A previously developed regional groundwater flow model was used to simulate the effects of changes in pumping rates on groundwater-flow paths and extent of recharge discharging to wells for a contaminated fractured bedrock aquifer in southeastern Pennsylvania. Groundwater in the vicinity of the North Penn Area 7 Superfund site, Montgomery County, Pennsylvania, was found to be contaminated with organic compounds, such as trichloroethylene (TCE), in 1979. At the time contamination was discovered, groundwater from the underlying fractured bedrock (shale) aquifer was the main source of supply for public drinking water and industrial use. As part of technical support to the U.S. Environmental Protection Agency (EPA) during the Remedial Investigation of the North Penn Area 7 Superfund site from 2000 to 2005, the U.S. Geological Survey (USGS) developed a model of regional groundwater flow to describe changes in groundwater flow and contaminant directions as a result of changes in pumping. Subsequently, large decreases in TCE concentrations (as much as 400 micrograms per liter) were measured in groundwater samples collected by the EPA from selected wells in 2010 compared to 2005‒06 concentrations.
To provide insight on the fate of potentially contaminated groundwater during the period of generally decreasing pumping rates from 1990 to 2010, steady-state simulations were run using the previously developed groundwater-flow model for two conditions prior to extensive remediation, 1990 and 2000, two conditions subsequent to some remediation 2005 and 2010, and a No Pumping case, representing pre-development or cessation of pumping conditions. The model was used to (1) quantify the amount of recharge, including potentially contaminated recharge from sources near the land surface, that discharged to wells or streams and (2) delineate the areas contributing recharge that discharged to wells or streams for the five conditions.
In all simulations, groundwater divides differed from surface-water divides, partly because of differences in stream elevations and because of geologic structure and pumping. In the 1990 and 2000 simulations, all recharge in and near the vicinity of North Penn Area 7 discharged to wells, but in the 2005 and 2010 simulations some recharge in this area discharged to streams, indicating possible discharge of contaminated groundwater from North Penn Area 7 sources to streams. As the amount of groundwater withdrawals by wells has declined since 1990, the area contributing recharge to wells in the vicinity of North Penn Area 7 has decreased.
To determine the effect of changes in pumping on flow paths and possible flow-path-related contributions to the observed changes in spatial distribution of contaminants in groundwater from 2005 to 2010, the USGS conducted simulations using the previously developed regional groundwater-flow model using reported pumping and estimated recharge rates for 2005 and 2010. Flow paths from recharge at known contaminant source areas to discharge locations at wells or streams were simulated under steady-state conditions for the two periods. Simulated groundwater-flow paths shifted only slightly from 2005 to 2010 as a result of changes in pumping rates. These slight changes in groundwater-flow paths from known sources of contamination are not coincident with the spatial distribution of observed changes in TCE concentrations from 2005 to 2010, indicating that the decreases of TCE concentrations may be a result of other processes, such as source removal or degradation. Results of the simulations and the absence of increases in TCE-degradation-product concentrations indicate that the decreases of TCE concentrations observed in 2010 may be at least partly related to contaminant-source removal by soil excavation completed in 2005, although additional data would be needed to confirm this preliminary explanation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175014","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Senior, L.A., and Goode, D.J., 2017, Effects of changes in pumping on regional groundwater-flow paths, 2005 and 2010, and areas contributing recharge to discharging wells, 1990–2010, in the vicinity of North Penn Area 7 Superfund site, Montgomery County, Pennsylvania: U.S. Geological Survey Scientific Investigations Report 2017–5014, 36 p., https://doi.org/10.3133/sir20175014.","productDescription":"Report: vi, 36 p.; Data Release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-077142","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":341375,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://dx.doi.org/10.5066/F7FN14BQ","text":"USGS data release","description":"USGS data release"},{"id":341337,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5014/sir20175014.pdf","text":"Report","size":"4.61 MB","linkFileType":{"id":1,"text":"pdf"}},{"id":341336,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5014/coverthb.jpg"}],"country":"United States","state":"Pennsylvania","county":"Montgomery County","otherGeospatial":"North Penn Area 7 Superfund Site","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.304167,\n 40.244444\n ],\n [\n -75.263333,\n 40.244444\n ],\n [\n -75.263333,\n 40.205556\n ],\n [\n -75.304167,\n 40.205556\n ],\n [\n -75.304167,\n 40.244444\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Pennsylvania Water Science Center
U.S. Geological Survey
215 Limekiln Road
New Cumberland, PA 17070
During two seasonal sampling events in spring (June) and fall (August) of 2015, the U.S. Geological Survey collected benthos (benthic invertebrates) and plankton (zooplankton and phytoplankton) at three sites each in the Waukegan Harbor Area of Concern (AOC) in Illinois and in Burns Harbor-Port of Indiana, a non-AOC comparison site in Indiana. The study was done in cooperation with the U.S. Environmental Protection Agency and the Illinois Department of Natural Resources. Samples were collected concurrently for physical and chemical parameters (specific conductance, temperature, pH, dissolved oxygen, chlorophyll-a, total and volatile suspended solids in water samples; particle size and volatile-on-ignition solids of sediment in dredge samples). The purpose of the study was to assess whether or not aquatic communities at the AOC were degraded in comparison to communities at the non-AOC, which was presumed to be less impaired than the AOC. Benthos were collected by using Hester-Dendy artificial substrate samplers and a Ponar® dredge sampler to collect composited grabs of bottom sediment; zooplankton were collected by using tows from depth to the surface with a 63-micrometer mesh plankton net; phytoplankton were collected by using whole water samples composited from set depth intervals. Aquatic communities at the AOC and the non-AOC were compared by use of univariate statistical analyses with metrics such as taxa richness (number of unique taxa), diversity, and a multimetric Index of Biotic Integrity (IBI, for artificial-substrate samples only) as well as by use of multivariate statistical analyses of taxa relative abundances.
Although benthos communities at Waukegan Harbor AOC were not rated as degraded in comparison to the non-AOC, metrics for zooplankton and phytoplankton communities did show some impairment for the 2015 sampling. Across seasons, benthos richness and diversity were significantly higher and rated as less degraded at the AOC compared to the non-AOC; however, benthos IBIs were not significantly different. Multivariate comparisons revealed that the benthos communities in the AOC and non-AOC were significantly different, but these comparisons do not address current degradation in either harbor. The dominant taxa in dredge samples were oligochaete worms in both harbors, but there were differences in the relative abundances of Dreissena as well as oligochaete and midge taxa. Although zooplankton richness and diversity in the AOC were lower and rated as more degraded in spring, these metrics were rated as less degraded in fall compared to the non-AOC, effectively balancing out so that there was no difference across seasons. Multivariate comparisons also indicated that zooplankton communities in the AOC were significantly different from those in the non-AOC for spring only but not across seasons, possibly because of lower water temperatures in spring at Waukegan Harbor than at the non-AOC site. The spring zooplankton community in Waukegan Harbor was dominated in density and biomass by the rotifer Synchaeta. Across seasons, diatom richness was significantly higher and rated as less degraded in the AOC than the non-AOC because of spring values, whereas soft algae richness was significantly lower and rated as more degraded in the AOC because of fall values. Spring richness of combined phytoplankton (soft algae and diatoms) was significantly higher in the AOC than in the non-AOC. Neither diatom diversity nor soft algae diversity differed significantly between the harbors, but combined phytoplankton diversity across seasons, if replicates were included, was significantly lower and rated as more degraded in the AOC than in the non-AOC. Multivariate tests indicated that the combined phytoplankton communities in the harbors were not significantly different across seasons. Significant differences were not found between harbors for chlorophyll-a, suspended solids, algal densities, or biomass.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20175039","collaboration":"Prepared in cooperation with the Illinois Department of Natural Resources and the U.S. Environmental Protection Agency-Great Lakes National Program Office","usgsCitation":"Scudder Eikenberry, B.C., Templar, H.A., Burns, D.J., Dobrowolski, E.G., and Schmude, K.L., 2017, Comparison of benthos and plankton for Waukegan Harbor Area of Concern, Illinois, and Burns Harbor-Port of Indiana non-Area of Concern, Indiana, in 2015: U.S. Geological Survey Scientific Investigations Report 2017–5039, 29 p., https://doi.org/10.3133/sir20175039.","productDescription":"Report: viii, 29 p.; Data Release","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-077261","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":342062,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7CN7259","text":"USGS data release","description":"USGS data release","linkHelpText":"Benthos and Plankton data for Waukegan Harbor Area of Concern, Illinois, and Burns Harbor-Port of Indiana Non-Area of Concern, Indiana, in 2015"},{"id":342020,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2017/5039/coverthb.jpg"},{"id":342021,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2017/5039/sir20175039.pdf","text":"Report","size":"4.72 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2017-5039"}],"country":"United States","state":"Illinois, Indiana","otherGeospatial":"Burns Harbor-Port of Indiana non-Area of Concern, Waukegon Harbor Area of Concern","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.827083,\n 42.374\n ],\n [\n -87.827083,\n 42.355\n ],\n [\n -87.808333,\n 42.355\n ],\n [\n -87.808333,\n 42.374\n ],\n [\n -87.827083,\n 42.374\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.163889,\n 41.649\n ],\n [\n -87.144444,\n 41.649\n ],\n [\n -87.144444,\n 41.627778\n ],\n [\n -87.163889,\n 41.627778\n ],\n [\n -87.163889,\n 41.649\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Wisconsin Water Science Center
U.S. Geological Survey
8505 Research Way
Middleton, WI 53562
There is little information on the oceanography in the National Park of American Samoa (NPSA). The transport pathways for potentially harmful constituents of land-derived runoff, as well as larvae and other planktonic organisms, are driven by nearshore circulation patterns. To evaluate the processes affecting coral reef ecosystem health, it is first necessary to understand the oceanographic processes driving nearshore circulation, residence times, exposure rates, and transport pathways. Information on how the NPSA’s natural resources may be affected by anthropogenic sources of pollution, sediment runoff, larval transport, or modifications to the marine protected areas is critical to NPSA resource managers for understanding and ultimately managing coastal and marine resources. To address this need, U.S. Geological Survey and U.S. National Park Service researchers conducted a collaborative study in 2015 to determine coastal circulation patterns and water-column properties along north-central Tutuila, American Samoa, in an area focused on NPSA’s Tutuila Unit and its coral reef ecosystem. The continuous measurements of waves, currents, tides, and water-column properties from these instrument deployments over 150 days, coupled with available meteorological measurements of wind and rainfall, provide information on nearshore circulation and the variability in these hydrodynamic properties for NPSA’s Tutuila Unit. In general, circulation was strongly driven by regional winds at longer (greater than day) timescales and by tides at shorter (less than day) timescales. Flows were primarily directed along shore, with current speeds faster offshore to the north and slower closer to shore, especially in embayments. Water-column properties exhibit strong seasonality coupled to the shift from non-trade wind season to trade wind season. During the non-trade wind season that was characterized by variable winds and larger waves in the NPSA, waters were warmer, slightly more saline, relatively less optically clear, and more stratified. When winds shifted to a more consistent trade wind pattern in the austral fall, the waters cooled and became less stratified because of decreased insolation. There are consistent spatial patterns in water column characteristics—Waters were warmer and less saline near the surface and closer to shore, especially in embayments, which tended to be more turbid, less clear, and characterized by higher chlorophyll than waters offshore. Water residence times were shorter farther offshore and longer closer to shore and in embayments, but varied spatially because of different forcing. Warmer, lower salinity, higher chlorophyll, and more turbid waters in embayments tend to reside in those locations for much greater durations, resulting in greater exposure of embayment ecosystems to those waters. This is in contrast with waters farther offshore, where the combination of shorter residence times and cooler, higher salinity water results in less exposure to land runoff. Understanding coastal circulation patterns and water-column properties in NPSA’s waters along north-central Tutuila may help to better understand how meteorological and oceanographic processes, at the regional and local scale, affect coral reef health and sustainability in this region.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20171060","usgsCitation":"Storlazzi, C.D., Cheriton, O.M., Rosenberger, K.J., Logan, J.B., and Clark, T.B., 2017, Coastal circulation and water-column properties in the National Park of American Samoa, February–July 2015: U.S. Geological Survey Open-File Report 2017–1060, 104 p., https://doi.org/10.3133/ofr20171060.","productDescription":"Report: ix, 104 p.; Data Release","numberOfPages":"113","onlineOnly":"Y","ipdsId":"IP-083344","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":341992,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2017/1060/coverthb.jpg"},{"id":342023,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7RN362H","text":"USGS data release","description":"USGS data release","linkHelpText":"Data from coastal circulation and water-column properties in the National Park of American Samoa, February–July 2015"},{"id":341994,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2017/1060/ofr20171060.pdf","text":"Report","size":"6.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2017-1060"}],"otherGeospatial":"National Park of American Samoa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -170.73646545410156,\n -14.295658268883681\n ],\n [\n -170.62454223632812,\n -14.295658268883681\n ],\n [\n -170.62454223632812,\n -14.219791816003891\n ],\n [\n -170.73646545410156,\n -14.219791816003891\n ],\n [\n -170.73646545410156,\n -14.295658268883681\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Pacific Coastal and Marine Science Center
U.S. Geological Survey
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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
Systematic conservation planning, a widely used approach to identify priority lands and waters, uses efficient, defensible, and transparent methods aimed at conserving biodiversity and ecological systems. Limited financial resources and competing land uses can be major impediments to conservation; therefore, participation of diverse stakeholders in the planning process is advantageous to help address broad-scale threats and challenges of the 21st century. Although a broad extent is needed to identify core areas and corridors for fish and wildlife populations, a fine-scale resolution is needed to manage for multiple, interconnected ecosystems. Here, we developed a conservation plan using a systematic approach to promote landscape-level conservation within the extent of the South Atlantic Landscape Conservation Cooperative. Our objective was to identify the highest-ranked 30% of lands and waters within the South Atlantic deemed necessary to conserve ecological and cultural integrity for the 10 primary ecosystems of the southeastern United States. These environments varied from terrestrial, freshwater aquatic, and marine. The planning process was driven by indicators of ecosystem integrity at a 4-ha resolution. We used the program Zonation and 28 indicators to optimize the identification of lands and waters to meet the stated objective. A novel part of our study was the prioritization of multiple ecosystems, and we discuss the advantages and disadvantages of this approach. The evaluation of indicator representation within prioritizations was a useful method to show where improvements could be made; some indicators dictated hotspots, some had a limited extent and were well represented, and others had a limited effect. Overall, we demonstrate that a broad-scale (408,276 km2 of terrestrial and 411,239 km2 of marine environments) conservation plan can be realized at a fine-scale resolution, which will allow implementation of the regional plan at a local level relevant to decision making.
","language":"English","publisher":"U.S. Fish and Wildlife Service","doi":"10.3996/062016-JFWM-044","usgsCitation":"Pickens, B.A., Mordecai, R.S., Drew, C.A., Alexander-Vaughn, L.B., Keister, A.S., Morris, H.L., and Collazo, J., 2017, Indicator-driven conservation planning across terrestrial, freshwater aquatic, and marine ecosystems of the south Atlantic, USA: Journal of Fish and Wildlife Management, v. 8, no. 1, p. 219-233, https://doi.org/10.3996/062016-JFWM-044.","productDescription":"15 p.","startPage":"219","endPage":"233","ipdsId":"IP-074523","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":469776,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/062016-jfwm-044","text":"Publisher Index Page"},{"id":349000,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -79.40917968749999,\n 37.26530995561875\n ],\n [\n -83.6279296875,\n 34.939985151560435\n ],\n [\n -85.9130859375,\n 33.486435450999885\n ],\n [\n -85.53955078125,\n 30.939924331023445\n ],\n [\n -85.1220703125,\n 29.6880527498568\n ],\n [\n -84.5947265625,\n 29.897805610155874\n ],\n [\n -84.0673828125,\n 30.107117887092357\n ],\n [\n -82.90283203125,\n 29.248063243796576\n ],\n [\n -81.27685546875,\n 29.859701442126756\n ],\n [\n -81.474609375,\n 30.581179257386985\n ],\n [\n -81.18896484375,\n 31.653381399664\n ],\n [\n -80.419921875,\n 32.39851580247402\n ],\n [\n -79.1015625,\n 33.211116472416855\n ],\n [\n -78.81591796875,\n 33.742612777346885\n ],\n [\n -78.02490234375,\n 33.87041555094183\n ],\n [\n -77.431640625,\n 34.542762387234845\n ],\n [\n -76.46484375,\n 34.813803317113155\n ],\n [\n -75.43212890625,\n 35.460669951495305\n ],\n [\n -76.26708984375,\n 37.50972584293751\n ],\n [\n -79.40917968749999,\n 37.26530995561875\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-01","publicationStatus":"PW","scienceBaseUri":"5a60fbace4b06e28e9c2345e","contributors":{"authors":[{"text":"Pickens, Bradley A.","contributorId":140926,"corporation":false,"usgs":false,"family":"Pickens","given":"Bradley","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":718509,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mordecai, Rua S.","contributorId":30328,"corporation":false,"usgs":true,"family":"Mordecai","given":"Rua","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":718510,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Drew, C. Ashton","contributorId":140953,"corporation":false,"usgs":false,"family":"Drew","given":"C.","email":"","middleInitial":"Ashton","affiliations":[],"preferred":false,"id":718511,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Alexander-Vaughn, Louise B.","contributorId":199257,"corporation":false,"usgs":false,"family":"Alexander-Vaughn","given":"Louise","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":718512,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Keister, Amy S.","contributorId":177319,"corporation":false,"usgs":false,"family":"Keister","given":"Amy","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":718513,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Morris, Hilary L.C.","contributorId":199258,"corporation":false,"usgs":false,"family":"Morris","given":"Hilary","email":"","middleInitial":"L.C.","affiliations":[],"preferred":false,"id":718514,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Collazo, Jaime A. 0000-0002-1816-7744 jaime_collazo@usgs.gov","orcid":"https://orcid.org/0000-0002-1816-7744","contributorId":173448,"corporation":false,"usgs":true,"family":"Collazo","given":"Jaime A.","email":"jaime_collazo@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":718508,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70188184,"text":"70188184 - 2017 - Snow and ice","interactions":[],"lastModifiedDate":"2020-08-20T19:26:43.019871","indexId":"70188184","displayToPublicDate":"2017-06-05T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":32,"text":"General Technical Report","active":false,"publicationSubtype":{"id":1}},"seriesNumber":"PNW-GTR-950","chapter":"3","title":"Snow and ice","docAbstract":"Monitoring the community structure and metabolic activities of cyanobacterial blooms in Upper Klamath Lake, Oregon, is critical to lake management because these blooms degrade water quality and produce toxic microcystins that are harmful to humans, domestic animals, and wildlife. Genetic tools, such as DNA fingerprinting by terminal restriction fragment length polymorphism (T-RFLP) analysis, high-throughput DNA sequencing (HTS), and real-time, quantitative polymerase chain reaction (qPCR), provide more sensitive and rapid assessments of bloom ecology than traditional techniques. The objectives of this study were (1) to characterize the microbial community at one site in Upper Klamath Lake and determine changes in the cyanobacterial community through time using T-RFLP and HTS in comparison with traditional light microscopy; (2) to determine relative abundances and changes in abundance over time of toxigenic Microcystis using qPCR; and (3) to determine relative abundances and changes in abundance over time of Aphanizomenon, Microcystis, and total cyanobacteria using qPCR. T-RFLP analysis of total cyanobacteria showed a dominance of only one or two distinct genotypes in samples from 2013, but results of HTS in 2013 and 2014 showed more variations in the bloom cycle that fit with the previous understanding of bloom dynamics in Upper Klamath Lake and indicated that potentially toxigenic Microcystis was more prevalent in 2014 than in years prior. The qPCR-estimated copy numbers of all target genes were higher in 2014 than in 2013, when microcystin concentrations also were higher. Total Microcystis density was shown with qPCR to be a better predictor of late-season increases in microcystin concentrations than the relative proportions of potentially toxigenic cells. In addition, qPCR targeting Aphanizomenon at one site in Upper Klamath Lake indicated a moderate bloom of this species (corresponding to chlorophyll a concentrations between approximately 75 and 200 micrograms per liter) from mid-June to mid-August, 2014. After August 18, the Aphanizomenon bloom was overtaken by Microcystis late in the season as microcystin concentrations peaked. Overall, results of this study showed how DNA-based, genetic methods may provide rapid and sensitive diagnoses for the presence of toxigenic cyanobacteria and that they are useful for general monitoring or ecological studies and identification of cyanobacterial community members in complex aquatic habitats. These same methods can also be used to simultaneously address spatial (horizontal and vertical) and temporal variation and under different conditions. Additionally, with some modifications, the same techniques can be applied to different sample types, including water, sediment, and tissue.
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U.S. Geological Survey
2130 SW 5th Avenue
Portland, Oregon 97201
A linked modeling approach has been undertaken to understand the impacts of climate and infrastructure on aquatic ecology and water quality in the San Francisco Bay-Delta region. The Delft3D Flexible Mesh modeling suite is used in this effort for its 3D hydrodynamics, salinity, temperature and sediment dynamics, phytoplankton and water-quality coupling infrastructure, and linkage to a habitat suitability model. The hydrodynamic model component of the suite is D-Flow FM, a new 3D unstructured finite-volume model based on the Delft3D model. In this paper, D-Flow FM is applied to the San Francisco Bay-Delta to investigate tidal, seasonal and annual dynamics of water levels, river flows and salinity under historical environmental and infrastructural conditions. The model is driven by historical winds, tides, ocean salinity, and river flows, and includes federal, state, and local freshwater withdrawals, and regional gate and barrier operations. The model is calibrated over a 9-month period, and subsequently validated for water levels, flows, and 3D salinity dynamics over a 2 year period.
Model performance was quantified using several model assessment metrics and visualized through target diagrams. These metrics indicate that the model accurately estimated water levels, flows, and salinity over wide-ranging tidal and fluvial conditions, and the model can be used to investigate detailed circulation and salinity patterns throughout the Bay-Delta. The hydrodynamics produced through this effort will be used to drive affiliated sediment, phytoplankton, and contaminant hindcast efforts and habitat suitability assessments for fish and bivalves. The modeling framework applied here will serve as a baseline to ultimately shed light on potential ecosystem change over the current century.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.ecss.2017.04.024","usgsCitation":"Martyr-Koller, R., Kernkamp, H., Van Dam, A., Mick van der Wegen, Lucas, L., Knowles, N., Jaffe, B., and Fregoso, T., 2017, Application of an unstructured 3D finite volume numerical model to flows and salinity dynamics in the San Francisco Bay-Delta: Estuarine, Coastal and Shelf Science, v. 192, p. 86-107, https://doi.org/10.1016/j.ecss.2017.04.024.","productDescription":"22 p. 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Western Branch","active":true,"usgs":true}],"preferred":true,"id":698576,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Knowles, N.","contributorId":61212,"corporation":false,"usgs":true,"family":"Knowles","given":"N.","email":"","affiliations":[],"preferred":false,"id":698581,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Jaffe, B.","contributorId":78517,"corporation":false,"usgs":true,"family":"Jaffe","given":"B.","affiliations":[],"preferred":false,"id":698582,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Fregoso, T.A.","contributorId":89371,"corporation":false,"usgs":true,"family":"Fregoso","given":"T.A.","affiliations":[],"preferred":false,"id":698583,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70188288,"text":"70188288 - 2017 - How misapplication of the hydrologic unit framework diminishes the meaning of watersheds","interactions":[],"lastModifiedDate":"2024-06-18T15:51:47.265282","indexId":"70188288","displayToPublicDate":"2017-06-05T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1547,"text":"Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"How misapplication of the hydrologic unit framework diminishes the meaning of watersheds","docAbstract":"Hydrologic units provide a convenient but problematic nationwide set of geographic polygons based on subjectively determined subdivisions of land surface areas at several hierarchical levels. The problem is that it is impossible to map watersheds, basins, or catchments of relatively equal size and cover the whole country. The hydrologic unit framework is in fact composed mostly of watersheds and pieces of watersheds. The pieces include units that drain to segments of streams, remnant areas, noncontributing areas, and coastal or frontal units that can include multiple watersheds draining to an ocean or large lake. Hence, half or more of the hydrologic units are not watersheds as the name of the framework “Watershed Boundary Dataset” implies. Nonetheless, hydrologic units and watersheds are commonly treated as synonymous, and this misapplication and misunderstanding can have some serious scientific and management consequences. We discuss some of the strengths and limitations of watersheds and hydrologic units as spatial frameworks. Using examples from the Northwest and Southeast United States, we explain how the misapplication of the hydrologic unit framework has altered the meaning of watersheds and can impair understanding associations between spatial geographic characteristics and surface water conditions.
","language":"English","publisher":"Springer","doi":"10.1007/s00267-017-0854-z","usgsCitation":"Omernik, J.M., Griffith, G.E., Hughes, R.M., Glover, J.B., and Weber, M.H., 2017, How misapplication of the hydrologic unit framework diminishes the meaning of watersheds: Environmental Management, v. 60, no. 1, p. 1-11, https://doi.org/10.1007/s00267-017-0854-z.","productDescription":"11 p.","startPage":"1","endPage":"11","ipdsId":"IP-067027","costCenters":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"links":[{"id":469773,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/6145848","text":"External Repository"},{"id":342118,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"60","issue":"1","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2017-04-04","publicationStatus":"PW","scienceBaseUri":"59366da7e4b0f6c2d0d7d603","contributors":{"authors":[{"text":"Omernik, James M.","contributorId":169740,"corporation":false,"usgs":false,"family":"Omernik","given":"James","email":"","middleInitial":"M.","affiliations":[{"id":25578,"text":"USGS -Volunteer","active":true,"usgs":false}],"preferred":false,"id":697136,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Griffith, Glenn E. 0000-0001-7966-4720 ggriffith@usgs.gov","orcid":"https://orcid.org/0000-0001-7966-4720","contributorId":4053,"corporation":false,"usgs":true,"family":"Griffith","given":"Glenn","email":"ggriffith@usgs.gov","middleInitial":"E.","affiliations":[{"id":657,"text":"Western Geographic Science Center","active":true,"usgs":true}],"preferred":true,"id":697135,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hughes, Robert M.","contributorId":113579,"corporation":false,"usgs":true,"family":"Hughes","given":"Robert","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":697137,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Glover, James B.","contributorId":192631,"corporation":false,"usgs":false,"family":"Glover","given":"James","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":697139,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Weber, Marc H.","contributorId":169742,"corporation":false,"usgs":false,"family":"Weber","given":"Marc","email":"","middleInitial":"H.","affiliations":[{"id":13529,"text":"US Environmental Protection Agency","active":true,"usgs":false}],"preferred":false,"id":697138,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70186892,"text":"cir1430 - 2017 - USGS integrated drought science","interactions":[],"lastModifiedDate":"2017-06-05T14:44:21","indexId":"cir1430","displayToPublicDate":"2017-06-05T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":307,"text":"Circular","code":"CIR","onlineIssn":"2330-5703","printIssn":"1067-084X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1430","title":"USGS integrated drought science","docAbstract":"Drought poses a serious threat to the resilience of 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
Organic compounds are removed from the atmosphere and deposited to the earth's surface via precipitation. In this study, we quantified variations of dissolved organic carbon (DOC) in precipitation during storm events at the Shale Hills Critical Zone Observatory, a forested watershed in central Pennsylvania (USA). Precipitation samples were collected consecutively throughout the storm during 13 events, which spanned a range of seasons and synoptic meteorological conditions, including a hurricane. Further, we explored factors that affect the temporal variability by considering relationships of DOC in precipitation with atmospheric and storm characteristics. Concentrations and chemical composition of DOC changed considerably during storms, with the magnitude of change within individual events being comparable or higher than the range of variation in average event composition among events. While some previous studies observed that concentrations of other elements in precipitation typically decrease over the course of individual storm events, results of this study show that DOC concentrations in precipitation are highly variable. During most storm events concentrations decreased over time, possibly as a result of washing out of the below-cloud atmosphere. However, increasing concentrations that were observed in the later stages of some storm events highlight that DOC removal with precipitation is not merely a dilution response. Increases in DOC during events could result from advection of air masses, local emissions during breaks in precipitation, or chemical transformations in the atmosphere that enhance solubility of organic carbon compounds. This work advances understanding of processes occurring during storms that are relevant to studies of atmospheric chemistry, carbon cycling, and ecosystem responses.
","language":"English","publisher":"Wiley","doi":"10.1002/hyp.11235","usgsCitation":"Iavorivska, L., Boyer, E.W., Grimm, J.W., Miller, M.P., DeWalle, D.R., Davis, K.J., and Kaye, M., 2017, Variability of dissolved organic carbon in precipitation during storms at the Shale Hills Critical Zone Observatory: Hydrological Processes, v. 31, no. 16, p. 2935-2950, https://doi.org/10.1002/hyp.11235.","productDescription":"16 p.","startPage":"2935","endPage":"2950","ipdsId":"IP-079411","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":342092,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Pennsylvania","otherGeospatial":"Stone Valley Forest","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.96344757080078,\n 40.60952174235882\n ],\n [\n -77.85358428955078,\n 40.60952174235882\n ],\n [\n -77.85358428955078,\n 40.71655807771725\n ],\n [\n -77.96344757080078,\n 40.71655807771725\n ],\n [\n -77.96344757080078,\n 40.60952174235882\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"31","issue":"16","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-28","publicationStatus":"PW","scienceBaseUri":"59366da7e4b0f6c2d0d7d615","contributors":{"authors":[{"text":"Iavorivska, Lidiia","contributorId":175230,"corporation":false,"usgs":false,"family":"Iavorivska","given":"Lidiia","email":"","affiliations":[],"preferred":false,"id":697077,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"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":697078,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Grimm, Jeffrey W.","contributorId":192616,"corporation":false,"usgs":false,"family":"Grimm","given":"Jeffrey","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":697079,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Miller, Matthew P. 0000-0002-2537-1823 mamiller@usgs.gov","orcid":"https://orcid.org/0000-0002-2537-1823","contributorId":3919,"corporation":false,"usgs":true,"family":"Miller","given":"Matthew","email":"mamiller@usgs.gov","middleInitial":"P.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":696000,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"DeWalle, David R.","contributorId":23291,"corporation":false,"usgs":true,"family":"DeWalle","given":"David","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":697080,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Davis, Kenneth J.","contributorId":192617,"corporation":false,"usgs":false,"family":"Davis","given":"Kenneth","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":697081,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kaye, Margot W.","contributorId":102031,"corporation":false,"usgs":false,"family":"Kaye","given":"Margot W.","affiliations":[],"preferred":false,"id":697082,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70186602,"text":"sir20175025 - 2017 - Evaluation of long-term trends in hydrologic and water-quality conditions, and estimation of water budgets through 2013, Chester County, Pennsylvania","interactions":[],"lastModifiedDate":"2017-07-10T14:14:42","indexId":"sir20175025","displayToPublicDate":"2017-06-02T11:15:00","publicationYear":"2017","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2017-5025","title":"Evaluation of long-term trends in hydrologic and water-quality conditions, and estimation of water budgets through 2013, Chester County, Pennsylvania","docAbstract":"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
Water wells (n = 116) overlying the Eagle Ford, Fayetteville, and Haynesville Shale hydrocarbon production areas were sampled for chemical, isotopic, and groundwater-age tracers to investigate the occurrence and sources of selected hydrocarbons in groundwater. Methane isotopes and hydrocarbon gas compositions indicate most of the methane in the wells was biogenic and produced by the CO2 reduction pathway, not from thermogenic shale gas. Two samples contained methane from the fermentation pathway that could be associated with hydrocarbon degradation based on their co-occurrence with hydrocarbons such as ethylbenzene and butane. Benzene was detected at low concentrations (<0.15 μg/L), but relatively high frequencies (2.4–13.3% of samples), in the study areas. Eight of nine samples containing benzene had groundwater ages >2500 years, indicating the benzene was from subsurface sources such as natural hydrocarbon migration or leaking hydrocarbon wells. One sample contained benzene that could be from a surface release associated with hydrocarbon production activities based on its age (10 ± 2.4 years) and proximity to hydrocarbon wells. Groundwater travel times inferred from the age-data indicate decades or longer may be needed to fully assess the effects of potential subsurface and surface releases of hydrocarbons on the wells.
","language":"English","publisher":"ACS Publications","doi":"10.1021/acs.est.7b00746","usgsCitation":"McMahon, P.B., Barlow, J.R., Engle, M.A., Belitz, K., Ging, P.B., Hunt, A.G., Jurgens, B.C., Kharaka, Y.K., Tollett, R.W., and Kresse, T.M., 2017, Methane and benzene in drinking-water wells overlying the Eagle Ford, Fayetteville, and Haynesville Shale hydrocarbon production areas: Environmental Science & Technology, v. 51, no. 12, p. 6727-6734, https://doi.org/10.1021/acs.est.7b00746.","productDescription":"8 p.","startPage":"6727","endPage":"6734","ipdsId":"IP-084127","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"links":[{"id":438307,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F77D2SC4","text":"USGS data release","linkHelpText":"Methane and benzene in drinking-water wells overlying the Eagle Ford, Fayetteville, and Haynesville Shale hydrocarbon production areas"},{"id":342035,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -100.92041015625,\n 27.6251403350933\n ],\n [\n -91.64794921875,\n 27.6251403350933\n ],\n [\n -91.64794921875,\n 35.92464453144099\n ],\n [\n -100.92041015625,\n 35.92464453144099\n ],\n [\n -100.92041015625,\n 27.6251403350933\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"51","issue":"12","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2017-05-31","publicationStatus":"PW","scienceBaseUri":"59327923e4b0e9bd0eab54f9","contributors":{"authors":[{"text":"McMahon, Peter B. 0000-0001-7452-2379 pmcmahon@usgs.gov","orcid":"https://orcid.org/0000-0001-7452-2379","contributorId":724,"corporation":false,"usgs":true,"family":"McMahon","given":"Peter","email":"pmcmahon@usgs.gov","middleInitial":"B.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":696915,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barlow, Jeannie R. 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","language":"English","publisher":"National Park Service","usgsCitation":"Baldwin, A.K., King, K., Damstra, R., Karns, B., Weller, L., Mason, S.A., Hoellein, T., and Kim, L.H., 2017, Microplastics are everywhere!: Great Lakes Network Resource Brief, 4 p.","productDescription":"4 p.","ipdsId":"IP-087253","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":342039,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":342038,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://irma.nps.gov/DataStore/Reference/Profile/2240437"}],"publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59327924e4b0e9bd0eab5504","contributors":{"authors":[{"text":"Baldwin, Austin K. 0000-0002-6027-3823 akbaldwi@usgs.gov","orcid":"https://orcid.org/0000-0002-6027-3823","contributorId":4515,"corporation":false,"usgs":true,"family":"Baldwin","given":"Austin","email":"akbaldwi@usgs.gov","middleInitial":"K.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true},{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"preferred":true,"id":696416,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"King, Kerensa","contributorId":192388,"corporation":false,"usgs":false,"family":"King","given":"Kerensa","affiliations":[],"preferred":false,"id":696417,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Damstra, Richard","contributorId":192389,"corporation":false,"usgs":false,"family":"Damstra","given":"Richard","email":"","affiliations":[],"preferred":false,"id":696418,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Karns, Byron","contributorId":192390,"corporation":false,"usgs":false,"family":"Karns","given":"Byron","affiliations":[],"preferred":false,"id":696419,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Weller, Lark","contributorId":192392,"corporation":false,"usgs":false,"family":"Weller","given":"Lark","email":"","affiliations":[],"preferred":false,"id":696420,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Mason, Sherri A.","contributorId":176172,"corporation":false,"usgs":false,"family":"Mason","given":"Sherri","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":696421,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hoellein, Timothy","contributorId":192393,"corporation":false,"usgs":false,"family":"Hoellein","given":"Timothy","email":"","affiliations":[],"preferred":false,"id":696422,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Kim, Lisa H.","contributorId":192394,"corporation":false,"usgs":false,"family":"Kim","given":"Lisa","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":696423,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70198379,"text":"70198379 - 2017 - Seasonal and spatial variabilities in northern Gulf of Alaska surface water iron concentrations driven by shelf sediment resuspension, glacial meltwater, a Yakutat eddy, and dust","interactions":[],"lastModifiedDate":"2018-08-02T11:57:27","indexId":"70198379","displayToPublicDate":"2017-06-01T11:57:20","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1836,"text":"Global Biogeochemical Cycles","active":true,"publicationSubtype":{"id":10}},"title":"Seasonal and spatial variabilities in northern Gulf of Alaska surface water iron concentrations driven by shelf sediment resuspension, glacial meltwater, a Yakutat eddy, and dust","docAbstract":"Phytoplankton growth in the Gulf of Alaska (GoA) is limited by iron (Fe), yet Fe sources are poorly constrained. We examine the temporal and spatial distributions of Fe, and its sources in the GoA, based on data from three cruises carried out in 2010 from the Copper River (AK) mouth to beyond the shelf break. April data are the first to describe late winter Fe behavior before surface water nitrate depletion began. Sediment resuspension during winter and spring storms generated high “total dissolvable Fe” (TDFe) concentrations of ~1000 nmol kg−1 along the entire continental shelf, which decreased beyond the shelf break. In July, high TDFe concentrations were similar on the shelf, but more spatially variable, and driven by low‐salinity glacial meltwater. Conversely, dissolved Fe (DFe) concentrations in surface waters were far lower and more seasonally consistent, ranging from ~4 nmol kg−1 in nearshore waters to ~0.6–1.5 nmol kg−1seaward of the shelf break during April and July, despite dramatic depletion of nitrate over that period. The reasonably constant DFe concentrations are likely maintained during the year across the shelf by complexation by strong organic ligands, coupled with ample supply of labile particulate Fe. The April DFe data can be simulated using a simple numerical model that assumes a DFe flux from shelf sediments, horizontal transport by eddy diffusion, and removal by scavenging. Given how global change is altering many processes impacting the Fe cycle, additional studies are needed to examine controls on DFe in the Gulf of Alaska.
","language":"English","publisher":"Ameican Geophysical Union","doi":"10.1002/2016GB005493","usgsCitation":"Crusius, J., Schroth, A.W., Resing, J.A., Cullen, J., and Campbell, R.W., 2017, Seasonal and spatial variabilities in northern Gulf of Alaska surface water iron concentrations driven by shelf sediment resuspension, glacial meltwater, a Yakutat eddy, and dust: Global Biogeochemical Cycles, v. 31, no. 6, p. 942-960, https://doi.org/10.1002/2016GB005493.","productDescription":"19 p.","startPage":"942","endPage":"960","ipdsId":"IP-078971","costCenters":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"links":[{"id":469779,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/2016gb005493","text":"Publisher Index Page"},{"id":438308,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7222S06","text":"USGS data release","linkHelpText":"Gulf of Alaska Shelf and Slope Iron and Nitrate data, Copper River Region, 2010"},{"id":356112,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Gulf of Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -147.5,\n 58\n ],\n [\n -143,\n 58\n ],\n [\n -143,\n 60.359564131824236\n ],\n [\n -147.5,\n 60.359564131824236\n ],\n [\n -147.5,\n 58\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"31","issue":"6","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-03","publicationStatus":"PW","scienceBaseUri":"5b6fc67ce4b0f5d57878eb84","contributors":{"authors":[{"text":"Crusius, John 0000-0003-2554-0831 jcrusius@usgs.gov","orcid":"https://orcid.org/0000-0003-2554-0831","contributorId":2155,"corporation":false,"usgs":true,"family":"Crusius","given":"John","email":"jcrusius@usgs.gov","affiliations":[{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":741299,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schroth, Andrew W.","contributorId":192042,"corporation":false,"usgs":false,"family":"Schroth","given":"Andrew","email":"","middleInitial":"W.","affiliations":[{"id":17809,"text":"University of Vermont, Burlington","active":true,"usgs":false}],"preferred":false,"id":741300,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Resing, Joseph A.","contributorId":206619,"corporation":false,"usgs":false,"family":"Resing","given":"Joseph","email":"","middleInitial":"A.","affiliations":[{"id":37351,"text":"University of Washington; Joint Institute for the Study of the Atmosphere and the Ocean","active":true,"usgs":false}],"preferred":false,"id":741301,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cullen, Jay","contributorId":206620,"corporation":false,"usgs":false,"family":"Cullen","given":"Jay","email":"","affiliations":[{"id":37352,"text":"University of Victoria; School of Earth and Ocean Sciences Victoria, B.C.","active":true,"usgs":false}],"preferred":false,"id":741302,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Campbell, Robert W.","contributorId":206621,"corporation":false,"usgs":false,"family":"Campbell","given":"Robert","email":"","middleInitial":"W.","affiliations":[{"id":37353,"text":"Prince William Sound Science Center, Cordova, AK","active":true,"usgs":false}],"preferred":false,"id":741303,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70192192,"text":"70192192 - 2017 - Reexamining ultrafiltration and solute transport in groundwater","interactions":[],"lastModifiedDate":"2017-10-23T13:33:16","indexId":"70192192","displayToPublicDate":"2017-06-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Reexamining ultrafiltration and solute transport in groundwater","docAbstract":"Geologic ultrafiltration—slowing of solutes with respect to flowing groundwater—poses a conundrum: it is consistently observed experimentally in clay-rich lithologies, but has been difficult to identify in subsurface data. Resolving this could be important for clarifying clay and shale transport properties at large scales as well as interpreting solute and isotope patterns for applications ranging from nuclear waste repository siting to understanding fluid transport in tectonically active environments. Simulations of one-dimensional NaCl transport across ultrafiltering clay membrane strata constrained by emerging data on geologic membrane properties showed different ultrafiltration effects than have often been envisioned. In relatively high-permeability advection-dominated regimes, salinity increases occurred mostly within membrane units while their effluent salinity initially fell and then rose to match solute delivery. In relatively low-permeability diffusion-dominated regimes, salinity peaked at the membrane upstream boundary and effluent salinity remained low. In both scenarios, however, only modest salinity changes (up to ∼3 g L−1) occurred because of self-limiting tendencies; membrane efficiency declines as salinity rises, and although sediment compaction increases efficiency, it is also decreases permeability and allows diffusive transport to dominate. It appears difficult for ultrafiltration to generate brines as speculated, but widespread and less extreme ultrafiltration effects in the subsurface could be unrecognized. Conditions needed for ultrafiltration are present in settings that include topographically-driven flow systems, confined aquifer systems subjected to injection or withdrawal, compacting basins, and accretionary complexes.
","language":"English","publisher":"American Geophysical Union","doi":"10.1002/2017WR020492","usgsCitation":"Neuzil, C.E., and Person, M., 2017, Reexamining ultrafiltration and solute transport in groundwater: Water Resources Research, v. 53, no. 6, p. 4922-4941, https://doi.org/10.1002/2017WR020492.","productDescription":"20 p.","startPage":"4922","endPage":"4941","ipdsId":"IP-086146","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":347123,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"53","issue":"6","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-16","publicationStatus":"PW","scienceBaseUri":"59eeffa7e4b0220bbd988f9a","contributors":{"authors":[{"text":"Neuzil, Christopher E. 0000-0003-2022-4055 ceneuzil@usgs.gov","orcid":"https://orcid.org/0000-0003-2022-4055","contributorId":2322,"corporation":false,"usgs":true,"family":"Neuzil","given":"Christopher","email":"ceneuzil@usgs.gov","middleInitial":"E.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":714671,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Person, Mark","contributorId":197964,"corporation":false,"usgs":false,"family":"Person","given":"Mark","email":"","affiliations":[],"preferred":false,"id":714672,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70192187,"text":"70192187 - 2017 - Analyzing cloud base at local and regional scales to understand tropical montane cloud forest vulnerability to climate change","interactions":[],"lastModifiedDate":"2017-10-23T13:41:14","indexId":"70192187","displayToPublicDate":"2017-06-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":922,"text":"Atmospheric Chemistry and Physics","active":true,"publicationSubtype":{"id":10}},"title":"Analyzing cloud base at local and regional scales to understand tropical montane cloud forest vulnerability to climate change","docAbstract":"The degree to which cloud immersion provides water in addition to rainfall, suppresses transpiration, and sustains tropical montane cloud forests (TMCFs) during rainless periods is not well understood. Climate and land use changes represent a threat to these forests if cloud base altitude rises as a result of regional warming or deforestation. To establish a baseline for quantifying future changes in cloud base, we installed a ceilometer at 100 m altitude in the forest upwind of the TMCF that occupies an altitude range from ∼ 600 m to the peaks at 1100 m in the Luquillo Mountains of eastern Puerto Rico. Airport Automated Surface Observing System (ASOS) ceilometer data, radiosonde data, and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite data were obtained to investigate seasonal cloud base dynamics, altitude of the trade-wind inversion (TWI), and typical cloud thickness for the surrounding Caribbean region. Cloud base is rarely quantified near mountains, so these results represent a first look at seasonal and diurnal cloud base dynamics for the TMCF. From May 2013 to August 2016, cloud base was lowest during the midsummer dry season, and cloud bases were lower than the mountaintops as often in the winter dry season as in the wet seasons. The lowest cloud bases most frequently occurred at higher elevation than 600 m, from 740 to 964 m. The Luquillo forest low cloud base altitudes were higher than six other sites in the Caribbean by ∼ 200–600 m, highlighting the importance of site selection to measure topographic influence on cloud height. Proximity to the oceanic cloud system where shallow cumulus clouds are seasonally invariant in altitude and cover, along with local trade-wind orographic lifting and cloud formation, may explain the dry season low clouds. The results indicate that climate change threats to low-elevation TMCFs are not limited to the dry season; changes in synoptic-scale weather patterns that increase frequency of drought periods during the wet seasons (periods of higher cloud base) may also impact ecosystem health.
","language":"English","publisher":"European Geophysical Union","doi":"10.5194/acp-17-7245-2017","usgsCitation":"Van Beusekom, A.E., Gonzalez, G., and Scholl, M.A., 2017, Analyzing cloud base at local and regional scales to understand tropical montane cloud forest vulnerability to climate change: Atmospheric Chemistry and Physics, v. 17, no. 11, p. 7245-7259, https://doi.org/10.5194/acp-17-7245-2017.","productDescription":"15 p.","startPage":"7245","endPage":"7259","ipdsId":"IP-084476","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":469802,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/acp-17-7245-2017","text":"Publisher Index Page"},{"id":347125,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Luquillo Mountains, Puerto Rico","volume":"17","issue":"11","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-16","publicationStatus":"PW","scienceBaseUri":"59eeffa8e4b0220bbd988f9c","contributors":{"authors":[{"text":"Van Beusekom, Ashley E.","contributorId":197950,"corporation":false,"usgs":false,"family":"Van Beusekom","given":"Ashley","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":714640,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gonzalez, Grizelle","contributorId":191117,"corporation":false,"usgs":false,"family":"Gonzalez","given":"Grizelle","email":"","affiliations":[],"preferred":false,"id":714641,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Scholl, Martha A. 0000-0001-6994-4614 mascholl@usgs.gov","orcid":"https://orcid.org/0000-0001-6994-4614","contributorId":1920,"corporation":false,"usgs":true,"family":"Scholl","given":"Martha","email":"mascholl@usgs.gov","middleInitial":"A.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":714639,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70194726,"text":"70194726 - 2017 - A critical review of the postulated role of the non-essential amino acid, β-N-methylamino-L-alanine, in neurodegenerative disease in humans","interactions":[],"lastModifiedDate":"2017-12-14T12:25:54","indexId":"70194726","displayToPublicDate":"2017-06-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2484,"text":"Journal of Toxicology and Environmental Health, Part B: Critical Reviews","active":true,"publicationSubtype":{"id":10}},"title":"A critical review of the postulated role of the non-essential amino acid, β-N-methylamino-L-alanine, in neurodegenerative disease in humans","docAbstract":"The compound BMAA (β-N-methylamino-L-alanine) has been postulated to play a significant role in four serious neurological human diseases: Amyotrophic Lateral Sclerosis/Parkinsonism Dementia Complex (ALS/PDC) found on Guam, and ALS, Parkinsonism, and dementia that occur globally. ALS/PDC with symptoms of all three diseases first came to the attention of the scientific community during and after World War II. It was initially associated with cycad flour used for food because BMAA is a product of symbiotic cycad root-dwelling cyanobacteria. Human consumption of flying foxes that fed on cycad seeds was later suggested as a source of BMAA on Guam and a cause of ALS/PDC. Subsequently, the hypothesis was expanded to include a causative role for BMAA in other neurodegenerative diseases including Alzheimer’s disease (AD) through exposures attributed to proximity to freshwaters and/or consumption of seafood due to its purported production by most species of cyanobacteria. The hypothesis that BMAA is the critical factor in the genesis of these neurodegenerative diseases received considerable attention in the medical, scientific, and public arenas. This review examines the history of ALS/PDC and the BMAA-human disease hypotheses; similarities and differences between ALS/PDC and the other diseases with similar symptomologies; the relationship of ALS/PDC to other similar diseases, studies of BMAA-mediated effects in lab animals, inconsistencies and data gaps in the hypothesis; and other compounds and agents that were suggested as the cause of ALS/PDC on Guam. The review concludes that the hypothesis of a causal BMAA neurodegenerative disease relationship is not supported by existing data.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/10937404.2017.1297592","usgsCitation":"Chernoff, N., Hill, D.J., Diggs, D.L., Faison, B.D., Francis, B.M., Lang, J.R., Larue, M.M., Le, T., Loftin, K.A., Lugo, J.N., Schmid, J.E., and Winnik, W.W., 2017, A critical review of the postulated role of the non-essential amino acid, β-N-methylamino-L-alanine, in neurodegenerative disease in humans: Journal of Toxicology and Environmental Health, Part B: Critical Reviews, v. 20, no. 4, p. 183-229, https://doi.org/10.1080/10937404.2017.1297592.","productDescription":"47 p.","startPage":"183","endPage":"229","ipdsId":"IP-085335","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":469809,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/6503681","text":"External Repository"},{"id":349986,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"20","issue":"4","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-09","publicationStatus":"PW","scienceBaseUri":"5a60fbbce4b06e28e9c2351d","contributors":{"authors":[{"text":"Chernoff, Neil","contributorId":25859,"corporation":false,"usgs":true,"family":"Chernoff","given":"Neil","email":"","affiliations":[],"preferred":false,"id":725024,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hill, D. J.","contributorId":147377,"corporation":false,"usgs":false,"family":"Hill","given":"D.","email":"","middleInitial":"J.","affiliations":[{"id":13344,"text":"University of Leeds","active":true,"usgs":false}],"preferred":false,"id":725025,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Diggs, D. L.","contributorId":201338,"corporation":false,"usgs":false,"family":"Diggs","given":"D.","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":725026,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Faison, B. D.","contributorId":201339,"corporation":false,"usgs":false,"family":"Faison","given":"B.","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":725027,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Francis, B. M.","contributorId":201340,"corporation":false,"usgs":false,"family":"Francis","given":"B.","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":725028,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Lang, J. R.","contributorId":201341,"corporation":false,"usgs":false,"family":"Lang","given":"J.","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":725029,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Larue, M. M.","contributorId":201342,"corporation":false,"usgs":false,"family":"Larue","given":"M.","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":725030,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Le, T.-T.","contributorId":201343,"corporation":false,"usgs":false,"family":"Le","given":"T.-T.","email":"","affiliations":[],"preferred":false,"id":725031,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Loftin, Keith A. 0000-0001-5291-876X kloftin@usgs.gov","orcid":"https://orcid.org/0000-0001-5291-876X","contributorId":868,"corporation":false,"usgs":true,"family":"Loftin","given":"Keith","email":"kloftin@usgs.gov","middleInitial":"A.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":725023,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Lugo, J. N.","contributorId":201344,"corporation":false,"usgs":false,"family":"Lugo","given":"J.","email":"","middleInitial":"N.","affiliations":[],"preferred":false,"id":725032,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Schmid, J. E.","contributorId":201345,"corporation":false,"usgs":false,"family":"Schmid","given":"J.","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":725033,"contributorType":{"id":1,"text":"Authors"},"rank":11},{"text":"Winnik, W. W.","contributorId":201346,"corporation":false,"usgs":false,"family":"Winnik","given":"W.","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":725034,"contributorType":{"id":1,"text":"Authors"},"rank":12}]}} ,{"id":70192098,"text":"70192098 - 2017 - Calculation of in situ acoustic sediment attenuation using off-the-shelf horizontal ADCPs in low concentration settings","interactions":[],"lastModifiedDate":"2017-10-23T15:30:30","indexId":"70192098","displayToPublicDate":"2017-06-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Calculation of in situ acoustic sediment attenuation using off-the-shelf horizontal ADCPs in low concentration settings","docAbstract":"The use of “off-the-shelf” acoustic Doppler velocity profilers (ADCPs) to estimate suspended sediment concentration and grain-size in rivers requires robust methods to estimate sound attenuation by suspended sediment. Theoretical estimates of sediment attenuation require a priori knowledge of the concentration and grain-size distribution (GSD), making the method impractical to apply in routine monitoring programs. In situ methods use acoustic backscatter profile slope to estimate sediment attenuation, and are a more attractive option. However, the performance of in situ sediment attenuation methods has not been extensively compared to theoretical methods. We used three collocated horizontally mounted ADCPs in the Fraser River at Mission, British Columbia and 298 observations of concentration and GSD along the acoustic beams to calculate theoretical and in situ sediment attenuation. Conversion of acoustic intensity from counts to decibels is influenced by the instrument noise floor, which affects the backscatter profile shape and therefore in situ attenuation. We develop a method that converts counts to decibels to maximize profile length, which is useful in rivers where cross-channel acoustic profile penetration is a fraction of total channel width. Nevertheless, the agreement between theoretical and in situ attenuation is poor at low concentrations because cross-stream gradients in concentration, sediment size or GSD can develop, which affect the backscatter profiles. We establish threshold concentrations below which in situ attenuation is unreliable in Fraser River. Our results call for careful examination of cross-stream changes in suspended sediment characteristics and acoustic profiles across a range of flows before in situ attenuation methods are applied in river monitoring programs.
","language":"English","publisher":"AGU","doi":"10.1002/2016WR019695","usgsCitation":"Haught, D., Venditti, J., and Wright, S., 2017, Calculation of in situ acoustic sediment attenuation using off-the-shelf horizontal ADCPs in low concentration settings: Water Resources Research, v. 53, no. 6, p. 5017-5037, https://doi.org/10.1002/2016WR019695.","productDescription":"21 p.","startPage":"5017","endPage":"5037","ipdsId":"IP-087639","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":347160,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"53","issue":"6","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2017-06-22","publicationStatus":"PW","scienceBaseUri":"59eeffa8e4b0220bbd988fa3","contributors":{"authors":[{"text":"Haught, Dan","contributorId":149407,"corporation":false,"usgs":false,"family":"Haught","given":"Dan","affiliations":[],"preferred":false,"id":714226,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Venditti, Jeremy G. 0000-0002-2876-4251","orcid":"https://orcid.org/0000-0002-2876-4251","contributorId":197757,"corporation":false,"usgs":false,"family":"Venditti","given":"Jeremy G.","affiliations":[],"preferred":false,"id":714227,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wright, Scott 0000-0002-0387-5713 sawright@usgs.gov","orcid":"https://orcid.org/0000-0002-0387-5713","contributorId":1536,"corporation":false,"usgs":true,"family":"Wright","given":"Scott","email":"sawright@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":714225,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70192977,"text":"70192977 - 2017 - Comparison of burbot populations across adjacent native and introduced ranges","interactions":[],"lastModifiedDate":"2017-11-06T16:07:49","indexId":"70192977","displayToPublicDate":"2017-06-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":868,"text":"Aquatic Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Comparison of burbot populations across adjacent native and introduced ranges","docAbstract":"Introduced species are a threat to biodiversity. Burbot, Lota lota, a fish native to the Wind River Drainage, Wyoming and a species of conservation concern, have been introduced into the nearby Green River Drainage, Wyoming, where they are having negative effects on native fish species. We compared these native and introduced burbot populations to evaluate potential mechanisms that could be leading to introduction success. We examined genetic ancestry, physical habitat characteristics, community composition, and burbot abundance, relative weight, and size structure between the native and introduced range to elucidate potential differences. The origin of introduced burbot in Flaming Gorge Reservoir is most likely Boysen Reservoir and several nearby river populations in the native Wind River Drainage. Burbot populations did not show consistent differences in abundance, size structure, and relative weight between drainages, though Fontenelle Reservoir, in the introduced drainage, had the largest burbot. There were also limited environmental and community composition differences, though reservoirs in the introduced drainage had lower species richness and a higher percentage of non-native fish species than the reservoir in the native drainage. Burbot introduction in the Green River Drainage is likely an example of reservoir construction creating habitat with suitable environmental conditions to allow a southwards range expansion of this cold-water species. An understanding of the factors driving introduction success can allow better management of species, both in their introduced and native range.
","language":"English","publisher":"REABIC","doi":"10.3391/ai.2017.12.2.12","usgsCitation":"Walters, A.W., Mandeville, E.G., Saunders, W.C., Gerrity, P.C., Skorupski, J.A., Underwood, Z.E., and Gardunio, E.I., 2017, Comparison of burbot populations across adjacent native and introduced ranges: Aquatic Invasions, v. 12, no. 2, p. 251-262, https://doi.org/10.3391/ai.2017.12.2.12.","productDescription":"12 p.","startPage":"251","endPage":"262","ipdsId":"IP-077779","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":469806,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3391/ai.2017.12.2.12","text":"Publisher Index Page"},{"id":348305,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Wyoming","otherGeospatial":"Green River, Wind River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -110.335693359375,\n 41.000629848685385\n ],\n [\n -107.89672851562499,\n 41.000629848685385\n ],\n [\n -107.89672851562499,\n 43.671844983221604\n ],\n [\n -110.335693359375,\n 43.671844983221604\n ],\n [\n -110.335693359375,\n 41.000629848685385\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"12","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a07e8dde4b09af898c8cbc3","contributors":{"authors":[{"text":"Walters, Annika W. 0000-0002-8638-6682 awalters@usgs.gov","orcid":"https://orcid.org/0000-0002-8638-6682","contributorId":4190,"corporation":false,"usgs":true,"family":"Walters","given":"Annika","email":"awalters@usgs.gov","middleInitial":"W.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":717511,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mandeville, Elizabeth G.","contributorId":166947,"corporation":false,"usgs":false,"family":"Mandeville","given":"Elizabeth","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":720763,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Saunders, W. Carl","contributorId":46883,"corporation":false,"usgs":true,"family":"Saunders","given":"W.","email":"","middleInitial":"Carl","affiliations":[],"preferred":false,"id":720764,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gerrity, Paul C.","contributorId":104198,"corporation":false,"usgs":true,"family":"Gerrity","given":"Paul","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":720765,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Skorupski, Joseph A.","contributorId":200037,"corporation":false,"usgs":false,"family":"Skorupski","given":"Joseph","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":720766,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Underwood, Zachary E.","contributorId":166946,"corporation":false,"usgs":false,"family":"Underwood","given":"Zachary","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":720767,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gardunio, Eric I.","contributorId":200038,"corporation":false,"usgs":false,"family":"Gardunio","given":"Eric","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":720768,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70192506,"text":"70192506 - 2017 - Effects of temperature, total dissolved solids, and total suspended solids on survival and development rate of larval Arkansas River Shiner","interactions":[],"lastModifiedDate":"2017-10-26T10:30:43","indexId":"70192506","displayToPublicDate":"2017-06-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Effects of temperature, total dissolved solids, and total suspended solids on survival and development rate of larval Arkansas River Shiner","docAbstract":"Decreases in the abundance and diversity of stream fishes in the North American Great Plains have been attributed to habitat fragmentation, altered hydrological and temperature regimes, and elevated levels of total dissolved solids and total suspended solids. Pelagic-broadcast spawning cyprinids, such as the Arkansas River Shiner Notropis girardi, may be particularly vulnerable to these changing conditions because of their reproductive strategy. Our objectives were to assess the effects of temperature, total dissolved solids, and total suspended solids on the developmental and survival rates of Arkansas River Shiner larvae. Results suggest temperature had the greatest influence on the developmental rate of Arkansas River Shiner larvae. However, embryos exposed to the higher levels of total dissolved solids and total suspended solids reached developmental stages earlier than counterparts at equivalent temperatures. Although this rapid development may be beneficial in fragmented waters, our data suggest it may be associated with lower survival rates. Furthermore, those embryos incubating at high temperatures, or in high levels of total dissolved solids and total suspended solids resulted in less viable embryos and larvae than those incubating in all other temperature, total dissolved solid, and total suspended solid treatment groups. As the Great Plains ecoregion continues to change, these results may assist in understanding reasons for past extirpations and future extirpation threats as well as predict stream reaches capable of sustaining Arkansas River Shiners and other species with similar early life-history strategies.
","language":"English","publisher":"Scientific Journals","doi":"10.3996/112015-JFWM-111","usgsCitation":"Mueller, J.S., Grabowski, T.B., Brewer, S.K., and Worthington, T.A., 2017, Effects of temperature, total dissolved solids, and total suspended solids on survival and development rate of larval Arkansas River Shiner: Journal of Fish and Wildlife Management, v. 8, no. 1, p. 79-88, https://doi.org/10.3996/112015-JFWM-111.","productDescription":"10 p.","startPage":"79","endPage":"88","ipdsId":"IP-052617","costCenters":[{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"links":[{"id":469796,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.repository.cam.ac.uk/handle/1810/290516","text":"External Repository"},{"id":347437,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"8","issue":"1","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2017-01-01","publicationStatus":"PW","scienceBaseUri":"5a07e8dee4b09af898c8cbcd","contributors":{"authors":[{"text":"Mueller, Julia S.","contributorId":176241,"corporation":false,"usgs":false,"family":"Mueller","given":"Julia","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":716099,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Grabowski, Timothy B. 0000-0001-9763-8948 tgrabowski@usgs.gov","orcid":"https://orcid.org/0000-0001-9763-8948","contributorId":4178,"corporation":false,"usgs":true,"family":"Grabowski","given":"Timothy","email":"tgrabowski@usgs.gov","middleInitial":"B.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":716093,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Brewer, Shannon K. 0000-0002-1537-3921 skbrewer@usgs.gov","orcid":"https://orcid.org/0000-0002-1537-3921","contributorId":2252,"corporation":false,"usgs":true,"family":"Brewer","given":"Shannon","email":"skbrewer@usgs.gov","middleInitial":"K.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":716094,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Worthington, Thomas A.","contributorId":140662,"corporation":false,"usgs":false,"family":"Worthington","given":"Thomas","email":"","middleInitial":"A.","affiliations":[{"id":7249,"text":"Oklahoma State University","active":true,"usgs":false}],"preferred":false,"id":716100,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70193288,"text":"70193288 - 2017 - Sensitivity analysis of a coupled hydrodynamic-vegetation model using the effectively subsampled quadratures method ","interactions":[],"lastModifiedDate":"2017-12-11T13:10:19","indexId":"70193288","displayToPublicDate":"2017-06-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1818,"text":"Geoscientific Model Development","active":true,"publicationSubtype":{"id":10}},"title":"Sensitivity analysis of a coupled hydrodynamic-vegetation model using the effectively subsampled quadratures method ","docAbstract":"Coastal hydrodynamics can be greatly affected by the presence of submerged aquatic vegetation. The effect of vegetation has been incorporated into the Coupled-Ocean-Atmosphere-Wave-Sediment Transport (COAWST) Modeling System. The vegetation implementation includes the plant-induced three-dimensional drag, in-canopy wave-induced streaming, and the production of turbulent kinetic energy by the presence of vegetation. In this study, we evaluate the sensitivity of the flow and wave dynamics to vegetation parameters using Sobol' indices and a least squares polynomial approach referred to as Effective Quadratures method. This method reduces the number of simulations needed for evaluating Sobol' indices and provides a robust, practical, and efficient approach for the parameter sensitivity analysis. The evaluation of Sobol' indices shows that kinetic energy, turbulent kinetic energy, and water level changes are affected by plant density, height, and to a certain degree, diameter. Wave dissipation is mostly dependent on the variation in plant density. Performing sensitivity analyses for the vegetation module in COAWST provides guidance for future observational and modeling work to optimize efforts and reduce exploration of parameter space.
","language":"English","publisher":"EGU","doi":"10.5194/gmd-2017-107","usgsCitation":"Kalra, T., Aretxabaleta, A., Seshadri, P., Ganju, N., and Beudin, A., 2017, Sensitivity analysis of a coupled hydrodynamic-vegetation model using the effectively subsampled quadratures method : Geoscientific Model Development, v. 10, p. 4511-4523, https://doi.org/10.5194/gmd-2017-107.","productDescription":"13 p.","startPage":"4511","endPage":"4523","ipdsId":"IP-088722","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":482065,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/gmd-2017-107","text":"Publisher Index Page"},{"id":348613,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"10","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5a07e8d2e4b09af898c8cbb7","contributors":{"authors":[{"text":"Kalra, Tarandeep S. 0000-0001-5468-248X tkalra@usgs.gov","orcid":"https://orcid.org/0000-0001-5468-248X","contributorId":178820,"corporation":false,"usgs":true,"family":"Kalra","given":"Tarandeep S.","email":"tkalra@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":718555,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aretxabaleta, Alfredo 0000-0002-9914-8018 aaretxabaleta@usgs.gov","orcid":"https://orcid.org/0000-0002-9914-8018","contributorId":140090,"corporation":false,"usgs":true,"family":"Aretxabaleta","given":"Alfredo","email":"aaretxabaleta@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":718556,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Seshadri, Pranay","contributorId":199287,"corporation":false,"usgs":false,"family":"Seshadri","given":"Pranay","email":"","affiliations":[{"id":27136,"text":"University of Cambridge","active":true,"usgs":false}],"preferred":false,"id":718558,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ganju, Neil K. 0000-0002-1096-0465 nganju@usgs.gov","orcid":"https://orcid.org/0000-0002-1096-0465","contributorId":1314,"corporation":false,"usgs":true,"family":"Ganju","given":"Neil K.","email":"nganju@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":718559,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Beudin, Alexis 0000-0001-9525-9450 abeudin@usgs.gov","orcid":"https://orcid.org/0000-0001-9525-9450","contributorId":178819,"corporation":false,"usgs":true,"family":"Beudin","given":"Alexis","email":"abeudin@usgs.gov","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":721678,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70192992,"text":"70192992 - 2017 - A land cover change detection and classification protocol for updating Alaska NLCD 2001 to 2011","interactions":[],"lastModifiedDate":"2018-03-08T13:03:59","indexId":"70192992","displayToPublicDate":"2017-06-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3254,"text":"Remote Sensing of Environment","printIssn":"0034-4257","active":true,"publicationSubtype":{"id":10}},"title":"A land cover change detection and classification protocol for updating Alaska NLCD 2001 to 2011","docAbstract":"Monitoring and mapping land cover changes are important ways to support evaluation of the status and transition of ecosystems. The Alaska National Land Cover Database (NLCD) 2001 was the first 30-m resolution baseline land cover product of the entire state derived from circa 2001 Landsat imagery and geospatial ancillary data. We developed a comprehensive approach named AKUP11 to update Alaska NLCD from 2001 to 2011 and provide a 10-year cyclical update of the state's land cover and land cover changes. Our method is designed to characterize the main land cover changes associated with different drivers, including the conversion of forests to shrub and grassland primarily as a result of wildland fire and forest harvest, the vegetation successional processes after disturbance, and changes of surface water extent and glacier ice/snow associated with weather and climate changes. For natural vegetated areas, a component named AKUP11-VEG was developed for updating the land cover that involves four major steps: 1) identify the disturbed and successional areas using Landsat images and ancillary datasets; 2) update the land cover status for these areas using a SKILL model (System of Knowledge-based Integrated-trajectory Land cover Labeling); 3) perform decision tree classification; and 4) develop a final land cover and land cover change product through the postprocessing modeling. For water and ice/snow areas, another component named AKUP11-WIS was developed for initial land cover change detection, removal of the terrain shadow effects, and exclusion of ephemeral snow changes using a 3-year MODIS snow extent dataset from 2010 to 2012. The overall approach was tested in three pilot study areas in Alaska, with each area consisting of four Landsat image footprints. The results from the pilot study show that the overall accuracy in detecting change and no-change is 90% and the overall accuracy of the updated land cover label for 2011 is 86%. The method provided a robust, consistent, and efficient means for capturing major disturbance events and updating land cover for Alaska. The method has subsequently been applied to generate the land cover and land cover change products for the entire state of Alaska.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.rse.2017.04.021","usgsCitation":"Jin, S., Yang, L., Zhu, Z., and Homer, C.G., 2017, A land cover change detection and classification protocol for updating Alaska NLCD 2001 to 2011: Remote Sensing of Environment, v. 195, p. 44-55, https://doi.org/10.1016/j.rse.2017.04.021.","productDescription":"12 p.","startPage":"44","endPage":"55","ipdsId":"IP-082390","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":347728,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","volume":"195","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59f83a36e4b063d5d30980dc","contributors":{"authors":[{"text":"Jin, Suming 0000-0001-9919-8077 sjin@usgs.gov","orcid":"https://orcid.org/0000-0001-9919-8077","contributorId":4397,"corporation":false,"usgs":true,"family":"Jin","given":"Suming","email":"sjin@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":717548,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Yang, Limin 0000-0002-2843-6944 lyang@usgs.gov","orcid":"https://orcid.org/0000-0002-2843-6944","contributorId":4305,"corporation":false,"usgs":true,"family":"Yang","given":"Limin","email":"lyang@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":717551,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zhu, Zhe 0000-0001-8283-6407 zhezhu@usgs.gov","orcid":"https://orcid.org/0000-0001-8283-6407","contributorId":168792,"corporation":false,"usgs":true,"family":"Zhu","given":"Zhe","email":"zhezhu@usgs.gov","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":717550,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Homer, Collin G. 0000-0003-4755-8135 homer@usgs.gov","orcid":"https://orcid.org/0000-0003-4755-8135","contributorId":2262,"corporation":false,"usgs":true,"family":"Homer","given":"Collin","email":"homer@usgs.gov","middleInitial":"G.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true},{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"preferred":true,"id":717549,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70192074,"text":"70192074 - 2017 - Sediment source fingerprinting as an aid to catchment management: A review of the current state of knowledge and a methodological decision-tree for end-users","interactions":[],"lastModifiedDate":"2017-10-26T09:44:47","indexId":"70192074","displayToPublicDate":"2017-06-01T00:00:00","publicationYear":"2017","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2258,"text":"Journal of Environmental Management","active":true,"publicationSubtype":{"id":10}},"title":"Sediment source fingerprinting as an aid to catchment management: A review of the current state of knowledge and a methodological decision-tree for end-users","docAbstract":"The growing awareness of the environmental significance of fine-grained sediment fluxes through catchment systems continues to underscore the need for reliable information on the principal sources of this material. Source estimates are difficult to obtain using traditional monitoring techniques, but sediment source fingerprinting or tracing procedures, have emerged as a potentially valuable alternative. Despite the rapidly increasing numbers of studies reporting the use of sediment source fingerprinting, several key challenges and uncertainties continue to hamper consensus among the international scientific community on key components of the existing methodological procedures. Accordingly, this contribution reviews and presents recent developments for several key aspects of fingerprinting, namely: sediment source classification, catchment source and target sediment sampling, tracer selection, grain size issues, tracer conservatism, source apportionment modelling, and assessment of source predictions using artificial mixtures. Finally, a decision-tree representing the current state of knowledge is presented, to guide end-users in applying the fingerprinting approach.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.jenvman.2016.09.075","usgsCitation":"Collins, A., Pulley, S., Foster, I., Gellis, A.C., Porto, P., and Horowitz, A., 2017, Sediment source fingerprinting as an aid to catchment management: A review of the current state of knowledge and a methodological decision-tree for end-users: Journal of Environmental Management, v. 194, p. 86-108, https://doi.org/10.1016/j.jenvman.2016.09.075.","productDescription":"23 p.","startPage":"86","endPage":"108","ipdsId":"IP-077303","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"links":[{"id":469789,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jenvman.2016.09.075","text":"Publisher Index Page"},{"id":347325,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"194","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59f1a2a5e4b0220bbd9d9f4f","contributors":{"authors":[{"text":"Collins, A.L","contributorId":197685,"corporation":false,"usgs":false,"family":"Collins","given":"A.L","affiliations":[],"preferred":false,"id":714084,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Pulley, S.","contributorId":197686,"corporation":false,"usgs":false,"family":"Pulley","given":"S.","email":"","affiliations":[],"preferred":false,"id":714085,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Foster, I.D.L","contributorId":197687,"corporation":false,"usgs":false,"family":"Foster","given":"I.D.L","affiliations":[],"preferred":false,"id":714086,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Gellis, Allen C. 0000-0002-3449-2889 agellis@usgs.gov","orcid":"https://orcid.org/0000-0002-3449-2889","contributorId":197684,"corporation":false,"usgs":true,"family":"Gellis","given":"Allen","email":"agellis@usgs.gov","middleInitial":"C.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":714083,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Porto, P.","contributorId":197688,"corporation":false,"usgs":false,"family":"Porto","given":"P.","email":"","affiliations":[],"preferred":false,"id":714087,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Horowitz, A.J.","contributorId":197689,"corporation":false,"usgs":false,"family":"Horowitz","given":"A.J.","email":"","affiliations":[],"preferred":false,"id":714088,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ]}