vicinity, geomorphology suggests two fault strands, one along the range front and another associated with a line of rounded hills that rise 5–10 meters above the middle of the valley. In 2017, we excavated two trenches across an apparent fault scarp on the east side of one elongate hill near Ehlers Lane north of Saint Helena. Examination of the walls revealed three main sedimentary packages. The oldest package, weakly lithified alluvial fan gravels with local sand and silt layers, is tilted 25°–35° to the west. Overlying these tilted strata are two younger sets of strata. On the west side, underlying the crest of the scarp, are alluvial fan gravels with local sand and silt lenses, potentially tilted a few degrees to the west. On the east side, deposited against the scarp, are much finer grained (dominantly fine sand to silt) subhorizontal fluvial strata, likely overbank deposits from the Napa River. We obtained age control on the two younger units through a combination of radiocarbon, infrared-stimulated luminescence, and obsidian hydration dating, establishing that they are latest Pleistocene to modern in age. Although there are no prominent unconformities within the alluvial fan sediments, sample dating indicates there are two generations, one in the 10–20 thousand year (ka) age range and one in the <3 ka age range. Owing to a general lack of well-defined laterally continuous alluvial fan units, it is difficult to distinguish contacts between the two generations except in the immediate proximity of dated samples. The river sediments approximately span the Holocene. No faults were apparent in either trench, indicating that any fault related to the observed surface deformation has not ruptured to the surface at this site during the Holocene and is likely blind.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221002","usgsCitation":"Philibosian, B.E., Sickler, R.R., Prentice, C.S., Pickering, A.J., Gannon, P., Broudy, K.N., Mahan, S.A., Titular, J.N., Turner, E.A., Folmar, C., Patterson, S.F., and Bowman, E.E., 2022, Photomosaics and logs associated with study of West Napa Fault at Ehlers Lane, north of Saint Helena, California: U.S. Geological Survey Open-File Report 2022–1002, 1 sheet, pamphlet 8 p., https://doi.org/10.3133/ofr20221002.","productDescription":"Report: iv, 8 p.; 1 Sheet: 82.00 x 43.00 inches","numberOfPages":"8","additionalOnlineFiles":"Y","ipdsId":"IP-114127","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":501537,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112153.htm","linkFileType":{"id":5,"text":"html"}},{"id":394764,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2022/1002/ofr20221002_sheet.pdf","size":"80 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":394763,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1002/ofr20221002_pamphlet.pdf","text":"Pamphlet","size":"300 KB","linkFileType":{"id":1,"text":"pdf"}},{"id":394762,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1002/covrthb.jpg"}],"country":"United States","state":"California","city":"Saint Helena","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.58407592773438,\n 38.47294404791815\n ],\n [\n -122.38494873046875,\n 38.47294404791815\n ],\n [\n -122.38494873046875,\n 38.586820096127674\n ],\n [\n -122.58407592773438,\n 38.586820096127674\n ],\n [\n -122.58407592773438,\n 38.47294404791815\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information, Menlo Park, Calif.
Office—Earthquake Science Center
U.S. Geological Survey
345 Middlefield Road, MS 977
Menlo Park, CA 94025
No abstract available.
","language":"English","publisher":"Minnesota Geological Survey","usgsCitation":"McClaughry, J.D., Madin, I.P., Bennett, S.E., and Conrey, R.M., 2022, Volcano-tectonic history of the Hood River graben: A late Pliocene-Holocene intra-arc graben at the crest of the northern Oregon Cascade Range, USA: Open-File Report 22-2, 2 p.","productDescription":"2 p.","startPage":"35","endPage":"36","ipdsId":"IP-138155","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":462921,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://conservancy.umn.edu/server/api/core/bitstreams/f0230ff9-4dc6-4865-8b40-a72b2d2be87c/content"},{"id":462955,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oregon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -122.86121809846372,\n 44.65404950748291\n ],\n [\n -120.60902083283865,\n 44.65404950748291\n ],\n [\n -120.60902083283865,\n 45.86041592045436\n ],\n [\n -122.86121809846372,\n 45.86041592045436\n ],\n [\n -122.86121809846372,\n 44.65404950748291\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"McClaughry, Jason D.","contributorId":194544,"corporation":false,"usgs":false,"family":"McClaughry","given":"Jason","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":915960,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Madin, Ian P. 0000-0003-2008-8815","orcid":"https://orcid.org/0000-0003-2008-8815","contributorId":345199,"corporation":false,"usgs":false,"family":"Madin","given":"Ian","email":"","middleInitial":"P.","affiliations":[{"id":32397,"text":"Oregon Department of Geology and Mineral Industries","active":true,"usgs":false}],"preferred":false,"id":915961,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bennett, Scott E.K. 0000-0002-9772-4122 sekbennett@usgs.gov","orcid":"https://orcid.org/0000-0002-9772-4122","contributorId":5340,"corporation":false,"usgs":true,"family":"Bennett","given":"Scott","email":"sekbennett@usgs.gov","middleInitial":"E.K.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":915962,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Conrey, Richard M.","contributorId":194345,"corporation":false,"usgs":false,"family":"Conrey","given":"Richard","email":"","middleInitial":"M.","affiliations":[{"id":13203,"text":"School of the Environment, Washington State University","active":true,"usgs":false}],"preferred":false,"id":915963,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70227372,"text":"ofr20211120 - 2022 - Implementation plan of the National Cooperative Geologic Mapping Program strategy—Great Lakes (Central Lowland and Superior Upland Physiographic Provinces)","interactions":[],"lastModifiedDate":"2026-03-25T17:51:49.580485","indexId":"ofr20211120","displayToPublicDate":"2022-01-14T14:40:00","publicationYear":"2022","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2021-1120","displayTitle":"Implementation Plan of the National Cooperative Geologic Mapping Program Strategy—Great Lakes (Central Lowland and Superior Upland Physiographic Provinces)","title":"Implementation plan of the National Cooperative Geologic Mapping Program strategy—Great Lakes (Central Lowland and Superior Upland Physiographic Provinces)","docAbstract":"The U.S. Geological Survey (USGS) National Cooperative Geologic Mapping Program (NCGMP) has published a strategic plan entitled “Renewing the National Cooperative Geologic Mapping Program as the Nation’s Authoritative Source for Modern Geologic Knowledge”. This plan provides the following vision, mission, and goals for the program for the years 2020–30:
To achieve the goal outlined in the strategic plan, the NCGMP has developed an Implementation Plan. This Implementation Plan will guide annual reviews of the FEDMAP component (that is, the component of the USGS NCGMP that funds geologic mapping by USGS geologists) of the NCGMP projects described in the plan and the development of the annual FEDMAP prospectus, which will ensure the application of the NCGMP strategy.
This publication is part of the Implementation Plan of the NCGMP strategy and addresses the following three major topics:
The regions used in this chapter correspond with physiographic divisions of the United States as defined by Fenneman. Physiographic divisions are delineated on the basis of topography, and to a lesser extent, the geologic structure and history. The physiographic divisions are subdivided into physiographic provinces, and the physiographic provinces are subdivided into physiographic sections. Fenneman’s physiographic divisions of the United States provide a robust and useful spatial organization for delineating large geographic regions of the United States for various scientific and industrial applications.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211120","usgsCitation":"Swezey, C.S., Blome, C.D., Kincare, K.A., Lundstrom, S.C., Stone, B.D., Sweetkind, D.S., Berg, R.C., Brown, S.E., and Yellich, J.A., 2022, Implementation plan of the National Cooperative Geologic Mapping Program strategy—Great Lakes (Central Lowland and Superior Upland Physiographic Provinces): U.S. Geological Survey Open-File Report 2021–1120, 24 p., https://doi.org/10.3133/ofr20211120.","productDescription":"iv, 24 p.","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-128891","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":501534,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112124.htm","linkFileType":{"id":5,"text":"html"}},{"id":394416,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.er.usgs.gov/publication/ofr20211120/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":394244,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1120/coverthb.jpg"},{"id":394245,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1120/ofr20211120.pdf","text":"Report","size":"3.16 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1120"},{"id":394246,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1120/images/"},{"id":394247,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1120/ofr20211120.XML"}],"country":"Canada, United States","otherGeospatial":"Great Lakes (Central Lowland and Superior Upland Physiographic Provinces)","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -98.701171875,\n 34.016241889667015\n ],\n [\n -75.234375,\n 34.016241889667015\n ],\n [\n -75.234375,\n 50.51342652633956\n ],\n [\n -98.701171875,\n 50.51342652633956\n ],\n [\n -98.701171875,\n 34.016241889667015\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Florence Bascom Geoscience Center
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 21092
The U.S. Geological Survey (USGS) 21st-century science strategy 2020–30 promotes a bureau-wide strategy to develop and deliver an integrated, predictive science capability that works at the scales and timelines needed to inform societally relevant resource management and protection and public safety and environmental health decisions (U.S. Geological Survey, 2021). This is the overarching goal of the USGS Earth Monitoring, Analysis, and Prediction (EarthMAP) vision, which consists of three components: (1) integrated data and information, (2) integrated predictive science, and (3) actionable information—all designed and delivered to respond to user needs. To launch this vision and help shape the design and implementation of integrated predictive science, the USGS Regional Offices each developed a set of use cases (hereafter Use Cases)—short descriptions of potential science applications that could clearly address high priority decision-making needs of our stakeholders and that align with an integrated science focus. Use Cases are not actionable science planning documents, nor stand-alone scholarly works, but should be considered as innovative, next-generation science ideas that can be considered as potential components of science plans still under development. The goal of Use Case development was to (1) identify and characterize existing USGS scientific capacities and expertise that can support science goals and products, (2) identify opportunities to leverage current capacities for next-generation science, and (3) foster engagement across the entire Bureau to further refine the USGS strategy for EarthMAP and integrated predictive science.
The Use Case development effort documented in this report was coordinated by the Use Case Development Team (UCDT), consisting of representatives from each region. The UCDT undertook five tasks: (1) develop a unified approach to engage bureau scientists consistently across all regions in aspirational thinking about what can be accomplished; (2) work with the regions and their Science Centers to generate an initial set of Use Cases, authored directly by scientists; (3) characterize, summarize, and document the initial set of Use Case submissions from authors to illuminate bureau-level demand for integrated science; (4) compare existing and needed capacities from the Use Case descriptions with preliminary results of the EarthMAP Capacity Assessment (Keisman and others, 2021); and (5) describe lessons learned from the Use Case development process and provide recommendations to inform future efforts to generate integrated science activities. This report outlines the approach the UCDT developed to solicit Use Cases from the regions and summarizes the high-level qualitative findings from this first-round effort.
The UCDT received 36 Use Cases from the regions and identified potential points of convergence and commonalities considered useful in making connections among the participating scientists. The Southwest (SW) Region and the Rocky Mountain (RM) Region asked scientists to give special consideration to Use Cases with applicability to the Colorado River Basin, and seven of the Use Cases specifically named that geographic area as a focus. Coastal hazards and coastal resilience were identified in Use Cases from the Alaska (AK), Northeast (NE), and Southeast (SE) Regions. Aspects of wildfire and post-wildfire response were part of Uses Cases from AK, RM, and SW Regions. The greatest convergence of Use Case themes was related to conservation of public lands and waters, which is a powerful linkage lending strength to future collaborative efforts.
The most common type of stakeholder decisions that would be informed by the Use Case science applications were related to adaptation, mitigation, and response (for example, how to increase the resilience of coastal communities to climate-related stressors and how to prevent or respond to harmful algal blooms). Other common types of decisions included water and land management decisions (including operational water management decisions such as reservoir operations and land use planning in the sagebrush biome), decisions about how to manage and conserve habitats and species, and risk management decisions (such as managing the post-wildfire flood risks). These decision types are not exclusive because many Use Cases cross categories.
Use Case authors identified existing and needed science and technology capabilities required for Use Case implementation, which were then aligned to capabilities assessed in the EarthMAP Capacity Assessment (Keisman and others, 2021). Strong alignment was found for data and information integration approaches, modeling and prediction approaches, and capabilities related to delivery of actionable information. A majority of Use Cases indicated insufficient current capacity for needed data collection methods, data integration, and modeling and prediction approaches, whereas only 25 percent indicated insufficient capacity for actionable information delivery. Overall, many Use Case capacity demand gaps could potentially be met by existing bureau-wide capacity. In addition, nearly half of the Use Cases could potentially be implemented within 3 years if funding, capabilities, and personnel impediments were removed and science priorities were realigned.
Several challenges emerged during the Use Case development process. The first challenge was developing an approach that was flexible enough to accommodate regional differences in planning and implementation, while also ensuring enough guidance to promote meaningful summary analyses. The UCDT encountered a strong demand for continuous communication and education to improve overall understanding of the integrated predictive science strategy. Another challenge was managing expectations about EarthMAP activities as a design effort that was not aligned to an immediate funding opportunity. Connecting the Use Cases to stakeholder needs without the opportunity for direct stakeholder engagement was also challenging. The last notable challenge was in obtaining consistent interpretation and characterization of the qualitative data housed in the narrative descriptions of Use Cases, written in different styles.
Overall, the 36 Use Cases can serve as components of a road map for advancing integrated monitoring and predictive science throughout the USGS by revealing opportunities to (1) encourage cross-region initiatives that address shared interests in common themes by integrating similar Use Cases and through direct involvement of stakeholders in identifying needs and designing effective responses, (2) leverage the Use Cases to target investments that are aligned with the Bureau and Department of the Interior (DOI) priorities, (3) connect Use Cases and the results of the companion EarthMAP Capacity Assessment (Keisman and others, 2021) to identify potential priorities for capacity building investments, and (4) raise awareness of common integrated and interdisciplinary science interests within and across the regions through Use Case and Capacity Assessment summary outreach activities.
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