Major flooding occurred August 24–25, 2016, in the Upper Iowa River Basin and Turkey River Basin in northeastern Iowa following severe thunderstorm activity over the region. About 8 inches of rain were recorded for the 24-hour period ending at 4 p.m., August 24, at Decorah, Iowa, and about 6 inches of rain were recorded for the 24-hour period ending at 7 a.m., August 24, at Cresco, Iowa, about 14 miles northwest of Spillville, Iowa. A maximum peak-of-record discharge of 38,000 cubic feet per second in the Upper Iowa River at streamgage 05388250 Upper Iowa River near Dorchester, Iowa, occurred on August 24, 2016, with an annual exceedance-probability range of 0.2–1 percent. High-water marks were measured at six locations along the Upper Iowa River between State Highway 26 near the mouth at the Mississippi River and State Highway 76 about 3.5 miles south of Dorchester, Iowa, a distance of 15 river miles. Along the profiled reach of the Turkey River, a maximum peak-of-record discharge of 15,300 cubic feet per second at streamgage 05411600 Turkey River at Spillville, Iowa, occurred on August 24, 2016, with an annual exceedance-probability range of 1–2 percent. A maximum peak discharge of 35,700 cubic feet per second occurred on August 25, 2016, along the profiled reach of the Turkey River at streamgage 05411850 Turkey River near Eldorado, Iowa, with an annual exceedance-probability range of 0.2–1 percent. High-water marks were measured at 11 locations along the Turkey River between County Road B64 in Elgin and 220th Street, located about 4.5 miles northwest of Spillville, Iowa, a distance of 58 river miles. The high-water marks were used to develop flood profiles for the Upper Iowa River and Turkey River.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171128","isbn":"978-1-4113-4201-9","collaboration":"Prepared in cooperation with the Iowa Department of Transportation and the Iowa Highway Research Board (Project HR–140)","usgsCitation":"Linhart, S.M., and O’Shea, P.S., 2018, Flood of August 24–25, 2016, Upper Iowa River and Turkey River, northeastern Iowa: U.S. Geological Survey Open-File Report 2017–1128, 20 p., with appendix, https://doi.org/10.3133/ofr20171128.","productDescription":"viii, 19 p.","numberOfPages":"32","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-088630","costCenters":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"links":[{"id":350963,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1128/of20171128.pdf","text":"Report","size":"1.45 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1128"},{"id":350962,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1128/coverthb.jpg"}],"country":"United States","state":"Iowa","otherGeospatial":"Turkey River, Upper Iowa River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -92.6667,\n 42.60869548716231\n ],\n [\n -91.065673828125,\n 42.60869548716231\n ],\n [\n -91.065673828125,\n 43.574421623084234\n ],\n [\n -92.6667,\n 43.574421623084234\n ],\n [\n -92.6667,\n 42.60869548716231\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Central Midwest Water Science Center
U.S. Geological Survey
400 S. Clinton Street
Iowa City, IA 52240
Understanding the evolution of the Colorado River system has direct implications for (1) the processes and timing of continental-scale river system integration, (2) the formation of iconic landscapes like those in and around Grand Canyon, and (3) the availability of groundwater resources. Spatial patterns in the position and type of Colorado River deposits, only discernible through geologic mapping, can be used to test models related to Colorado River evolution. This is particularly true downstream from Grand Canyon where ancestral Colorado River deposits are well-exposed. We are principally interested in (1) regional patterns in the minimum and maximum elevation of each depositional unit, which are affected by depositional mechanism and postdepositional deformation; and (2) the volume of each unit, which reflects regional changes in erosion, transport efficiency, and accommodation space. The volume of Colorado River deposits below Grand Canyon has implications for groundwater resources, as the primary regional aquifer there is composed of those deposits. To this end, we are presently mapping Colorado River deposits and compiling and updating older mapping. This preliminary data release shows the current status of our mapping and compilation efforts. We plan to update it at regular intervals in conjunction with ongoing mapping.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181005","usgsCitation":"Crow, R.S., Block, D., Felger, T.J., House, P.K., Pearthree, P.A., Gootee, B.F., Youberg, A.M., Howard, K.A., and Beard, L.S., 2018, The Colorado River and its deposits downstream from Grand Canyon in Arizona, California, and Nevada: U.S. Geological Survey Open-File Report 2018–1005, 6 p., https://doi.org/10.3133/ofr20181005.","productDescription":"Report: iii, 6 p.; Geodatabase","numberOfPages":"9","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-080360","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":351008,"rank":3,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/of/2018/1005/ofr20181005_gdb.zip","text":"Geodatabase","size":"4.5 MB","linkFileType":{"id":6,"text":"zip"},"description":"OFR 2018-1005"},{"id":351006,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1005/coverthb.jpg"},{"id":351007,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1005/ofr20181005.pdf","text":"Report","size":"250 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1005"}],"country":"United States","state":"Arizona, California, Nevada","otherGeospatial":"Colorado River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -115,\n 33.00866349457558\n ],\n [\n -114,\n 33.00866349457558\n ],\n [\n -114,\n 36\n ],\n [\n -115,\n 36\n ],\n [\n -115,\n 33.00866349457558\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Two identical Radar Stage Sensors from Forest Technology Systems were evaluated to determine if they are suitable for U.S. Geological Survey (USGS) hydrologic data collection. The sensors were evaluated in laboratory conditions to evaluate the distance accuracy of the sensor over the manufacturer’s specified operating temperatures and distance to water ranges. Laboratory results were compared to the manufacturer’s accuracy specification of ±0.007 foot (ft) and the USGS Office of Surface Water (OSW) policy requirement that water-level sensors have a measurement uncertainty of no more than 0.01 ft or 0.20 percent of the indicated reading. Both of the sensors tested were within the OSW policy requirement in both laboratory tests and within the manufacturer’s specification in the distance to water test over tested distances from 3 to 15 ft. In the temperature chamber test, both sensors were within the manufacturer’s specification for more than 90 percent of the data points collected over a temperature range of –40 to +60 degrees Celsius at a fixed distance of 8 ft. One sensor was subjected to an SDI-12 communication test, which it passed. A field test was conducted on one sensor at a USGS field site near Landon, Mississippi, from February 5 to March 29, 2016. Water-level measurements made by the radar during the field test were in agreement with those made by the Sutron Accubar Constant Flow Bubble Gauge.
Upon the manufacturer’s release of updated firmware version 1.09, additional SDI-12 and temperature testing was performed to evaluate added SDI-12 functions and verify that performance was unaffected by the update. At this time, an Axiom data logger is required to perform a firmware update on this sensor. The data confirmed the results of the original test. Based on the test results, the Radar Stage Sensor is a suitable choice for USGS hydrologic data collection.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171085","usgsCitation":"Kunkle, G.A., 2018, Evaluation of the Radar Stage Sensor manufactured by Forest Technology Systems—Results of laboratory and field testing: U.S. Geological Survey Open-File Report 2017–1085, 12 p., https://doi.org/10.3133/ofr20171085.","productDescription":"Report: iv, 12 p.; Data Release","numberOfPages":"20","onlineOnly":"Y","ipdsId":"IP-083860","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":350803,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F71C1VSR","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Evaluation of the Radar Stage Sensor Manufactured by Forest Technology Systems, Incorporated—Results of Laboratory and Field Testing"},{"id":350800,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1085/ofr20171085.pdf","text":"Report","size":"918 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017–1085"},{"id":350799,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1085/coverthb.jpg"}],"contact":"Chief, Hydrologic Instrumentation Facility
U.S. Geological Survey
Building 2101
Stennis Space Center, MS 39529
In Autumn 2015, USA National Phenology Network (USA-NPN) staff implemented new U.S. Geological Survey (USGS) data-management policies intended to ensure that the results of Federally funded research are made available to the public. The effort aimed both to improve USA-NPN data releases and to provide a model for similar programs within the USGS. This report provides an overview of the steps taken to ensure compliance, following the USGS Science Data Lifecycle, and provides lessons learned about the data-release process for USGS program leaders and data managers.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181007","usgsCitation":"Rosemartin, A., Langseth, M.L., Crimmins, T.M., and Weltzin, J.F., 2018, Development and release of phenological data products—A case study in compliance with federal open data policy: U.S. Geological Survey Open-File Report 2018–1007, 13 p., https://doi.org/10.3133/ofr20181007.","productDescription":"iv, 13 p.","numberOfPages":"18","onlineOnly":"Y","ipdsId":"IP-090322","costCenters":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true},{"id":37226,"text":"Core Science Analytics, Synthesis, and Libraries","active":true,"usgs":true}],"links":[{"id":350850,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1007/coverthb.jpg"},{"id":350851,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1007/ofr20181007.pdf","text":"Report","size":"350 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1007"}],"contact":"Ecosystems Mission Area
U.S. Geological Survey
12201 Sunrise Valley Dr., MS 300
Reston, VA 20192
Despite the wealth of global paleoclimate data available for the warm period in the middle of the Piacenzian Stage of the Pliocene Epoch (about 3.3 to 3.0 million years ago [Ma]; Dowsett and others, 2013, and references therein), the Indian Ocean has remained a region of sparse geographic coverage in terms of microfossil analysis. In an effort to characterize the surface Indian Ocean during this interval, we examined the planktic foraminifera from Ocean Drilling Program (ODP) sites 709, 716, 722, 754, 757, 758, and 763, encompassing a wide range of oceanographic conditions. We quantitatively analyzed the data for sea surface temperature (SST) estimation using both the modern analog technique (MAT) and a factor analytic transfer function. The data will contribute to the U.S. Geological Survey (USGS) Pliocene Research, Interpretation and Synoptic Mapping (PRISM) Project’s global SST reconstruction and climate model SST boundary condition for the mid-Piacenzian and will become part of the PRISM verification dataset designed to ground-truth Pliocene climate model simulations (Dowsett and others, 2013).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171158","usgsCitation":"Robinson, M.M., Dowsett, H.J., and Stoll, D.K., 2018, Sea surface temperature estimates for the mid-Piacenzian Indian Ocean—Ocean Drilling Program sites 709, 716, 722, 754, 757, 758, and 763: U.S. Geological Survey Open-File Report 2017–1158, 14 p., https://doi.org/10.3133/ofr20171158.","productDescription":"iv, 14 p.","numberOfPages":"19","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-087996","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":350488,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1158/coverthb.jpg"},{"id":350489,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1158/ofr20171158.pdf","text":"Report","size":"11 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1158"}],"otherGeospatial":"Indian Ocean","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 59.80,\n -30.93\n ],\n [\n 112.21,\n -30.93\n ],\n [\n 112.21,\n 16.62\n ],\n [\n 59.80,\n 16.62\n ],\n [\n 59.80,\n -30.93\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Eastern Geology and Paleoclimate Science Center
U.S. Geological Survey
12201 Sunrise Valley Drive
926A National Center
Reston, VA 20192
In 1990, the U.S. Geological Survey, in cooperation with the U.S. Department of Energy Idaho Operations Office, established the Lithologic Core Storage Library at the Idaho National Laboratory (INL). The facility was established to consolidate, catalog, and permanently store nonradioactive drill cores and cuttings from subsurface investigations conducted at the INL, and to provide a location for researchers to examine, sample, and test these materials.
The facility is open by appointment to researchers for examination, sampling, and testing of cores and cuttings. This report describes the facility and cores and cuttings stored at the facility. Descriptions of cores and cuttings include the corehole names, corehole locations, and depth intervals available.
Most cores and cuttings stored at the facility were drilled at or near the INL, on the eastern Snake River Plain; however, two cores drilled on the western Snake River Plain are stored for comparative studies. Basalt, rhyolite, sedimentary interbeds, and surficial sediments compose most cores and cuttings, most of which are continuous from land surface to their total depth. The deepest continuously drilled core stored at the facility was drilled to 5,000 feet below land surface. This report describes procedures and researchers' responsibilities for access to the facility and for examination, sampling, and return of materials.
","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181001","collaboration":"DOE/ID-22244Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702
With the decline of Chinook salmon (Oncorhynchus tshawytscha) and steelhead (O. mykiss), habitat restoration actions in freshwater tributaries have been implemented to improve conditions for juveniles. Typically, physical (for example, hydrologic and engineering) based models are used to design restoration alternatives with the assumption that biological responses will be improved with changes to the physical habitat. Biological models rarely are used. Here, we describe simulations of a food web model, the Aquatic Trophic Productivity (ATP) model, to aid in the design of a restoration project in the Methow River, north-central Washington. The ATP model mechanistically links environmental conditions of the stream to the dynamics of river food webs, and can be used to simulate how alternative river restoration designs influence the potential for river reaches to sustain fish production. Four restoration design alternatives were identified that encompassed varying levels of side channel and floodplain reconnection and large wood addition. Our model simulations suggest that design alternatives focused on reconnecting side channels and the adjacent floodplain may provide the greatest increase in fish capacity. These results were robust to a range of discharge and thermal regimes that naturally occur in the Methow River. Our results suggest that biological models, such as the ATP model, can be used during the restoration planning phase to increase the effectiveness of restoration actions. Moreover, the use of multiple modeling efforts, both physical and biological, when evaluating restoration design alternatives provides a better understanding of the potential outcome of restoration actions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181002","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Benjamin, J.R., Bellmore, J.R., and Dombroski, Daniel, 2018, Using a food web model to inform the design of river restoration—An example at the Barkley Bear Segment, Methow River, north-central Washington: U.S. Geological Survey Open-File Report 2018–1002, 24 p., https://doi.org/10.3133/ofr20181002.","productDescription":"iv, 24 p.","numberOfPages":"32","onlineOnly":"Y","ipdsId":"IP-092102","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":350751,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1002/ofr20181002.pdf","text":"Report","size":"4.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1002"},{"id":350750,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1002/coverthb.jpg"}],"country":"United States","state":"Washington","otherGeospatial":"Methow River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.497802734375,\n 47.646886969413\n ],\n [\n -119.02587890624999,\n 47.646886969413\n ],\n [\n -119.02587890624999,\n 49.15296965617042\n ],\n [\n -121.497802734375,\n 49.15296965617042\n ],\n [\n -121.497802734375,\n 47.646886969413\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Forest and Rangeland Ecosystem Science Center
U.S. Geological Survey
777 NW 9th St., Suite 400
Corvallis, Oregon 97330
This report provides information from a general public survey conducted in early 2017 to help inform the North American Waterfowl Management Plan (NAWMP) 2018 update. This report is intended for use by the NAWMP advisory committees and anyone interested in the human dimensions of wetlands and waterfowl management. A mail-out survey was sent to 5,000 addresses in the United States, which were selected randomly in proportion to the population of each State. A total of 1,030 completed surveys representing 49 States were returned, resulting in a 23 percent overall response rate.
When comparing the demographics of the respondents to the U.S. census data, this sample overrepresented people who are male, older, highly educated, and white. Data were weighted on gender and age to make the results more representative of the overall U.S. population. Additionally, this sample had higher participation rates in all wildlife-related recreation activities than has been found in previous studies; this indicates there may have been selection bias, with people interested in nature-related topics more likely to complete the survey. Therefore, results likely represent a segment of the U.S. public that is more oriented toward and aware of wildlife and conservation issues than the general public as a whole. Because of this bias, responses for each question were also broken down by recreationist type (hunters, anglers, wildlife viewers, and no wildlife-related recreation). Additionally, responses for each question were split by administrative flyway (Atlantic, Central, Mississippi, Pacific) and residency (urban, urban cluster, rural) to better understand the different groups.
Most respondents knew of wetlands in their local area or community, and more than half had visited wetlands in the previous 12 months. Of those who had visited wetlands, the most common reasons were for walking/hiking/biking and enjoying nature/picnicking. In addition, this sample was very concerned about the reduction or loss of ecosystem services resulting from wetlands degradation or loss. A majority of respondents were somewhat or very concerned about 9 out of 10 wetlands benefits, with hunting opportunities being the only benefit the majority of people were not concerned about. People were the most concerned about clean water, clean air, and providing a home for wildlife. In contrast, people were least concerned about hunting opportunities and wetlands providing scenic places for inspiration or spiritual renewal. Communication about wetlands that focuses on habitat, clean air, and clean water may resonate with the widest variety of people. However, if communication is targeted toward wildlife-related recreationists, including more information about the recreation benefits of wetlands and emphasizing habitat benefits may be the most effective.
Many people reported having participated in conservation behaviors in the last year. The most popular activity was making the yard more desirable to wildlife, with more than three-fourths of respondents participating, followed by donating money to support wildlife/habitat conservation and talking to others in their community about conservation issues. There was lower participation in conservation behavior specifically related to wetlands and waterfowl, with two-fifths of respondents voting for candidates or ballot issues to support wetlands/waterfowl conservation and one-third advocating for political action to conserve wetlands/waterfowl.
In order to better understand how to reach out to the public on nature-related topics, preferences in information channels and trust in information sources were explored. Respondents were mostly likely to want to receive their information through personal experience, by reading or accessing online content, and through watching visual media online. People were least likely to want to receive information through listening to recorded audio media, attending educational opportunities, and listening to live audio media. These results emphasize the importance of having content available online in an easily accessible and appealing format. Visual media in particular seems to be preferred across a wide variety of people. Additionally, people had the highest trust in scientific organizations, universities/educational organizations, and friends/family/neighbors/colleagues. The least trusted sources were national media/news, religious organizations, and local media/news. Urban respondents had higher trust levels overall, particularly for the government. Hunters and those in rural areas had lower levels of trust in the government but higher trust in family/friends.
In this sample, few respondents reported hunting waterfowl (5 percent) or hunting other game (16 percent) in the last year. Additionally, few respondents said they were very or somewhat likely to hunt waterfowl in the following 12 months. Even after considering that self-selection bias would make it more likely for hunters to respond to the survey, the relatively small number of respondents who identified as hunters reinforces that engagement of other wildlife-related recreationists is critical to meeting the third goal of the NAWMP 2012 revision—to increase numbers of wetlands/waterfowl conservationists. Many people also had negative perceptions of hunting. Half of the respondents stated that hunting would be unpleasant, and two-fifths believed hunting would be boring. In contrast, people had more favorable attitudes toward birdwatching, with only one-sixth saying it would be unpleasant and less than one-third saying it would be boring. A majority of respondents thought they could easily go hunting or birdwatching in the following 12 months. Overall, people had much more positive views toward birdwatching and expressed fewer barriers to participating in it. When asked what would prevent them from hunting, the most frequently stated reasons were moral opposition, no interest, personal health, and time constraints; for birdwatching, the most popular responses were nothing, no interest, and time constraints. These responses indicate it may be beneficial to move beyond hunting and find ways for other groups, such as birdwatchers, to play a more active role in conservation.
Although not many people hunted and many people tended to have negative attitudes toward hunting, over three-fourths of people said they knew a hunter. Given that wildlife viewers, those who did not participate in wildlife-related recreation, and urban residents tended to have negative attitudes toward hunting and (or) were not interested in participating, attempting to recruit them to participate in hunting may not be effective. However, given how many people across all groups knew a hunter and the relatively high levels of trust people had in their friends/family, hunters may be effective ambassadors for promoting waterfowl and wetlands conservation among nonhunters. Additionally, because people had less preference for viewing waterfowl and other game birds compared to their preference for seeing hummingbirds and birds of prey, conservation efforts that extend beyond waterfowl and include other species that benefit from wetlands may have more appeal to a broader range of people.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171148","usgsCitation":"Wilkins, E.J., and Miller, H.M., 2018, Public views of wetlands and waterfowl conservation in the United States—Results of a survey to inform the 2018 update of the North American Waterfowl Management Plan: U.S. Geological Survey Open-File Report 2017–1148, 134 p., https://doi.org/10.3133/ofr20171148.","productDescription":"xii, 134 p.","numberOfPages":"147","onlineOnly":"Y","ipdsId":"IP-088573","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":438050,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7G15ZQ6","text":"USGS data release","linkHelpText":"Results of a U.S. General Public Survey to Inform the 2018 North American Waterfowl Management Plan Update (2017)"},{"id":350493,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1148/ofr20171148.pdf","text":"Report","size":"8.40 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1148"},{"id":350492,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1148/coverthb.jpg"}],"contact":"Director, Fort Collins Science Center
U.S. Geological Survey
2150 Centre Ave., Building C
Fort Collins, CO 80526-8118
We summarize recent (2002–17) publicly available information from studies within the 1002 Area of the Arctic National Wildlife Refuge as well as terrestrial and coastal ecosystems elsewhere on the Arctic Coastal Plain that are relevant to the 1002 Area. This report provides an update on earlier research summaries on caribou (Rangifer tarandus), forage quality and quantity, polar bears (Ursus maritimus), muskoxen (Ovibos moschatus), and snow geese (Chen caerulescens). We also provide information on new research related to climate, migratory birds, permafrost, coastal erosion, coastal lagoons, fish, water resources, and potential effects of industrial disturbance on wildlife. From this literature review, we noted evidence for change in the status of some wildlife and their habitats, and the lack of change for others. In the 1002 Area, muskox numbers have decreased and the Porcupine Caribou Herd has exhibited variation in use of the area during the calving season. Polar bears are now more common on shore in summer and fall because of declines in sea ice in the Beaufort Sea. In a study spanning 25 years, there were no significant changes in vegetation quality and quantity, soil conditions, or permafrost thaw in the coastal plain of the 1002 Area. Based on studies from the central Arctic Coastal Plain, there are persistent and emerging uncertainties about the long-term effects of energy development for caribou. In contrast, recent studies that examined direct and indirect effects of industrial activities and infrastructure on birds in the central Arctic Coastal Plain found little effect for the species and disturbances examined, except for the possibility of increased predator activity near human developments.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181003","collaboration":"Prepared in cooperation with the U.S. Fish and Wildlife Service","usgsCitation":"Pearce, J.M., Flint, P.L., Atwood, T.C., Douglas, D.C., Adams, L.G., Johnson, H.E., Arthur, S.M., and Latty, C.J., 2018, Summary of wildlife-related research on the coastal plain of the Arctic National Wildlife Refuge, Alaska, 2002–17: U.S. Geological Survey Open-File Report 2018–1003, 27 p., https://doi.org/10.3133/ofr20181003.","productDescription":"iv, 27 p.","numberOfPages":"36","onlineOnly":"Y","ipdsId":"IP-092189","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":350490,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1003/coverthb2.jpg"},{"id":350491,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1003/ofr20181003.pdf","text":"Report","size":"7.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1003"}],"country":"United States","state":"Alaska","otherGeospatial":"Arctic 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 -146.480712890625,\n 69.5\n ],\n [\n -142,\n 69.5\n ],\n [\n -142,\n 70.15901707518466\n ],\n [\n -146.480712890625,\n 70.15901707518466\n ],\n [\n -146.480712890625,\n 69.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Alaska Science Center
U.S. Geological Survey
4230 University Drive
Anchorage, Alaska 99508
The U.S. Geological Survey, in cooperation with DuPage County Stormwater Management Department, is testing a near real-time streamflow simulation system that assists in the management and operation of reservoirs and other flood-control structures in the Salt Creek and West Branch DuPage River drainage basins in DuPage County, Illinois. As part of this effort, the U.S. Geological Survey maintains a database of hourly meteorological and hydrologic data for use in this near real-time streamflow simulation system. Among these data are next generation weather radar-multisensor precipitation estimates and quantitative precipitation forecast data, which are retrieved from the North Central River Forecasting Center of the National Weather Service. The DuPage County streamflow simulation system uses these quantitative precipitation forecast data to create streamflow predictions for the two simulated drainage basins. This report discusses in detail how these data are processed for inclusion in the Watershed Data Management files used in the streamflow simulation system for the Salt Creek and West Branch DuPage River drainage basins.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171159","collaboration":"Prepared in cooperation with the DuPage County Stormwater Management Department","usgsCitation":"Bera, Maitreyee, and Ortel, T.W., 2018, Processing of next generation weather radar-multisensor precipitation estimates and quantitative precipitation forecast data for the DuPage County streamflow simulation system: \nU.S. Geological Survey Open-File Report 2017–1159, 16 p., https://doi.org/10.3133/ofr20171159.","productDescription":"iv, 15 p.","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-087229","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":350409,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1159/coverthb.jpg"},{"id":350410,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1159/ofr20171159.pdf","text":"Report","size":"3.64 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1159"}],"country":"United States","state":"Illinois","county":"DuPage County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-88.2634,41.9876],[-88.1473,41.9883],[-88.0342,41.9925],[-87.9175,41.9938],[-87.9188,41.9076],[-87.9178,41.8185],[-87.9142,41.7318],[-87.9139,41.7172],[-87.9438,41.7017],[-87.9482,41.694],[-87.9674,41.6879],[-87.9883,41.6877],[-88.0013,41.6874],[-88.0308,41.6868],[-88.0317,41.7295],[-88.1499,41.7272],[-88.2625,41.7251],[-88.2628,41.811],[-88.2632,41.8623],[-88.2631,41.9],[-88.2634,41.9876]]]},\"properties\":{\"name\":\"Dupage\",\"state\":\"IL\"}}]}","contact":"Director, Illinois-Iowa Water Science Center
U.S. Geological Survey
405 North Goodwin Avenue
Urbana, IL 61801
The Geospatial Semantic Web (GSW) is an emerging technology that uses the Internet for more effective knowledge engineering and information extraction. Among the aims of the GSW are to structure the semantic specifications of data to reduce ambiguity and to link those data more efficiently. The data are stored as triples, the basic data unit in graph databases, which are similar to the vector data model of geographic information systems (GIS); that is, a node-edge-node model that forms a graph of semantically related information. The GSW is supported by emerging technologies such as linked geospatial data, described below, that enable it to store and manage geographical data that require new cartographic methods for visualization. This report describes a map that can interact with linked geospatial data using a simulation of a data query approach called the browsable graph to find information that is semantically related to a subject of interest, visualized using the Data Driven Documents (D3) library. Such a semantically enabled map functions as a map knowledge base (MKB) (Varanka and Usery, 2017).
A MKB differs from a database in an important way. The central element of a triple, alternatively called the edge or property, is composed of a logic formalization that structures the relation between the first and third parts, the nodes or objects. Node-edge-node represents the graphic form of the triple, and the subject-property-object terms represent the data structure. Object classes connect to build a federated graph, similar to a network in visual form. Because the triple property is a logical statement (a predicate), the data graph represents logical propositions or assertions accepted to be true about the subject matter. These logical formalizations can be manipulated to calculate new triples, representing inferred logical assertions, from the existing data.
To demonstrate a MKB system, a technical proof-of-concept is developed that uses geographically attributed Resource Description Framework (RDF) serializations of linked data for mapping. The proof-of-concept focuses on accessing triple data from visual elements of a geographic map as the interface to the MKB. The map interface is embedded with other essential functions such as SPARQL Protocol and RDF Query Language (SPARQL) data query endpoint services and reasoning capabilities of Apache Marmotta (Apache Software Foundation, 2017). An RDF database of the Geographic Names Information System (GNIS), which contains official names of domestic feature in the United States, was linked to a county data layer from The National Map of the U.S. Geological Survey. The county data are part of a broader Government Units theme offered to the public as Esri shapefiles. The shapefile used to draw the map itself was converted to a geographic-oriented JavaScript Object Notation (JSON) (GeoJSON) format and linked through various properties with a linked geodata version of the GNIS database called “GNIS–LD” (Butler and others, 2016; B. Regalia and others, University of California-Santa Barbara, written commun., 2017). The GNIS–LD files originated in Terse RDF Triple Language (Turtle) format but were converted to a JSON format specialized in linked data, “JSON–LD” (Beckett and Berners-Lee, 2011; Sorny and others, 2014). The GNIS–LD database is composed of roughly three predominant triple data graphs: Features, Names, and History. The graphs include a set of namespace prefixes used by each of the attributes. Predefining the prefixes made the conversion to the JSON–LD format simple to complete because Turtle and JSON–LD are variant specifications of the basic RDF concept.
To convert a shapefile into GeoJSON format to capture the geospatial coordinate geometry objects, an online converter, Mapshaper, was used (Bloch, 2013). To convert the Turtle files, a custom converter written in Java reconstructs the files by parsing each grouping of attributes belonging to one subject and pasting the data into a new file that follows the syntax of JSON–LD. Additionally, the Features file contained its own set of geometries, which was exported into a separate JSON–LD file along with its elevation value to form a fourth file, named “features-geo.json.” Extracted data from external files can be represented in HyperText Markup Language (HTML) path objects. The goal was to import multiple JSON–LD files using this approach.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171150","usgsCitation":"Powell, L.J., and Varanka, D.E., 2018, A linked GeoData map for enabling information access: U.S. Geological Survey Open–File Report 2017–1150, 6 p, https://doi.org/10.3133/ofr20171150.","productDescription":"iv, 6 p.","numberOfPages":"14","onlineOnly":"Y","ipdsId":"IP-090452","costCenters":[{"id":5074,"text":"Center for Geospatial Information Science (CEGIS)","active":true,"usgs":true}],"links":[{"id":350413,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1150/coverthb.jpg"},{"id":350414,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1150/ofr20171150.pdf","text":"Report","size":"376 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1150"}],"contact":"Director, National Geospatial Technical Operations Center
U.S. Geological Survey
1400 Independence Road
Rolla, MO 65401
Groundwater provides more than 40 percent of California’s drinking water. To protect this vital resource, the State of California created the Groundwater Ambient Monitoring and Assessment (GAMA) Program. The GAMA Program’s Priority Basin Project assesses the quality of groundwater resources used for drinking-water supply and increases public access to groundwater-quality information. Many households and small communities in the Madera– Chowchilla and Kings subbasins of the San Joaquin Valley rely on private domestic wells for their drinking-water supplies.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171162","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Fram, M.S. and Shelton, J.L., 2018, Groundwater Quality in the Shallow Aquifers of the Madera–Chowchilla and Kings Subbasins, San Joaquin Valley, California: U.S. Geological Survey Open-File Report 2017–1162, 4 p., https://doi.org/10.3133/ofr20171162.","productDescription":"4 p.","ipdsId":"IP-089766","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":350380,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1162/ofr20171162.pdf","text":"Report","size":"1.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1162"},{"id":350379,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1162/coverthb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Madera– Chowchilla Subbasin, Kings Subbasin, San Joaquin Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.5,\n 36.25\n ],\n [\n -119.25,\n 36.25\n ],\n [\n -119.25,\n 37.25\n ],\n [\n -120.5,\n 37.25\n ],\n [\n -120.5,\n 36.25\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"California Water Science Center
California GAMA
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
Heavy rainfall occurred across central and southern West
Virginia in June 2016 as a result of repeated rounds of torrential
thunderstorms. The storms caused major flooding and flash
flooding in central and southern West Virginia with Kanawha,
Fayette, Nicholas, and Greenbrier Counties among the hardest
hit. Over the duration of the storms, from 8 to 9.37 inches of
rain was reported in areas in Greenbrier County. Peak streamflows
were the highest on record at 7 locations, and streamflows
at 18 locations ranked in the top five for the period of
record at U.S. Geological Survey streamflow-gaging stations
used in this study. Following the storms, U.S. Geological Survey
hydrographers identified and documented 422 high-water
marks in West Virginia, noting location and height of the water
above land surface. Many of these high-water marks were
used to create flood-inundation maps for selected communities
of West Virginia that experienced flooding in June 2016.
Digital datasets of the inundation areas, mapping boundaries,
and water depth rasters are available online.
Director, Virginia and West Virginia Water Science Center
U.S. Geological Survey
1730 East Parham Road
Richmond, VA 23228
A shapefile of 311 undersea features from all major oceans and seas has been created as an aid for retrieving georeferenced information resources. Geospatial information systems with the capability to search user-defined, polygonal geographic areas will be able to utilize this shapefile or secondary products derived from it, such as linked data based on well-known text representations of the individual polygons within the shapefile. Version 1.1 of this report also includes a linked data representation of 299 of these features and their spatial extents.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20141040","usgsCitation":"Hartwell, S., Wingfield, D.K., Allwardt, A., Lightsom, F.L., and Wong, F.L., 2018, Polygons of global undersea features for geographic searches (Version 1.1: June 2018; Version 1.0: March 2014): U.S. Geological Survey Open-File Report 2014-1040, HTML, https://doi.org/10.3133/ofr20141040.","productDescription":"HTML","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-053850","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":284379,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20141040.jpg"},{"id":284377,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1040/","text":"Index page","linkFileType":{"id":5,"text":"html"},"description":"OFR 2014-1040"},{"id":354598,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2014/1040/versionHist.txt","size":"1.75 KB","linkFileType":{"id":2,"text":"txt"}},{"id":284378,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2014/1040/ofr2014-1040-title_page.html","text":"Report (HTML)"}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -180.0,-90.0 ], [ -180.0,90.0 ], [ 180.0,90.0 ], [ 180.0,-90.0 ], [ -180.0,-90.0 ] ] ] } } ] }","edition":"Version 1.1: June 2018; Version 1.0: March 2014","contact":"Director, Woods Hole Coastal and Marine Science Center
U.S. Geological Survey
384 Woods Hole Road
Quissett Campus
Woods Hole, MA 02543
The U.S. Geological Survey currently (2020) publishes information on concentrations and loads of water-quality constituents at 110 sites across the United States as part of the U.S. Geological Survey National Water Quality Network (NWQN). This report details historical and updated methods for computing water-quality loads at NWQN sites. The primary updates to historical load estimation methods include (1) an adaptation to methods for computing loads to the Gulf of Mexico; (2) the inclusion of loads and trends computed using the Weighted Regressions on Time, Discharge, and Season (WRTDS) and Weighted Regressions on Time, Discharge, and Season with Kalman filtering (WRTDS–K) methods; and (3) the inclusion of loads computed using continuous water-quality data. Loads computed using WRTDS and WRTDS–K and continuous water-quality data are provided along with those computed using historical methods. Various aspects of method updates are evaluated in this report to help users of water-quality loading data determine which estimation methods best suit their particular application.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171120","usgsCitation":"Lee, C.J., Murphy, J.C., Crawford, C.G., and Deacon, J.R, 2017, Methods for computing water-quality loads at sites in the U.S. Geological Survey National Water Quality Network (ver. 1.3, August 2021): U.S. Geological Survey Open-File Report 2017–1120, 20 p., https://doi.org/10.3133/ofr20171120.","productDescription":"Report: vii, 20 p.; Version History","onlineOnly":"Y","ipdsId":"IP-086966","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":438099,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P93DHTRJ","text":"USGS data release","linkHelpText":"Nutrient and pesticide data collected from the USGS National Water Quality Network and previous networks, 1950-2022"},{"id":438098,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P948Z0VZ","text":"USGS data release","linkHelpText":"Nutrient and pesticide data collected from the USGS National Water Quality Network and previous networks, 1950-2021"},{"id":388566,"rank":3,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2017/1120/versionHist.txt","text":"Version History","size":"9.89 kB","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2017–1120 Version History"},{"id":388565,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1120/ofr20171120.pdf","text":"Report","size":"14.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017–1120"},{"id":347239,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1120/coverthb4.jpg"}],"edition":"Version 1.3: August 2021; Version 1.2: November 2020; Version 1.1: January 2020; Version 1.0: October 2017","contact":"Director, Kansas Water Science Center
U.S. Geological Survey
1217 Biltmore Drive
Lawrence, KS 66049
The Washington West 30’ × 60’ quadrangle covers an area of approximately 4,884 square kilometers (1,343 square miles) in and west of the Washington, D.C., metropolitan area. The eastern part of the area is highly urbanized, and more rural areas to the west are rapidly being developed. The area lies entirely within the Chesapeake Bay drainage basin and mostly within the Potomac River watershed. It contains part of the Nation's main north-south transportation corridor east of the Blue Ridge Mountains, consisting of Interstate Highway 95, U.S. Highway 1, and railroads, as well as parts of the Capital Beltway and Interstate Highway 66. Extensive Federal land holdings in addition to those in Washington, D.C., include the Marine Corps Development and Education Command at Quantico, Fort Belvoir, Vint Hill Farms Station, the Naval Ordnance Station at Indian Head, the Chesapeake and Ohio Canal National Historic Park, Great Falls Park, and Manassas National Battlefield Park. The quadrangle contains most of Washington, D.C.; part or all of Arlington, Culpeper, Fairfax, Fauquier, Loudoun, Prince William, Rappahannock, and Stafford Counties in northern Virginia; and parts of Charles, Montgomery, and Prince Georges Counties in Maryland.
The Washington West quadrangle spans four geologic provinces. From west to east these provinces are the Blue Ridge province, the early Mesozoic Culpeper basin, the Piedmont province, and the Coastal Plain province. There is some overlap in ages of rocks in the Blue Ridge and Piedmont provinces. The Blue Ridge province, which occupies the western part of the quadrangle, contains metamorphic and igneous rocks of Mesoproterozoic to Early Cambrian age. Mesoproterozoic (Grenville-age) rocks are mostly granitic gneisses, although older metaigneous rocks are found as xenoliths. Small areas of Neoproterozoic metasedimentary rocks nonconformably overlie Mesoproterozoic rocks. Neoproterozoic granitic rocks of the Robertson River Igneous Suite intruded the Mesoproterozoic rocks. The Mesoproterozoic rocks are nonconformably overlain by Neoproterozoic metasedimentary rocks of the Fauquier and Lynchburg Groups, which in turn are overlain by metabasalt of the Catoctin Formation. The Catoctin Formation is overlain by Lower Cambrian clastic metasedimentary rocks of the Chilhowee Group. The Piedmont province is exposed in the east-central part of the map area, between overlapping sedimentary units of the Culpeper basin on the west and those of the Coastal Plain province on the east. In this area, the Piedmont province contains Neoproterozoic and lower Paleozoic metamorphosed sedimentary, volcanic, and plutonic rocks. Allochthonous mélange complexes on the western side of the Piedmont are bordered on the east by metavolcanic and metasedimentary rocks of the Chopawamsic Formation, which has been interpreted as part of volcanic arc. The mélange complexes are unconformably overlain by metasedimentary rocks of the Popes Head Formation. The Silurian and Ordovician Quantico Formation is the youngest metasedimentary unit in this part of the Piedmont. Igneous rocks include the Garrisonville Mafic Complex, transported ultramafic and mafic inclusions in mélanges, monzogranite of the Dale City pluton, and Ordovician tonalitic and granitic plutons. Jurassic diabase dikes are the youngest intrusions. The fault boundary between rocks of the Blue Ridge and Piedmont provinces is concealed beneath the Culpeper basin in this area but is exposed farther south. Early Mesozoic rocks of the Culpeper basin unconformably overlie those of the Piedmont and Blue Ridge provinces in the central part of the quadrangle. The north-northeast-trending extensional basin contains Upper Triassic to Lower Jurassic nonmarine sedimentary rocks. Lower Jurassic sedimentary strata are interbedded with basalt flows, and both Upper Triassic and Lower Jurassic strata are intruded by diabase of Early Jurassic age. The Bull Run Mountain fault, a major Mesozoic normal fault characterized by down-to-the-east displacement, separates rocks of the Culpeper basin from those of the Blue Ridge province on the west. On the east, the contact between rocks of the Culpeper basin and those of the Piedmont province is an unconformity, which has been locally disrupted by normal faults. Sediments of the Coastal Plain province unconformably overlie rocks of the Piedmont province along the Fall Zone and occupy the eastern part of the quadrangle. Lower Cretaceous deposits of the Potomac Formation consist of fluvial-deltaic gravels, sands, silts, and clays. Discontinuous fluvial and estuarine terrace deposits of Pleistocene and middle- to late-Tertiary age flank the modern Potomac River valley unconformable capping these Cretaceous strata and the crystalline basement where the Cretaceous has been removed by erosion. East of the Potomac River, the Potomac Formation is onlapped and unconformably overlain by a westward thinning wedge of marine sedimentary deposits of Late Cretaceous and early- and late-Tertiary age. Basement rooted Coastal Plain faults of Tertiary to Quaternary age occur along the Fall Zone and this part of the inner Coastal Plain. These Coastal Plain faults have geomorphic expression that appear to influence river drainage patterns.
The geologic map of the Washington West quadrangle is intended to serve as a foundation for applying geologic information to problems involving land use decisions, groundwater availability and quality, earth resources such as natural aggregate for construction, assessment of natural hazards, and engineering and environmental studies for waste disposal sites and construction projects. This 1:100,000-scale map is mainly based on more detailed geologic mapping at a scale of 1:24,000.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171142","usgsCitation":"Lyttle, P.T., Aleinikoff, J.N., Burton, W.C., Crider, E.A., Jr., Drake, A.A., Jr., Froelich, A.J., Horton, J.W., Jr., Kasselas, Gregorios, Mixon, R.B., McCartan, Lucy, Nelson, A.E., Newell, W.L., Pavlides, Louis, Powars, D.S., Southworth, C.S., and Weems, R.E., 2017, Geologic map of the Washington West 30’ × 60’ quadrangle, Maryland, Virginia, and Washington D.C.: U.S. Geological Survey Open-File Report 2017–1142, 1 sheet, scale 1:100,000, https://doi.org/10.3133/ofr20171142.","productDescription":"Map: 55.30 x 60.78 inches; Database; Database Metadata; Spatial Data","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-052801","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":350265,"rank":6,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/of/2017/1142/ofr20171142_washington-west-geologic-map-database.zip","text":"Database","size":"102 MB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Washington West Geologic Map Database"},{"id":350266,"rank":7,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2017/1142/ofr20171142_washingtonwestVADCMD-ArcGIS-10.0.mxd","size":"438 KB mxd","linkHelpText":"- Washington West: Maryland, Virginia, and Washington, D.C. (ArcGIS 10.0)"},{"id":350263,"rank":4,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2017/1142/ofr20171142_washington-west-base-map.zip","text":"Base Map","size":"50.4 MB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Washington West Base Map Files"},{"id":350262,"rank":3,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2017/1142/ofr20171142_washington-west-geologic-shapefiles.zip","text":"Shapefiles","size":"9.08 MB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Washington West Geologic Shapefiles"},{"id":350260,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1142/coverthb.jpg"},{"id":350261,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1142/ofr20171142.pdf","text":"Report","size":"35.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1142"},{"id":350264,"rank":5,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/2017/1142/ofr20171142_washington-west-geologic-database-metadata.zip","text":"Database Metadata","linkHelpText":"- Washington West Geologic Database Metadata"}],"country":"United States","state":"Maryland, Virginia","otherGeospatial":"Washington, D.C.","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -78,\n 38.5\n ],\n [\n -77,\n 38.5\n ],\n [\n -77,\n 39\n ],\n [\n -78,\n 39\n ],\n [\n -78,\n 38.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Eastern Geology and Paleoclimate Science Center
U.S. Geological Survey
12201 Sunrise Valley Drive
926A National Center
Reston, VA 20192
In support of earthquake hazard studies and ground motion simulations in the Pacific Northwest, three-dimensional P- and S-wave velocity (VP and VS, respectively) models incorporating the Cascadia subduction zone were previously developed for the region encompassed from about 40.2°N. to 50°N. latitude, and from about 122°W. to 129°W. longitude. This report describes updates to the Cascadia velocity property volumes of model version 1.3 (V1.3), herein called model version 1.6 (V1.6). As in model V1.3, the updated V1.6 model volume includes depths from 0 kilometers (mean sea level) to 60 kilometers, and it is intended to be a reference for researchers who have used, or are planning to use, this model in their Earth science investigations. To this end, it is intended that the VP and VS property volumes of model V1.6 will be considered a template for a community velocity model of the Cascadia region as additional results become available. With the recent and ongoing development of the National Crustal Model, we envision any future versions of this model will be directly integrated with that effort.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171152","collaboration":"Earthquake Hazards Ground Motion Investigations","usgsCitation":"Stephenson, W.J., Reitman, N.G., and Angster, S.J., 2017, P- and S-wave velocity models incorporating the Cascadia subduction zone for 3D earthquake ground motion simulations, version 1.6—Update for Open-File Report 2007–1348 (ver. 1.1, Sept. 10, 2019): U.S. Geological Survey Open-File Report 2017–1152, 17 p., https://doi.org/10.3133/ofr20171152. [Supersedes USGS Open-File Report 2007–1348.]","productDescription":"Report: vi, 17 p.; Read Me; Data Release","numberOfPages":"28","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-088666","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":350108,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7NS0SWM","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Data for P- and S-wave Seismic Velocity Models Incorporating the Cascadia Subduction Zone for 3D Earthquake Ground Motion simulations-Update for Open-File Report 2007-1348"},{"id":350107,"rank":3,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/of/2017/1152/Readme.txt","text":"Read Me","size":"3.82 kB","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2017–1152 Read Me"},{"id":350105,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1152/coverthb2.jpg"},{"id":350106,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1152/ofr20171152.pdf","text":"Report","size":"9.72 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017–1152"},{"id":367615,"rank":5,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2017/1152/versionHist.txt","text":"Version History","size":"4.0 kB","linkFileType":{"id":2,"text":"txt"},"description":"OFR 2017–1152 Version History"}],"country":"Canada, United States","state":"Oregon, Vancouver, Washington","otherGeospatial":"Cascadia Subduction Zone","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -128.583984375,\n 40.36328834091583\n ],\n [\n -121.61865234375,\n 40.36328834091583\n ],\n [\n -121.61865234375,\n 49.92293545449574\n ],\n [\n -128.583984375,\n 49.92293545449574\n ],\n [\n -128.583984375,\n 40.36328834091583\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: December 20, 2017; Version 1.1: September 11, 2019","contact":"Center Director, Geologic Hazards Science Center
U.S. Geological Survey
Box 25046 Mail Stop 966
Denver, CO 80225
Generating an informative display of groundwater withdrawals can sometimes be difficult because the symbols for closely spaced wells can overlap. An alternative method for displaying groundwater withdrawals is to generate a “footprint” of the withdrawals. WellFootprint version 1.0 implements the Footprint algorithm with two optional variations that can speed up the footprint calculation. ModelMuse has been modified in order to generate the input for WellFootprint and to read and graphically display the output from WellFootprint.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171137","usgsCitation":"Winston, R.B., and Goode, D.J., 2017, Visualization of groundwater withdrawals: U.S. Geological Survey Open-File Report 2017–1137, 8 p., https://doi.org/10.3133/ofr20171137.","productDescription":"Report: vi, 8 p.; Application Site","numberOfPages":"18","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-089907","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":438124,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F70C4TQ8","text":"USGS data release","linkHelpText":"WellFootprint Software Release"},{"id":350110,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1137/ofr20171137.pdf","text":"Report","size":"1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1137"},{"id":350113,"rank":3,"type":{"id":4,"text":"Application Site"},"url":"https://doi.org/10.5066/F70C4TQ8","linkHelpText":"- WellFootprint source code and examples: U.S. Geological Survey software release"},{"id":350109,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1137/coverthb.jpg"}],"contact":"Director, Integrated Modeling and Prediction Division
U.S. Geological Survey
MS 415 National Center
12201 Sunrise Valley Drive
Reston, VA 20192
The U.S. Geological Survey (USGS) Hydrologic Instrumentation Facility evaluated three Hydrolab HL4 multiparameter water-quality sondes by OTT Hydromet. The sondes were equipped with temperature, conductivity, pH, dissolved oxygen (DO), and turbidity sensors. The sensors were evaluated for compliance with the USGS National Field Manual for the Collection of Water-Quality Data (NFM) criteria for continuous water-quality monitors and to verify the validity of the manufacturer’s technical specifications. The conductivity sensors were evaluated for the accuracy of the specific conductance (SC) values (conductance at 25 degrees Celsius [oC]), that were calculated by using the vendor default method, Hydrolab Fresh. The HL4’s communication protocols and operating temperature range along with accuracy of the water-quality sensors were tested in a controlled laboratory setting May 1–19, 2016. To evaluate the sonde’s performance in a surface-water field application, an HL4 equipped with temperature, conductivity, pH, DO, and turbidity sensors was deployed June 20–July 22, 2016, at USGS water-monitoring site 02492620, Pearl River at National Space Technology Laboratories (NSTL) Station, Mississippi, located near Bay Saint Louis, Mississippi, and compared to the adjacent well-maintained EXO2 site sonde.
The three HL4 sondes met the USGS temperature testing criteria and the manufacturer’s technical specifications for temperature based upon the median room temperature difference between the measured and standard temperatures, but two of the three sondes exceeded the allowable difference criteria at the temperature extremes of approximately 5 and 40 ºC. Two sondes met the USGS criteria for SC. One of the sondes failed the criteria for SC when evaluated in a 100,000-microsiemens-per-centimeter (μS/cm) standard at room temperature, and also failed in a 10,000-μS/cm standard at 5, 15, and 40 ºC. All three sondes met the USGS criteria for pH and DO at room temperature, but one sonde exceeded the allowable difference criteria when tested in pH 5.00 buffer and at 40 ºC. The USGS criteria and the technical specifications for turbidity were met by one sonde in standards ranging from 10 to 3,000 nephelometric turbidity units (NTU). A second sonde met the USGS criteria and the technical specifications except in the 3,000-NTU standard, and the third sonde exceeded the USGS calibration criteria in the 10- and 20-NTU standards and the technical specifications in the 20-NTU standard.
Results of the field test showed acceptable performance and revealed that differences in data sample processing between sonde manufacturers may result in variances between the reported measurements when comparing one sonde to another. These variances in data would be more pronounced in dynamic site conditions. The lack of a wiper or other sensor-cleaning device on the DO sensor could prove problematic, and could limit the use of the HL4 to profiling applications or at sites with limited biofouling.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171153","usgsCitation":"Snazelle, T.T., 2017, Evaluation of the Hydrolab HL4 water-quality sonde and sensors: U.S. Geological Survey Open-File Report 2017–1153, 20 p., https://doi.org/10.3133/ofr20171153.","productDescription":"Report: v, 20 p.; Data; Metadata","numberOfPages":"30","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-072173","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":350018,"rank":3,"type":{"id":16,"text":"Metadata"},"url":"https://www.sciencebase.gov/catalog/item/59b94eaae4b091459a54d8f9","text":"Data and Metadata ","linkHelpText":"Evaluation of Hydrolab HL4 Water-Quality Sondes and Sensors"},{"id":350016,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1153/coverthb.jpg"},{"id":350017,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1153/ofr20171153.pdf","text":"Report","size":"602 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017–1153"}],"contact":"Chief, Hydrologic Instrumentation Facility
U.S. Geological Survey
Building 2101
Stennis Space Center, MS 39529
We worked with managers in two focal areas to plan for the uncertain future by integrating quantitative climate change scenarios and simulation modeling into scenario planning exercises.
In our central North Dakota focal area, centered on Knife River Indian Villages National Historic Site, managers are concerned about how changes in flood severity and growing conditions for native and invasive plants may affect archaeological resources and cultural landscapes associated with the Knife and Missouri Rivers. Climate projections and hydrological modeling based on those projections indicate plausible changes in spring and summer soil moisture ranging from a 7 percent decrease to a 13 percent increase and maximum winter snowpack (important for spring flooding) changes ranging from a 13 percent decrease to a 47 percent increase. Facilitated discussions among managers and scientists exploring the implications of these different climate scenarios for resource management revealed potential conflicts between protecting archeological sites and fostering riparian cottonwood forests. The discussions also indicated the need to prioritize archeological sites for excavation or protection and culturally important plant species for intensive management attention.
In our southwestern South Dakota focal area, centered on Badlands National Park, managers are concerned about how changing climate will affect vegetation production, wildlife populations, and erosion of fossils, archeological artifacts, and roads. Climate scenarios explored by managers and scientists in this focal area ranged from a 13 percent decrease to a 33 percent increase in spring precipitation, which is critical to plant growth in the northern Great Plains region, and a slight decrease to a near doubling of intense rain events. Facilitated discussions in this focal area concluded that greater effort should be put into preparing for emergency protection, excavation, and preservation of exposed fossils or artifacts and revealed substantial opportunities for different agencies to learn from each other and cooperate on common management goals. Follow up quantitative simulation modeling of grassland dynamics helped quantify the degree of change expected in vegetation production under the wide range of climate scenarios and suggested that (a) low grazing rates could be adversely affecting vegetation composition in the national park and (b) understanding of the management practices needed to maintain desired vegetation conditions is incomplete.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171129","usgsCitation":"Symstad, A.J., Miller, B.W., Friedman, J.M., Fisichelli, N.A., Ray, A.J., Rowland, Erika, and Schuurman, G.W., 2017, Model-based scenario planning to inform climate change adaptation in the Northern Great Plains—Final report: U.S. Geological Survey Open-File Report 2017–1129, 22 p., https://doi.org/10.3133/ofr20171129.","productDescription":"Report: vii, 22 p.; Data Release","numberOfPages":"34","onlineOnly":"Y","ipdsId":"IP-089059","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":348794,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1129/coverthb.jpg"},{"id":348795,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1129/ofr20171129.pdf","text":"Report","size":"2.63 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017–1129"},{"id":348796,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7T1524X","text":"USGS data release","linkHelpText":"State-and-transition simulation model of rangeland vegetation in southwest South Dakota (1969–2050)"}],"country":"United States","state":"Montana, Nebraska, North Dakota, South Dakota, Wyoming","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114,\n 41\n ],\n [\n -97,\n 41\n ],\n [\n -97,\n 49\n ],\n [\n -114,\n 49\n ],\n [\n -114,\n 41\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Northern Prairie Wildlife Research Center
U.S. Geological Survey
8711 37th Street Southeast
Jamestown, North Dakota 58401
Sequoia Scientific’s LISST-ABS is an acoustic backscatter sensor designed to measure suspended-sediment concentration at a point source. Three LISST-ABS were evaluated at the U.S. Geological Survey (USGS) Hydrologic Instrumentation Facility (HIF). Serial numbers 6010, 6039, and 6058 were assessed for accuracy in solutions with varying particle-size distributions and for the effect of temperature on sensor accuracy. Certified sediment samples composed of different ranges of particle size were purchased from Powder Technology Inc. These sediment samples were 30–80-micron (µm) Arizona Test Dust; less than 22-µm ISO 12103-1, A1 Ultrafine Test Dust; and 149-µm MIL-STD 810E Silica Dust. The sensor was able to accurately measure suspended-sediment concentration when calibrated with sediment of the same particle-size distribution as the measured. Overall testing demonstrated that sensors calibrated with finer sized sediments overdetect sediment concentrations with coarser sized sediments, and sensors calibrated with coarser sized sediments do not detect increases in sediment concentrations from small and fine sediments. These test results are not unexpected for an acoustic-backscatter device and stress the need for using accurate site-specific particle-size distributions during sensor calibration. When calibrated for ultrafine dust with a less than 22-µm particle size (silt) and with the Arizona Test Dust with a 30–80-µm range, the data from sensor 6039 were biased high when fractions of the coarser (149-µm) Silica Dust were added. Data from sensor 6058 showed similar results with an elevated response to coarser material when calibrated with a finer particle-size distribution and a lack of detection when subjected to finer particle-size sediment. Sensor 6010 was also tested for the effect of dissimilar particle size during the calibration and showed little effect. Subsequent testing revealed problems with this sensor, including an inadequate temperature compensation, making this data questionable. The sensor was replaced by Sequoia Scientific with serial number 6039. Results from the extended temperature testing showed proper temperature compensation for sensor 6039, and results from the dissimilar calibration/testing particle-size distribution closely corroborated the results from sensor 6058.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171154","usgsCitation":"Snazelle, T.T., 2017, Laboratory evaluation of the Sequoia Scientific LISST-ABS acoustic backscatter sediment sensor: U.S. Geological Survey Open-File Report 2017–1154, 21 p., https://doi.org/10.3133/ofr20171154.","productDescription":"Report: vii, 21 p.; Data; Metadata","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-083385","costCenters":[{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"links":[{"id":350020,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1154/ofr20171154.pdf","text":"Report","size":"921 kB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017–1154"},{"id":350021,"rank":3,"type":{"id":16,"text":"Metadata"},"url":"https://www.sciencebase.gov/catalog/item/59ba9376e4b091459a563ba7","text":"Data and Metadata","linkHelpText":"HIF evaluation of LISST-ABS"},{"id":350019,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1154/coverthb.jpg"}],"contact":"Chief, Hydrologic Instrumentation Facility
U.S. Geological Survey
Building 2101
Stennis Space Center, MS 39529
In previous tests of the effectiveness of four common fish screen materials for excluding lamprey ammocoetes, we determined that woven wire (WW) allowed substantially more entrainment than perforated plate (PP), profile bar (PB), or Intralox (IL) material. These tests were simplistic because they used small vertically-oriented screens positioned perpendicular to the flow without a bypass or a sweeping velocity (SV). In the subsequent test discussed in this report, we exposed ammocoetes to much larger (2.5-m-wide) screen panels with flows up to 10 ft3 /s, a SV component, and a simulated bypass channel. The addition of a SV modestly improved protection of lamprey ammocoetes for all materials tested. A SV of 35 cm/s with an approach velocity (AV) of 12 cm/s, was able to provide protection for fish about 5–15 mm smaller than the protection provided by an AV of 12 cm/s without a SV component. The best-performing screen panels (PP, IL, and PB) provided nearly complete protection from entrainment for fish greater than 50-mm toal length, but the larger openings in the WW material only protected fish greater than 100-mm total length. Decreasing the AV and SV by 50 percent expanded the size range of protected lampreys by about 10–15 mm for those exposed to IL and WW screens, and it decreased the protective ability of PP screens by about 10 mm. Much of the improvement for IL and WW screens under the reduced flow conditions resulted from an increase in the number of lampreys swimming away from the screen. Fish of all sizes became impinged (that is, stuck on the screen surface for more than 1 s) on the screens, with the rate of impingement highest on PP (39– 72 percent) and lowest on WW (7–22 percent). Although impingements were common, injuries were rare, and 24-h post-test survival was greater than 99 percent. Our results refined the level of protection provided by these screen materials when both an AV and SV are present and confirmed our earlier recommendation that WW screens be replaced with more effective materials. Future work should focus on determining the risks associated with other screen types (for example, rotary drum screens, horizontal flat plate screens) and exploring the effectiveness of higher SV:AV ratios, because it may help expand the range of sizes protected by the best performing materials.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171163","usgsCitation":"Mesa, M.G., Liedtke, T.L., Weiland, L.K., and Christiansen, H.E., 2017, Effectiveness of common fish screen materials for protecting lamprey ammocoetes—Influence of sweeping velocities and decreasing flows: U.S. Geological Survey Open-File Report 2017-1163, 19 p., https://doi.org/10.3133/ofr20171163.","productDescription":"iv, 19 p.","numberOfPages":"28","ipdsId":"IP-092482","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":350014,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1163/ofr20171163.pdf","text":"Report","size":"836 KB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1163"},{"id":350013,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1163/coverthb.jpg"}],"contact":"Director, Western Fisheries Research Center
U.S. Geological Survey
6505 NE 65th Street
Seattle, Washington 98115
The U.S. Geological Survey evaluated the interaction of groundwater and surface water in the central part of Sevier County, Tennessee, from October 2015 through October 2016. Stream base flow was surveyed in December 2015 and in July and October 2016 to evaluate losing and gaining stream reaches along three streams in the area. During a July 2016 synoptic survey, groundwater levels were measured in wells screened in the Cambrian-Ordovician aquifer to define the potentiometric surface in the area. The middle and lower reaches of the Little Pigeon River and the middle reaches of Middle Creek and the West Prong Little Pigeon River were gaining streams at base-flow conditions. The lower segments of the West Prong Little Pigeon River and Middle Creek were losing reaches under base-flow conditions, with substantial flow losses in the West Prong Little Pigeon River and complete subsurface diversion of flow in Middle Creek through a series of sinkholes that developed in the streambed and adjacent flood plain beginning in 2010. The potentiometric surface of the Cambrian-Ordovician aquifer showed depressed water levels in the area where loss of flow occurred in the lower reaches of West Prong Little Pigeon River and Middle Creek. Continuous dewatering activities at a rock quarry located in this area appear to have lowered groundwater levels by as much as 180 feet, which likely is the cause of flow losses observed in the two streams, and a contributing factor to the development of sinkholes at Middle Creek near Collier Drive.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171147","collaboration":"Prepared in cooperation with the City of Sevierville and Tennessee Department of Environment and Conservation","usgsCitation":"Carmichael, J.K., and Johnson, G.C., 2017, Groundwater/surface-water interaction in central Sevier County, Tennessee, October 2015–2016: U.S. Geological Survey Open-File Report 2017–1147, 22 p., https://doi.org/10.3133/ofr20171147.","productDescription":"v, 22 p.","numberOfPages":"32","onlineOnly":"N","ipdsId":"IP-086182","costCenters":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"links":[{"id":349937,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1147/coverthb.jpg"},{"id":349938,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1147/ofr20171147.pdf","text":"Report","size":"2.53 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017–1147"}],"country":"United States","state":"Tennessee","county":"Sevier County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.60664367675781,\n 35.74261114799056\n ],\n [\n -83.38485717773438,\n 35.74261114799056\n ],\n [\n -83.38485717773438,\n 35.88126165890356\n ],\n [\n -83.60664367675781,\n 35.88126165890356\n ],\n [\n -83.60664367675781,\n 35.74261114799056\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Lower Mississippi-Gulf Water Science Center—Tennessee
U.S. Geological Survey
640 Grassmere Park, Suite 100
Nashville, TN 37211
Concentrations of particulate organic carbon (POC) and dissolved organic carbon (DOC), which together comprise total organic carbon, were measured in this reconnaissance study at sampling sites in the Upper Klamath River, Lost River, and Klamath Straits Drain in 2013–16. Optical absorbance and fluorescence properties of dissolved organic matter (DOM), which contains DOC, also were analyzed. Parallel factor analysis was used to decompose the optical fluorescence data into five key components for all samples. Principal component analysis (PCA) was used to investigate differences in DOM source and processing among sites.
At all sites in this study, average DOC concentrations were higher than average POC concentrations. The highest DOC concentrations were at sites in the Klamath Straits Drain and at Pump Plant D. Evaluation of optical properties indicated that Klamath Straits Drain DOM had a refractory, terrestrial source, likely extracted from the interaction of this water with wetland peats and irrigated soils. Pump Plant D DOM exhibited more labile characteristics, which could, for instance, indicate contributions from algal or microbial exudates. The samples from Klamath River also had more microbial or algal derived material, as indicated by PCA analysis of the optical properties. Most sites, except Pump Plant D, showed a linear relation between fluorescent dissolved organic matter (fDOM) and DOC concentration, indicating these measurements are highly correlated (R2=0.84), and thus a continuous fDOM probe could be used to estimate DOC loads from these sites.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171160","collaboration":"Prepared in cooperation with the Bureau of Reclamation","usgsCitation":"Goldman, J.H., and Sullivan, A.B., 2017, Characteristics of dissolved organic matter in the Upper Klamath River, Lost River, and Klamath Straits Drain, Oregon and California: U.S. Geological Survey Open File Report 2017-1160, 21 p., https://doi.org/10.3133/ofr20171160.","productDescription":"Report: iv, 21 p.; Data Release","numberOfPages":"29","onlineOnly":"Y","ipdsId":"IP-088888","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":349912,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1160/coverthb.jpg"},{"id":349913,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1160/ofr20171160.pdf","text":"Report","size":"3.2 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1160"},{"id":349914,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F71Z42V4","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Data from an analysis of dissolved organic matter in the Upper Klamath River, Lost River, and Klamath Straits Drain, Oregon and California, 2013–16"}],"country":"United States","state":"California, Oregon","otherGeospatial":"Lost River, Klamath Straits Drain, Upper Klamath River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.05261230468751,\n 41.77131167976407\n ],\n [\n -121.0308837890625,\n 41.77131167976407\n ],\n [\n -121.0308837890625,\n 42.44980808481614\n ],\n [\n -122.05261230468751,\n 42.44980808481614\n ],\n [\n -122.05261230468751,\n 41.77131167976407\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Oregon Water Science Center
U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
The mission of the National Strong-Motion Project is to provide measurements of how the ground and built environment behave during earthquake shaking to the earthquake engineering community, the scientific community, emergency managers, public agencies, industry, media, and other users for the following purposes:
Director,
Earthquake Science Center
U.S. Geological Survey
345 Middlefield Road
Mail Stop 977
Menlo Park, CA 94025