Transient electromagnetic (TEM) soundings were made in the San Luis Valley, Colorado, to map the location of a blue clay unit as well as to investigate the presence of suspected faults. A total of 147 soundings were made near and in Great Sand Dunes National Park and Preserve, and an additional 6 soundings were made near Hansen Bluff on the eastern edge of the Alamosa National Wildlife Refuge. The blue clay is a significant hydrologic feature in the area that separates an unconfined surface aquifer from a deeper confined aquifer. Knowledge of its location is important to regional hydrological models. Previous analysis of well logs has shown that the blue clay has a resistivity of 10 ohm-meters or less, which is in contrast to the higher resistivity of sand, gravel, and other clay units found in the area, making it a very good target for TEM soundings. The top of the blue clay was found to have considerable relief, suggesting the possibility of deformation of the clay during or after deposition. Because of rift activity, deformation is to be expected. Of the TEM profiles made across faults identified by aeromagnetic data, some showed resistivity variations and (or) subsurface elevation relief of resistivity units, suggestive of faulting. Such patterns were not associated with all suspected faults. The Hansen Bluff profile showed variations in resistivity and depth to conductor that coincide with a scarp between the highlands to the east and the floodplain of the Rio Grande to the west.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds1043","collaboration":"Prepared in cooperation with the National Park Service","usgsCitation":"Fitterman, D.V., 2017, Transient electromagnetic soundings in the San Luis Valley, Colorado, near the Great Sand Dunes National Park and Preserve and the Alamosa National Wildlife Refuge (field seasons 2007, 2009, and 2011): U.S. Geological Survey Data Series 1043, 39 p., https://doi.org/10.3133/ds1043.","productDescription":"Report: vii; 52 p.","startPage":"1","endPage":"39","numberOfPages":"52","onlineOnly":"Y","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":342428,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7D21VQ5","text":"USGS data release","description":"USGS Data Release","linkHelpText":"Transient Electromagnetic Sounding Data Collected in the San Luis Valley, Colorado near the Great Sand Dunes National Park and Preserve and the Alamosa National Wildlife Refuge (Field Seasons 2007, 2009, and 2011)"},{"id":342407,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/1043/coverthb.jpg"},{"id":342408,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/1043/ds1043.pdf","text":"Report","size":"3.92 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 1043"}],"country":"United States ","state":"Colorado","otherGeospatial":"San Luis Valley ","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.11145019531249,\n 37.42906945530332\n ],\n [\n -105.56488037109375,\n 37.42906945530332\n ],\n [\n -105.56488037109375,\n 37.93444993515032\n ],\n [\n -106.11145019531249,\n 37.93444993515032\n ],\n [\n -106.11145019531249,\n 37.42906945530332\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Crustal Geophysics and Geochemistry Science Center
U.S. Geological Survey
Box 25046, MS 964
Denver, CO 80225
Water quality in groundwater resources used for public drinking-water supply in the Western San Joaquin Valley (WSJV) was investigated by the USGS in cooperation with the California State Water Resources Control Board (SWRCB) as part of its Groundwater Ambient Monitoring and Assessment (GAMA) Program Priority Basin Project. The WSJV includes two study areas: the Delta–Mendota and Westside subbasins of the San Joaquin Valley groundwater basin. Study objectives for the WSJV study unit included two assessment types: (1) a status assessment yielding quantitative estimates of the current (2010) status of groundwater quality in the groundwater resources used for public drinking water, and (2) an evaluation of natural and anthropogenic factors that could be affecting the groundwater quality. The assessments characterized the quality of untreated groundwater, not the quality of treated drinking water delivered to consumers by water distributors.
The status assessment was based on data collected from 43 wells sampled by the U.S. Geological Survey for the GAMA Priority Basin Project (USGS-GAMA) in 2010 and data compiled in the SWRCB Division of Drinking Water (SWRCB-DDW) database for 74 additional public-supply wells sampled for regulatory compliance purposes between 2007 and 2010. To provide context, concentrations of constituents measured in groundwater were compared to U.S. Environmental Protection Agency (EPA) and SWRCB-DDW regulatory and non-regulatory benchmarks for drinking-water quality. The status assessment used a spatially weighted, grid-based method to estimate the proportion of the groundwater resources used for public drinking water that has concentrations for particular constituents or class of constituents approaching or above benchmark concentrations. This method provides statistically unbiased results at the study-area scale within the WSJV study unit, and permits comparison of the two study areas to other areas assessed by the GAMA Priority Basin Project statewide.
Groundwater resources used for public drinking water in the WSJV study unit are among the most saline and most affected by high concentrations of inorganic constituents of all groundwater resources used for public drinking water that have been assessed by the GAMA Priority Basin Project statewide. Among the 82 GAMA Priority Basin Project study areas statewide, the Delta–Mendota study area ranked above the 90th percentile for aquifer-scale proportions of groundwater resources having concentrations of total dissolved solids (TDS), sulfate, chloride, manganese, boron, chromium(VI), selenium, and strontium above benchmarks, and the Westside study area ranked above the 90th percentile for TDS, sulfate, manganese, and boron.
In the WSJV study unit as a whole, one or more inorganic constituents with regulatory or non-regulatory, health-based benchmarks were present at concentrations above benchmarks in about 53 percent of the groundwater resources used for public drinking water, and one or more organic constituents with regulatory health-based benchmarks were detected at concentrations above benchmarks in about 3 percent of the resource. Individual constituents present at concentrations greater than health-based benchmarks in greater than 2 percent of groundwater resources used for public drinking water included: boron (51 percent, SWRCB-DDW notification level), chromium(VI) (25 percent, SWRCB-DDW maximum contaminant level (MCL)), arsenic (10 percent, EPA MCL), strontium (5.1 percent, EPA Lifetime health advisory level (HAL)), nitrate (3.9 percent, EPA MCL), molybdenum (3.8 percent, EPA HAL), selenium (2.6 percent, EPA MCL), and benzene (2.6 percent, SWRCB-DDW MCL). In addition, 50 percent of the resource had TDS concentrations greater than non-regulatory, aesthetic-based SWRCB-DDW upper secondary maximum contaminant level (SMCL), and 44 percent had manganese concentrations greater than the SWRCB-DDW SMCL.
Natural and anthropogenic factors that could affect the groundwater quality were evaluated by using results from statistical testing of associations between constituent concentrations and values of potential explanatory factors, inferences from geochemical and age-dating tracer results, and by considering the water-quality results in the context of the hydrogeologic setting of the WSJV study unit.
Natural factors, particularly the lithologies of the source areas for groundwater recharge and of the aquifers, were the dominant factors affecting groundwater quality in most of the WSJV study unit. However, where groundwater resources used for public supply included groundwater recharged in the modern era, mobilization of constituents by recharge of water used for irrigation also affected groundwater quality. Public-supply wells in the Westside study area had a median depth of 305 m and primarily tapped groundwater recharged hundreds to thousands of years ago, whereas public-supply wells in the Delta–Mendota study area had a median depth of 85 m and primarily tapped either groundwater recharged within the last 60 years or groundwater consisting of mixtures of this modern recharge and older recharge.
Public-supply wells in the WSJV study unit are screened in the Tulare Formation and zones above and below the Corcoran Clay Member are used. The Tulare Formation primarily consists of alluvial sediments derived from the Coast Ranges to the west, except along the valley trough at the eastern margin of the WSJV study unit where the Tulare Formation consists of fluvial sands derived from the Sierra Nevada to the east. Groundwater from wells screened in the Sierra Nevada sands had manganese-reducing or manganese- and iron-reducing oxidation-reduction (redox) conditions. These redox conditions commonly were associated with elevated arsenic or molybdenum concentrations, and the dominance of arsenic(III) in the dissolved arsenic supports reductive dissolution of iron and manganese oxyhydroxides as the mechanism. In addition, groundwater from many wells screened in Sierra Nevada sands contained low concentrations of nitrite or ammonium, indicating reduction of nitrate by denitrification or dissimilatory processes, respectively.
Geology of the Coast Ranges westward of the study unit strongly affects groundwater quality in the WSJV. Elevated concentrations of TDS, sulfate, boron, selenium and strontium in groundwater were primarily associated with aquifer sediments and recharge derived from areas of the Coast Ranges dominated by Cretaceous-to-Miocene age, organic-rich, reduced marine shales, known as the source of selenium in WSJV soils, surface water, and groundwater. Low sulfur-isotopic values (δ34S) of dissolved sulfate indicate that the sulfate was largely derived from oxidation of biogenic pyrite from the shales, and correlations with trace element concentrations, geologic setting, and groundwater geochemical modeling indicated that distributions of sulfate, strontium, and selenium in groundwater were controlled by dissolution of secondary sulfate minerals in soils and sediments.
Elevated concentrations of chromium(VI) were primarily associated with aquifer sediments and recharge derived from areas of the Coast Ranges dominated by the Franciscan Complex and ultramafic rocks. The Franciscan Complex also has boron-rich, sodium-chloride dominated hydrothermal fluids that contribute to elevated concentrations of boron and TDS.
Groundwater from wells screened in Coast Ranges alluvium was primarily oxic and relatively alkaline (median pH value of 7.55) in the Delta–Mendota study area, and primarily nitrate-reducing or suboxic and alkaline (median pH value of 8.4) in the Westside study area. Many groundwater samples from those wells have elevated concentrations of arsenic(V), molybdenum, selenium, or chromium(VI), consistent with desorption of metal oxyanions from mineral surfaces under those geochemical conditions.
High concentrations of benzene were associated with deep wells located in the vicinity of petroleum deposits at the southern end of the Westside study area. Groundwater from these wells had premodern age and anoxic geochemical conditions, and the ratios among concentrations of hydrocarbon constituents were different from ratios found in fuels and combustion products, which is consistent with a geogenic source for the benzene rather than contamination from anthropogenic sources.
Water stable-isotope compositions, groundwater recharge temperatures, and groundwater ages were used to infer four types of groundwater: (1) groundwater derived from natural recharge of water from major rivers draining the Sierra Nevada; (2) groundwater primarily derived from natural recharge of water from Coast Ranges runoff; (3) groundwater derived from recharge of pumped groundwater applied to the land surface for irrigation; and (4) groundwater derived from recharge during a period of much cooler paleoclimate. Water previously used for irrigation was found both above and below the Corcoran Clay, supporting earlier inferences that this clay member is no longer a robust confining unit.
Recharge of water used for irrigation has direct and indirect effects on groundwater quality. Elevated nitrate concentrations and detections of herbicides and fumigants in the Delta–Mendota study area generally were associated with greater agricultural land use near the well and with water recharged during the last 60 years. However, the extent of the groundwater resource affected by agricultural sources of nitrate was limited by groundwater redox conditions sufficient to reduce nitrate. The detection frequency of perchlorate in Delta–Mendota groundwater was greater than expected for natural conditions. Perchlorate, nitrate, selenium, and strontium concentrations were correlated with one another and were greater in groundwater inferred to be recharge of previously pumped groundwater used for irrigation. The source of the perchlorate, selenium, and strontium appears to be salts deposited in the soils and sediments of the arid WSJV that are dissolved and flushed into groundwater by the increased amount of recharge caused by irrigation. In the Delta–Mendota study area, the groundwater with elevated concentrations of selenium was found deeper in the aquifer system than it was reported by a previous study 25 years earlier, suggesting that this transient front of groundwater with elevated concentrations of constituents derived from dissolution of soil salts by irrigation recharge is moving down through the aquifer system and is now reaching the depth zone used for public drinking water supply.
California Water Science Center
California GAMA
U.S. Geological Survey
6000 J Street, Placer Hall
Sacramento, California 95819
The Piney Point aquifer in Virginia is newly described and delineated as being composed of six geologic units, in a study conducted by the U.S. Geological Survey in cooperation with the Virginia Department of Environmental Quality (VA DEQ). The eastward-dipping geologic units include, in stratigraphically ascending order, the
Identification of geologic units is based on typical sediment lithologies of geologic formations. Fine-grained sediments that compose confining units positioned immediately above and below the Piney Point aquifer are also described.
The Piney Point aquifer is one of several confined aquifers within the Virginia Coastal Plain and includes a highly porous and solution-channeled indurated limestone within the Piney Point Formation from which withdrawals are made. The limestone is relatively continuous laterally across central parts of the Northern Neck, Middle Peninsula, and York-James Peninsula. Other geologic units are of variable extent. The configurations of most of the geologic units are further affected by newly identified faults that are aligned radially from the Chesapeake Bay impact crater and create constrictions or barriers to groundwater flow. Some geologic units are also truncated beneath the lower Rappahannock River by a resurge channel associated with the impact crater.
Groundwater withdrawals from the Piney Point aquifer increased from approximately 1 million gallons per day (Mgal/d) during 1900 to 7.35 Mgal/d during 2004. As a result, a water-level cone of depression in James City and northern York Counties was estimated to be as low as 70 feet (ft) below the National Geodetic Vertical Datum of 1929 (NGVD 29) by 2005. Withdrawals decreased to 5.01 Mgal/d by 2009 as withdrawals were shifted toward other sources, and by 2015 water levels had recovered to approximately 50 ft below NGVD 29.
The mean estimated transmissivity of the Piney Point aquifer in York and James City Counties is 16,300 feet squared per day (ft2/d), but farther north it is only 925 ft2/d. The mean well specific capacity in York and James City Counties is 11.4 gallons per minute per foot (gal/min/ft). Farther north in Virginia, mean specific capacity is only 2.26 gal/min/ft, and in Maryland it is 0.99 gal/min/ft. The northward decrease in specific capacity probably reflects the northward decrease in transmissivity, which results from poor development of the solution-channeled limestone.
An aquifer test in northern York County induced vertical leakage to the solution-channeled limestone from overlying silty sand and a change in response of the aquifer to pumping from a single layer to two layers. Transmissivity of the limestone of approximately 19,800 ft2/d was distinguished from the silty sand of approximately 2,500 ft2/d.
Most of the water in the Piney Point aquifer is slightly alkaline with moderate concentrations primarily of sodium and bicarbonate that are slightly undersaturated with respect to calcite. Iron concentrations are generally less than 0.3 milligrams per liter (mg/L). Mixing of freshwater with seawater has elevated chloride concentrations to the southeast to as much as 7,120 mg/L.
Information on the Piney Point aquifer can benefit water-resource management in siting production wells, predicting likely well yield, and anticipating water-level response to withdrawals. Models that vertically discretize individual geologic units can potentially be used to evaluate groundwater flow in greater detail by representing lateral flow and vertical leakage among the geologic units.
Because groundwater withdrawals are made primarily from the limestone and sand of the Piney Point Formation, the VA DEQ has considered regarding the limestone and sand singly as a regulated aquifer apart from the other geologic units. Under current policy in Virginia, if only the limestone and sand were regarded as a regulated aquifer, a greater amount of drawdown would be allowed than is allowed for the Piney Point aquifer consisting of six geologic units. Some production wells intercept multiple geologic units, and the units can undergo water-level decline and vertical leakage induced by pumping from the limestone and sand. Whether the other geologic units are to be regarded as regulated aquifers is an additional consideration for the VA DEQ.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175041","collaboration":"Prepared in cooperation with the Virginia Department of Environmental Quality","usgsCitation":"McFarland, E.R., 2017, Hydrogeologic framework and hydrologic conditions of the Piney Point aquifer in Virginia: U.S. Geological Survey Scientific Investigations Report 2017–5041, 63 p., 2 pl., and CD-ROM, https://doi.org/10.3133/sir20175041.","productDescription":"Report: vii, 62 p.; 2 Plates: 24 x 36 inches and 36 x 24 inches; Appendixes 1-2; Data Release; Read Me","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-075864","costCenters":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true}],"links":[{"id":342072,"rank":7,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sir/2017/5041/readme.txt","size":"1.27 KB","linkFileType":{"id":2,"text":"txt"}},{"id":342068,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2017/5041/sir20175041_appendix1.xlsx","text":"Appendix 1","size":"36.2 KB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"- Borehole Geologic-Unit Top-Surface Altitudes, Piney Point Aquifer, Virginia"},{"id":342066,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5041/coverthb.jpg"},{"id":342069,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2017/5041/sir20175041_appendix2.xlsx","text":"Appendix 2 ","size":"23.1 MB","linkFileType":{"id":3,"text":"xlsx"},"linkHelpText":"- Aquifer-Component Test data, Piney Point Aquifer, Virginia"},{"id":342071,"rank":6,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2017/5041/sir20175041_plate2.pdf","text":"Plate 2 ","size":"397 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Hydrogeologic Sections A–A’, B–B’, and C–C’ of the Piney Point Aquifer in Virginia"},{"id":342076,"rank":8,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7BV7DV5","text":"USGS data release","description":"USGS data release","linkHelpText":"Hydrogeologic Framework and Hydrologic Conditions of the Piney Point Aquifer in Virginia"},{"id":342067,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5041/sir20175041.pdf","text":"Report","size":"8.09 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5041"},{"id":342070,"rank":5,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sir/2017/5041/sir20175041_plate1.pdf","text":"Plate 1 ","size":"444 KB","linkFileType":{"id":1,"text":"pdf"},"linkHelpText":"- Locations of Boreholes and Extent of Productive Limestone in the Piney Point Aquifer in Virginia"}],"country":"United States","state":"Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.291667,\n 38.291667\n ],\n [\n -76.208333,\n 38.291667\n ],\n [\n -76.208333,\n 37.125\n ],\n [\n -77.291667,\n 37.125\n ],\n [\n -77.291667,\n 38.291667\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Virginia Water Science Center
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Intrusive rock sequences in the central and eastern Mojave Desert segment of the Jurassic Cordilleran arc of the western United States record regional and temporal variations in magmas generated during the second prominent pulse of Mesozoic continental arc magmatism. U/Pb zircon ages provide temporal control for describing variations in rock and zircon geochemistry that reflect differences in magma source components. These source signatures are discernible through mixing and fractionation processes associated with magma ascent and emplacement. The oldest well-dated Jurassic rocks defining initiation of the Jurassic pulse are a 183 Ma monzodiorite and a 181 Ma ignimbrite. Early to Middle Jurassic intrusive rocks comprising the main stage of magmatism include two high-K calc-alkalic groups: to the north, the deformed 183–172 Ma Fort Irwin sequence and contemporaneous rocks in the Granite and Clipper Mountains, and to the south, the 167–164 Ma Bullion sequence. A Late Jurassic suite of shoshonitic, alkali-calcic intrusive rocks, the Bristol Mountains sequence, ranges in age from 164 to 161 Ma and was emplaced as the pulse began to wane. Whole-rock and zircon trace-element geochemistry defines a compositionally coherent Jurassic arc with regional and secular variations in melt compositions. The arc evolved through the magma pulse by progressively greater input of old cratonic crust and lithospheric mantle into the arc magma system, synchronous with progressive regional crustal thickening.
","language":"English","publisher":"The Geological Society of America","doi":"10.1130/B31550.1","usgsCitation":"Barth, A., Wooden, J., Miller, D., Howard, K.A., Fox, L., Schermer, E.R., and Jacobson, C., 2017, Regional and temporal variability of melts during a Cordilleran magma pulse: Age and chemical evolution of the jurassic arc, eastern mojave desert, California: Geological Society of America Bulletin, v. 129, no. 3-4, p. 429-448, https://doi.org/10.1130/B31550.1.","productDescription":"20 p.","startPage":"429","endPage":"448","ipdsId":"IP-073981","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":461519,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/1805/14626","text":"External Repository"},{"id":342163,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","otherGeospatial":"Mojave Desert, Transverse Ranges","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -119.267578125,\n 34.288991865037524\n ],\n [\n -119.24560546875001,\n 34.19817309627726\n ],\n [\n -119.267578125,\n 33.8521697014074\n ],\n [\n -118.125,\n 33.55970664841198\n ],\n [\n -117.61962890624999,\n 33.578014746143985\n ],\n [\n -117.26806640625,\n 33.706062655101206\n ],\n [\n -116.87255859374999,\n 33.99802726234877\n ],\n [\n -116.08154296875001,\n 34.34343606848294\n ],\n [\n -115.20263671874999,\n 34.994003757575776\n ],\n [\n -114.12597656249999,\n 35.94243575255426\n ],\n [\n -114.06005859375,\n 37.19533058280065\n ],\n [\n -113.818359375,\n 38.976492485539396\n ],\n [\n -113.92822265625,\n 39.027718840211605\n ],\n [\n -114.36767578124999,\n 39.027718840211605\n ],\n [\n -114.76318359375,\n 38.95940879245423\n ],\n [\n -115.11474609375001,\n 38.87392853923629\n ],\n [\n -115.6640625,\n 38.75408327579141\n ],\n [\n -116.30126953125,\n 38.53097889440024\n ],\n [\n -117.00439453125,\n 38.42777351132902\n ],\n [\n -117.6416015625,\n 38.09998264736481\n ],\n [\n -118.2568359375,\n 37.70120736474139\n ],\n [\n -118.95996093749999,\n 36.63316209558658\n ],\n [\n -118.740234375,\n 36.155617833818525\n ],\n [\n -118.65234374999999,\n 35.38904996691167\n ],\n [\n -119.267578125,\n 34.288991865037524\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"129","issue":"3-4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2016-11-03","publicationStatus":"PW","scienceBaseUri":"5937bf2ce4b0f6c2d0d9c73e","contributors":{"authors":[{"text":"Barth, A.P.","contributorId":192663,"corporation":false,"usgs":false,"family":"Barth","given":"A.P.","email":"","affiliations":[],"preferred":false,"id":697317,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wooden, J.L.","contributorId":192664,"corporation":false,"usgs":false,"family":"Wooden","given":"J.L.","email":"","affiliations":[],"preferred":false,"id":697318,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Miller, David M. 0000-0003-3711-0441 dmiller@usgs.gov","orcid":"https://orcid.org/0000-0003-3711-0441","contributorId":140769,"corporation":false,"usgs":true,"family":"Miller","given":"David M.","email":"dmiller@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":309,"text":"Geology and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":697316,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Howard, Keith A. 0000-0002-6462-2947 khoward@usgs.gov","orcid":"https://orcid.org/0000-0002-6462-2947","contributorId":3439,"corporation":false,"usgs":true,"family":"Howard","given":"Keith","email":"khoward@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":697319,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fox, Lydia","contributorId":192666,"corporation":false,"usgs":false,"family":"Fox","given":"Lydia","email":"","affiliations":[],"preferred":false,"id":697321,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schermer, Elizabeth R.","contributorId":184060,"corporation":false,"usgs":false,"family":"Schermer","given":"Elizabeth","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":697322,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jacobson, C.E.","contributorId":192665,"corporation":false,"usgs":false,"family":"Jacobson","given":"C.E.","email":"","affiliations":[],"preferred":false,"id":697320,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70188342,"text":"70188342 - 2017 - System identification based on deconvolution and cross correlation: An application to a 20‐story instrumented building in Anchorage, Alaska","interactions":[],"lastModifiedDate":"2017-06-06T16:30:14","indexId":"70188342","displayToPublicDate":"2017-06-06T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1135,"text":"Bulletin of the Seismological Society of America","onlineIssn":"1943-3573","printIssn":"0037-1106","active":true,"publicationSubtype":{"id":10}},"title":"System identification based on deconvolution and cross correlation: An application to a 20‐story instrumented building in Anchorage, Alaska","docAbstract":"Deconvolution and cross‐correlation techniques are used for system identification of a 20‐story steel, moment‐resisting frame building in downtown Anchorage, Alaska. This regular‐plan midrise structure is instrumented with a 32‐channel accelerometer array at 10 levels. The impulse response functions (IRFs) and correlation functions (CFs) are computed based on waveforms recorded from ambient vibrations and five local and regional earthquakes. The earthquakes occurred from 2005 to 2014 with moment magnitudes between 4.7 and 6.2 over a range of azimuths at epicenter distances of 13.3–183 km. The building’s fundamental frequencies and mode shapes are determined using a complex mode indicator function based on singular value decomposition of multiple reference frequency‐response functions. The traveling waves, identified in IRFs with a virtual source at the roof, and CFs are used to estimate the intrinsic attenuation associated with the fundamental modes and shear‐wave velocity in the building. Although the cross correlation of the waveforms at various levels with the corresponding waveform at the first floor provides more complicated wave propagation than that from the deconvolution with virtual source at the roof, the shear‐wave velocities identified by both techniques are consistent—the largest difference in average values is within 8%. The median shear‐wave velocity from the IRFs of five earthquakes is 191 m/s for the east–west (E‐W), 205 m/s for the north–south (N‐S), and 176 m/s for the torsional responses. The building’s average intrinsic‐damping ratio is estimated to be 3.7% and 3.4% in the 0.2–1 Hz frequency band for the E‐W and N‐S directions, respectively. These results are intended to serve as reference for the undamaged condition of the building, which may be used for tracking changes in structural integrity during and after future earthquakes.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0120160069","usgsCitation":"Wen, W., and Kalkan, E., 2017, System identification based on deconvolution and cross correlation: An application to a 20‐story instrumented building in Anchorage, Alaska: Bulletin of the Seismological Society of America, v. 107, no. 2, p. 718-740, https://doi.org/10.1785/0120160069.","productDescription":"23 p.","startPage":"718","endPage":"740","ipdsId":"IP-068688","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":342192,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","city":"Anchorage","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -149.90917682647705,\n 61.20793488105243\n ],\n [\n -149.88252639770508,\n 61.20793488105243\n ],\n [\n -149.88252639770508,\n 61.21661483933352\n ],\n [\n -149.90917682647705,\n 61.21661483933352\n ],\n [\n -149.90917682647705,\n 61.20793488105243\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"107","issue":"2","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-02-14","publicationStatus":"PW","scienceBaseUri":"5937bf2ce4b0f6c2d0d9c73c","contributors":{"authors":[{"text":"Wen, Weiping","contributorId":192669,"corporation":false,"usgs":false,"family":"Wen","given":"Weiping","email":"","affiliations":[],"preferred":false,"id":697331,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kalkan, Erol 0000-0002-9138-9407 ekalkan@usgs.gov","orcid":"https://orcid.org/0000-0002-9138-9407","contributorId":1218,"corporation":false,"usgs":true,"family":"Kalkan","given":"Erol","email":"ekalkan@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":697330,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70177812,"text":"sim3367 - 2017 - Geologic map of the Beacon Rock quadrangle, Skamania County, Washington","interactions":[],"lastModifiedDate":"2022-04-19T18:50:25.77411","indexId":"sim3367","displayToPublicDate":"2017-06-06T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3367","title":"Geologic map of the Beacon Rock quadrangle, Skamania County, Washington","docAbstract":"The Beacon Rock 7.5′ quadrangle is located approximately 50 km east of Portland, Oregon, on the north side of the Columbia River Gorge, a scenic canyon carved through the axis of the Cascade Range by the Columbia River. Although approximately 75,000 people live within the gorge, much of the region remains little developed and is encompassed by the 292,500-acre Columbia River Gorge National Scenic Area, managed by a consortium of government agencies “to protect and provide for the enhancement of the scenic, cultural, recreational and natural resources of the Gorge and to protect and support the economy of the Columbia River Gorge area.” As the only low-elevation corridor through the Cascade Range, the gorge is a critical regional transportation and utilities corridor (Wang and Chaker, 2004). Major state and national highways and rail lines run along both shores of the Columbia River, which also provides important water access to ports in the agricultural interior of the Pacific Northwest. Transmission lines carry power from hydroelectric facilities in the gorge and farther east to the growing urban areas of western Oregon and Washington, and natural-gas pipelines transect the corridor (Wang and Chaker, 2004). These lifelines are highly vulnerable to disruption by earthquakes, landslides, and floods. A major purpose of the work described here is to identify and map geologic hazards, such as faults and landslide-prone areas, to provide more accurate assessments of the risks associated with these features.
The steep canyon walls of the map area reveal extensive outcrops of Miocene flood-basalt flows of the Columbia River Basalt Group capped by fluvial deposits of the ancestral Columbia River, Pliocene lavas erupted from the axis of the Cascade arc to the east, and volcanic rocks erupted from numerous local vents. The Columbia River Basalt Group unconformably rests on a sequence of late Oligocene and early Miocene rocks of the ancestral Cascade volcanic arc, which underlies most of the map area. The resistant flood-basalt flows form some of the famous landforms in the map area, such as Hamilton Mountain. Extensive landslide complexes have developed where the basalt flows were emplaced on weak volcaniclastic rocks.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3367","usgsCitation":"Evarts, R.C., and Fleck, R.J., 2017, Geologic map of the Beacon Rock quadrangle, Skamania County, Washington: U.S. Geological Survey Scientific Investigations Map 3367, pamphlet 61 p., scale 1:24,000, https://doi.org/10.3133/sim3367.","productDescription":"Pamphlet: ii, 61 p.; 2 Sheets: 53.90 x 37.06 inches and 61.75 x 31.64 inches; Basemap: 24.00 x 30.00 inches; Database; Metadata; Read Me","onlineOnly":"Y","ipdsId":"IP-056187","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":399112,"rank":9,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_105748.htm"},{"id":342054,"rank":8,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/sim/3367/sim3367_base.pdf","text":"Basemap","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3367 Basemap"},{"id":342053,"rank":7,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sim/3367/sim3367_metadata.zip","text":"Metadata","linkFileType":{"id":6,"text":"zip"},"description":"SIM 3367 Metadata"},{"id":342052,"rank":6,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3367/sim3367_pamphlet.pdf","text":"Pamphlet","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3367 Pamphlet"},{"id":342047,"rank":4,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3367/sim3367_sheet2.pdf","text":"Sheet 2","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3367 Sheet 2","linkHelpText":"Geologic Map of the Beacon Rock Quadrangle, Skamania County, Washington - Station locations and sample sites in the the Beacon Rock quadrangle, Skamania County, Washington"},{"id":342048,"rank":5,"type":{"id":20,"text":"Read Me"},"url":"https://pubs.usgs.gov/sim/3367/sim3367_readme.txt","text":"Read Me","linkFileType":{"id":2,"text":"txt"},"description":"SIM 3367 Read Me"},{"id":342046,"rank":3,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/sim/3367/sim3367_sheet1.pdf","text":"Sheet 1","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3367 Sheet 1","linkHelpText":"Geologic Map of the Beacon Rock Quadrangle, Skamania County, Washington"},{"id":342045,"rank":2,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/sim/3367/SIM3367_database.zip","text":"Database","linkFileType":{"id":6,"text":"zip"},"description":"SIM 3367 Database"},{"id":342041,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3367/coverthb2.jpg"}],"scale":"24000","country":"United States","state":"Washington","county":"Skamania County","otherGeospatial":"Beacon Rock quadrangle","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.125,\n 45.625\n ],\n [\n -122,\n 45.625\n ],\n [\n -122,\n 45.75\n ],\n [\n -122.125,\n 45.75\n ],\n [\n -122.125,\n 45.625\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Geology, Minerals, Energy, & Geophysics Science Center
U.S. Geological Survey
345 Middlefield Road
Menlo Park, CA 94025-3591
The Pacific–North American plate boundary in California is composed of a 400-km-wide network of faults and zones of distributed deformation. Earthquakes, even large ones, can occur along individual or combinations of faults within the larger plate boundary system. While research often focuses on the primary and secondary faults, holistic study of the plate boundary is required to answer several fundamental questions. How do plate boundary motions partition across California faults? How do faults within the plate boundary interact during earthquakes? What fraction of strain accumulation is relieved aseismically and does this provide limits on fault rupture propagation? Geodetic imaging, broadly defined as measurement of crustal deformation and topography of the Earth’s surface, enables assessment of topographic characteristics and the spatio-temporal behavior of the Earth’s crust. We focus here on crustal deformation observed with continuous Global Positioning System (GPS) data and Interferometric Synthetic Aperture Radar (InSAR) from NASA’s airborne UAVSAR platform, and on high-resolution topography acquired from lidar and Structure from Motion (SfM) methods. Combined, these measurements are used to identify active structures, past ruptures, transient motions, and distribution of deformation. The observations inform estimates of the mechanical and geometric properties of faults. We discuss five areas in California as examples of different fault behavior, fault maturity and times within the earthquake cycle: the M6.0 2014 South Napa earthquake rupture, the San Jacinto fault, the creeping and locked Carrizo sections of the San Andreas fault, the Landers rupture in the Eastern California Shear Zone, and the convergence of the Eastern California Shear Zone and San Andreas fault in southern California. These examples indicate that distribution of crustal deformation can be measured using interferometric synthetic aperture radar (InSAR), Global Navigation Satellite System (GNSS), and high-resolution topography and can improve our understanding of tectonic deformation and rupture characteristics within the broad plate boundary zone.
","language":"English","publisher":"Multidisciplinary Digital Publishing Institute","doi":"10.3390/geosciences7010015","usgsCitation":"Donnellan, A., Arrowsmith, R., and DeLong, S.B., 2017, Spatio-temporal mapping of plate boundary faults in California using geodetic imaging: Geosciences, v. 7, no. 1, p. 1-26, https://doi.org/10.3390/geosciences7010015.","productDescription":"Article 15; 26 p.","startPage":"1","endPage":"26","ipdsId":"IP-082746","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":469772,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/geosciences7010015","text":"Publisher Index Page"},{"id":342133,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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\"}}]}","volume":"7","issue":"1","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-03-21","publicationStatus":"PW","scienceBaseUri":"59366da6e4b0f6c2d0d7d5f5","contributors":{"authors":[{"text":"Donnellan, Andrea","contributorId":176745,"corporation":false,"usgs":false,"family":"Donnellan","given":"Andrea","email":"","affiliations":[{"id":18954,"text":"Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA","active":true,"usgs":false}],"preferred":false,"id":697149,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Arrowsmith, Ramon","contributorId":181555,"corporation":false,"usgs":false,"family":"Arrowsmith","given":"Ramon","email":"","affiliations":[],"preferred":false,"id":697150,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeLong, Stephen B. 0000-0002-0945-2172 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human communities and ecosystems in the United States (Easterling and others, 2000). Over the past several years, many regions have experienced extreme drought conditions, fueled by prolonged periods of reduced precipitation and exceptionally warm temperatures. Extreme drought has far-reaching impacts on water supplies, ecosystems, agricultural production, critical infrastructure, energy costs, human health, and local economies (Milly and others, 2005; Wihlite, 2005; Vörösmarty and others, 2010; Choat and others, 2012; Ledger and others, 2013). As global temperatures continue to increase, the frequency, severity, extent, and duration of droughts are expected to increase across North America, affecting both humans and natural ecosystems (Parry and others, 2007).
The U.S. Geological Survey (USGS) has a long, proven history of delivering science and tools to help decision-makers manage and mitigate effects of drought. That said, there is substantial capacity for improved integration and coordination in the ways that the USGS provides drought science. A USGS Drought Team was formed in August 2016 to work across USGS Mission Areas to identify current USGS drought-related research and core capabilities. This information has been used to initiate the development of an integrated science effort that will bring the full USGS capacity to bear on this national crisis.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/cir1430","collaboration":"USGS Coordinated and Integrated Drought Science","usgsCitation":"Ostroff, A.C., Muhlfeld, C.C., Lambert, P.M., Booth, N.L., Carter, S.L., Stoker, J.M., and Focazio, M.J., 2017, USGS integrated drought science: U.S. Geological Survey Circular 1430, 24 p., https://doi.org/10.3133/cir1430.","productDescription":"iv, 24 p.","numberOfPages":"32","ipdsId":"IP-083129","costCenters":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true}],"links":[{"id":341891,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/circ/1430/coverthb.jpg"},{"id":341892,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/circ/1430/cir1430.pdf","text":"Report","size":"2.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"CIR 1430"}],"contact":"USGS Drought Coordinator
National Center, MS 301
12201 Sunrise Valley Dr., MS 300
Reston, VA 20192
https://www.usgs.gov/special-topic/drought
An evaluation of trends in hydrologic and water quality conditions and estimation of water budgets through 2013 was done by the U.S. Geological Survey in cooperation with the Chester County Water Resources Authority. Long-term hydrologic, meteorologic, and biologic data collected in Chester County, Pennsylvania, which included streamflow, groundwater levels, surface-water quality, biotic integrity, precipitation, and air temperature were analyzed to determine possible trends or changes in hydrologic conditions. Statistically significant trends were determined by applying the Kendall rank correlation test; the magnitudes of the trends were determined using the Sen slope estimator. Water budgets for eight selected watersheds were updated and a new water budget was developed for the Marsh Creek watershed. An average water budget for Chester County was developed using the eight selected watersheds and the new Marsh Creek water budget.
Annual and monthly mean streamflow, base flow, and runoff were analyzed for trends at 10 streamgages. The periods of record at the 10 streamgages ranged from 1961‒2013 to 1988‒2013. The only statistically significant trend for annual mean streamflow was for West Branch Brandywine Creek near Honey Brook, Pa. (01480300) where annual mean streamflow increased 1.6 cubic feet per second (ft3/s) per decade. The greatest increase in monthly mean streamflow was for Brandywine Creek at Chadds Ford, Pa. (01481000) for December; the increase was 47 ft3/s per decade. No statistically significant trends in annual mean base flow or runoff were determined for the 10 streamgages. The greatest increase in monthly mean base flow was for Brandywine Creek at Chadds Ford, Pa. (01481000) for December; the increase was 26 ft3/s per decade.
The magnitude of peaks greater than a base streamflow was analyzed for trends for 12 streamgages. The period of record at the 12 stream gages ranged from 1912‒2012 to 2004–11. Fifty percent of the streamgages showed a small statistically significant increase in peaks greater than the base streamflow. The greatest increase was for Brandywine Creek at Chadds Ford, Pa. (01481000) during 1962‒2012; the increase was 1.8 ft3/s per decade. There were no statistically significant trends in the number of floods equal to or greater than the 2-year recurrence interval flood flow.
Twenty‒one monitoring wells were evaluated for statistically significant trends in annual mean water level, minimum annual water level, maximum annual water level, and annual range in water-level fluctuations. For four wells, a small statistically significant increase in annual mean water level was determined that ranged from 0.16 to 0.7 feet per decade. There was poor or no correlation between annual mean groundwater levels and annual mean streamflow and base flow. No correlation was determined between annual mean groundwater level and annual precipitation. Despite rapid population growth and land-use change since 1950, there appears to have been little or no detrimental effects on groundwater levels in 21 monitoring wells.
Long-term precipitation and temperature data were available from the West Chester (1893‒2013) and Phoenixville, Pa. (1915‒2013) National Oceanic and Atmospheric Administration (NOAA) weather stations. No statistically significant trends in annual mean precipitation or annual mean temperature were determined for either station. Both weather stations had a significant decrease in the number of days per year with precipitation greater than or equal to 0.1 inch. Annual mean minimum and maximum temperatures from the NOAA Southeastern Piedmont Climate Division increased 0.2 degrees Fahrenheit (F) per decade between 1896 and 2014. The number of days with a maximum temperature equal to or greater than 90 degrees F increased at West Chester and decreased at Phoenixville. No statistically significant trend was determined for annual snowfall amounts.
Data from 1974 to 2013 for three stream water-quality monitors in the Brandywine Creek watershed were evaluated. The monitors are on the West Branch Brandywine Creek at Modena, Pa. (01480617), East Branch Brandywine Creek below Downingtown, Pa. (01480870), and Brandywine Creek at Chadds Ford, Pa. (01481000). Statistically significant upward trends were determined for annual mean specific conductance at all three stations, indicating the total dissolved solids load has been increasing. If the current trend continues, the annual mean specific conductance could almost double from 1974 to 2050. The increase in specific conductance likely is due to increases in chloride concentrations, which have been increasing steadily over time at all three stations. No correlation was found between monthly mean specific conductance and monthly mean streamflow or base flow. Statistically significant upward trends in pH were determined for all three stations. Statistically significant upward trends in stream temperature were determined for East Branch Brandywine Creek below Downingtown, Pa. (01480870) and Brandywine Creek at Chadds Ford, Pa. (01481000). The stream water-quality data indicate substantial increases in the minimum daily dissolved oxygen concentrations in the Brandywine Creek over time.
The Chester County Index of Biotic Integrity (CC-IBI) determined for 1998‒2013 was evaluated for the five biological sampling sites collocated with streamgages. CC-IBI scores are based on a 0‒100 scale with higher scores indicating better stream quality. Statistically significant upward trends in the CC-IBI were determined for West Branch Brandywine Creek at Modena, Pa. (01480617) and East Branch Brandywine Creek below Downingtown, Pa. (01480870). No correlation was found between the CC-IBI and streamflow, precipitation, or stream specific conductance, pH, temperature, or dissolved oxygen concentration.
A Chester County average water budget was developed using the nine estimated watershed water budgets. Average precipitation was 48.4 inches, and average streamflow was 21.4 inches. Average runoff and base flow were 8.3 and 13.1 inches, respectively, and average evapotranspiration and estimation of errors was 27.2 inches.\"
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175025","collaboration":"Prepared in cooperation with the Chester County Water Resources Authority","usgsCitation":"Sloto, R.A., and Reif, A.G., 2017, Evaluation of long-term trends in hydrologic and water-quality conditions, and estimation of water budgets through 2013, Chester County, Pennsylvania (ver.1.1, July 2017): U.S. Geological Survey Scientific Investigations Report 2017–5025, 59 p., https://doi.org/10.3133/sir20175025.","productDescription":"vii, 59 p.","numberOfPages":"71","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-064731","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":341981,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5025/sir20175025.pdf","text":"Report","size":"8.49 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 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1.0: Originally posted June 2,2017; Version 1.1: July 10, 2017","contact":"Director, Pennsylvania Water Science Center
U.S. Geological Survey
215 Limekiln Road
New Cumberland, PA 17070
We present a detailed example of how a subbasin develops adjacent to a transfer zone in the Rio Grande rift. The Embudo transfer zone in the Rio Grande rift is considered one of the classic examples and has been used as the inspiration for several theoretical models. Despite this attention, the history of its development into a major rift structure is poorly known along its northern extent near Taos, New Mexico. Geologic evidence for all but its young rift history is concealed under Quaternary cover. We focus on understanding the pre-Quaternary evidence that is in the subsurface by integrating diverse pieces of geologic and geophysical information. As a result, we present a substantively new understanding of the tectonic configuration and evolution of the northern extent of the Embudo fault and its adjacent subbasin.
We integrate geophysical, borehole, and geologic information to interpret the subsurface configuration of the rift margins formed by the Embudo and Sangre de Cristo faults and the geometry of the subbasin within the Taos embayment. Key features interpreted include (1) an imperfect D-shaped subbasin that slopes to the east and southeast, with the deepest point ∼2 km below the valley floor located northwest of Taos at ∼36° 26′N latitude and 105° 37′W longitude; (2) a concealed Embudo fault system that extends as much as 7 km wider than is mapped at the surface, wherein fault strands disrupt or truncate flows of Pliocene Servilleta Basalt and step down into the subbasin with a minimum of 1.8 km of vertical displacement; and (3) a similar, wider than expected (5–7 km) zone of stepped, west-down normal faults associated with the Sangre de Cristo range front fault.
From the geophysical interpretations and subsurface models, we infer relations between faulting and flows of Pliocene Servilleta Basalt and older, buried basaltic rocks that, combined with geologic mapping, suggest a revised rift history involving shifts in the locus of fault activity as the Taos subbasin developed. We speculate that faults related to north-striking grabens at the end of Laramide time formed the first west-down master faults. The Embudo fault may have initiated in early Miocene southwest of the Taos region. Normal-oblique slip on these early fault strands likely transitioned in space and time to dominantly left-lateral slip as the Embudo fault propagated to the northeast. During and shortly after eruption of Servilleta Basalt, proto-Embudo fault strands were active along and parallel to the modern, NE-aligned Rio Pueblo de Taos, ∼4–7 km basinward of the modern, mapped Embudo fault zone. Faults along the northeastern subbasin margin had northwest strikes for most of the period of subbasin formation and were located ∼5–7 km basinward of the modern Sangre de Cristo fault. The locus of fault activity shifted to more northerly striking faults within 2 km of the modern range front sometime after Servilleta volcanism had ceased. The northerly faults may have linked with the northeasterly proto-Embudo faults at this time, concurrent with the development of N-striking Los Cordovas normal faults within the interior of the subbasin. By middle Pleistocene(?) time, the Los Cordovas faults had become inactive, and the linked Embudo–Sangre de Cristo fault system migrated to the south, to the modern range front.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/GES01425.1","usgsCitation":"Grauch, V.J., Bauer, P.W., Drenth, B.J., and Kelson, K.I., 2017, A shifting rift—Geophysical insights into the evolution of Rio Grande rift margins and the Embudo transfer zone near Taos, New Mexico: Geosphere, v. 13, no. 3, p. 870-910, https://doi.org/10.1130/GES01425.1.","productDescription":"41 p.","startPage":"870","endPage":"910","ipdsId":"IP-076788","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":469777,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/ges01425.1","text":"Publisher Index Page"},{"id":342032,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Mexico","city":"Taos","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -105.71456909179686,\n 36.32950909247666\n ],\n [\n -105.53466796874999,\n 36.32950909247666\n ],\n [\n -105.53466796874999,\n 36.474306755095235\n ],\n [\n -105.71456909179686,\n 36.474306755095235\n ],\n [\n -105.71456909179686,\n 36.32950909247666\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"13","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-07","publicationStatus":"PW","scienceBaseUri":"59327922e4b0e9bd0eab54ed","contributors":{"authors":[{"text":"Grauch, V. J. S. 0000-0002-0761-3489 tien@usgs.gov","orcid":"https://orcid.org/0000-0002-0761-3489","contributorId":886,"corporation":false,"usgs":true,"family":"Grauch","given":"V.","email":"tien@usgs.gov","middleInitial":"J. S.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":696930,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bauer, Paul W.","contributorId":145562,"corporation":false,"usgs":false,"family":"Bauer","given":"Paul","email":"","middleInitial":"W.","affiliations":[{"id":16150,"text":"New Mexico Bureau of Geology and Mineral Resources","active":true,"usgs":false}],"preferred":false,"id":696931,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Drenth, Benjamin J. 0000-0002-3954-8124 bdrenth@usgs.gov","orcid":"https://orcid.org/0000-0002-3954-8124","contributorId":1315,"corporation":false,"usgs":true,"family":"Drenth","given":"Benjamin","email":"bdrenth@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":696932,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kelson, Keith I.","contributorId":192585,"corporation":false,"usgs":false,"family":"Kelson","given":"Keith","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":696933,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70193287,"text":"70193287 - 2017 - Seasonal movements of the Short-eared Owl (Asio flammeus) in western North America as revealed by satellite telemetry","interactions":[],"lastModifiedDate":"2017-11-01T16:38:03","indexId":"70193287","displayToPublicDate":"2017-06-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2442,"text":"Journal of Raptor Research","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Seasonal movements of the Short-eared Owl (Asio flammeus) in western North America as revealed by satellite telemetry","title":"Seasonal movements of the Short-eared Owl (Asio flammeus) in western North America as revealed by satellite telemetry","docAbstract":"The Short-eared Owl (Asio flammeus) is a widespread raptor whose abundance and distribution fluctuates in response to the varying amplitudes of its prey, which are predominately microtines. Previous efforts to describe the seasonal movements of Short-eared Owls have been hindered by few band recoveries and the species' cryptic and irruptive behavior. We attached satellite transmitters to adult Short-eared Owls at breeding areas in western and interior Alaska in June 2009 and July 2010, and tracked their movements for up to 19 mo. Owls initiated long-distance southward movements from Alaska and most followed a corridor east of the Rocky Mountains into the Prairie provinces and Great Plains states. Four owls followed a coastal route west of the Rocky Mountains, including one owl that crossed the Gulf of Alaska. Completed autumn migration distances ranged from 3205–6886 km (mean = 4722 ± 1156 km [SD]). Wintering areas spanned 21° of latitude from central Montana to southern Texas, and 24° of longitude from central California to western Kansas. Subsequent seasonal migrations were generally northward in spring and southward in autumn; these movements were comparatively short-distance (mean = 767.5 ± 517.4 km [SD]) and the owls exhibited low site fidelity. The Short-eared Owls we tracked from two relatively local breeding areas in Alaska used a patchwork of diverse open habitats across a large area of North America, which highlights that effective conservation of this species requires a collaborative, continental-scale focus.
","language":"English","publisher":"The Raptor Research Foundation","doi":"10.3356/JRR-15-81.1","usgsCitation":"Johnson, J.A., Booms, T.L., DeCicco, L.H., and Douglas, D.C., 2017, Seasonal movements of the Short-eared Owl (Asio flammeus) in western North America as revealed by satellite telemetry: Journal of Raptor Research, v. 51, no. 2, p. 115-128, https://doi.org/10.3356/JRR-15-81.1.","productDescription":"14 p.","startPage":"115","endPage":"128","ipdsId":"IP-064603","costCenters":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"links":[{"id":461523,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3356/jrr-15-81.1","text":"Publisher Index Page"},{"id":348053,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"51","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59fadd22e4b0531197b13c93","contributors":{"authors":[{"text":"Johnson, James A.","contributorId":199284,"corporation":false,"usgs":false,"family":"Johnson","given":"James","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":718552,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Booms, Travis L.","contributorId":199285,"corporation":false,"usgs":false,"family":"Booms","given":"Travis","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":718553,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"DeCicco, Lucas H.","contributorId":199286,"corporation":false,"usgs":false,"family":"DeCicco","given":"Lucas","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":718554,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Douglas, David C. 0000-0003-0186-1104 ddouglas@usgs.gov","orcid":"https://orcid.org/0000-0003-0186-1104","contributorId":2388,"corporation":false,"usgs":true,"family":"Douglas","given":"David","email":"ddouglas@usgs.gov","middleInitial":"C.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true}],"preferred":true,"id":718551,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70191697,"text":"70191697 - 2017 - Geodetic slip model of the 3 September 2016 Mw 5.8 Pawnee, Oklahoma, earthquake: Evidence for fault‐zone collapse","interactions":[],"lastModifiedDate":"2017-10-17T17:00:22","indexId":"70191697","displayToPublicDate":"2017-06-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Geodetic slip model of the 3 September 2016 Mw 5.8 Pawnee, Oklahoma, earthquake: Evidence for fault‐zone collapse","title":"Geodetic slip model of the 3 September 2016 Mw 5.8 Pawnee, Oklahoma, earthquake: Evidence for fault‐zone collapse","docAbstract":"The 3 September 2016 Mw 5.8 Pawnee earthquake in northern Oklahoma is the largest earthquake ever recorded in Oklahoma. The coseismic deformation was measured with both Interferometric Synthetic Aperture Radar and Global Positioning System (GPS), with measureable signals of order 1 cm and 1 mm, respectively. We derive a coseismic slip model from Sentinel‐1A and Radarsat 2 interferograms and GPS static offsets, dominated by distributed left‐lateral strike slip on a primary west‐northwest–east‐southeast‐trending subvertical plane, whereas strike slip is concentrated near the hypocenter (5.6 km depth), with maximum slip of ∼1 m located slightly east and down‐dip of the hypocenter. Based on systematic misfits of observed interferogram line‐of‐sight (LoS) displacements, with LoS based on shear‐dislocation models, a few decimeters of fault‐zone collapse are inferred in the hypocentral region where coseismic slip was the largest. This may represent the postseismic migration of large volumes of fluid away from the high‐slip areas, made possible by the creation of a temporary high‐permeability damage zone around the fault.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220170002","usgsCitation":"Pollitz, F., Wicks, C., Schoenball, M., Ellsworth, W.L., and Murray, M., 2017, Geodetic slip model of the 3 September 2016 Mw 5.8 Pawnee, Oklahoma, earthquake: Evidence for fault‐zone collapse: Seismological Research Letters, v. 88, no. 4, p. 983-993, https://doi.org/10.1785/0220170002.","productDescription":"11 p.","startPage":"983","endPage":"993","ipdsId":"IP-082300","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":346768,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Oklahoma","city":"Pawnee","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -97.5,\n 35.75\n ],\n [\n -95.5,\n 35.75\n ],\n [\n -95.5,\n 37\n ],\n [\n -97.5,\n 37\n ],\n [\n -97.5,\n 35.75\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"88","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-03","publicationStatus":"PW","scienceBaseUri":"59e71691e4b05fe04cd331a3","contributors":{"authors":[{"text":"Pollitz, Frederick 0000-0002-4060-2706 fpollitz@usgs.gov","orcid":"https://orcid.org/0000-0002-4060-2706","contributorId":139578,"corporation":false,"usgs":true,"family":"Pollitz","given":"Frederick","email":"fpollitz@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":713103,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wicks, Charles W. Jr. cwicks@usgs.gov","contributorId":3476,"corporation":false,"usgs":true,"family":"Wicks","given":"Charles W.","suffix":"Jr.","email":"cwicks@usgs.gov","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":false,"id":713104,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schoenball, Martin mschoenball@usgs.gov","contributorId":5760,"corporation":false,"usgs":true,"family":"Schoenball","given":"Martin","email":"mschoenball@usgs.gov","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":713105,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ellsworth, William L. ellsworth@usgs.gov","contributorId":787,"corporation":false,"usgs":true,"family":"Ellsworth","given":"William","email":"ellsworth@usgs.gov","middleInitial":"L.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":713106,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Murray, Mark","contributorId":197272,"corporation":false,"usgs":false,"family":"Murray","given":"Mark","affiliations":[],"preferred":false,"id":713107,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70193620,"text":"70193620 - 2017 - Microhabitat selection of the Virginia Northern Flying Squirrel (Glaucomys sabrinus fuscus Miller) in the central Appalachians","interactions":[],"lastModifiedDate":"2017-11-13T15:14:44","indexId":"70193620","displayToPublicDate":"2017-06-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2898,"text":"Northeastern Naturalist","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Microhabitat selection of the Virginia Northern Flying Squirrel (Glaucomys sabrinus fuscus Miller) in the central Appalachians","title":"Microhabitat selection of the Virginia Northern Flying Squirrel (Glaucomys sabrinus fuscus Miller) in the central Appalachians","docAbstract":"Glaucomys sabrinus fuscus (Virginia Northern Flying Squirrel; VNFS) is a rare Sciurid that occurrs in the Allegheny Mountains of eastern West Virginia and northwest Virginia. Previous work on this subspecies has confirmed close associations with Picea rubens (Red Spruce) at the landscape and stand levels in the region. However, ongoing Red Spruce restoration actions using canopy-gap creation to release single or small groups of trees requires a better understanding of within-stand habitat selection of VNFS to assess potential short- and medium-term impacts. To address these questions, we conducted a microhabitat study using radio-collared squirrels in montane conifer and mixed conifer—hardwood stands. We used points obtained from telemetry surveys and randomly generated points within each squirrel's home range to compare microhabitat variables for 13 individuals. We found that VNFS preferentially selected plots with conifer-dominant overstories and deep organic-soil horizons. VNFS avoided plots with dense Red Spruce regeneration in the understory in stands with hardwood-dominated overstories—the types of areas targeted for Red Spruce restoration. We also opportunistically searched for hypogeal fungi at telemetry points and found 3 species of Elaphomyces during our surveys. Our results indicate that microhabitat selection is associated with Red Spruce-dominant forests. Efforts to restore Red Spruce where hardwoods dominate in the central Appalachians may improve the connectivity and extent of habitat of VNFS.
","language":"English","publisher":"Eagle Hill Institute","doi":"10.1656/045.024.0209","usgsCitation":"Diggins, C.A., and Ford, W., 2017, Microhabitat selection of the Virginia Northern Flying Squirrel (Glaucomys sabrinus fuscus Miller) in the central Appalachians: Northeastern Naturalist, v. 24, no. 2, p. 173-190, https://doi.org/10.1656/045.024.0209.","productDescription":"18 p.","startPage":"173","endPage":"190","ipdsId":"IP-068510","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":348728,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"West Virginia","otherGeospatial":"Appalachian Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.13565063476562,\n 38.39226254196437\n ],\n [\n -79.75799560546875,\n 38.39226254196437\n ],\n [\n -79.75799560546875,\n 38.60721278935162\n ],\n [\n -80.13565063476562,\n 38.60721278935162\n ],\n [\n -80.13565063476562,\n 38.39226254196437\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"24","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-15","publicationStatus":"PW","scienceBaseUri":"5a60fbbde4b06e28e9c2352b","contributors":{"authors":[{"text":"Diggins, Corinne A.","contributorId":171667,"corporation":false,"usgs":false,"family":"Diggins","given":"Corinne","email":"","middleInitial":"A.","affiliations":[{"id":33131,"text":"Dept of Fish and Wildlife Conservation, Virginia Tech","active":true,"usgs":false}],"preferred":false,"id":721873,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ford, W. Mark 0000-0002-9611-594X wford@usgs.gov","orcid":"https://orcid.org/0000-0002-9611-594X","contributorId":172499,"corporation":false,"usgs":true,"family":"Ford","given":"W. Mark","email":"wford@usgs.gov","affiliations":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true},{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":false,"id":719654,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70188140,"text":"70188140 - 2017 - Historical patterns of acidification and increasing CO2 flux associated with Florida springs","interactions":[],"lastModifiedDate":"2017-11-29T16:39:08","indexId":"70188140","displayToPublicDate":"2017-06-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2620,"text":"Limnology and Oceanography","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Historical patterns of acidification and increasing CO2 flux associated with Florida springs","title":"Historical patterns of acidification and increasing CO2 flux associated with Florida springs","docAbstract":"Florida has one of the highest concentrations of springs in the world, with many discharging into rivers and predominantly into eastern Gulf of Mexico coast, and they likely influence the hydrochemistry of these adjacent waters; however, temporal and spatial trends have not been well studied. We present over 20 yr of hydrochemical, seasonally sampled data to identify temporal and spatial trends of pH, alkalinity, partial pressure of carbon dioxide (pCO2), and CO2flux from five first-order-magnitude (springs that discharge greater than 2.83 m3 s−1) coastal spring groups fed by the Floridan Aquifer System that ultimately discharge into the Gulf of Mexico. All spring groups had pCO2 levels (averages 3174.3–6773.2 μatm) that were much higher than atmospheric levels of CO2 and demonstrated statistically significant temporal decreases in pH and increases in CO2 flux, pCO2, and alkalinity. Total carbon flux emissions increased from each of the spring groups by between 3.48 × 107 and 2.856 × 108 kg C yr−1 over the time period. By 2013 the Springs Groups in total emitted more than 1.1739 × 109 kg C yr−1. Increases in alkalinity and pCO2 varied from 90.9 to 347.6 μmol kg−1 and 1262.3 to 2666.7 μatm, respectively. Coastal data show higher CO2 evasion than the open Gulf of Mexico, which suggests spring water influences nearshore waters. The results of this study have important implications for spring water quality, dissolution of the Florida carbonate platform, and identification of the effect and partitioning of carbon fluxes to and within coastal and marine ecosystems.
","language":"English","publisher":"ASLO","doi":"10.1002/lno.10573","usgsCitation":"Barrera, K.E., and Robbins, L.L., 2017, Historical patterns of acidification and increasing CO2 flux associated with Florida springs: Limnology and Oceanography, v. 62, no. 6, p. 2404-2417, https://doi.org/10.1002/lno.10573.","productDescription":"14 p.","startPage":"2404","endPage":"2417","ipdsId":"IP-073748","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":469783,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/lno.10573","text":"Publisher Index Page"},{"id":341976,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -82.75,\n 28.5\n ],\n [\n -82.25,\n 28.5\n ],\n [\n -82.25,\n 29.1\n ],\n [\n -82.75,\n 29.1\n ],\n [\n -82.75,\n 28.5\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"62","issue":"6","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-21","publicationStatus":"PW","scienceBaseUri":"593127afe4b0e9bd0ea9ef03","contributors":{"authors":[{"text":"Barrera, Kira E. 0000-0002-2807-4795 kbarrera@usgs.gov","orcid":"https://orcid.org/0000-0002-2807-4795","contributorId":4910,"corporation":false,"usgs":true,"family":"Barrera","given":"Kira","email":"kbarrera@usgs.gov","middleInitial":"E.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":696864,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Robbins, Lisa L. 0000-0003-3681-1094 lrobbins@usgs.gov","orcid":"https://orcid.org/0000-0003-3681-1094","contributorId":422,"corporation":false,"usgs":true,"family":"Robbins","given":"Lisa","email":"lrobbins@usgs.gov","middleInitial":"L.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":696863,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70187974,"text":"70187974 - 2017 - Formation of Fe-Mn crusts within a continental margin environment","interactions":[],"lastModifiedDate":"2017-05-26T11:18:24","indexId":"70187974","displayToPublicDate":"2017-05-26T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2954,"text":"Ore Geology Reviews","active":true,"publicationSubtype":{"id":10}},"title":"Formation of Fe-Mn crusts within a continental margin environment","docAbstract":"This study examines Fe-Mn crusts that form on seamounts along the California continental-margin (CCM), within the United States 200 nautical mile exclusive economic zone. The study area extends from approximately 30° to 38° North latitudes and from 117° to 126° West longitudes. The area of study is a tectonically active northeast Pacific plate boundary region and is also part of the North Pacific Subtropical Gyre with currents dominated by the California Current System. Upwelling of nutrient-rich water results in high primary productivity that produces a pronounced oxygen minimum zone. Hydrogenetic Fe-Mn crusts forming along the CCM show distinct chemical and mineral compositions compared to open-ocean crusts. On average, CCM crusts contain more Fe relative to Mn than open-ocean Pacific crusts. The continental shelf and slope release both Fe and Mn under low-oxygen conditions. Silica is also enriched relative to Al compared to open-ocean crusts. This is due to the North Pacific silica plume and enrichment of Si along the path of deep-water circulation, resulting in Si enrichment in bottom and intermediate waters of the eastern Pacific.
The CCM Fe-Mn crusts have a higher percentage of birnessite than open-ocean crusts, reflecting lower dissolved seawater oxygen that results from the intense coastal upwelling and proximity to zones of continental slope pore-water anoxia. Carbonate fluorapatite (CFA) is not present and CCM crusts do not show evidence of phosphatization, even in the older sections. The mineralogy indicates a suboxic environment under which birnessite forms, but in which pH is not high enough to facilitate CFA deposition. Growth rates of CCM crusts generally increase with increasing water depth, likely due to deep-water Fe sources mobilized from reduced shelf and slope sediments.
Many elements of economic interest including Mn, Co, Ni, Cu, W, and Te have slightly or significantly lower concentrations in CCM crusts relative to crusts from the Pacific Prime Crust Zone and other open-ocean basins. However, concentrations of total rare earth elements and yttrium average only slightly lower contents and in the future may be a strategic resource for the U.S.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.oregeorev.2016.09.010","collaboration":"James R. Hein;","usgsCitation":"Conrad, T.A., Hein, J., Paytan, A., and Clague, D.A., 2017, Formation of Fe-Mn crusts within a continental margin environment: Ore Geology Reviews, v. 87, p. 25-40, https://doi.org/10.1016/j.oregeorev.2016.09.010.","productDescription":"16 p.","startPage":"25","endPage":"40","ipdsId":"IP-074776","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":341798,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -126,\n 30\n ],\n [\n -117,\n 30\n ],\n [\n -117,\n 38\n ],\n [\n -126,\n 38\n ],\n [\n -126,\n 30\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"87","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59293e94e4b016f7a94076f6","contributors":{"authors":[{"text":"Conrad, Tracey A. 0000-0002-2648-5451","orcid":"https://orcid.org/0000-0002-2648-5451","contributorId":192284,"corporation":false,"usgs":false,"family":"Conrad","given":"Tracey","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":696130,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hein, James R. jhein@usgs.gov","contributorId":140283,"corporation":false,"usgs":true,"family":"Hein","given":"James R.","email":"jhein@usgs.gov","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":696131,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Paytan, Adina","contributorId":75242,"corporation":false,"usgs":true,"family":"Paytan","given":"Adina","affiliations":[],"preferred":false,"id":696132,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Clague, David A.","contributorId":77105,"corporation":false,"usgs":false,"family":"Clague","given":"David","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":696133,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70185589,"text":"ofr20171032 - 2017 - Summary of oceanographic and water-quality measurements in Chincoteague Bay, Maryland and Virginia, 2014–15","interactions":[],"lastModifiedDate":"2017-05-25T15:43:23","indexId":"ofr20171032","displayToPublicDate":"2017-05-25T13:50:00","publicationYear":"2017","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":"2017-1032","title":"Summary of oceanographic and water-quality measurements in Chincoteague Bay, Maryland and Virginia, 2014–15","docAbstract":"U.S. Geological Survey scientists and technical support staff measured oceanographic, waterquality, seabed-elevation-change, and meteorological parameters in Chincoteague Bay, Maryland and Virginia, during the period of August 13, 2014, to July 14, 2015, as part of the Estuarine Physical Response to Storms project (GS2–2D) supported by the Department of the Interior Hurricane Sandy recovery program. These measurements provide time series data that quantify the response and can be used to better understand the resilience of this back-barrier estuarine system to storms. The Assateague Island National Seashore (National Park Service) and the Chincoteague National Wildlife Refuge (U.S. Fish and Wildlife Service) are on the east side of Chincoteague Bay.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171032","usgsCitation":"Suttles, S.E., Ganju, N.K, Brosnahan, S.M., Montgomery, E.T., Dickhudt, P.J., Beudin, Alexis, Nowacki, D.J., and Martini, M.A., 2017, Summary of oceanographic and water-quality measurements in Chincoteague Bay, Maryland and Virginia, 2014–15: U.S. Geological Survey Open-File Report 2017–1032, 95 p., https://doi.org/10.3133/ofr20171032.","productDescription":"xii, 95 p.","numberOfPages":"112","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-079627","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":341661,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7DF6PBV","text":"USGS data release","description":"USGS data release","linkHelpText":"Oceanographic and water-quality measurements in Chincoteague Bay, Maryland/Virginia, 2014–2015 "},{"id":341660,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1032/ofr20171032.pdf","text":"Report","size":"25.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1032"},{"id":338262,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1032/coverthb.jpg"},{"id":341663,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7WD3XSF","text":"USGS data release","description":"USGS data release","linkHelpText":"Water samples in support of oceanographic and water-quality measurements in Chincoteague Bay, Maryland and Virginia, 2014–15, U.S. Geological Survey Field Activity 2014-048-FA"}],"country":"United States","state":"Maryland, Virginia","otherGeospatial":"Chincoteague Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.05996704101562,\n 38.34273329203372\n ],\n [\n -75.11489868164062,\n 38.36857886877816\n ],\n [\n -75.23300170898438,\n 38.28885871419223\n ],\n [\n -75.35110473632812,\n 38.13455657705411\n ],\n [\n -75.52001953125,\n 37.90194871393947\n ],\n [\n -75.38681030273436,\n 37.826056694926535\n ],\n [\n -75.16021728515624,\n 38.08160859009049\n ],\n [\n -75.05996704101562,\n 38.34273329203372\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Woods Hole Coastal and Marine Science Center
U.S. Geological Survey
384 Woods Hole Road
Quissett Campus
Woods Hole, MA 02543
The Camas National Wildlife Refuge (Refuge) in eastern Idaho, established in 1937, contains wetlands, ponds, and wet meadows that are essential resting and feeding habitat for migratory birds and nesting habitat for waterfowl. Initially, natural sources of water supported these habitats. However, during the past few decades, changes in climate and surrounding land use have altered and reduced natural groundwater and surface-water inflows, resulting in a 5-meter decline in the water table and an earlier, and more frequent, occurrence of no flow in Camas Creek at the Refuge. Due to these changes in water availability, water management that includes extensive groundwater pumping is now necessary to maintain the wetlands, ponds, and wet meadows.
These water management activities have proven to be inefficient and expensive, and the Refuge is seeking alternative water-management options that are more efficient and less expensive. More efficient water management at the Refuge may be possible through knowledge of the seepage rates from ditches, ponds, and lakes at the Refuge. With this knowledge, water-management efficiency may be improved by natural means through selective use of water bodies with the smallest seepage rates or through engineering efforts to minimize seepage losses from water bodies with the largest seepage rates.
The U.S. Geological Survey performed field studies in 2015 and 2016 to estimate seepage rates for selected ditches, ponds, and lakes at the Refuge. Estimated seepage rates from ponds and lakes ranged over an order of magnitude, from 3.4 ± 0.2 to 103.0 ± 0.5 mm/d, with larger seepage rates calculated for Big Pond and Redhead Pond, intermediate seepage rates calculated for Two-way Pond, and smaller seepages rates calculated for the south arm of Sandhole Lake. Estimated seepage losses from two reaches of Main Diversion Ditch were 21 ± 2 and 17 ± 2 percent/km. These losses represent seepage rates of about 890 and 860 mm/d, which are one- to two-orders-of-magnitude larger than seepage rates from the ponds and lake.
The depth-integrated vertical hydraulic conductivity (Kv) for sediment underlying the ponds and lake was the primary control of seepage rates. The Kv's were 30 and 34 m/d for Big Pond, 14 and 18 m/d for Toomey Pond, 8 and 10 m/d for Two-way Pond, and 47 m/d for the north arm of Sandhole Lake.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2017.02.063","usgsCitation":"Rattray, G.W., 2017, Estimated seepage rates from selected ditches, ponds, and lakes at the Camas National Wildlife Refuge, eastern Idaho: Journal of Environmental Management, v. 203, no. 1, p. 578-591, https://doi.org/10.1016/j.jenvman.2017.02.063.","productDescription":"14 p.","startPage":"578","endPage":"591","ipdsId":"IP-083400","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":341508,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","otherGeospatial":"Camas National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -112.24765777587889,\n 43.989603470452224\n ],\n [\n -112.2531509399414,\n 43.989603470452224\n ],\n [\n -112.25349426269531,\n 43.98589821991874\n ],\n [\n -112.2637939453125,\n 43.985774707584255\n ],\n [\n -112.26362228393555,\n 43.98206921804778\n ],\n [\n -112.25349426269531,\n 43.98219273809204\n ],\n [\n -112.2531509399414,\n 43.97873407971019\n ],\n [\n -112.25812911987305,\n 43.97836349721919\n ],\n [\n -112.25812911987305,\n 43.971074904863265\n ],\n [\n -112.26430892944336,\n 43.9711984477796\n ],\n [\n -112.2670555114746,\n 43.968356895686235\n ],\n [\n -112.2670555114746,\n 43.96551520764685\n ],\n [\n -112.26808547973633,\n 43.96514454266273\n ],\n [\n -112.27117538452148,\n 43.965268097914425\n ],\n [\n -112.27254867553711,\n 43.96625653067646\n ],\n [\n -112.27666854858398,\n 43.96613297748065\n ],\n [\n -112.27855682373045,\n 43.96477387536573\n ],\n [\n -112.29263305664062,\n 43.96514454266273\n ],\n [\n -112.29246139526367,\n 43.9576071863508\n ],\n [\n -112.30327606201172,\n 43.95773075727856\n ],\n [\n -112.30293273925781,\n 43.94302401260679\n ],\n [\n -112.29297637939453,\n 43.94277680933283\n ],\n [\n -112.29297637939453,\n 43.92843726069337\n ],\n [\n -112.3080825805664,\n 43.92843726069337\n ],\n [\n -112.3077392578125,\n 43.92497547227071\n ],\n [\n -112.31306076049803,\n 43.924851833243785\n ],\n [\n -112.31254577636719,\n 43.90655042390404\n ],\n [\n -112.30258941650389,\n 43.90667410096243\n ],\n [\n -112.30241775512695,\n 43.91038429322458\n ],\n [\n -112.28799819946289,\n 43.91026062387522\n ],\n [\n -112.28765487670898,\n 43.90667410096243\n ],\n [\n -112.28284835815428,\n 43.90655042390404\n ],\n [\n -112.28216171264647,\n 43.90296367743057\n ],\n [\n -112.27752685546875,\n 43.90321104619439\n ],\n [\n -112.2776985168457,\n 43.89962409851726\n ],\n [\n -112.24662780761719,\n 43.89925302263017\n ],\n [\n -112.24679946899414,\n 43.917309366668476\n ],\n [\n -112.24250793457031,\n 43.917309366668476\n ],\n [\n -112.2421646118164,\n 43.921018895951235\n ],\n [\n -112.22705841064453,\n 43.92077160119423\n ],\n [\n -112.22705841064453,\n 43.92769546584876\n ],\n [\n -112.2169303894043,\n 43.92806636442745\n ],\n [\n -112.2169303894043,\n 43.94079914613631\n ],\n [\n -112.22328186035156,\n 43.957483615166055\n ],\n [\n -112.24782943725586,\n 43.957854327949335\n ],\n [\n -112.24731445312499,\n 43.9788576066932\n ],\n [\n -112.24285125732422,\n 43.97836349721919\n ],\n [\n -112.24267959594727,\n 43.98206921804778\n ],\n [\n -112.22963333129883,\n 43.98206921804778\n ],\n [\n -112.23066329956055,\n 43.99306149560464\n ],\n [\n -112.24782943725586,\n 43.99306149560464\n ],\n [\n -112.24765777587889,\n 43.989603470452224\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"203","issue":"1","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59200449e4b0ac16dbdeb77c","contributors":{"authors":[{"text":"Rattray, Gordon W. 0000-0002-1690-3218 grattray@usgs.gov","orcid":"https://orcid.org/0000-0002-1690-3218","contributorId":2521,"corporation":false,"usgs":true,"family":"Rattray","given":"Gordon","email":"grattray@usgs.gov","middleInitial":"W.","affiliations":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":695642,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70187713,"text":"70187713 - 2017 - Performance and retention of lightweight satellite radio tags applied to the ears of polar bears (Ursus maritimus)","interactions":[],"lastModifiedDate":"2017-05-16T11:02:37","indexId":"70187713","displayToPublicDate":"2017-05-16T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":773,"text":"Animal Biotelemetry","active":true,"publicationSubtype":{"id":10}},"title":"Performance and retention of lightweight satellite radio tags applied to the ears of polar bears (Ursus maritimus)","docAbstract":"Background
Satellite telemetry studies provide information that is critical to the conservation and management of species affected by ecological change. Here we report on the performance and retention of two types (SPOT-227 and SPOT-305A) of ear-mounted Argos-linked satellite transmitters (i.e., platform transmitter terminal, or PTT) deployed on free-ranging polar bears in Eastern Greenland, Baffin Bay, Kane Basin, the southern Beaufort Sea, and the Chukchi Sea during 2007–2013.
Results
Transmissions from 142 out of 145 PTTs deployed on polar bears were received for an average of 69.3 days. The average functional longevity, defined as the number of days they transmitted while still attached to polar bears, for SPOT-227 was 56.8 days and for SPOT-305A was 48.6 days. Thirty-four of the 142 (24%) PTTs showed signs of being detached before they stopped transmitting, indicating that tag loss was an important aspect of tag failure. Furthermore, 10 of 26 (38%) bears that were re-observed following application of a PTT had a split ear pinna, suggesting that some transmitters were detached by force. All six PTTs that were still on bears upon recapture had lost the antenna, which indicates that antenna breakage was a significant contributor to PTT failure. Finally, only nine of the 142 (6%) PTTs—three of which were still attached to bears—had a final voltage reading close to the value indicating battery exhaustion. This suggests that battery exhaustion was not a major factor in tag performance.
Conclusions
The average functional longevity of approximately 2 months for ear-mounted PTTs (this study) is poor compared to PTT collars fitted to adult female polar bears, which can last for several years. Early failure of the ear-mounted PTTs appeared to be caused primarily by detachment from the ear or antenna breakage. We suggest that much smaller and lighter ear-mounted transmitters are necessary to reduce the risk of tissue irritation, tissue damage, and tag detachment, and with a more robust antenna design. Our results are applicable to other tag types (e.g., iridium and VHF systems) and to research on other large mammals that cannot wear radio collars.
Water is a precious and limited commodity in the western United States and its conveyance is extremely important. Therefore, it is critical to do as much as possible to prevent the spread of two species of dreissenid mussels, both non-native and highly invasive aquatic species already well-established in the eastern half of the United States. This book addresses the occurrences of the two dreissenid mussels in the West, the quagga mussel and the zebra mussel, that are both known to negatively impact water delivery systems and natural ecosystems. It is edited by two researchers whom have extensive experience working with the mussels in the West and is composed of 34 chapters, or articles, written by a variety of experts.
Book information: Biology and Management of Invasive Quagga and Zebra Mussels in the Western United States. Edited by Wai Hing Wong and Shawn L. Gerstenberger. Boca Raton (Florida): CRC Press (Taylor & Francis Group). $149.95. xx + 545 p.; ill.; index. ISBN: 978-1-4665-9561-3. [Compact Disc included.] 2015.
","language":"English","publisher":"University of Chicago Press","doi":"10.1086/692233","usgsCitation":"Benson, A.J., 2017, Book review: Biology and management of invasive quagga and zebra mussels in the western United States: The Quarterly Review of Biology, v. 92, no. 2, p. 209-210, https://doi.org/10.1086/692233.","productDescription":"2 p.","startPage":"209","endPage":"210","ipdsId":"IP-084644","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":341243,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"92","issue":"2","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5916c9b0e4b044b359e48686","contributors":{"authors":[{"text":"Benson, Amy J. 0000-0002-4517-1466 abenson@usgs.gov","orcid":"https://orcid.org/0000-0002-4517-1466","contributorId":3836,"corporation":false,"usgs":true,"family":"Benson","given":"Amy","email":"abenson@usgs.gov","middleInitial":"J.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":true,"id":694944,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70187642,"text":"70187642 - 2017 - Atmospheric deposition to forests in the eastern USA","interactions":[],"lastModifiedDate":"2017-05-12T09:42:09","indexId":"70187642","displayToPublicDate":"2017-05-12T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1555,"text":"Environmental Pollution","active":true,"publicationSubtype":{"id":10}},"title":"Atmospheric deposition to forests in the eastern USA","docAbstract":"Atmospheric mercury (Hg) deposition to forests is important because half of the land cover in the eastern USA is forest. Mercury was measured in autumn litterfall and weekly precipitation samples at a total of 27 National Atmospheric Deposition Program (NADP) monitoring sites in deciduous and mixed deciduous-coniferous forests in 16 states in the eastern USA during 2007–2014. These simultaneous, uniform, repeated, annual measurements of forest Hg include the broadest area and longest time frame to date. The autumn litterfall-Hg concentrations and litterfall mass at the study sites each year were combined with annual precipitation-Hg data. Rates of litterfall-Hg deposition were higher than or equal to precipitation-Hg deposition rates in 70% of the annual data, which indicates a substantial contribution from litterfall to total atmospheric-Hg deposition. Annual litterfall-Hg deposition in this study had a median of 11.7 μg per square meter per year (μg/m2/yr) and ranged from 2.2 to 23.4 μg/m2/yr. It closely matched modeled dry-Hg deposition, based on land cover at selected NADP Hg-monitoring sites. Mean annual atmospheric-Hg deposition at forest study sites exhibited a spatial pattern partly explained by statistical differences among five forest-cover types and related to the mapped density of Hg emissions. Forest canopies apparently recorded changes in atmospheric-Hg concentrations over time because litterfall-Hg concentrations decreased year to year and litterfall-Hg concentrations were significantly higher in 2007–2009 than in 2012–2014. These findings reinforce reported decreases in Hg emissions and atmospheric elemental-Hg concentrations during this same time period. Methylmercury (MeHg) was detected in all litterfall samples at all sites, compared with MeHg detections in less than half the precipitation samples at selected sites during the study. These results indicate MeHg in litterfall is a pathway into the terrestrial food web where it can accumulate in the prey of songbirds, bats, and raptors.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.envpol.2017.05.004","usgsCitation":"Risch, M.R., DeWild, J.F., Gay, D.A., Zhang, L., Boyer, E.W., and Krabbenhoft, D.P., 2017, Atmospheric deposition to forests in the eastern USA: Environmental Pollution, v. 228, p. 8-18, https://doi.org/10.1016/j.envpol.2017.05.004.","productDescription":"11 p. 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]\n}","volume":"228","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5916c9b3e4b044b359e4868c","contributors":{"authors":[{"text":"Risch, Martin R. 0000-0002-7908-7887 mrrisch@usgs.gov","orcid":"https://orcid.org/0000-0002-7908-7887","contributorId":2118,"corporation":false,"usgs":true,"family":"Risch","given":"Martin","email":"mrrisch@usgs.gov","middleInitial":"R.","affiliations":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true},{"id":27231,"text":"Indiana-Kentucky Water Science Center","active":true,"usgs":true},{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":694910,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"DeWild, John F. 0000-0003-4097-2798 jfdewild@usgs.gov","orcid":"https://orcid.org/0000-0003-4097-2798","contributorId":2525,"corporation":false,"usgs":true,"family":"DeWild","given":"John","email":"jfdewild@usgs.gov","middleInitial":"F.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":694911,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gay, David A.","contributorId":177963,"corporation":false,"usgs":false,"family":"Gay","given":"David","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":694912,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zhang, Leiming 0000-0001-5437-5412","orcid":"https://orcid.org/0000-0001-5437-5412","contributorId":191971,"corporation":false,"usgs":false,"family":"Zhang","given":"Leiming","email":"","affiliations":[],"preferred":false,"id":694913,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Boyer, Elizabeth W.","contributorId":44659,"corporation":false,"usgs":false,"family":"Boyer","given":"Elizabeth","email":"","middleInitial":"W.","affiliations":[{"id":7260,"text":"Pennsylvania State University","active":true,"usgs":false}],"preferred":false,"id":694914,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Krabbenhoft, David P. 0000-0003-1964-5020 dpkrabbe@usgs.gov","orcid":"https://orcid.org/0000-0003-1964-5020","contributorId":1658,"corporation":false,"usgs":true,"family":"Krabbenhoft","given":"David","email":"dpkrabbe@usgs.gov","middleInitial":"P.","affiliations":[{"id":37464,"text":"WMA - Laboratory & Analytical Services Division","active":true,"usgs":true},{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true},{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":694915,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70187620,"text":"70187620 - 2017 - Geologic controls on cave development in Burnsville Cove, Bath and Highland Counties, Virginia","interactions":[],"lastModifiedDate":"2017-05-12T10:37:16","indexId":"70187620","displayToPublicDate":"2017-05-12T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1724,"text":"GSA Field Guides","active":true,"publicationSubtype":{"id":10}},"title":"Geologic controls on cave development in Burnsville Cove, Bath and Highland Counties, Virginia","docAbstract":"Burnsville Cove in Bath and Highland Counties (Virginia, USA) is a karst region in the Valley and Ridge Province of the Appalachian Mountains. The region contains many caves in Silurian to Devonian limestone, and is well suited for examining geologic controls on cave location and cave passage morphology. In Burnsville Cove, many caves are located preferentially near the axes of synclines and anticlines. For example, Butler Cave is an elongate cave where the trunk channel follows the axis of Sinking Creek syncline and most of the side passages follow joints at right angles to the syncline axis. In contrast, the Water Sinks Subway Cave, Owl Cave, and Helictite Cave have abundant maze patterns, and are located near the axis of Chestnut Ridge anticline. The maze patterns may be related to fact that the anticline axis is the site of the greatest amount of flexure, leading to more joints and (or) greater enlargement of joints. Many of the larger caves of Burnsville Cove (e.g., Breathing Cave, Butler Cave–Sinking Creek Cave System, lower parts of the Water Sinks Cave System) are developed in the Silurian Tonoloway Limestone, the stratigraphic unit with the greatest surface exposure in the area. Other caves are developed in the Silurian to Devonian Keyser Limestone of the Helderberg Group (e.g., Owl Cave, upper parts of the Water Sinks Cave System) and in the Devonian Shriver Chert and (or) Licking Creek Limestone of the Helderberg Group (e.g., Helictite Cave). Within the Tonoloway Limestone, the larger caves are developed in the lower member of the Tonoloway Limestone immediately below a bed of silica-cemented sandstone. In contrast, the larger caves in the Keyser Limestone are located preferentially in limestone beds containing stromatoporoid reefs, and some of the larger caves in the Licking Creek Limestone are located in beds of cherty limestone below the Devonian Oriskany Sandstone. Geologic controls on cave passage morphology include joints, bedding planes, and folds. The influence of joints results in tall and narrow cave passages, whereas the influence of bedding planes results in cave passages with flat ceilings and (or) floors. The influence of folds is less common, but a few cave passages follow fold axes and have distinctive arched ceilings.
","largerWorkTitle":"From the Blue Ridge to the Beach: Geological Field Excursions across Virginia","language":"English","publisher":"Geological Society of America","publisherLocation":"Boulder, CO","doi":"10.1130/2017.0047(04)","usgsCitation":"Swezey, C.S., Haynes, J.T., Lucas, P.C., and Lambert, R.A., 2017, Geologic controls on cave development in Burnsville Cove, Bath and Highland Counties, Virginia: GSA Field Guides, v. 47, p. 89-123, https://doi.org/10.1130/2017.0047(04).","productDescription":"35 p.","startPage":"89","endPage":"123","ipdsId":"IP-081746","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":438346,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9YMM9EM","text":"USGS data release","linkHelpText":"Data Release for Luminescence: Butler Cave, Burnsville Cove, Bath and Highland Counties, VA"},{"id":341195,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","county":"Bath County, Highland County","otherGeospatial":"Burnsville Cove","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.680556,\n 38.141667\n ],\n [\n -79.5625,\n 38.141667\n ],\n [\n -79.5625,\n 38.241667\n ],\n [\n -79.680556,\n 38.241667\n ],\n [\n -79.680556,\n 38.141667\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"47","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5916c9b3e4b044b359e48690","contributors":{"authors":[{"text":"Swezey, Christopher S. 0000-0003-4019-9264 cswezey@usgs.gov","orcid":"https://orcid.org/0000-0003-4019-9264","contributorId":173033,"corporation":false,"usgs":true,"family":"Swezey","given":"Christopher","email":"cswezey@usgs.gov","middleInitial":"S.","affiliations":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":694787,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haynes, John T.","contributorId":54842,"corporation":false,"usgs":true,"family":"Haynes","given":"John","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":694788,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lucas, Philip C.","contributorId":191928,"corporation":false,"usgs":false,"family":"Lucas","given":"Philip","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":694789,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lambert, Richard A.","contributorId":191929,"corporation":false,"usgs":false,"family":"Lambert","given":"Richard","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":694952,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70187543,"text":"70187543 - 2017 - Evidence for distributed clockwise rotation of the crust in the northwestern United States from fault geometries and focal mechanisms","interactions":[],"lastModifiedDate":"2017-06-20T13:13:53","indexId":"70187543","displayToPublicDate":"2017-05-08T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3524,"text":"Tectonics","active":true,"publicationSubtype":{"id":10}},"title":"Evidence for distributed clockwise rotation of the crust in the northwestern United States from fault geometries and focal mechanisms","docAbstract":"Paleomagnetic and GPS data indicate that Washington and Oregon have rotated clockwise for the past 16 Myr. Late Cenozoic and Quaternary fault geometries, seismicity lineaments, and focal mechanisms provide evidence that this rotation is accommodated by north directed thrusting and right-lateral strike-slip faulting in Washington, and SW to W directed normal faulting and right-lateral strike-slip faulting to the east. Several curvilinear NW to NNW trending high-angle strike-slip faults and seismicity lineaments in Washington and NW Oregon define a geologic pole (117.7°W, 47.9°N) of rotation relative to North America. Many faults and focal mechanisms throughout northwestern U.S. and southwestern British Columbia have orientations consistent with this geologic pole as do GPS surface velocities corrected for elastic Cascadia subduction zone coupling. Large Quaternary normal faults radial to the geologic pole, which appear to accommodate crustal rotation via crustal extension, are widespread and can be found along the Lewis and Clark zone in Montana, within the Centennial fault system north of the Snake River Plain in Idaho and Montana, to the west of the Wasatch Front in Utah, and within the northern Basin and Range in Oregon and Nevada. Distributed strike-slip faults are most prominent in western Washington and Oregon and may serve to transfer slip between faults throughout the northwestern U.S.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2016TC004223","usgsCitation":"Brocher, T.M., Wells, R.E., Lamb, A.P., and Weaver, C.S., 2017, Evidence for distributed clockwise rotation of the crust in the northwestern United States from fault geometries and focal mechanisms: Tectonics, v. 36, no. 5, p. 787-818, https://doi.org/10.1002/2016TC004223.","productDescription":"32 p.","startPage":"787","endPage":"818","ipdsId":"IP-068687","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":469865,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016tc004223","text":"Publisher Index Page"},{"id":340937,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"British Columbia, Oregon, Washington","otherGeospatial":"Vancouver Island","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -125,\n 42\n ],\n [\n -118,\n 42\n ],\n [\n -118,\n 49\n ],\n [\n -125,\n 49\n ],\n [\n -125,\n 42\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"36","issue":"5","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-05","publicationStatus":"PW","scienceBaseUri":"591183afe4b0e541a03c1a46","contributors":{"authors":[{"text":"Brocher, Thomas M. 0000-0002-9740-839X brocher@usgs.gov","orcid":"https://orcid.org/0000-0002-9740-839X","contributorId":262,"corporation":false,"usgs":true,"family":"Brocher","given":"Thomas","email":"brocher@usgs.gov","middleInitial":"M.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":694440,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wells, Ray E. 0000-0002-7796-0160 rwells@usgs.gov","orcid":"https://orcid.org/0000-0002-7796-0160","contributorId":141072,"corporation":false,"usgs":true,"family":"Wells","given":"Ray","email":"rwells@usgs.gov","middleInitial":"E.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":false,"id":694441,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lamb, Andrew P. alamb@usgs.gov","contributorId":5720,"corporation":false,"usgs":true,"family":"Lamb","given":"Andrew","email":"alamb@usgs.gov","middleInitial":"P.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":694442,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Weaver, Craig S. craig@usgs.gov","contributorId":2690,"corporation":false,"usgs":true,"family":"Weaver","given":"Craig","email":"craig@usgs.gov","middleInitial":"S.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":694443,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70187518,"text":"70187518 - 2017 - Using publicly available data to quantify plant–pollinator interactions and evaluate conservation seeding mixes in the Northern Great Plains","interactions":[],"lastModifiedDate":"2017-06-01T10:28:51","indexId":"70187518","displayToPublicDate":"2017-05-08T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1536,"text":"Environmental Entomology","active":true,"publicationSubtype":{"id":10}},"title":"Using publicly available data to quantify plant–pollinator interactions and evaluate conservation seeding mixes in the Northern Great Plains","docAbstract":"Concern over declining pollinators has led to multiple conservation initiatives for improving forage for bees in agroecosystems. Using data available through the Pollinator Library (npwrc.usgs.gov/pollinator/), we summarize plant–pollinator interaction data collected from 2012–2015 on lands managed by the U.S. Fish and Wildlife Service and private lands enrolled in U.S. Department of Agriculture conservation programs in eastern North Dakota (ND). Furthermore, we demonstrate how plant–pollinator interaction data from the Pollinator Library and seed cost information can be used to evaluate hypothetical seeding mixes for pollinator habitat enhancements. We summarize records of 314 wild bee and 849 honey bee (Apis mellifera L.) interactions detected on 63 different plant species. The wild bee observations consisted of 46 species, 15 genera, and 5 families. Over 54% of all wild bee observations were represented by three genera―Bombus, Lassioglossum, and Melissodes. The most commonly visited forbs by wild bees were Monarda fistulosa, Sonchus arvensis, and Zizia aurea. The most commonly visited forbs by A. mellifera were Cirsium arvense, Melilotus officinalis, and Medicago sativa. Among all interactions, 13% of A. mellifera and 77% of wild bee observations were made on plants native to ND. Our seed mix evaluation shows that mixes may often need to be tailored to meet the unique needs of wild bees and managed honey bees in agricultural landscapes. Our evaluation also demonstrates the importance of incorporating both biologic and economic information when attempting to design cost-effective seeding mixes for supporting pollinators in a critically important part of the United States.
","language":"English","publisher":"Entomological Society of America","doi":"10.1093/ee/nvx070","usgsCitation":"Otto, C., O’Dell, S., Bryant, R.B., Euliss, N., Bush, R., and Smart, M., 2017, Using publicly available data to quantify plant–pollinator interactions and evaluate conservation seeding mixes in the Northern Great Plains: Environmental Entomology, v. 46, no. 3, p. 565-578, https://doi.org/10.1093/ee/nvx070.","productDescription":"14 p.","startPage":"565","endPage":"578","ipdsId":"IP-081790","costCenters":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":340909,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"46","issue":"3","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-02","publicationStatus":"PW","scienceBaseUri":"591183b1e4b0e541a03c1a50","contributors":{"authors":[{"text":"Otto, Clint 0000-0002-7582-3525 cotto@usgs.gov","orcid":"https://orcid.org/0000-0002-7582-3525","contributorId":5426,"corporation":false,"usgs":true,"family":"Otto","given":"Clint","email":"cotto@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":694286,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"O’Dell, Samuel sodell@usgs.gov","contributorId":152473,"corporation":false,"usgs":true,"family":"O’Dell","given":"Samuel","email":"sodell@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":694397,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bryant, R. B.","contributorId":191824,"corporation":false,"usgs":false,"family":"Bryant","given":"R.","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":694287,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Euliss, Ned H. Jr.","contributorId":178233,"corporation":false,"usgs":false,"family":"Euliss","given":"Ned H. Jr.","affiliations":[],"preferred":false,"id":694288,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bush, Rachel","contributorId":191796,"corporation":false,"usgs":false,"family":"Bush","given":"Rachel","email":"","affiliations":[],"preferred":false,"id":694289,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Smart, Matthew 0000-0003-0711-3035 msmart@usgs.gov","orcid":"https://orcid.org/0000-0003-0711-3035","contributorId":174424,"corporation":false,"usgs":true,"family":"Smart","given":"Matthew","email":"msmart@usgs.gov","affiliations":[{"id":480,"text":"Northern Prairie Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":694290,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70187326,"text":"ofr20171047 - 2017 - Characterization of peak streamflows and flood inundation at selected areas in North Carolina following Hurricane Matthew, October 2016","interactions":[],"lastModifiedDate":"2017-08-29T15:36:32","indexId":"ofr20171047","displayToPublicDate":"2017-05-05T12:00:00","publicationYear":"2017","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":"2017-1047","title":"Characterization of peak streamflows and flood inundation at selected areas in North Carolina following Hurricane Matthew, October 2016","docAbstract":"The passage of Hurricane Matthew through central and eastern North Carolina during October 7–9, 2016, brought heavy rainfall, which resulted in major flooding. More than 15 inches of rain was recorded in some areas. More than 600 roads were closed, including Interstates 95 and 40, and nearly 99,000 structures were affected by floodwaters. Immediately following the flooding, the U.S. Geological Survey documented 267 high-water marks, of which 254 were surveyed. North Carolina Emergency Management documented and surveyed 353 high-water marks. Using a subset of these highwater marks, six flood-inundation maps were created for hard-hit communities. Digital datasets of the inundation areas, study reach boundary, and water-depth rasters are available for download. In addition, peak gage-height data, peak streamflow data, and annual exceedance probabilities (in percent) were determined for 24 U.S. Geological Survey streamgages located near the heavily flooded communities.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171047","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency","usgsCitation":"Musser, J.W., Watson, K.M., and Gotvald, A.J., 2017, Characterization of peak streamflows and flood inundation at selected areas in North Carolina following Hurricane Matthew, October 2016 (ver. 2.0, August 2017): U.S. Geological Survey Open-File Report 2017–1047, 23 p., https://doi.org/10.3133/ofr20171047.","productDescription":"Report: v, 23 p.; Data Release, Version History","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-085645","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":340658,"rank":2,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F75X276T","text":"USGS data release","description":"USGS data release","linkHelpText":"Flood inundation, flood depth, and high-water marks for selected areas in North Carolina from the October 2016 flood"},{"id":340659,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1047/ofr20171047.pdf","text":"Report","size":"4.02 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1047"},{"id":340657,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1047/coverthb3.jpg"},{"id":342197,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2017/1047/versionHist.txt","size":"2.31 MB","linkFileType":{"id":2,"text":"txt"}}],"country":"United States","state":"North Carolina, South Carolina","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.75,\n 34\n ],\n [\n -76.75,\n 34\n ],\n [\n -76.75,\n 36.116667\n ],\n [\n -79.75,\n 36.116667\n ],\n [\n -79.75,\n 34\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0: October 2016; Version 1.1: June 2017; Version 2.0: August 2017","contact":"Director, South Atlantic Water Science Center
U.S. Geological Survey
720 Gracern Road
Stephenson Center, Suite 129
Columbia, SC 29210