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":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics 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.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211108","programNote":"Science Synthesis, Analysis and Research Program","usgsCitation":"Wilson, T.S., Wiltermuth, M.T., Jenni, K.E., Horton, R.J., Hunt, R.J., Williams, D.M., Nolan, V.P., Aumen, N.G., Brown, D.S., Blasch, K.W., and Murdoch, P.S., 2022, Use case development for earth monitoring, analysis, and prediction (EarthMAP)—A road map for future integrated predictive science at the U.S. Geological Survey: U.S. Geological Survey Open-File Report 2021–1108, 137 p., https://doi.org/10.3133/ofr20211108.","productDescription":"vii, 132 p.","numberOfPages":"132","onlineOnly":"Y","ipdsId":"IP-129972","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true},{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":394402,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1108/covrthb.jpg"},{"id":394403,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1108/ofr20211108.pdf","text":"Report","size":"10.5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":394404,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1108/ofr20211108.xml"},{"id":394405,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1108/images"}],"contact":"Director,
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192
Dry conditions during 2020 and 2021 affected the water supply within the Souris River Basin and highlighted the need for better understanding of the streamflow dynamics for managing the resource during low-flow conditions. In June 2021, a loss of streamflow was observed on the Souris River between U.S. Geological Survey streamgages on the Souris River near Foxholm, North Dakota (site 1), and near Verendrye, N. Dak. (site 22). The largest loss was upstream from the Souris River above Minot, N. Dak. (site 7). On June 6, 2021, the daily mean streamflow decreased from 33.8 cubic feet per second at site 1 to 16.3 cubic feet per second at site 7, a loss of 17.5 cubic feet per second. To better understand where streamflow losses occurred in the reach from site 1 to site 22, multiple sites were selected for streamflow measurements between the three streamgages (sites 1, 7, and 22). Streamflow measurements made at 22 selected sites on the Souris River on August 31 and September 1, 2021, did not indicate the loss in streamflow that was observed at the three streamgages (sites 1, 7, and 22) in June 2021. Measurements made at the three streamgages (sites 1, 7, and 22) on August 31 had streamflows of 44.2, 45.9, and 46.8 cubic feet per second, respectively. Streamflow measured at all 22 sites on August 31 and September 1 on the Souris River ranged from 38.4 (site 9) to 49.8 cubic feet per second (site 12). In general, the largest change in streamflow was measured among sites on the Souris River in or near the city of Minot, N. Dak.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20221005","collaboration":"Prepared in cooperation with the North Dakota Department of Water Resources, the U.S. Fish and Wildlife Service, and the U.S. Army Corps of Engineers, St. Paul District","usgsCitation":"Galloway, J.M., and Hanson, B.R., 2022, Measurements of streamflow gain and loss on the Souris River between Lake Darling and Verendrye, North Dakota, August 31 and September 1, 2021: U.S. Geological Survey Open-File Report 2022–1005, 10 p., https://doi.org/10.3133/ofr20221005.","productDescription":"Report: vi, 10 p.; Dataset","numberOfPages":"20","onlineOnly":"Y","ipdsId":"IP-135605","costCenters":[{"id":34685,"text":"Dakota Water Science Center","active":true,"usgs":true}],"links":[{"id":394315,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2022/1005/coverthb.jpg"},{"id":394317,"rank":3,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"U.S. Geological Survey National Water Information System database","description":"USGS Dataset","linkHelpText":"— USGS water data for the Nation"},{"id":394316,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2022/1005/ofr20221005.pdf","text":"Report","size":"1.23 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2022–1005"},{"id":501538,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112123.htm","linkFileType":{"id":5,"text":"html"}},{"id":394329,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2022/1005/images","description":"OFR 2022–1005 images"},{"id":394328,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2022/1005/ofr20221005.XML","description":"OFR 2022–1005 XML"}],"country":"United States","state":"North Dakota","otherGeospatial":"Souris River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -101.6667,\n 48\n ],\n [\n -100.5,\n 48\n ],\n [\n -100.5,\n 48.50\n ],\n [\n -101.6667,\n 48.50\n ],\n [\n -101.6667,\n 48\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Dakota Water Science Center
U.S. Geological Survey
821 East Interstate Avenue
Bismarck, ND 58503
1608 Mountain View Road
Rapid City, SD 57702
This report addresses system characterization of Planet’s SkySat 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.
SkySat is a constellation of submeter resolution Earth observation satellites providing analytics services, high-definition video, and imagery. The goal for the constellation is to capture multiple daily repeats of high-resolution imagery over any spot on the Earth. As of September 2020, 21 SkySat satellites have been launched, and the first launch occurred in November 2013. 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 SkySat has an interior geometric performance in the range of a 0.38- (0.47 pixel) to 0.75-meter (m; 0.93 pixel) root mean square error in easting and a 0.27- (0.33 pixel) to 0.55-m (0.68 pixel) root mean square error in northing, in band-to-band registration; an exterior geometric performance in the range of 0.26 (0.32 pixel) to 1.04 m (1.28 pixels) offset in comparison to ground control points; a radiometric performance in the range of 0.033 to 0.797 (linear regression); and a spatial performance in the range of 3.7 to 4.3 pixels at full width at half maximum, with a modulation transfer function at a Nyquist frequency in the range of 0.004 to 0.009.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"System characterization of Earth observation sensors","largerWorkSubtype":{"id":4,"text":"Other Government Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211030E","usgsCitation":"Kim, M., Park, S., Sampath, A., Anderson, C., and Stensaas, G.L., 2022, System characterization report on Planet SkySat, chap. E of Ramaseri Chandra, S.N., comp., System characterization of Earth observation sensors: U.S. Geological Survey Open-File Report 2021–1030, 17 p., https://doi.org/10.3133/ofr20211030E.","productDescription":"iv, 17 p.","numberOfPages":"17","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-126680","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":394021,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1030/e/coverthb.jpg"},{"id":394022,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1030/e/ofr20211030e.pdf","text":"Report","size":"1.73 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1030-E"}],"contact":"Director, Earth Resources Observation and Science (EROS) Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
The Des Moines River alluvial aquifer is an important source of water for Des Moines Water Works, the municipal water utility that provides residential and commercial water resources to the residents of Des Moines, Iowa, and surrounding municipalities. As an initial step in developing a better understanding of the groundwater resources of the Des Moines River alluvial aquifer, the U.S. Geological Survey constructed a steady-state numerical groundwater flow model in cooperation with Des Moines Water Works to simulate water-table elevations in the Des Moines River alluvial aquifer near Prospect Park in Des Moines under winter low-flow conditions.
A simple conceptual model consisting of a hydrogeologic framework, water budget, and inferred water-table elevation map was developed for the model area. The inferred water-table elevation map was constructed based on general knowledge of hydrogeology within the model area and was used to set calibration targets for numerical model calibration. A steady-state numerical model was constructed based on the conceptual model using MODFLOW-NWT to simulate an area of about 15 square kilometers near Prospect Park in Des Moines. Parameter ESTimation software was used for model calibration to assess and optimize performance of the horizontal hydraulic conductivity and recharge parameters. The numerical groundwater flow model and supporting data are available in the USGS data release associated with this report, which contains the model archive.
Performance of the calibrated steady-state model was assessed by comparing observed and simulated water-table elevations, as well as estimated and simulated contributions to streamflow within the model area. The difference between observed water-table elevations and simulated water-table elevations was −0.1 meter at the majority of calibration targets, with the negative value indicating an overestimation of the simulated water-table elevation value compared to the observed water-table elevation value, and the root mean square error was 0.13 meter, which represents about 20 percent of the difference in observed water-table elevations. The simulated value of contributions to streamflow within the model area was considered similar to the estimated value, increasing confidence in the ability of the model to accurately represent the groundwater flow system in the Des Moines River alluvial aquifer in the model area during winter low-flow conditions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211110","collaboration":"Prepared in cooperation with Des Moines Water Works","usgsCitation":"FitzGerald, K.M., Ha, W.S., Haj, A.E., Gruhn, L.R., Bristow, E.L., and Weber, J.R., 2022, A steady-state groundwater flow model for the Des Moines River alluvial aquifer near Prospect Park, Des Moines, Iowa: U.S. Geological Survey Open-File Report 2021–1110, 20 p., https://doi.org/10.3133/ofr20211110.","productDescription":"Report: vii, 20 p.; Data Release; Dataset","numberOfPages":"20","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-130288","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":501532,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_112070.htm","linkFileType":{"id":5,"text":"html"}},{"id":393916,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1110/ofr20211110.pdf","text":"Report","size":"2.45 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1110"},{"id":393915,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1110/coverthb.jpg"},{"id":393917,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9F3CKLC","text":"USGS data release","linkHelpText":"MODFLOW-NWT model used to simulate groundwater levels in the Des Moines River alluvial aquifer near Des Moines, Iowa"},{"id":393918,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://doi.org/10.5066/F7P55KJN","text":"USGS National Water Information System database","linkHelpText":"- USGS water data for the Nation"}],"country":"United States","state":"Iowa","city":"Des Moines","otherGeospatial":"Prospect Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.65175247192383,\n 41.611463744813506\n ],\n [\n -93.61836433410645,\n 41.611463744813506\n ],\n [\n -93.61836433410645,\n 41.63019942878951\n ],\n [\n -93.65175247192383,\n 41.63019942878951\n ],\n [\n -93.65175247192383,\n 41.611463744813506\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
This report addresses system characterization of Satellogic’s NewSat satellite (also known as ÑuSat) 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 2016, Satellogic has launched 17 NewSat satellites. All NewSat satellites have four-band imagers with a 1-meter (m) ground sample distance, and values in pixels are identical to values in meters. All NewSats have been launched into Sun-synchronous orbits of about 475 kilometers, with inclinations of about 97.5 degrees. The satellites have expected lifetimes of about 3 years. More information on the Satellogic satellites and sensors is available in the “2020 Joint Agency Commercial Imagery Evaluation—Remote Sensing Satellite Compendium” and from the manufacturer at https://satellogic.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 the NewSat satellites have an interior geometric performance in the range of −0.119 (−0.119 pixel) to 0.020 m (0.020 pixel) in easting and −0.148 (−0.148 pixel) to 0.014 m (0.014 pixel) in northing in band-to-band registration, an exterior geometric performance of −9.04 (−9.04 pixels) to −5.84 m (−5.84 pixels) in easting and 1.25 (1.25 pixels) to 3.11 m (3.11 pixels) in northing offset in comparison to Sentinel-2, an exterior geometric performance using ground control points of a 6.5-m circular error (95 percent), a radiometric performance in the range of 0.034 to 0.081 in offset and 0.652 to 0.808 in slope, and a spatial performance in the range of 1.61 to 1.76 pixels for full width at half maximum, with a modulation transfer function at a Nyquist frequency in the range of 0.081 to 0.138.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"System characterization of Earth observation sensors","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211030L","usgsCitation":"Vrabel, J.C., Bresnahan, P., Stensaas, G.L., Anderson, C., Christopherson, J., Kim, M., and Park, S., 2022, System characterization report on the Satellogic NewSat multispectral sensor (ver. 1.1, April 2022), chap. L of Ramaseri Chandra, S.N., comp., System characterization of Earth observation sensors: U.S. Geological Survey Open-File Report 2021–1030, 28 p., https://doi.org/10.3133/ofr20211030L.","productDescription":"v, 28 p.","numberOfPages":"28","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-135435","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":393738,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1030/l/ofr20211030l.pdf","text":"Report","size":"7.48 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1030-L"},{"id":393737,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1030/l/coverthb2.jpg"},{"id":399739,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2021/1030/l/versionHist.txt","size":"1 kB"}],"edition":"Version 1.0: January 3, 2022; Version 1.1: April 28, 2022","contact":"Director, Earth Resources Observation and Science (EROS) Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
We conducted the first assessment of eelgrass and seaweed distribution and abundance along the coast of the Alaska Peninsula-Becharof National Wildlife Refuges in Chignik Lagoon and Mud Bay. Areal extent of eelgrass, as determined from remote-sensing techniques, was estimated to be 2,414 hectares in Chignik Lagoon and 188 hectares in Mud Bay, and eelgrass was the dominant marine macrophyte in each of the embayments. During an embayment-wide point survey of Chignik Lagoon, eelgrass and seaweeds were observed on 76 and 62 percent of survey points, respectively. Average percent cover was greater for eelgrass (82 percent) than for seaweeds (37 percent) when each was present at a survey point. In contrast, eelgrass and seaweeds were distributed nearly equally in Mud Bay, occurring on 64 and 70 percent of the points, respectively, and when present, cover of eelgrass and seaweeds were 70 and 60 percent, respectively. Brown and red seaweeds, such as Polysiphonia pacifica, Saccharina latissima, Neorhodomela oregona, and Eudesme borealis, were the most common seaweeds in Chignik Lagoon, while green seaweeds, particularly Kornmannia leptoderma and Cladophora sericea, were dominant in Mud Bay. Standing crop of eelgrass was 44 percent greater in Chignik Lagoon (98.0±6.4 grams dry weight per square meter) than in Mud Bay (68.3±6.7 grams dry weight per square meter) in 2010. Five types of macro-invertebrates were assessed during the point survey. At least one of these macro-invertebrates was observed on 45 percent of points in Chignik Lagoon and 64 percent of points in Mud Bay. Gastropods were the most common of the macro-invertebrates, occurring on 40–57 percent of points in each of the embayments. This assessment of eelgrass and seaweeds can serve as a baseline for determining future changes in the distribution and abundance of these marine macrophytes in Chignik Lagoon and Mud Bay.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20201144","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Ward, D.H., Hogrefe, K.R., Donnelly,T.F., Fairchild, L.L., and Britton, R., 2022, Eelgrass (Zostera marina) and seaweed assessment Alaska Peninsula-Becharof National Wildlife Refuges, 2010: U.S. Geological Survey Open-File Report 2020–1144, 14 p., https://doi.org/10.3133/ofr20201144.","productDescription":"Report v, 14 p.; 2 Data Releases","onlineOnly":"Y","ipdsId":"IP-118490","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":405810,"rank":9,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20211034","text":"OFR 2021-1034 —","description":"OFR 2021-1034","linkHelpText":"Inventory of eelgrass (Zostera marina) and seaweeds at the end of the Alaska Peninsula, August–September 2012"},{"id":405809,"rank":8,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20201143","text":"OFR 2020-1143 —","description":"OFR 2020-1143","linkHelpText":"Eelgrass (Zostera marina) and seaweed abundance along the coast of Nunivak Island, Yukon Delta National Wildlife Refuge, Alaska, 2010"},{"id":405808,"rank":7,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20201114","text":"OFR 2020-1114 —","description":"OFR 2020-1114","linkHelpText":"Eelgrass (Zostera marina) and Seaweed Abundance along the Coast of Togiak National Wildlife Refuge, Alaska, 2008–10"},{"id":384519,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2020/1144/coverthb1.jpg"},{"id":384520,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2020/1144/ofr20201144.pdf","text":"Report","size":"1.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2020-1144"},{"id":384521,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WEK4JI","text":"USGS data release","description":"USGS data release","linkHelpText":"Imagery and mapping data of eelgrass (Zostera marina) distribution, Alaska and Baja California, Mexico"},{"id":384522,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9URZJYW","text":"USGS data release","description":"USGS data release","linkHelpText":"Point sampling data for eelgrass (Zostera marina) and seaweed distribution and abundance in bays adjacent to the Alaska Peninsula-Becharof National Wildlife Refuges, Alaska, 2010"},{"id":405806,"rank":5,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20201035","text":"OFR 2020-1035 —","description":"OFR 2020-1035","linkHelpText":"Abundance and distribution of eelgrass (Zostera marina) and seaweeds at Izembek National Wildlife Refuge, Alaska, 2007–10"},{"id":405807,"rank":6,"type":{"id":22,"text":"Related Work"},"url":"https://doi.org/10.3133/ofr20201080","text":"OFR 2020-1080 —","description":"OFR 2020-1080","linkHelpText":"Distribution of eelgrass (Zostera marina) in coastal waters adjacent to Togiak National Wildlife Refuge, Alaska"}],"country":"United States","state":"Alaska","otherGeospatial":"Alaska Peninsula-Becharof National Wildlife Refuges","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -158.75,\n 56.2333\n ],\n [\n -158.333,\n 56.2333\n ],\n [\n -158.333,\n 56.3667\n ],\n [\n -158.75,\n 56.3667\n ],\n [\n -158.75,\n 56.2333\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Alaska Science Center
U.S. Geological Survey
4210 University Drive
Anchorage, Alaska 99508
The Valmont TCE Superfund Site, Luzerne County, Pennsylvania is underlain by fractured and folded sandstones and shales of the Pottsville and Mauch Chunk Formations, which form a fractured-rock aquifer recharged locally by precipitation. Industrial activities at the former Chromatex Plant resulted in trichloroethene (TCE) contamination of groundwater at and near the facility, which was identified in 1987 and led to listing as a Superfund site by the U.S. Environmental Protection Agency (EPA) in 1989. To address the problem of TCE concentrations in nearby residential wells that exceed the maximum contaminant level (MCL) of 5 micrograms per liter (μg/L), alternate water supplies were provided. A 2015 review of initial characterization and subsequent remediation by the EPA identified the need for an updated understanding of the complex hydrogeology and the conceptual site model. Additional contaminants present in groundwater at the site include some other volatile organic compounds (VOCs) and per- and polyfluoroalkyl substances (PFAS), predominantly consisting of perfluorooctanoic acid (PFOA) and perfluorooctanesulfonic acid (PFOS) present in concentrations that exceeded the EPA Health Advisory (HA) level of 5 nanograms per liter (ng/L) for combined PFOA and PFOS.
In response to a request from the EPA in 2019, the U.S. Geological Survey (USGS) prepared cross sections and maps to provide more information about the hydrogeologic framework at and near the site and assist in improving the conceptual site model using water level and contaminant data collected by the EPA in 2020. The cross sections present lithologic correlations from available geophysical logs collected in wells from 2002 to 2014; they show alternating intervals of relatively elevated and reduced natural gamma activity that correspond to changes in lithology, with water-bearing zones and well screens commonly located at lithologic contacts, sometimes near thin coal seams. Water-bearing zones commonly are associated with fractures at or near lithologic contacts but also may be associated with fractures at or near apparent faulting. Recent (March 2020) water-level data shown on cross sections and maps indicate large downward vertical gradients and apparent radial gradients laterally to the northeast, northwest, and southwest that generally following topography. Recent (February to March 2020) data for TCE groundwater concentration shown on cross sections and maps indicate the highest TCE concentrations (greater than 3,000 μg/L and as much as 75,000 μg/L) and combined PFOA and PFOS concentrations (greater than 1,000 ng/L and up to at least 2,350 ng/L) are from shallow (less than 60 feet [ft] below land surface [bls]) and intermediate depth (60 to 100 ft bls) wells near the center of the former Chromatex Plant. TCE and PFAS (as combined PFOA and PFOS) contamination is present at greater depths, as much as 304 ft bls, as evidenced by samples collected from one well (a reconstructed former production well) near the plant, that contained concentrations of about 240 μg/L and 508 ng/L, respectively. The 2020 data also indicate that TCE and PFAS concentrations which exceed drinking-water MCL or HA levels are present in groundwater depths of less than 200 ft in an area that extends predominantly in a northeast direction from the former Chromatex Plant, and is apparently influenced by hydraulic gradients, lithology, and geologic structure.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211093","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Senior, L.A., Fiore, A.R., and Bird, P.H., 2021, Hydrogeologic framework, water levels, and selected contaminant concentrations at Valmont TCE Superfund Site, Luzerne County, Pennsylvania, 2020 (ver. 1.1, August 2022): U.S. Geological Survey Open-File Report 2021–1093, 80 p., https://doi.org/10.3133/ofr20211093.","productDescription":"Report: xii, 80 p.; 17 Plates: 17.00 x 11.00 inches or smaller","numberOfPages":"80","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-128502","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true},{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":501527,"rank":21,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_111788.htm","linkFileType":{"id":5,"text":"html"}},{"id":389684,"rank":17,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2021/1093/ofr20211093_plate15.pdf","text":"Plate 15","size":"470 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Section C-Cʹ with generalized potentiometric surfaces and trichloroethene concentrations, Valmont TCE Superfund Site, Luzerne County, Pennsylvania, February-March 2020"},{"id":389683,"rank":16,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2021/1093/ofr20211093_plate14.pdf","text":"Plate 14","size":"919 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Section Bd-Bdʹ detail with generalized potentiometric surfaces and trichloroethene concentrations, Valmont TCE Superfund Site, Luzerne County, Pennsylvania, February-March 2020"},{"id":389680,"rank":13,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2021/1093/ofr20211093_plate11.pdf","text":"Plate 11","size":"587 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Section A-Aʹ with generalized potentiometric surfaces and trichloroethene concentrations, Valmont TCE Superfund Site, Luzerne County, Pennsylvania, February-March 2020"},{"id":389679,"rank":12,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2021/1093/ofr20211093_plate10.pdf","text":"Plate 10","size":"229 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Section H-Hʹ with geophysical log correlations and trichloroethene concentrations, Valmont TCE Superfund Site, Luzerne County, Pennsylvania"},{"id":389678,"rank":11,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2021/1093/ofr20211093_plate9.pdf","text":"Plate 9","size":"1.96 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Section G-Gʹ with geophysical log correlations (A) and generalized potentiometric surfaces and trichloroethene concentrations (B), Valmont TCE Superfund Site, Luzerne County, Pennsylvania, February-March 2020"},{"id":389676,"rank":9,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2021/1093/ofr20211093_plate7.pdf","text":"Plate 7","size":"287 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Section E-Eʹ with geophysical log correlations, Valmont TCE Superfund Site, Luzerne County, Pennsylvania"},{"id":389675,"rank":8,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2021/1093/ofr20211093_plate6.pdf","text":"Plate 6","size":"293 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Section D-Dʹ with geophysical log correlations, generalized potentiometric surfaces, and trichloroethene concentrations, Valmont TCE Superfund Site, Luzerne County, Pennsylvania, February-March 2020"},{"id":389674,"rank":7,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2021/1093/ofr20211093_plate5.pdf","text":"Plate 5","size":"303 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Section C-Cʹ with geophysical log correlations, Valmont TCE Superfund Site, Luzerne County, Pennsylvania"},{"id":389673,"rank":6,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2021/1093/ofr20211093_plate4.pdf","text":"Plate 4","size":"2.32 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Section Bd-Bdʹ detail with geophysical log correlations, Valmont TCE Superfund Site, Luzerne County, Pennsylvania"},{"id":404943,"rank":20,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2021/1093/versionHist.txt","size":"1.31 KB","linkFileType":{"id":2,"text":"txt"}},{"id":389686,"rank":19,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2021/1093/ofr20211093_plate17.pdf","text":"Plate 17","size":"774 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Pennsylvania"},{"id":389671,"rank":4,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2021/1093/ofr20211093_plate2.pdf","text":"Plate 2","size":"220 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Section Ad-Adʹ detail with geophysical log correlations, Valmont TCE Superfund Site, Luzerne County, Pennsylvania"},{"id":389670,"rank":3,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2021/1093/ofr20211093_plate1.pdf","text":"Plate 1","size":"277 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Section A-Aʹ with geophysical log correlations, Valmont TCE Superfund Site, Luzerne County, Pennsylvania"},{"id":389668,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1093/ofr20211093.pdf","text":"Report","size":"26.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1093"},{"id":389667,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1093/coverthb3.jpg"},{"id":389677,"rank":10,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2021/1093/ofr20211093_plate8.pdf","text":"Plate 8","size":"1.98 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Section F-Fʹ with geophysical log correlations, Valmont TCE Superfund Site, Luzerne County, Pennsylvania"},{"id":389681,"rank":14,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2021/1093/ofr20211093_plate12.pdf","text":"Plate 12","size":"396 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Section Ad-Adʹ detail with generalized potentiometric surfaces and trichloroethene concentrations, Valmont TCE Superfund Site, Luzerne County, Pennsylvania, February-March 2020"},{"id":389682,"rank":15,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/of/2021/1093/ofr20211093_plate13.pdf","text":"Plate 13","size":"0.99 MB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Section B-Bʹ with generalized potentiometric surfaces and trichloroethene concentrations, Valmont TCE Superfund Site, Luzerne County, Pennsylvania, February-March 2020"}],"country":"United States","state":"Pennsylvania","county":"Luzerne 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1.0: September 30, 2021; Version 1.1: August 9, 2022","contact":"Director, Pennsylvania Water Science Center
U.S. Geological Survey
215 Limekiln Road
New Cumberland, PA 17070-2424
A portable suction-dredge and sluice-box system were used to collect larval lampreys (Entosphenus tridentatus and Lampetra spp.) from fine and coarse sediment in field and laboratory tests. We evaluated the injury rate, survival, and burrowing capability of lamprey following passage through the dredge system and used collection of lamprey from water without sediment as a control. The system used a hydraulic eductor (also known as a Venturi valve) to create suction so that sediment and lamprey avoided passage through the pump impeller. For the field test, lamprey were tagged with visible elastomer implants based on small (89 millimeter [mm] or less) and large (92 mm or more) size categories and stocked into mesh enclosures over fine or coarse sediment. The dredge was used inside each enclosure to collect lamprey and they were transported to the laboratory for evaluation and holding. The mean time to burrow was recorded for each study group (3 fine, 3 coarse, 3 controls) on the day of the field test; injury was evaluated at 24 hours; and survival was evaluated at 24 hours, and at 7 and 14 days after the test. The suction dredge collected 32 lamprey in fine sediment, 21 lamprey in coarse sediment, and 28 lamprey in the control group, including 30 lamprey that were not initially stocked. One lamprey died the day of the test (fine sediment) and 24 hours later, three lamprey were found to be injured (2 in fine and 1 in coarse sediment). No injuries or mortalities occurred in the control group. Lamprey burrowing performance was similar across the two treatment groups and the controls. The mean time for all fish in a group to burrow was highly variable. For all groups in a treatment combined, the mean burrow times were fastest for the fine treatment (9.8 minutes), followed by the controls (11.4 minutes) and the coarse treatment (11.6 minutes). The mean times to burrow for the main group of fish in each treatment group (those that burrowed in quick succession) were similar: 4.3 minutes for the fine group, 4.4 minutes for the coarse group, and 4.5 minutes for the controls. The laboratory test collected 147 lamprey (73 small and 74 large size category) from coarse sediment using the same procedures as the field test. One fish (small) was killed the day of the test, and six lamprey (3 small and 3 large) were found with injuries during the 24-hour exams. No mortalities were recorded 7 days after the test, when monitoring was terminated. The overall injury rate for the laboratory test was 4.1 percent and the mortality rate was 0.7 percent. Injuries in the field and laboratory tests were localized minor hemorrhages or red, irritated areas. The suction- dredge system appears to be a safe option to collect larval lamprey from sediment and will be a useful addition to lamprey assessment and salvage tools.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211116","collaboration":"Prepared in cooperation with U.S. Fish and Wildlife Service","usgsCitation":"Liedtke, T.L., Skalicky, J.J., and Weiland, L.K., 2022, Collection of larval lampreys (Entosphenus tridentatus and Lampetra spp.) using a portable suction dredge—A pilot test: U.S. Geological Survey Open-File Report 2021–1116, 12 p., https://doi.org/10.3133/ofr20211116.","productDescription":"vi, 12 p.","onlineOnly":"Y","ipdsId":"IP-129003","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":436076,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9B337X6","text":"USGS data release","linkHelpText":"Evaluating injury and mortality to larval lamprey collected out of sediment using a portable suction dredge"},{"id":394472,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1116/coverthb2.jpg"},{"id":394473,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1116/ofr20212116.pdf","text":"Report","size":"2.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1116"}],"country":"United States","state":"Washington","otherGeospatial":"Wind River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.8229293823242,\n 45.68651588881847\n ],\n [\n -121.74190521240234,\n 45.68651588881847\n ],\n [\n -121.74190521240234,\n 45.74380820334429\n ],\n [\n -121.8229293823242,\n 45.74380820334429\n ],\n [\n -121.8229293823242,\n 45.68651588881847\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115-5016
The High Point paleosol is 2.28-meters-thick aggradational soil developed in fining upward estuarine-alluvial sand and loess. The paleosol is exposed in a few shoreline cliff faces of Mason Neck, Virginia. Although a former A horizon is missing, the E, Bw, Bt, and C horizon sequence seen in the sediments indicates subaerial pedogenesis. Pedogenesis began with initial estuarine-alluvial floodplain emergence as sea level was lowering in late marine isotope stage 5 (MIS5) and MIS4, continued during eolian silt deposition accompanied by incorporation of the silt into the estuarine-alluvial sand, and ended with a period of loess and eolian sand deposition, erosion, and development of periglacial(?) features. Six optically stimulated luminescence ages provide an age range from 86 to 56 ka (thousand years ago) for sedimentary units below and above the paleosol. These ages indicate a 10,000- to 30,000-year interval in late MIS5 and MIS4 for these events to have occurred.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211113","usgsCitation":"Markewich, H.W., Wysocki, D.A., Pavich, M.J., Smoot, J.P., and Litwin, R.J., 2021, Stratigraphy and age of a prominent paleosol in a late Pleistocene sedimentary sequence, Mason Neck, Virginia: U.S. Geological Survey Open-File Report 2021–1113, 24 p., https://doi.org/10.3133/ofr20211113.","productDescription":"vii, 24 p.","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-129382","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":393454,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1113/ofr20211113.pdf","text":"Report","size":"2.46 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1113"},{"id":393453,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1113/coverthb.jpg"}],"country":"United States","state":"Virginia","otherGeospatial":"Mason Neck","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.40966796875,\n 38.507340712903456\n ],\n [\n -76.7724609375,\n 38.507340712903456\n ],\n [\n -76.7724609375,\n 38.884619201291905\n ],\n [\n -77.40966796875,\n 38.884619201291905\n ],\n [\n -77.40966796875,\n 38.507340712903456\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Florence Bascom Geoscience Center
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 21092
Two existing flood management structures in U.S. Army Garrison Fort Gordon, Georgia, were evaluated for potential retrofitting to address water-quality impacts, pursuant of U.S. Army Garrison Fort Gordon’s storm water management program. Stormwater calculations were computed according to the Georgia Stormwater Management Manual, including drainage area delineations, design-storm runoff volumes and peak discharges, stage-storage and stage-discharge curves, and outflow calculations. The results of these analyses were compared to Georgia’s regulatory requirements for dry detention basins. The two existing flood management structures did not meet the requirements for a dry detention basin. Planning-level analyses for these basins indicate that the existing structures do not have adequate storage capacity for the overbank flood design-storm runoff volume (25-year, 24-hour storm) or the extreme flood design-storm runoff volume (100-year, 24-hour storm) and neither storm water structural control 2 nor storm water structural control 3 has the emergency spillway needed to safely convey overflows. Furthermore, land use changes (forest removal) and the risk for additional sediment loads to these structures may reduce available storage volume, increasing the risk for design failure. Three potential retrofit alternatives were provided for planning purposes only, with a brief discussion of advantages and disadvantages of each alternative retrofit strategy.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211121","collaboration":"Prepared in cooperation with the Environmental and Natural Resources Management Division of the U.S. Army Garrison Fort Gordon","usgsCitation":"Stillwell, C.C., 2021, Evaluation of two existing flood management structures in U.S. Army Garrison Fort Gordon, Georgia, 2020: U.S. Geological Survey Open-File Report 2021–1121, 16 p., https://doi.org/10.3133/ofr20211121.","productDescription":"v, 16 p.","numberOfPages":"16","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-126439","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":394595,"rank":5,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20211121/full","text":"Report","linkFileType":{"id":5,"text":"html"}},{"id":393446,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1121/images/"},{"id":393440,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1121/ofr20211121.XML"},{"id":393438,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1121/ofr20211121.pdf","text":"Report","size":"6.04 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1121"},{"id":393439,"rank":2,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1121/coverthb.jpg"}],"country":"United States","state":"Georgia","otherGeospatial":"Fort Gordon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.18254089355469,\n 33.415018689904805\n ],\n [\n -82.1664047241211,\n 33.415018689904805\n ],\n [\n -82.1664047241211,\n 33.42742998368805\n ],\n [\n -82.18254089355469,\n 33.42742998368805\n ],\n [\n -82.18254089355469,\n 33.415018689904805\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
1770 Corporate Drive Suite 500
Norcross, GA 30093
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 2 (April–June), 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/ofr20211105","usgsCitation":"Micijevic, E., Rengarajan, R., Haque, M.O., Lubke, M., Tuli, F.T., 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., 2021, ECCOE Landsat quarterly Calibration and Validation report — Quarter 2, 2021: U.S. Geological Survey Open-File Report 2021–1105, 40 p., https://doi.org/10.3133/ofr20211105.","productDescription":"vii, 40 p.","numberOfPages":"52","onlineOnly":"Y","ipdsId":"IP-130990","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":393445,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1105/images"},{"id":393443,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1105/ofr20211105.pdf","text":"Report","size":"4.86 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021–1105"},{"id":393442,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1105/coverthb.jpg"},{"id":393444,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1105/ofr20211105.XML","size":"118 kB","description":"OFR 2021–1105 xml"}],"contact":"Director, Earth Resources Observation and Science Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
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 Eastern Shore of Virginia and Fisherman Island National Wildlife Refuges in Virginia. Refuge biologists, refuge managers, and research scientists identified multiple potential management actions to improve the ecological integrity of six marsh management units within the refuges, totaling about 575 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 approximately $143,000, but that further expenditures may yield diminishing return on investment. Potential management actions in optimal portfolios at total costs less than $143,000 included digging runnels by hand to improve drainage from the marsh surface, breaching a road to restore natural hydrology, trapping predators to enhance nest success of tidal marsh birds, and reducing the abundance of Odocoileus virginianus (white-tailed deer) to minimize their effects on marsh vegetation. The potential management benefits were derived from expected increases in number of tidal marsh obligate breeding birds, species richness of nekton, and density of spiders (as an indicator of trophic health); and an expected decrease in duration of surface flooding. The prototype presented here does not resolve management decisions; rather, it provides a framework for decision making at the Eastern Shore of Virginia and Fisherman Island National Wildlife Refuges that can be updated as new data and information become available. Insights from this process may also be useful to inform future habitat management planning at the refuges.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211117","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., Denmon, P., and Leffel, R., 2021, Optimization of salt marsh management at the Eastern Shore of Virginia and Fisherman Island National Wildlife Refuges, Virginia, through use of structured decision making: U.S. Geological Survey Open-File Report 2021–1117, 32 p., https://doi.org/10.3133/ofr20211117.","productDescription":"Report: vi, 32 p.; Database","numberOfPages":"32","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-131973","costCenters":[{"id":50464,"text":"Eastern Ecological Science Center","active":true,"usgs":true}],"links":[{"id":393431,"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":393427,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1117/coverthb.jpg"},{"id":393428,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1117/ofr20211117.pdf","text":"Report","size":"2.75 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1117"},{"id":393429,"rank":3,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1117/images/"},{"id":393430,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1117/ofr20211117.XML"}],"country":"United States","state":"Virginia","otherGeospatial":"Fisherman Island 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 -75.99586486816406,\n 37.072162624715375\n ],\n [\n -75.92857360839844,\n 37.072162624715375\n ],\n [\n -75.92857360839844,\n 37.14061402065652\n ],\n [\n -75.99586486816406,\n 37.14061402065652\n ],\n [\n -75.99586486816406,\n 37.072162624715375\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
11649 Leetown Road
Kearneysville, WV 25430
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 Moosehorn National Wildlife Refuge in Maine. Refuge biologists, refuge managers, and research scientists identified multiple potential management actions to improve the ecological integrity of four marsh management units within the refuge, totaling about 13 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 $1,000, 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 $1,000 included improving nesting habitat for Ammodramus nelsoni (Nelson’s sparrow) or restoring hydrologic connections to the upper marsh in one marsh management unit (Hobart Stream West). The potential management benefits were derived from expected increases in the density of nekton and of spiders (as an indicator of trophic health). The prototype presented here does not resolve management decisions; rather, it provides a framework for decision making at the Moosehorn National Wildlife Refuge 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.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211115","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., Mills, M., Brown, R.E., and Ramos, K., 2021, Optimization of salt marsh management at the Moosehorn National Wildlife Refuge, Maine, through use of structured decision making: U.S. Geological Survey Open-File Report 2021–1115, 28 p., https://doi.org/10.3133/ofr20211115.","productDescription":"Report: vi, 28 p.; Database","numberOfPages":"28","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-131976","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":393375,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1115/coverthb.jpg"},{"id":393376,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1115/ofr20211115.pdf","text":"Report","size":"4.5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":393377,"rank":3,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2021/1115/ofr20211115.xml"},{"id":393379,"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":393378,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2021/1115/images"}],"country":"United States","state":"Maine","otherGeospatial":"Moosehorn 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 -67.27890014648438,\n 44.80132682904856\n ],\n [\n -67.15,\n 44.80132682904856\n ],\n [\n -67.15,\n 44.918625522424925\n ],\n [\n -67.27890014648438,\n 44.918625522424925\n ],\n [\n -67.27890014648438,\n 44.80132682904856\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Eastern Ecological Science Center
U.S. Geological Survey
11649 Leetown Road
Kearneysville, WV 25430
The August 14, 2021, magnitude 7.2 Nippes, Haiti, earthquake triggered thousands of landslides on the Tiburon Peninsula. The landslides directly caused fatalities and damage and impeded response efforts by blocking roads and causing other infrastructure damage. Adverse effects of the landslides likely will continue for months to years. This report presents an assessment of potential postearthquake landslide-related geologic hazards for the Tiburon Peninsula and a preliminary map of the landslides triggered by the earthquake. This hazard assessment is based on an emergency analysis of the currently available, postearthquake satellite imagery. In this report, we highlight specific areas of concern that may benefit from more detailed assessment and longer-term monitoring. Our mapping efforts revealed that at least 4,893 landslides were triggered across the Tiburon Peninsula by the earthquake and subsequent rainfall from Tropical Cyclone Grace. We also observed hundreds of landslide deposits potentially restricting flow in rivers and streams. In addition, we observed landslides that likely affected roads by rendering them impassable or susceptible to subsequent damage from existing landslides. Because of the preliminary nature of this report and the limits of remote analyses, additional investigation and monitoring would be beneficial to accurately determine the threat posed by these hazards to people and infrastructure.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20211112","usgsCitation":"Martinez, S.N., Allstadt, K.E., Slaughter, S.L., Schmitt, R., Collins, E., Schaefer, L.N., and Ellison, S., 2021, Landslides triggered by the August 14, 2021, magnitude 7.2 Nippes, Haiti, earthquake: U.S. Geological Survey Open-File Report 2021–1112, 17 p., https://doi.org/10.3133/ofr20211112.","productDescription":"Report; vi, 17 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-134308","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":393322,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P99MYPXK","text":"USGS data release","linkHelpText":"Rapid Response Landslide Inventory for the 14 August 2021 M7.2 Nippes, Haiti, Earthquake"},{"id":393237,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2021/1112/ofr20211112.pdf","text":"Report","size":"19.0 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2021-1112"},{"id":393236,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2021/1112/coverthb.jpg"}],"country":"Haiti","otherGeospatial":"Nippes","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.50927734375,\n 17.95260646769184\n ],\n [\n -73.36669921875,\n 17.95260646769184\n ],\n [\n -73.36669921875,\n 18.729501999072138\n ],\n [\n -74.50927734375,\n 18.729501999072138\n ],\n [\n -74.50927734375,\n 17.95260646769184\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Geologic Hazards Science Center
U.S. Geological Survey
Box 25046, MS 966
Denver, CO 80225