Approximately 2 million California residents rely on privately owned domestic wells for drinking water. During the California drought of 2012−16 groundwater levels declined in many parts of the state and wells were deepened in response. Most of the wells deepened during this time were domestic wells that were drilled into fractured bedrock throughout the Sierra Nevada foothills region of northern California. To understand the impacts of extreme drought on groundwater supply availability and quality in this setting, the United States Geological Survey completed a geochemical survey of domestic wells throughout the Yuba and Bear River watersheds during 2015–16 as part of the State Water Board’s Groundwater Ambient Monitoring and Assessment Program Priority Basin Project (GAMA-PBP). This fact sheet highlights key findings from the GAMA-PBP assessment.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20193077","collaboration":"Prepared in cooperation with the California State Water Resources Control Board","usgsCitation":"Levy, Z.F., Fram, M.S., and Taylor, K.A., 2020, Effects of surface-water use on domestic groundwater availability and quality during drought in the Sierra Nevada foothills, California: U.S. Geological Survey Fact Sheet 2019–3077, 4 p., https://doi.org/10.3133/fs20193077.","productDescription":"4 p.","ipdsId":"IP-109313","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":399144,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109594.htm"},{"id":371195,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2019/3077/coverthb.jpg"},{"id":371196,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2019/3077/fs20193077.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2019-3077"}],"country":"United States","state":"California","otherGeospatial":"Sierra Nevada foothills","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.3314,\n 38.9833\n ],\n [\n -120.3167,\n 38.9833\n ],\n [\n -120.3167,\n 39.7769\n ],\n [\n -121.3314,\n 39.7769\n ],\n [\n -121.3314,\n 38.9833\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"GAMA Project Chief
U.S. Geological Survey
California Water Science Center
6000 J Street, Placer Hall
Sacramento, CA 95819
Telephone number: (916) 278-3000
GAMA Program Unit Chief
State Water Resources Control Board
Division of Water Quality
PO Box 2231, Sacramento, CA 95812
Telephone number: (916) 341-5855
Multiple aquifer tests were conducted in Lovelock, Nevada, to determine hydraulic conductivity and storage properties to be used with the numerical groundwater flow model of the lower Humboldt River Basin while accounting for the influence of surface features with a modeling component. The numerical model will ultimately provide the Nevada Division of Water Resources (NDWR) with information regarding the impacts of groundwater pumping on the Humboldt River, allowing the Nevada State Engineer to make informed decisions in the conjunctive management of the State’s groundwater and surface water resources. Seven slug tests, one single-well pumping test, and two multi-well pumping tests were conducted to evaluate properties of shallow Lahontan clays and silts; shallow fluvial deposits; and coarser, water-bearing deposits of the younger alluvium. Aquifer tests were conducted between March 2017 and April 2018. Results indicate aquifers in the Lovelock Valley have transmissivity ranging between 0.0001 and 95,000 feet squared per day (ft2/day). The results of these tests provide constraints on hydraulic properties for a numerical groundwater flow model being developed for a capture study in the lower Humboldt River Basin.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191133","collaboration":"Prepared in cooperation with the Nevada Division of Water Resources","usgsCitation":"Nadler, C., 2020, Analysis of aquifer framework and hydraulic properties of Lovelock Valley, Lovelock, Nevada: U.S. Geological Survey Open-File Report 2019–1133, 48 p., https://doi.org/10.3133/ofr20191133.","productDescription":"Report: viii, 48 p.; Data Release","numberOfPages":"40","onlineOnly":"Y","ipdsId":"IP-098941","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":399425,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109593.htm"},{"id":371146,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1133/ofr20191133.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"}},{"id":371147,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9LIL7PZ","linkHelpText":"Supplemental data for analysis of aquifer framework and hydraulic properties of Lovelock Valley, Lovelock, NV"},{"id":371145,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1133/coverthb.jpg"}],"country":"United States","state":"Nevada","otherGeospatial":"Humboldt River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.597412109375,\n 39.14710270770074\n ],\n [\n -114.70825195312501,\n 39.14710270770074\n ],\n [\n -114.70825195312501,\n 41.91045347666418\n ],\n [\n -118.597412109375,\n 41.91045347666418\n ],\n [\n -118.597412109375,\n 39.14710270770074\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Nevada Water Science Center
U.S. Geological Survey
2730 N. Deer Run Road
Carson City, Nevada 95819
This geologic map of the Greater Antilles and the Virgin Islands is a compilation of information from the literature, integrated to provide a seamless geologic map of the region. The geology shown on sheet 1 covers Cuba, the island of Hispaniola, which includes Haiti and the Dominican Republic, Jamaica, the Cayman Islands, Puerto Rico, and the U.S. and British Virgin Islands. A second more detailed sheet shows the geology of Puerto Rico and the Virgin Islands. The map units shown here are integrated across the islands of the Greater Antilles and the Virgin Islands.
The Greater Antilles and the Virgin Islands, although they appear to reflect the character of a magmatic arc, actually represent multiple, distinct geologic features. Only in Cuba are there unquestioned Jurassic-age, and perhaps older, rocks present. On the islands of Hispaniola (Haiti and the Dominican Republic) and Puerto Rico, metamorphic assemblages contain rocks that may be of Jurassic age. Ophiolite assemblages that may include rocks of Jurassic age are present in Cuba, the Dominican Republic, Haiti, and Puerto Rico. Metamorphic rocks of Cretaceous age are more widespread, present in Cuba, Hispaniola, and the U.S. and British Virgin Islands. Cretaceous plutonic rocks are present in Cuba and Puerto Rico, as well as in the Dominican Republic (in the Cordillera Central and in the eastern part of the country). Gabbro and trondhjemite of inferred Early Cretaceous age are present in the U.S. Virgin Islands. Cretaceous volcanic rocks are widespread in Cuba, Hispaniola, Puerto Rico, and the Virgin Islands; they are of variable age and do not appear to reflect a single arc system. Cretaceous volcanic rocks are also found in Jamaica, in inliers on the eastern part of the island. Eocene volcanic rocks are prominent in southern Cuba, Haiti, eastern Jamaica, Puerto Rico, and the Virgin Islands. Volcanic rocks possibly as young as early Miocene are present in the southern Dominican Republic; the youngest volcanic rocks in the region are the Low Layton Lavas of Jamaica of late Miocene age and alkali basalt of Quaternary age on Hispaniola.
Carbonate rocks are an important component of the sedimentary section in the Greater Antilles, which is as old as Jurassic in Cuba and as young as Holocene in many areas. In Cuba, Early Cretaceous sedimentary rocks tend to be dominantly carbonates; volcanic clasts and debris are not present until the Late Cretaceous in Cuba, as well as in Jamaica and Puerto Rico. In contrast, Early Cretaceous volcaniclastic sedimentary rocks are common in the Virgin Islands. Olistostrome deposits are commonly described in latest Cretaceous and Eocene rocks; in the Paleocene and the early Eocene, these deposits are commonly associated with mélange units. Volcanic debris and tuff are common in sedimentary rocks of Paleocene and Eocene age, typically associated with carbonate rocks. Sedimentary rocks that postdate the Eocene either are dominantly carbonates or are mixed clastic and carbonate rocks in which the clastic component reflects erosion of earlier units, including older carbonate rocks. Rocks that contain lignite, which are only present in Cuba and on Hispaniola, generally are of Miocene age.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191036","usgsCitation":"Wilson, F.H., Orris, G., and Gray, F., 2019, Preliminary geologic map of the Greater Antilles and the Virgin Islands: U.S. Geological Survey Open-File Report 2019–1036, pamphlet 50 p., 2 sheets, scales 1:2,500,000 and 1:300,000, https://doi.org/10.3133/ofr20191036.","productDescription":"Pamphlet: iv, 50 p.; 2 Sheets: 51.00 x 34.00 inches and 46.10 x 24.93 inches; 2 Tables; Spatial Data","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-098596","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":399410,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109592.htm"},{"id":399409,"rank":8,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109591.htm"},{"id":371178,"rank":7,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2019/1036/ofr20191036_spatialdata.zip","text":"OFR 2019-1036 spatial data","linkFileType":{"id":6,"text":"zip"},"description":"OFR 2019-1036 Spatial Data"},{"id":371177,"rank":6,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2019/1036/ofr20191036_table2.xlsx","text":"Table 2","linkFileType":{"id":3,"text":"xlsx"},"description":"OFR 2019-1036 Table 2 XLSX"},{"id":371176,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/of/2019/1036/ofr20191036_table2.pdf","text":"Table 2","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1036 Table 2 PDF"},{"id":371173,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1036/ofr20191036_pamphlet.pdf","text":"Pamphlet","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1036"},{"id":371175,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2019/1036/ofr20191036_sheet2.pdf","text":"Sheet 2","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1036 Sheet 2"},{"id":371174,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2019/1036/ofr20191036_sheet1.pdf","text":"Sheet 1","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1036 Sheet 1"},{"id":371172,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1036/coverthb2.jpg"}],"scale":"2500000","country":"Cuba, Dominican Republic, Great Britain, Haiti, Jamaica, United States","otherGeospatial":"Greater Antilles, Hispaniola, Puerto Rico, Virgin Islands","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -85.517578125,\n 23.725011735951796\n ],\n [\n -85.4296875,\n 22.105998799750566\n ],\n [\n -83.84765625,\n 20.138470312451155\n ],\n [\n -76.2890625,\n 15.623036831528264\n ],\n [\n -69.169921875,\n 15.792253570362446\n ],\n [\n -61.435546875,\n 16.46769474828897\n ],\n [\n -60.64453125000001,\n 17.895114303749143\n ],\n [\n -61.52343749999999,\n 21.04349121680354\n ],\n [\n -72.50976562499999,\n 22.187404991398775\n ],\n [\n -82.265625,\n 24.046463999666567\n ],\n [\n -85.517578125,\n 23.725011735951796\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Alaska Science Center
U.S. Geological Survey
4210 University Dr.
Anchorage, AK 99508
Dos Palmas Preserve is a Colorado Desert oasis and wetland in Riverside County, California, located near the base of the Orocopia Mountains and northeast of the Salton Sea. The original source of water for the oasis was artesian springs that developed at the base of the Orocopia Mountains, but more abundant water supplies were later provided to Dos Palmas Preserve when the Coachella Canal was built and water seeped from unlined parts of the canal. As a result of this abundant water supply in a desert setting, Dos Palmas Preserve, managed by the Bureau of Land Management, is now a wildlife preserve that became home to multiple plants, fowl, insects, rodents, reptiles, and bats, including some endangered and threatened species. More recently, sections of the Coachella Canal have been lined, resulting in a reduction of water seepage and threatening the sustainability of parts of Dos Palmas Preserve. Faults usually act as barriers to groundwater flow and Dos Palmas Preserve is only a few kilometers from the active trace of the San Andreas Fault, where splays of the fault trend through the area. Additionally, numerous closely spaced faults that have been mapped at the surface northwest of Dos Palmas Preserve are believed to extend southward into the Dos Palmas Preserve, where they are covered by alluvium. Thus, evaluation of the subsurface lithology and structure is needed to determine how the current allocation of water from the Coachella Canal affects various parts of Dos Palmas Preserve.
To better understand the distribution of the shallow lithology, faulting, and groundwater in Dos Palmas Preserve, the U.S. Geological Survey, in collaboration with the Bureau of Land Management, conducted a seismic survey across the northern part of Dos Palmas Preserve. The seismic survey was designed to “map” the upper part of the aquifer system and to more precisely locate faults that may affect groundwater flow in Dos Palmas Preserve. In this report, we present seismic velocity and reflection images of the shallow subsurface and relate those images to interpretative structures and stratigraphy that may affect groundwater at Dos Palmas Preserve.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191130","usgsCitation":"Catchings, R.D., Goldman, M.R., Chan, J.H., Sickler, R.R., Rymer, M.J., and Criley, C.J., 2020, Seismic evaluation of shallow-depth structure, faulting, and groundwater variations across the Dos Palmas Preserve, Riverside County, California: U.S. Geological Survey Open-File Report 2019–1130, 21 p., https://doi.org/ 10.3133/ofr20191130.","productDescription":"Report: vi, 21 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-101151","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":399421,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109590.htm"},{"id":371135,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9WQJ5EH","text":"USGS data release","description":"USGS Data Release","linkHelpText":"2015 high resolution seismic acquisition at Dos Palmas Preserve, Mecca, California"},{"id":371134,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1130/ofr20191130.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1130"},{"id":371133,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1130/coverthb.jpg"}],"country":"United States","state":"California","county":"Riverside County","otherGeospatial":"Dos Palmas Preserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.0925,\n 33.2881\n ],\n [\n -115.4408,\n 33.2881\n ],\n [\n -115.4408,\n 33.6419\n ],\n [\n -116.0925,\n 33.6419\n ],\n [\n -116.0925,\n 33.2881\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
Repeated sampling and grain-size analysis of surficial sediments along the sandy shorelines of Louisiana is necessary to characterize coastal-zone sediment properties and evaluate sediment transport patterns within the nearshore environments. In 2008, and again in 2015 and 2016, sediment grab samples were collected along the shorelines of the western Chenier plain, the Isles Dernieres (Raccoon, Whiskey, Trinity and East Islands), the Lafourche delta (Timbalier Islands, Caminada Headland, and Grand Isle), the modern delta (Grand Terre Islands from Chaland Headland to Sandy Point), and the Chandeleur Islands (from Curlew Island to Hewes Point). The samples were collected as part of the Louisiana Coastal Protection and Restoration Authority (CPRA) Barrier Island Comprehensive Monitoring (BICM) Program in collaboration with the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center (USGS–SPCMSC) and the University of New Orleans Pontchartrain Institute for Environmental Studies (UNO–PIES). Physical properties of the samples (sediment grain size and sorting) were measured and provided in data reports to CPRA. Additional samples collected by the USGS from around Breton Island in 2014 and 2015 supplemented the 2015–2016 BICM data to complete the coastwide dataset. This report compares the results of the 2008 and 2015–2016 sedimentologic analyses and documents changes in composition (percent sand) and mean sediment grain size between the two time periods. At most sample sites, differences in mean grain size varied by less than ±0.25 Φ. The largest changes occurred at sites located near tidal inlets or along rapidly eroding shorelines.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191132","collaboration":"Prepared in cooperation with the University of New Orleans and Louisiana Coastal Protection and Restoration Authority","usgsCitation":"Bosse, S.T., Flocks, J.G., Bernier, J.C., Georgiou, I.Y., Kulp, M.A., and Brown, M., 2019, Louisiana Coastal Zone sediment characterization; comparison of sediment grain sizes for samples collected in 2008 and 2015–2016 from the western Chenier plain to the Chandeleur Islands, Louisiana—Louisiana Barrier Island Comprehensive Monitoring (BICM) Program: U.S. Geological Survey Open-File Report 2019–1132, 17 p., https://doi.org/10.3133/ofr20191132.","productDescription":"vi, 17 p.","numberOfPages":"24","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-107806","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":371101,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1132/report-thumb.jpg"},{"id":371102,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1132/ofr20191132.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1132"},{"id":399424,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109589.htm"},{"id":399423,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109588.htm"}],"country":"United States","state":"Louisiana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.8333,\n 29.6667\n ],\n [\n -93,\n 29.6667\n ],\n [\n -93,\n 29.7889\n ],\n [\n -93.8333,\n 29.7889\n ],\n [\n -93.8333,\n 29.6667\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"St. Petersburg Coastal and Marine Science Center
U.S. Geological Survey
600 4th Street South
St. Petersburg, FL 33701
The United States Geological Survey (USGS) provided technical support to the Washington Department of Ecology (Ecology) in their assessment of the role groundwater plays in contributing pollutant loading to the Green-Duwamish River near Seattle, Washington. Ecology is developing watershed hydrology models of the Green-Duwamish watershed, and need to assign realistic contaminant concentrations to the various Hydrologic Response Units represented in their models. The USGS compiled existing groundwater quality data in the Green-Duwamish watershed, and this report summarizes results and interpretation of the dataset, including identifying data gaps and needs for further research and monitoring. The sources of existing data were the USGS’s National Water Information System, Ecology’s Environmental Information Management System, and a compilation of several studies by Leidos, a scientific research company. The water-quality parameters of interest included polychlorinated biphenyl (PCB) Aroclors and congeners, phthalates, carcinogenic polycyclic aromatic hydrocarbons (cPAHs), arsenic, copper, and zinc. Results were grouped into the four subwatersheds delineated in Ecology’s hydrology models: Duwamish, Lower Green, Soos, and Upper Green. Results from the Duwamish subwatershed were further sub-divided by the USGS into the Lower Duwamish, containing land adjacent to the Lower Duwamish Waterway Superfund site, and the Upper Duwamish, containing the remaining area of the Duwamish subwatershed. Groundwater quality data in the Lower Duwamish were treated separately because there is known contamination in this area. The availability of water quality data varied by subwatershed as follows: phthalate data was only available within the Duwamish, PCB data was available within the Duwamish and Lower Green, cPAH data was available within the Duwamish, Lower Green, and Soos, and data for arsenic, copper, and zinc were available within all four subwatersheds. More than 99 percent of the available data was within the Duwamish subwatershed, identifying a need for additional monitoring of groundwater quality in the other subwatersheds.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191131","collaboration":"Prepared in cooperation with the Washington State Department of Ecology","usgsCitation":"Senter, C.A., Conn, K.E., Black, R.W., Welch, W.B., and Fasser, E.T., 2020, Assessment of existing groundwater quality data in the Green-Duwamish watershed, Washington: U.S. Geological Survey Open-File Report 2019-1131, 35 p., https://doi.org/10.3133/ofr20191131.","productDescription":"iv, 35 p.","onlineOnly":"Y","ipdsId":"IP-111911","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":371094,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1131/coverthb2.jpg"},{"id":371095,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1131/ofr20191131.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1131"},{"id":399422,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109587.htm"}],"country":"United States","state":"Washington","otherGeospatial":"Green-Duwamish watershed","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.26684570312499,\n 47.59505101193038\n ],\n [\n -122.420654296875,\n 47.60245929546312\n ],\n [\n -122.43713378906249,\n 47.51349065484327\n ],\n [\n -122.431640625,\n 47.32393057095941\n ],\n [\n -122.420654296875,\n 47.18597932702905\n ],\n [\n -122.3876953125,\n 47.010225655683485\n ],\n [\n -122.288818359375,\n 46.912750956378915\n ],\n [\n -122.2283935546875,\n 46.781254534638606\n ],\n [\n -122.0855712890625,\n 46.558860303117164\n ],\n [\n -121.59667968749999,\n 46.32417161725691\n ],\n [\n -121.39892578125,\n 46.32796494040746\n ],\n [\n -121.30004882812499,\n 46.49839225859763\n ],\n [\n -121.168212890625,\n 46.78501604269254\n ],\n [\n -121.36596679687499,\n 46.991494313050424\n ],\n [\n -121.95922851562501,\n 47.4355191531953\n ],\n [\n -122.26684570312499,\n 47.59505101193038\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
The Amerasia Basin Province encompasses the Canada Basin and the sediment prisms along the Alaska and Canada margins, outboard from basinward margins (hingelines) of the rift shoulders that formed during extensional opening of the Canada Basin. The province includes the Mackenzie River delta and slope, the outer shelves and marine slopes along the Arctic margins of Alaska and Canada, and the deep Canada Basin.
The province is divided into four assessment units (AUs): (1) The Canning-Mackenzie Deformed Margin AU is that part of the rifted margin where the Brooks Range orogenic belt has overridden the rift shoulder and is deforming the rifted-margin prism of sediment outboard of the hingeline. This is the only part of the Amerasia Basin Province that has been explored and—even though more than 3 billion barrels of oil equivalent (BBOE) of oil, gas, and condensate have been discovered— none has been commercially produced. (2) The Alaska Passive Margin AU is the rifted-margin prism of sediment lying beneath the Beaufort Sea outer shelf and slope that has not been deformed by tectonism. (3) The Canada Passive Margin AU is the rifted-margin prism of sediment lying beneath the Arctic outer shelf and slope (also known as the polar margin) of Canada that has not been deformed by tectonism. (4) The Canada Basin AU includes the sedimentary wedge that lies beneath the deep Canada Basin, north of the marine slope developed along the Alaska and Canada margins. Mean estimates of risked, undiscovered, technically recoverable resources include more than 6 billion barrels of oil (BBO), more than 19 trillion cubic feet (TCF) of associated gas, and more than 16 TCF of nonassociated gas in the Canning-Mackenzie Deformed Margin AU; about 1 BBO, about 3 TCF of associated gas, and about 3 TCF of associated gas in the Alaska Passive Margin AU; and more than 2 BBO, about 7 TCF of associated gas, and about 8 TCF of nonassociated gas in the Canada Passive Margin AU. Quantities of natural gas liquids also are assessed in each AU. The Canada Basin AU was not quantitatively assessed because it is judged to hold less than 10 percent probability of containing at least one accumulation of 50 million barrels of oil equivalent.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1824BB","usgsCitation":"Houseknecht, D.W., Bird, K.J., and Garrity, C.P., 2020, Geology and assessment of undiscovered oil and gas resources of the Amerasia Basin Province, 2008, chap. BB of Moore, T.E., and Gautier, D.L., eds., The 2008 Circum-Arctic Resource Appraisal: U.S. Geological Survey Professional Paper 1824, 33 p., https://doi.org/10.3133/pp1824BB. [Supersedes USGS Scientific Investigations Report 2012–5146.","productDescription":"Report: viii, 33 p.; 3 Appendixes","onlineOnly":"Y","ipdsId":"IP-114214","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":371072,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1824/bb/pp1824bb_appendix3.xlsx","text":"Appendix 3 —","linkFileType":{"id":3,"text":"xlsx"},"description":"PP 1824 Chapter BB Appendix 3","linkHelpText":"Input data for the Canada Passive Margin Assessment Unit"},{"id":371071,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1824/bb/pp1824bb_appendix2.xlsx","text":"Appendix 2 —","linkFileType":{"id":3,"text":"xlsx"},"description":"PP 1824 Chapter BB Appendix 2","linkHelpText":"Input data for the Alaska Passive Margin Assessment Unit"},{"id":371070,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/pp/1824/bb/pp1824bb_appendix1.xlsx","text":"Appendix 1 —","linkFileType":{"id":3,"text":"xlsx"},"description":"PP 1824 Chapter BB Appendix 1","linkHelpText":"Input data for the Canning-Mackenzie Deformed Margin Assessment Unit"},{"id":371069,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/1824/bb/pp1824bb.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"PP 1824 Chapter BB"},{"id":371068,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/pp/1824/bb/coverthb.jpg"},{"id":399505,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109586.htm"}],"country":"United States, Canada","state":"Alaska","otherGeospatial":"Amerasia Basin Province","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -165,\n 69.75\n ],\n [\n -85,\n 69.75\n ],\n [\n -85,\n 80\n ],\n [\n -165,\n 80\n ],\n [\n -165,\n 69.75\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information, Geology, Minerals, Energy, & Geophysics Science Center—Menlo Park
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The key to Horned Lark (Eremophila alpestris) management is maintaining areas with short, sparse vegetation by burning, mowing, or grazing. Horned Larks have been reported to use habitats with less than or equal to (≤) 70 centimeters (cm) average vegetation height, 3–26 cm visual obstruction reading, 15–67 percent grass cover, 3–70 percent forb cover, ≤21 percent shrub cover, 1–44 percent bare ground, ≤63 percent litter cover, and ≤9 cm litter depth.
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During 2014, highly pathogenic (HP) influenza A viruses (IAVs) of the A/Goose/Guangdong/1/1996 lineage (GsGD-HP-H5), originating from Asia, were detected in domestic poultry and wild birds in Canada and the US. These clade 2.3.4.4 GsGD-HP-H5 viruses included reassortants possessing North American lineage gene segments; were detected in wild birds in the Pacific, Central, and Mississippi flyways; and caused the largest HP IAV outbreak in poultry in US history. To determine if an antibody response indicative of previous infection with clade 2.3.4.4 GsGD-HP-H5 IAV could be detected in North American wild waterfowl sampled before, during, and after the 2014–15 outbreak, sera from 2,793 geese and 3,715 ducks were tested by blocking enzyme-linked immunosorbent assay and hemagglutination inhibition (HI) tests using both clade 2.3.4.4 GsGD-HPH5 and North American lineage low pathogenic (LP) H5 IAV antigens. We detected an antibody response meeting a comparative titer-based criteria (HI titer observed with 2.3.4.4 GsGD-HP-H5 antigens exceeded the titer observed for LP H5 antigen by two or more dilutions) for previous infection with clade 2.3.4.4 GsGD-HP-H5 IAV in only five birds, one Blue-winged Teal (Spatula discors) sampled during the outbreak and three Mallards (Anas platyrhynchos) and one Canada Goose (Branta canadensis) sampled during the post-outbreak period. These serologic results are consistent with the spatiotemporal extent of the outbreak in wild birds in North America during 2014 and 2015 and limited exposure of waterfowl to GsGD-HP-H5 IAV, particularly in the central and eastern US.
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Plain, the southeasternmost physiographic province in the United States, is underlain by strata that regionally dip gently eastward and gradually thicken toward the Atlantic Ocean basin. These strata, ranging in age from Middle Jurassic to Holocene, accumulated along the eastern margin of North America after the break-up of the supercontinent Pangaea during the Early Jurassic. In the east-central United States north of Florida, Cape Hatteras is the point of land that most closely approaches the eastern edge of the Atlantic Continental Shelf of the United States. In 1946, Esso (now part of ExxonMobil) drilled a deep oil exploration well to basement rock near the Cape Hatteras lighthouse. No oil or gas was found there, or in any of the other test wells that were drilled within the onshore North Carolina Coastal Plain. Recent work indicates that the top of the oil window lies at 9,000 feet near the base of the Cape Hatteras Esso #1 test well. Therefore, any mature petroleum source rocks that may be present in the North Carolina Coastal Plain are only likely to be found east of the present coastline.
Although the Cape Hatteras test well did not produce oil or gas, it did produce a wealth of stratigraphic information about the outer portion of the onshore Atlantic Continental Shelf. Advances in global stratigraphic correlation, in tandem with our analyses of calcareous nannofossils and dinoflagellate cysts (dinocysts) from the Cape Hatteras test-well spot samples have produced significant advances beyond earlier interpretations of this well and other deep test wells inshore of Cape Hatteras. These results, when coupled with work done offshore of Cape Hatteras, have allowed us to create a more detailed cross section of the North Carolina Coastal Plain and adjacent continental shelf than previously possible.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191145","usgsCitation":"Weems, R.E., Self-Trail, J.M., and Edwards L.E., 2019, Cross section of the North Carolina coastal plain from Enfield through Cape Hatteras: U.S. Geological Survey Open-File Report 2019–1145, 2 sheets, https://doi.org/10.3133/ofr20191145.","productDescription":"2 Sheets: 40.00 x 37.00 inches and 35.00 x 37.00 inches","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-102465","costCenters":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":399432,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109585.htm"},{"id":370654,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1145/ofr20191145_sheet2.pdf","text":"Sheet 2","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1145"},{"id":371011,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1145/ofr20191145_sheet1.pdf","text":"Sheet 1","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1145"},{"id":370630,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1145/coverthb.jpg"}],"country":"United States","state":"North Carolina","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.6513671875,\n 34.63320791137959\n ],\n [\n -75.5419921875,\n 34.63320791137959\n ],\n [\n -75.5419921875,\n 36.1733569352216\n ],\n [\n -77.6513671875,\n 36.1733569352216\n ],\n [\n -77.6513671875,\n 34.63320791137959\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Florence Bascom Geoscience Center
U.S. Geological Survey
926A National Center
12201 Sunrise Valley Drive
Reston, VA 20192
Harrat Rahat, in the west-central part of the Kingdom of Saudi Arabia, is the largest of 15 Cenozoic harrats (Arabic for “volcanic field”) distributed on the Arabian plate. It extends more than 300 km north-south and 50 to 75 km east-west, and it covers an area of approximately 20,000 km2, has a volume of approximately 2,000 km3, and encompasses more than 900 observable vents. Volcanism commenced around 10 Ma and has continued into historic time, the most recent eruption occurring in 1256 C.E. Volcanic products are dominated by alkali basalt and hawaiite lava flows, with subordinate mugearite lava flows, as well as benmoreite and trachyte lava flows, domes, and pyroclastic flows.
This geologic map distinguishes 239 eruptive units that cover an area of 3,340 km2 in northern Harrat Rahat and the adjacent city of Al-Madinah. Results are presented as a geologic map of the study area at 1:75,000 scale and of smaller regions of particular interest at 1:25,000 scale, along with interpretive text.
Most units are basaltic lava flows that erupted from the broadly north-northwest-trending main vent axis that constructed the topographic crest of the volcanic field. This 300- to 400-m-high vent axis, which has a width of 6 to 10 km, lies in the eastern one-third of northern Harrat Rahat. Basalt and hawaiite lava flows can extend as far as 27 km from their vents, but most are 10 to 15 km long. Evolved products such as mugearites, benmoreites, and trachytes are less extensive; the trachytic pyroclastic flows extend as far as 9 km from their source vents, although most only reach 4 to 6 km. Vents of the evolved products are restricted to the main vent axis or its flanks.
No volcanic rocks older than 1.2 Ma are exposed in the map area, and about 90 percent of the exposed volcanic rocks erupted during the past 570 thousand years. As depicted on the geologic maps, eruption ages and field relations define 12 eruptive stages for northern Harrat Rahat for the past 1.2 million years. Other important geochronological findings include (1) several late Pleistocene lava flows near Al-Madinah, which previously were interpreted as Holocene from archeological evidence; (2) the eruption age of a cluster of cinder cones and small lava flows in the western outskirts of Al-Madinah (previously ascribed to an eruption in 641 C.E.) is actually 13.3±1.9 ka, close to the Pleistocene-Holocene boundary; and (3) only two Holocene eruptions have been identified in the map area, those of the historically described basalt of Al Labah in 1256 C.E. and the dome and pyroclastic flows of the trachyte of Um Rgaibah at 4.2±5.2 ka.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3428","collaboration":"Jointly published with the Saudi Geological Survey [as Saudi Geological Survey Special Report SGS–SP–2019–2]","usgsCitation":"Downs, D.T., Robinson, J.E., Stelten, M.E., Champion, D.E., Dietterich, H.R., Sisson, T.W., Zahran, H., Hassan, K., and Shawali, J., 2019, Geologic map of the northern Harrat Rahat volcanic field, Kingdom of Saudi Arabia: U.S. Geological Survey Scientific Investigations Map 3428 [also released as Saudi Geological Survey Special Report SGS–SP–2019–2], 65 p., 4 sheets, scales 1:75,000, 1:25,000, https://doi.org/10.3133/sim3428.","productDescription":"Report: vi, 65 p.; 4 Sheets; Data Release","numberOfPages":"62","additionalOnlineFiles":"Y","ipdsId":"IP-096080","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":370934,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3428/coverthb.jpg"},{"id":370935,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3428/sim3428_pamphlet.pdf","text":"Pamphlet","size":"10 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3428 Pamphlet"},{"id":370936,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3428/sim3428_sheet1.pdf","text":"Sheet 1","size":"45 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3428 Sheet 1","linkHelpText":" - Geologic Map of the Northern Harrat Rahat Volcanic Field, Kingdom of Saudi Arabia"},{"id":370937,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3428/sim3428_sheet2.pdf","text":"Sheet 2","size":"35 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3428 Sheet 2","linkHelpText":" - Geologic Map of the Northern, Central, and Southern Fingers Lava Flows, Northern Harrat Rahat Volcanic Field, Kingdom of Saudi Arabia"},{"id":370938,"rank":5,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3428/sim3428_sheet3.pdf","text":"Sheet 3","size":"30 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3428 Sheet 3","linkHelpText":" - Geologic Map of the Silicic Volcanic Centers Near Al Efairia, Al Wabarah, and Matan, Northern Harrat Rahat Volcanic Field, Kingdom of Saudi Arabia"},{"id":370939,"rank":6,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3428/sim3428_sheet4.pdf","text":"Sheet 4","size":"18 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3428 Sheet 4","linkHelpText":" - Correlation and List of Map Units for the Geologic Map of the Northern Harrat Rahat Volcanic Field, Kingdom of Saudi Arabia"},{"id":370940,"rank":7,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9Q3WGTN","linkHelpText":"Database for the geologic map of the northern Harrat Rahat volcanic field, Kingdom of Saudi Arabia"}],"country":"Kingdom of Saudi Arabia","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[42.77933,16.34789],[42.64957,16.77464],[42.34799,17.07581],[42.27089,17.47472],[41.75438,17.83305],[41.22139,18.6716],[40.93934,19.48649],[40.24765,20.17463],[39.80168,20.33886],[39.1394,21.2919],[39.0237,21.98688],[39.06633,22.57966],[38.49277,23.68845],[38.02386,24.07869],[37.48363,24.28549],[37.15482,24.85848],[37.20949,25.08454],[36.93163,25.60296],[36.6396,25.82623],[36.24914,26.57014],[35.64018,27.37652],[35.13019,28.06335],[34.63234,28.05855],[34.78778,28.60743],[34.83222,28.95748],[34.95604,29.35655],[36.06894,29.19749],[36.50121,29.50525],[36.74053,29.86528],[37.50358,30.00378],[37.66812,30.33867],[37.99885,30.5085],[37.00217,31.50841],[39.00489,32.01022],[39.19547,32.16101],[40.39999,31.88999],[41.88998,31.19001],[44.7095,29.17889],[46.56871,29.09903],[47.45982,29.00252],[47.70885,28.52606],[48.41609,28.552],[48.80759,27.68963],[49.29955,27.46122],[49.47091,27.11],[50.15242,26.68966],[50.21294,26.27703],[50.1133,25.94397],[50.23986,25.60805],[50.52739,25.32781],[50.66056,24.9999],[50.81011,24.75474],[51.11242,24.55633],[51.38961,24.62739],[51.57952,24.2455],[51.61771,24.01422],[52.00073,23.00115],[55.0068,22.49695],[55.20834,22.70833],[55.66666,22],[54.99998,19.99999],[52.00001,19],[49.11667,18.61667],[48.18334,18.16667],[47.46669,17.11668],[47,16.95],[46.74999,17.28334],[46.36666,17.23332],[45.4,17.33334],[45.21665,17.43333],[44.06261,17.41036],[43.79152,17.31998],[43.38079,17.57999],[43.1158,17.08844],[43.21838,16.66689],[42.77933,16.34789]]]},\"properties\":{\"name\":\"Saudi Arabia\"}}]}","contact":"Volcano Science Center - Menlo Park
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Tidal wetland loss in Jamaica Bay, New York, is well documented. Maintaining wetlands is important from an environmental and ecological perspective and because wetlands buffer coastal communities from storm damage. An estimate of suspended-sediment flux through Rockaway Inlet is needed to improve understanding of sediment dynamics in Jamaica Bay and could be used in salt marsh restoration efforts. To estimate sediment flux, an index-velocity station and turbidity sensor were installed and operated in Rockaway Inlet near the mouth of Jamaica Bay from November 2014 to December 2016 and point and cross-sectional suspended-sediment samples were collected and analyzed. Index-velocity data coupled with cross-sectional acoustic Doppler current profiler measurements were used to develop an index-velocity rating. A simple linear regression rating with a strong coefficient of determination (R2 of 0.981) was developed. Discharge was computed from the stage-area and index-velocity relations, and a low-pass Godin filter was used to remove the tidal aliasing. A second simple linear regression (R2 of 0.75) between fixed-point suspended-sediment concentration (SSC) samples and turbidity allowed for the calculation of SSC through Rockaway Inlet, and then sediment flux was found by multiplying SSC and discharge for continuous (6-minute) data. Turbidity values were low in the near-ocean conditions at Rockaway Inlet, with daily means ranging from 0.6 to 8.2 formazin nephelometric units during the period of November 2014 through December 2016. During this time, computed daily mean suspended-sediment concentrations ranged from 3 to 13 milligrams per liter. High sediment loads generally occurred during incoming tides, during both storm and nonstorm conditions, suggesting a net inward sediment flux into Jamaica Bay. The fate of sediment after it enters Jamaica Bay was not investigated. Trends in sediment flux during major storms could not be evaluated because no major storms occurred during this investigation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195085","usgsCitation":"Cartwright, R.A., and Simonson, A.E., 2019, Estimating sediment flux to Jamaica Bay, New York: U.S. Geological Survey Scientific Investigations Report 2019–5085, 25 p., https://doi.org/10.3133/sir20195085.","productDescription":"vii, 25 p.","numberOfPages":"38","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-090709","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":399538,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109566.htm"},{"id":370919,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5085/sir20195085_hi_res.pdf","text":"Report","size":"5.91 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5085","linkHelpText":"- high resolution, not accessible as defined in Section 508"},{"id":370783,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5085/sir20195085.pdf","text":"Report","size":"3.86 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2019-5085"},{"id":370634,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5085/coverthb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Jamaica Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.94004821777344,\n 40.54980899258771\n ],\n [\n -73.76014709472656,\n 40.603526799885884\n ],\n [\n -73.729248046875,\n 40.645740600821476\n ],\n [\n -73.75053405761719,\n 40.65303410892721\n ],\n [\n -73.77113342285156,\n 40.63844629557923\n ],\n [\n -73.81507873535156,\n 40.66293116628907\n ],\n [\n -73.8720703125,\n 40.65615965408628\n ],\n [\n -73.9215087890625,\n 40.61916465186328\n ],\n [\n -73.93043518066406,\n 40.589449604232975\n ],\n [\n -73.95790100097656,\n 40.57536944461837\n ],\n [\n -73.94004821777344,\n 40.54980899258771\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New York Water Science Center
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This report is a deliverable to the RESTORE Council for Task 7: Document the existing baseline habitat and water quality conditions prior to implementation of the restoration projects; these baseline conditions will serve as a basis for measuring change/progress after restoration. It is the second in a series of CMAP reports. The first report describes the process and development of the CMAP monitoring program inventory, herein the Inventory (NOAA and USGS, 2019). The goals and objectives for the Inventory were to identify and document existing habitat and water quality monitoring, and mapping programs, data, and protocols in the GoM. The Inventory built upon existing databases, such as the Ocean Conservancy (Love, 2015), Global Change Monitoring Portal (GCMP; GCMP, 2017),
and Gulf of Mexico Alliance (GOMA) databases (GOMA, 2013), including habitat and water quality monitoring programs at national, regional, State and local scales. This second report identifies and catalogs existing water quality, habitat and mapping assessments within the Gulf of Mexico. This assessment catalog, herein the Catalog, was intended to supplement the Inventory to identify the best available science necessary for restoration, conservation or management activities. Both the Inventory and the Catalog databases will be accessible to the Council and the greater GoM restoration, monitoring, management, and academic communities through a searchable web-based tool.
Substantial effort has been dedicated to developing reliable monitoring schemes for North American bird populations, but our ability to monitor bird populations in the boreal forest remains limited because of the sparsity of long-term data sets, particularly in northerly regions. Given the importance of the boreal forest for many migratory birds, we set out to (1) summarize the main challenges associated with monitoring avian populations, (2) describe the available statistical tools for population monitoring and their applications, and (3) identify future directions to overcome current challenges in monitoring bird populations in the boreal forest. Defining and delineating populations of interest and identifying the drivers that affect those populations present the greatest current challenges. This is because migratory birds may be affected by many population-limiting processes at different stages of their annual life cycles. These factors are often hierarchically structured and can influence populations at the local, regional, or continental scales. Some of the challenges associated with delineating populations and identifying population drivers can be addressed via the plethora of sampling and analytic methods available to examine population change over time. Choosing the proper analytic methods depends on the goals of the study and the nature of the data such as single or multiple populations, repeated occurrence or count-based surveys, or demographic rates. Recent advances in hierarchical and integrated population models make these analytic approaches some of the most promising avenues for the development of future methods. However, these tools require large data sets, and acquiring sufficient data on bird populations and potential explanatory variables is difficult in the boreal forest. If the current challenges to monitoring birds in the boreal forest are to be overcome, serious effort should be dedicated to integrating existing data and making them accessible. Enhancing survey effort through multispecies surveys will also play an important role. Implementing spatially balanced sampling plans with a rotating panel design could balance the trade-offs between spatial versus temporal replication at an affordable cost. Improving the accessibility of environmental covariates that are spatially and temporally explicit would also enable development of mechanistic population models that improve our understanding of migratory bird population dynamics. Finally, given that long-term monitoring programs can take many decades before delivering reliable population trends and that organizational priorities often change over time, we suggest that collaborative efforts will help ensure the long-term survival of new monitoring programs.
","language":"English","publisher":"Resilience Alliance Publications","doi":"10.5751/ACE-01397-140208","usgsCitation":"Roy, C., Michel, N.L., Handel, C.M., Van Wilgenburg, S., Burkhalter, C., Gurney, K.A., Messmer, D., Prince, K., Rushing, C.S., Saracco, J.E., Schuster, R., Smith, A.C., Smith, P.A., Solymos, P., Venier, L.A., and Zuckerberg, B., 2019, Monitoring boreal avian populations: How can we estimate trends and trajectories from noisy data?: Avian Conservation and Ecology, v. 14, no. 2, 8, 26 p., https://doi.org/10.5751/ACE-01397-140208.","productDescription":"8, 26 p.","ipdsId":"IP-095185","costCenters":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true}],"links":[{"id":458858,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5751/ace-01397-140208","text":"Publisher Index Page"},{"id":377117,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, 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","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191123","usgsCitation":"Hsu, L., and Colasuonno, L., 2019, Community for Data Integration 2018 annual report: U.S. Geological Survey Open-File Report 2019–1123, 26 p., https://doi.org/10.3133/ofr20191123.","productDescription":"v, 26 p.","onlineOnly":"Y","ipdsId":"IP-106299","costCenters":[{"id":208,"text":"Core Science Analytics and Synthesis","active":true,"usgs":true}],"links":[{"id":370860,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1123/coverthb.jpg"},{"id":370861,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1123/ofr20191123.pdf","text":"Report","size":"5.19 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1123"}],"contact":"Director, Science Analytics and Synthesis
U.S. Geological Survey
National Center, MS 108
12201 Sunrise Valley Drive
Reston, VA 20192
The Triassic Shublik Formation in northern Alaska is one of the major source rocks in North America, having generated much of the petroleum in Prudhoe Bay and associated fields. The middle Shublik Formation, the focus of this study, is a highly phosphatic, organic-rich carbonate mudstone interval. Apatite cements can occur as phosphatic peloids, steinkerns, elongate or angular nodules, and shells or shell fragments. We propose a model whereby phosphatization is favored in early diagenetic environments that have low concentrations of dissolved iron relative to reactive organic matter in the pore water sulfate reduction zone.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"New directions in geosciences for unconventional resources","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"New Directions in Geosciences for Unconventional Resources","conferenceDate":"October 15-17, 2019","conferenceLocation":"Banff, Canada","language":"English","publisher":"CSPG","usgsCitation":"Whidden, K.J., Dumoulin, J.A., Macquaker, J., Birdwell, J.E., Boehlke, A., and French, K.L., 2019, Element cycling in the Middle-Late Triassic Shublik Formation: Mineralization vs. recycling of biolimiting nutrients in an unconventional resource play, in New directions in geosciences for unconventional resources, Banff, Canada, October 15-17, 2019, 11 p.","productDescription":"11 p.","ipdsId":"IP-108677","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":375132,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":364996,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.cspg.org/Conferences/Conference_Archives/Gussow_Conferences/Conferences/Gussow/Gussow_Archive/Gussow-Archives.aspx?hkey=c92a974d-b253-4d2e-b6df-88e61db23877"}],"country":"United States","state":"Alaska","otherGeospatial":"National Petroleum Reserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -162.509765625,\n 67.13582938531948\n ],\n [\n -150.029296875,\n 67.13582938531948\n ],\n [\n -150.029296875,\n 71.35706654962706\n ],\n [\n -162.509765625,\n 71.35706654962706\n ],\n [\n -162.509765625,\n 67.13582938531948\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Whidden, Katherine J. 0000-0002-7841-2553 kwhidden@usgs.gov","orcid":"https://orcid.org/0000-0002-7841-2553","contributorId":3960,"corporation":false,"usgs":true,"family":"Whidden","given":"Katherine","email":"kwhidden@usgs.gov","middleInitial":"J.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":764975,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dumoulin, Julie A. 0000-0003-1754-1287 dumoulin@usgs.gov","orcid":"https://orcid.org/0000-0003-1754-1287","contributorId":203209,"corporation":false,"usgs":true,"family":"Dumoulin","given":"Julie","email":"dumoulin@usgs.gov","middleInitial":"A.","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":764976,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Macquaker, James","contributorId":216534,"corporation":false,"usgs":false,"family":"Macquaker","given":"James","email":"","affiliations":[{"id":39472,"text":"ExxonMobil","active":true,"usgs":false}],"preferred":false,"id":764977,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Birdwell, Justin E. 0000-0001-8263-1452 jbirdwell@usgs.gov","orcid":"https://orcid.org/0000-0001-8263-1452","contributorId":3302,"corporation":false,"usgs":true,"family":"Birdwell","given":"Justin","email":"jbirdwell@usgs.gov","middleInitial":"E.","affiliations":[{"id":255,"text":"Energy Resources Program","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true}],"preferred":true,"id":764978,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Boehlke, Adam 0000-0003-4980-431X aboehlke@usgs.gov","orcid":"https://orcid.org/0000-0003-4980-431X","contributorId":3470,"corporation":false,"usgs":true,"family":"Boehlke","given":"Adam","email":"aboehlke@usgs.gov","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":789929,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"French, Katherine L. 0000-0002-0153-8035","orcid":"https://orcid.org/0000-0002-0153-8035","contributorId":205462,"corporation":false,"usgs":true,"family":"French","given":"Katherine","email":"","middleInitial":"L.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":false,"id":764979,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70215873,"text":"70215873 - 2019 - Applying circuit theory and landscape linkage maps to reintroduction planning for California condors","interactions":[],"lastModifiedDate":"2020-11-02T12:50:26.995399","indexId":"70215873","displayToPublicDate":"2019-12-31T12:56:41","publicationYear":"2019","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Applying circuit theory and landscape linkage maps to reintroduction planning for California condors","docAbstract":"Conservation practitioners are increasingly looking to species translocations as a tool to recover imperiled taxa. Quantitative predictions of where animals are likely to move when released into new areas would allow managers to better address the social, institutional, and ecological dimensions of conservation translocations. Using >5 million California condor (Gymnogyps californianus) occurrence locations from 75 individuals, we developed and tested circuit-based models to predict condor movement away from release sites. We found that circuit-based models of electrical current were well calibrated to the distribution of condor movement data in southern and central California (continuous Boyce Index = 0.86 and 0.98, respectively). Model calibration was improved in southern California when additional nodes were added to the circuit to account for nesting and feeding areas, where condor movement densities were higher (continuous Boyce Index = 0.95). Circuit-based projections of electrical current around a proposed release site in northern California comported with the condor’s historical distribution and revealed that, initially, condor movements would likely be most concentrated in northwestern California and southwest Oregon. Landscape linkage maps, which incorporate information on landscape resistance, complement circuit-based models and aid in the identification of specific avenues for population connectivity or areas where movement between populations may be constrained. We found landscape linkages in the Coast Range and the Sierra Nevada provided the most connectivity to a proposed reintroduction site in northern California. Our methods are applicable to conservation translocations for other species and are flexible, allowing researchers to develop multiple competing hypotheses when there are uncertainties about landscape or social attractants, or uncertainties in the landscape conductance surface.
","language":"English","publisher":"Public Library of Science","doi":"10.1371/journal.pone.0226491","usgsCitation":"D’Elia, J., Brandt, J., Burnett, L., Haig, S.M., Hollenbeck, J.P., Kirkland, S., Marcot, B.G., Punzalan, A., West, C.J., Williams-Claussen, T., Wolstenholme, R., and Young, R., 2019, Applying circuit theory and landscape linkage maps to reintroduction planning for California condors: PLoS ONE, v. 14, no. 12, e0226491, 22 p., https://doi.org/10.1371/journal.pone.0226491.","productDescription":"e0226491, 22 p.","ipdsId":"IP-115028","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":458861,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0226491","text":"Publisher Index Page"},{"id":379985,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Central California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.68505859375,\n 37.96152331396614\n ],\n [\n -122.03613281249999,\n 36.96744946416934\n ],\n [\n -121.88232421875,\n 36.19109202182454\n ],\n [\n -120.4541015625,\n 34.43409789359469\n ],\n [\n -118.6083984375,\n 33.96158628979907\n ],\n [\n -118.0810546875,\n 34.03445260967645\n ],\n [\n -116.56494140625001,\n 35.24561909420681\n ],\n [\n -119.68505859375,\n 37.96152331396614\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"14","issue":"12","noUsgsAuthors":false,"publicationDate":"2019-12-31","publicationStatus":"PW","contributors":{"authors":[{"text":"D’Elia, Jesse 0000-0002-1843-8495","orcid":"https://orcid.org/0000-0002-1843-8495","contributorId":244237,"corporation":false,"usgs":false,"family":"D’Elia","given":"Jesse","email":"","affiliations":[{"id":36188,"text":"U.S. Fish and 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,{"id":70204582,"text":"70204582 - 2019 - Managed aquifer recharge in snow-fed river basins: What, why and how?","interactions":[],"lastModifiedDate":"2020-08-27T17:51:13.062663","indexId":"70204582","displayToPublicDate":"2019-12-31T12:48:45","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":2,"text":"State or Local Government Series"},"seriesTitle":{"id":6473,"text":"Fact Sheet","active":true,"publicationSubtype":{"id":2}},"seriesNumber":"19-10","title":"Managed aquifer recharge in snow-fed river basins: What, why and how?","docAbstract":"Climate change poses unique challenges in snow-fed river basins across the western United States because the majority of water supply originates as snow (Dettinger, Udall, & Georgakakos, 2015). In the Sierra Nevada, recent observations include changes in snow accumulation and snowmelt, and shifts in peak streamflow timing (Barnhart et al., 2016; Hatchett et al., 2017; Kim & Jain, 2010; McCabe, Wolock, & Valentin, 2018; Mote, Li, Lettenmaier, Xiao, & Engel, 2018). Such changes upstream alter surface water deliveries downstream, as well as groundwater recharge utilized as both primary and supplemental water supply (Godsey et al., 2014; Harpold, 2016; Jasechko et al., 2014).
basin where snowmelt runoff produces substantial water supply to meet diverse agricultural, environmental and urban water demand (Figure 1). The East and West Forks join at the confluence of the Carson River near the north end of the Carson Valley, a rich agricultural region (40,000 acres) that grows primarily alfalfa hay. The majority of irrigators rely on surface water delivered through a network of earthen ditches constructed in the mid-19th and early 20th centuries. Flow through these earthen networks and the practice of flood irrigation contribute significantly to groundwater recharge.
Because no upstream surface water reservoirs exist, snowpack that accumulates through winter and melts slowly through spring has acted as a “natural” reservoir, providing ample supply through the summer irrigati agricultural, environmental and urban water demand (Figure 1). The East and West Forks join at the confluence of the Carson River near the north end of the season. Some irrigators have permitted access to supplemental groundwater that is useful during periods of drought for augmenting shortfalls in surface water delivery. Groundwater is the primary source of municipal and industrial water supply for surrounding communities (e.g., Carson City, Minden, Gardnerville, Dayton).
Across the basin, water use is highly regulated through federal, tribal, state and local water-sharing agreements based on prior appropriation doctrine (Wilds, 2014). Carson River surface water allocations follow the Alpine Decree, initiated by the United States Department of Interior in 1925 and signed into law in 1980, following 55 years of litigation, to adjudicate surface water rights to individual parties (NDWP, 1999). The Alpine Decree acknowledges return flows to lower river segments, and thus each river segment is distributed autonomously. This means that the most junior water right on an upper segment can be fulfilled before considering the most senior water right on a lower segment. Ultimately, the ruling is at the discretion of the Federal Water Master to satisfy the needs of each water right
Downstream of Carson Valley, surface water flows are stored in Lahontan Reservoir, the nation’s first desert reclamation project (est. 1906), where releases are managed to meet the Newland’s Project irrigation water demand and for environmental use on the Stillwater National Wildlife Refuge. Flows from the Carson River are supplemented through diversions from the Truckee River via the Truckee Canal, resulting in a trans-basin water supply system.
In the Truckee-Carson River System, researchers and local water managers are working together to assess climate change impacts to water supply and explore how model simulations can produce useful information to support local climate adaptation. Twelve key water managers represent agricultural, environmental, urban and regulatory water-use communities, and bring to the table diverse input and perspectives on how to adapt to climate change.
Hydrologists use this input to craft scenarios and simulations that meet the information needs of local water managers. Biannual workshops provide an opportunity for information exchange, where researchers and key water managers generate new knowledge of river system function. That is, researchers share results of models that examine the physical potential, and managers validate the on-the-ground potential, further informing the research process.
Coincident to this research program, the region faced a prolonged drought period (2012-2016) with historically low snowpack, followed by a historic wet year (2017) that brought winter and spring flooding as a result of atmospheric river storm events (Sterle et al., 2019). For the Carson River, an important observation made by managers was that peak streamflow that had traditionally coincided with peak irrigation demands, had shifted to earlier in the spring, with summer baseflow also decreasing (Sterle & Singletary, 2017). Managers shared with researchers concerns over potential future impacts that changing snowpack will have on surface water deliveries and reliance on groundwater, as the region’s population and economy continue to grow. During workshops that occurred over this period, local water managers and researchers discussed ways to evaluate water distribution and use that honors the existing legal framework and accounts for changing snowpack regimes (amount, rain versus snow, timing). In response to managers growing interest, researchers introduced the concept of managed aquifer recharge as one potential strategy to adapt and enhance regional water sustainability.
What is managed aquifer recharge? Simply stated, managed aquifer recharge is the intentional recharge of structures to spread water over agricultural lands, allowing water to naturally infiltrate into the groundwater system (Bouwer, 1999; Niswonger et al., 2017). The latter may occur during the irrigation season by applying excess water, or during the nonirrigation season when evapotranspiration losses are low. Figure 2 illustrates managed aquifer recharge in a snow-fed river basin, where streamflow generated from snowmelt runoff is diverted to agricultural lands to recharge the aquifer. Such flood irrigation practices, including water delivery through earthen ditch networks, provide incidental but significant aquifer recharge through seepage and deep drainage beneath fields (Niswonger, Allander, & Jeton, 2014). The effects of managed aquifer recharge can vary depending on the location and intensity of practice.
For example, implementing managed aquifer recharge water into the groundwater system (Dillon, 2009). This differs from the incidental recharge that may occur as part of normal irrigation practices. Managed recharge may occur by injection into the aquifer through existingwells, or by using existing conveyance adjacent to/along the river’s floodplain has the potential to enhance late-season instream flows due to increased return flows, resulting in greater downstream deliveries as well as improving ecological conditions (Niswonger et al., 2017). Implementing managed aquifer recharge away from the river’s floodplain has the potential to enhance groundwater supply which is increasingly relied upon during surface water shortage (Green et al., 2011), by storing water in available aquifer space in the deep aquifer. At the basin scale, managed aquifer recharge may lead to regional groundwater sustainability.
The physical limitations to implementing managed aquifer recharge in the Carson River Basin hinges on three key factors. The first factor relates to the physical connectivity between rivers and streams, and the irrigation delivery network of canals and ditches that divert water to agricultural lands (Niswonger et al., 2017). In the Carson River Basin the mechanisms for getting water to fields is already in place. Thus, intentionally routing high flows that occur in wet years through this system during the nonirrigation season would mimic what occurs naturally during the irrigation season. The second factor relates to the occurrence of atmospheric river storm events that deliver large amounts of precipitation to the region, much greater than average (Dettinger et al., 2015). With increased frequency and intensity projected under a warmer climate, such events have the potential to produce excess water over short periods of time that could be stored through mechanisms such as managed aquifer recharge (Niswonger et al., 2017). The third factor relates to the change in snowpack accumulation and shifts in snowmelt timing observed elsewhere in the Sierra Nevada (e.g., Godsey et al., 2014; Mote et al., 2018). Having a mechanism in place to maximize use of earlier snowmelt and shifts in streamflow timing could be advantageous and enhance regional groundwater sustainability. As part of the Water for the Seasons study, a hypothetical scenario was developed to determine the feasibility of managed aquifer recharge in the Carson River Basin, assuming no legal constraints. During “wet” or above-average water years, irrigators in the Upper Carson Valley would divert high flows and spread water over agricultural lands during the nonirrigation season. Assuming flows are abundant and “early,” diversions would begin prior to the growing season, when water would otherwise flow downstream to the Lahontan Reservoir. During “dry” years or drought periods, when surface water availability is less, irrigators in the Upper Carson Valley could augment surface water shortages with groundwater, allowing available surface water flows to flow downstream. Researchers hypothesize the amount of water has the potential to boost baseflow to support environmental instream flows, for example.
The hypothetical managed aquifer recharge scenario was presented to water managers in a workshop setting. Presentations included an overview of the hydrologic and operations modeling tools used to evaluate managed aquifer recharge by simulating the timing and distribution of water in the upper watershed. Specifically, in the Upper Carson Valley, a hydrologic model (GSFLOW) simulates streamflow driven by snowmelt, and surface and groundwater interactions, while a river basin operations model (MODSIM) allocates water according to the prior appropriation doctrine in the basin (see Figure 1) (Morway, Niswonger, & Triana, 2016; Niswonger et al., 2017). Integrating these two modeling tools advances the evaluation of climate impacts on water availability in agricultural communities and the resulting impacts of alternative management strategies (Morway et al., 2016).
When asked about the viability of managed aquifer recharge, the perspectives of 11 managers varied (Figure 3). Regardless of rating, all managers questioned, “How would thisreally work?” Several managers questioned whether models could simulate the connectivity between surface and groundwater to accurately quantify changes to instream flow. Others raised concerns that managed aquifer recharge violates the Alpine Decree and Nevada Water Law. Still others requested researchers consider alternatives that could work within the confines of current (2019) water law.
Managers posed specific questions that should be considered when evaluating the potential for managed aquifer recharge. For example:
Managers’ perspectives help to validate the on-the-ground potential of particular strategies and further refine alternative management scenarios. For example, understanding that managers are concerned with oversaturated fields helps researchers to define conditions in the model, such as what defines a wet versus “too” wet type of year and where to focus irrigation for managed aquifer recharge. Incorporating these nuances provides more accurate quantification of the potential benefits and consequences for users across the basin. Modeling is underway to simulate managed aquifer recharge scenarios and explore basin-wide implications. Researchers and local water managers will convene to collaboratively review results and further assess whether this or other strategies could work under the confines of existing water law. Subsequent fact sheets will present these findings.
","language":"English","publisher":"University of Nevada, Reno Extension","usgsCitation":"Sterle, K., Kitlasten, W., Morway, E.D., Niswonger, R.G., and Singletary, L., 2019, Managed aquifer recharge in snow-fed river basins: What, why and how?: Fact Sheet 19-10, 8 p.","productDescription":"8 p.","ipdsId":"IP-106943","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":377948,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":377947,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://extension.unr.edu/publication.aspx?PubID=3416"}],"country":"United States","state":"Nevada","city":"Carson City","otherGeospatial":"Carson River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.74685668945312,\n 38.849333913235476\n ],\n [\n -119.67681884765624,\n 38.976492485539396\n ],\n [\n -119.64248657226562,\n 39.15881700964971\n ],\n [\n -119.06295776367188,\n 39.299236474818194\n ],\n [\n -118.96545410156251,\n 39.454221498848895\n ],\n [\n -118.70590209960938,\n 39.459523110465156\n ],\n [\n -118.61114501953125,\n 39.68288289049806\n ],\n [\n -118.62213134765626,\n 39.79059962227577\n ],\n [\n -118.73886108398438,\n 39.79059962227577\n ],\n [\n -118.8336181640625,\n 39.53899882354987\n ],\n [\n -119.1412353515625,\n 39.527348072681455\n ],\n [\n -119.32662963867188,\n 39.35659979720227\n ],\n [\n -119.53262329101562,\n 39.34598050985849\n ],\n [\n -119.77157592773436,\n 39.196076813671695\n ],\n [\n -119.88418579101561,\n 39.03838632847035\n ],\n [\n -119.86358642578125,\n 38.935911987561624\n ],\n [\n -119.74685668945312,\n 38.849333913235476\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Sterle, Kelley","contributorId":195683,"corporation":false,"usgs":false,"family":"Sterle","given":"Kelley","email":"","affiliations":[],"preferred":false,"id":797450,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kitlasten, Wesley 0000-0002-2049-9107","orcid":"https://orcid.org/0000-0002-2049-9107","contributorId":217832,"corporation":false,"usgs":true,"family":"Kitlasten","given":"Wesley","email":"","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":767633,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Morway, Eric D. 0000-0002-8553-6140 emorway@usgs.gov","orcid":"https://orcid.org/0000-0002-8553-6140","contributorId":4320,"corporation":false,"usgs":true,"family":"Morway","given":"Eric","email":"emorway@usgs.gov","middleInitial":"D.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":767634,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Niswonger, Richard G. 0000-0001-6397-2403 rniswon@usgs.gov","orcid":"https://orcid.org/0000-0001-6397-2403","contributorId":197892,"corporation":false,"usgs":true,"family":"Niswonger","given":"Richard","email":"rniswon@usgs.gov","middleInitial":"G.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":767635,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Singletary, Loretta","contributorId":195685,"corporation":false,"usgs":false,"family":"Singletary","given":"Loretta","email":"","affiliations":[],"preferred":false,"id":797451,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70206564,"text":"ofr20191122 - 2019 - Trends in mammalian predator control trapping events intended to protect ground-nesting, endangered birds at Haleakalā National Park, Hawaiʻi: 2000–14","interactions":[],"lastModifiedDate":"2020-02-21T12:03:56","indexId":"ofr20191122","displayToPublicDate":"2019-12-31T11:59:59","publicationYear":"2019","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":"2019-1122","displayTitle":"Trends in Mammalian Predator Control Trapping Events Intended to Protect Ground-Nesting, Endangered Birds at Haleakalā National Park, Hawaiʻi: 2000–14","title":"Trends in mammalian predator control trapping events intended to protect ground-nesting, endangered birds at Haleakalā National Park, Hawaiʻi: 2000–14","docAbstract":"Predation and habitat degradation by non-native species are principal terrestrial threats to the federally endangered Hawaiian Petrel (ʻuaʻu, Pterodroma sandwichensis) and Hawaiian Goose (nēnē, Branta sandvicensis) within Haleakalā National Park (HALE), Maui, Hawaiʻi. Since 1981, HALE has maintained a network of live traps to control invasive mammalian predators and protect these endangered birds. To evaluate trapping efficiency in HALE, we evaluated four types of trap outcomes for the years 2000–14: Bait Lost (62 percent), No Event (23 percent), Trap Triggered (10 percent), and Predator Event (Rat Caught, Cat Caught, or Mongoose Caught; 4 percent). We used a multinomial logistic regression model to explore trends in the probabilities of broad outcomes (No Event, Other Event [Bait Lost or Trap Triggered], or Predator Event [Rat Caught, Cat Caught, or Mongoose Caught]). Temporal variations in the probabilities of No Event, Other Event, or Predator Event were best explained by ʻuaʻu season (off-season, pre-laying, incubation, or nestling), month, year, and seasonal rainfall with greater probabilities of Predator Event during the ʻuaʻu nestling period (July–October). The probability of Predator Event or Other Event decreased with increased rainfall. Spatial analysis showed that percent vegetative cover and vegetation type best explained variations in the probabilities of trapping outcomes with the probability of Predator Event being greatest in developed and tree covered areas. The proportion of trapping events that resulted in Rat Caught was at least 20 times greater than the proportions of events resulting in Cat or Mongoose Caught throughout the 15-year management period. Temporal analysis showed that season, year, and maximum temperature best explained variations in probabilities of Predator Event; the probability of Rat Caught was greatest during the ʻuaʻu pre-laying and incubation periods (February–June), was greater during periods of warmer maximum temperatures, and overall, increased over the 15-year management period. The probability of Mongoose Caught was greatest during the ʻuaʻu offseason (November–January), decreased through time (2000–14), and decreased with increasing weekly maximum temperatures. Trends in Cat Caught were hard to detect because of small sample sizes, though slight trends indicated cat captures were most frequent during the ʻuaʻu off season and less frequent through time (2000–14). The probability of a Cat Caught event was also negatively correlated with weekly temperatures. Spatial analysis showed elevation best explained variations in probabilities of capture for rats, cats, and mongoose. Overall, predator catches were fewer at higher elevations, and of predators caught at higher elevations, the clear majority were rats. Our results are being used by HALE Endangered Wildlife Management staff to evaluate existing methods for predator control and efficacy of existing trap-based control strategies intended to protect ʻuaʻu and nēnē.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20191122","collaboration":"Prepared in cooperation with Haleakalā National Park","usgsCitation":"Kelsey, E.C., Adams, J., Czapanskiy, M.F., Felis, J.J., Yee, J.L., Kaholoaa R.L., and Bailey, C.N., 2019, Trends in mammalian predator control trapping events intended to protect ground-nesting, endangered birds at Haleakalā National Park, Hawaiʻi: 2000–14: U.S. Geological Survey Open-File Report 2019–1122, 27 p., https://doi.org/10.3133/ofr20191122.","productDescription":"Report: vi, 28 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-104150","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":370049,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P98RJ12I","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Trap records used to analyze trends in mammalian predator control trapping events intended to protect ground-nesting, endangered birds at Haleakalā National Park, Hawai'i (2000 - 2014)"},{"id":370036,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2019/1122/ofr20191122.pdf","text":"Report","size":"22.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2019-1122"},{"id":370035,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2019/1122/coverthb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Haleakalā National Park","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -156.275743,20.586349 ], [ -156.275743,20.795098 ], [ -156.020951,20.795098 ], [ -156.020951,20.586349 ], [ -156.275743,20.586349 ] ] ] } } ] }","contact":"Director,
Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
Most of the population of the Treasure Valley and the surrounding area of southwestern Idaho and easternmost Oregon depends on groundwater for domestic supply, either from domestic or municipal-supply wells. As of 2017, 41 percent of Idaho’s population was concentrated in Idaho’s portion of the Treasure Valley, and current and projected rapid population growth in the area has caused concern about the long-term sustainability of the groundwater resource. In 2016, the U.S. Geological Survey, in cooperation with the Idaho Water Resource Board and the Idaho Department of Water Resources, began a project to construct a numerical groundwater-flow model of the westernmost western Snake River Plain (WSRP) aquifer system. As part of this project, a three-dimensional hydrogeologic framework model (3D HFM) of the aquifer system was generated, primarily from lithologic data compiled from 291 well-driller reports.
Four major hydrogeologic units are shown in the 3D HFM: Coarse-grained fluvial and alluvial deposits, Pliocene-Pleistocene and Miocene basalts, fine-grained lacustrine deposits, and granitic and rhyolitic bedrock. Generally, the 3D HFM is in agreement with the geologic history of the WSRP and hydrogeologic frameworks developed by previous authors. The resolution (voxel size) of the 3D HFM is sufficient for the construction of a regional groundwater-flow model.
The major components of inflow (or recharge) to the WSRP aquifer system are seepage from irrigation canals, direct infiltration from precipitation and excess irrigation water, seepage from the Boise and Payette Rivers and Lake Lowell, and subsurface inflow from adjoining uplands. The major components of outflow (or discharge) from the aquifer system are discharge to surface water (rivers, agricultural drains, and streams), groundwater pumping, and direct evapotranspiration from groundwater.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195138","collaboration":"Prepared in cooperation with the Idaho Water Resource Board and the Idaho Department of Water Resources","usgsCitation":"Bartolino, J.R., 2019, Hydrogeologic framework of the Treasure Valley and surrounding area, Idaho and Oregon (ver. 1.1, January 2020): U.S. Geological Survey Scientific Investigations Report 2019–5138, 31 p., https://doi.org/10.3133/sir20195138.","productDescription":"Report: v, 31 p.; Data Release","onlineOnly":"Y","ipdsId":"IP-093399","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":371171,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5138/coverthb.jpg"},{"id":371344,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5138/sir20195138_v1.1.pdf","text":"Report","size":"6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Scientific Investigations Report 2019-5138"},{"id":371345,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9CAC0F6","linkHelpText":"Hydrogeologic Framework of the Treasure Valley and Surrounding Area, Idaho and Oregon"},{"id":371346,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2019/5138/sir20195138_versionHist.txt","size":"1 KB","linkFileType":{"id":2,"text":"txt"},"description":"Scientific Investigations Report 2019-5138"},{"id":399614,"rank":5,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109577.htm"}],"country":"United States","state":"Idaho, Oregon","otherGeospatial":"Treasure Valley and surrounding area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.1097,\n 43.1803\n ],\n [\n -115.86,\n 43.1803\n ],\n [\n -115.86,\n 44.0381\n ],\n [\n -117.1097,\n 44.0381\n ],\n [\n -117.1097,\n 43.1803\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.1: January 2020; Version 1: December 2019","contact":"Director,
Idaho Water Science Center
U.S. Geological Survey
230 Collins Rd
Boise, Idaho 83702-4520
Director,
Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
The level to which data are aggregated can impact analytical and predictive modeling results. In this short paper we discuss some of our findings regarding the impacts of data aggregation on estimating change points in the production profiles of horizontal hydraulically fractured Bakken oil wells. Change points occur when production transitions from one flow regime to another. Change point determination is important because it governs calculation of ultimate recovery from these and similar wells drilled in shale plays.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"20th Annual conference of the International Association for Mathematical Geosciences (IAMG2019)","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"20th Annual Conference of the International Association for Mathematical Geosciences (IAMG2019)","conferenceDate":"Aug 10-15, 2019","conferenceLocation":"State College, PA","language":"English","usgsCitation":"Coburn, T.C., and Attanasi, E., 2019, Implications of aggregating daily production data on estimates of ultimate recovery from horizontal hydraulically fractured Bakken oil wells, in 20th Annual conference of the International Association for Mathematical Geosciences (IAMG2019), State College, PA, Aug 10-15, 2019, p. 232-236.","productDescription":"5 p.","startPage":"232","endPage":"236","ipdsId":"IP-107885","costCenters":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":375188,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana, North Dakota","otherGeospatial":"Bakken Formation","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.7598876953125,\n 45.96260622242165\n ],\n [\n -102.45849609375,\n 45.96260622242165\n ],\n [\n -102.45849609375,\n 47.71345768748889\n ],\n [\n -105.7598876953125,\n 47.71345768748889\n ],\n [\n -105.7598876953125,\n 45.96260622242165\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Coburn, T. C.","contributorId":219832,"corporation":false,"usgs":false,"family":"Coburn","given":"T.","email":"","middleInitial":"C.","affiliations":[{"id":40076,"text":"1 University of Tulsa, School of Energy Economics, Policy and Commerce, USA,","active":true,"usgs":false}],"preferred":false,"id":773271,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Attanasi, Emil D. 0000-0001-6845-7160 attanasi@usgs.gov","orcid":"https://orcid.org/0000-0001-6845-7160","contributorId":198728,"corporation":false,"usgs":true,"family":"Attanasi","given":"Emil D.","email":"attanasi@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":773270,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70206597,"text":"sir20195133 - 2019 - Iodine-129 in the Eastern Snake River Plain aquifer at and near the Idaho National Laboratory, Idaho, 2017–18","interactions":[],"lastModifiedDate":"2022-04-25T19:40:42.618075","indexId":"sir20195133","displayToPublicDate":"2019-12-31T11:41:00","publicationYear":"2019","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2019-5133","displayTitle":"Iodine-129 in the Eastern Snake River Plain Aquifer at and near the Idaho National Laboratory, Idaho, 2017–18","title":"Iodine-129 in the Eastern Snake River Plain aquifer at and near the Idaho National Laboratory, Idaho, 2017–18","docAbstract":"From 1953 to 1988, approximately 0.941 curies of iodine-129 (129I) were contained in wastewater generated at the Idaho National Laboratory, with almost all of it discharged at or near the Idaho Nuclear Technology and Engineering Center (INTEC). Until 1984, most of the wastewater was discharged directly into the eastern Snake River Plain (ESRP) aquifer through a deep disposal well; however, some wastewater was also discharged into unlined infiltration ponds or leaked from distribution systems below the INTEC.
During 2017–18, the U.S. Geological Survey, in cooperation with the U.S. Department of Energy, collected samples for 129I from 30 wells that monitor the ESRP aquifer to track concentrations and changes of the carcinogenic radionuclide that has a 15.7 million-year half-life. Concentrations of 129I in the aquifer ranged from 0.000016 ± 0.000001 to 0.88+/- 0.03 picocuries per liter (pCi/L), and concentrations generally decreased in wells near the INTEC as compared with previously collected samples. The average concentration of 15 wells sampled during 5 different sample periods decreased from 1.15 pCi/L in 1990–91 to 0.168 pCi/L in 2017–18, but average concentrations were similar to 2011–12 within analytical uncertainty. All but four wells within a 3-mile radius of the INTEC showed decreases in concentration, and all samples had concentrations less than the U.S. Environmental Protection Agency’s maximum contaminant level of 1 pCi/L. These decreases are attributed to the discontinuation of disposal of 129I in wastewater and to dilution and dispersion in the aquifer. Some wells southeast of INTEC showed increasing trends; these increases were attributed to variable transmissivity.
Although wells near INTEC sampled in 2017–18 showed decreases in concentrations compared with data collected previously, some wells south of the INL boundary showed small increases. These increases are attributed to historical variable discharge rates of wastewater that eventually moved to these well locations as a pulse of water from a particular disposal period.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20195133","collaboration":"Prepared in cooperation with the U.S. Department of Energy","usgsCitation":"Maimer, N.V., and Bartholomay, R.C., 2019, Iodine-129 in the eastern Snake River Plain aquifer at and near the Idaho National Laboratory, Idaho, 2017–18: U.S. Geological Survey Scientific Investigations Report 2019-5133, 20 p., https://doi.org/10.3133/sir20195133.","productDescription":"v, 20 p.","numberOfPages":"20","onlineOnly":"Y","ipdsId":"IP-096468","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":399612,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_109576.htm"},{"id":370908,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2019/5133/sir20195133.pdf","text":"Report","size":"1.5 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":370907,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2019/5133/coverthb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Idaho National Laboratory","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.9,\n 43.3333\n ],\n [\n -113.1667,\n 43.3333\n ],\n [\n -113.1667,\n 43.5833\n ],\n [\n -112.9,\n 43.5833\n ],\n [\n -112.9,\n 43.3333\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director,
Idaho Water Science Center
U.S. Geological Survey
230 Collins Rd
Boise, Idaho 83702-4520