The Chicago Area Waterway System (CAWS) consists of a combination of natural and manmade channels that form an interconnected navigable waterway of approximately 90-plus miles in the metropolitan Chicago area of northeastern Illinois. The CAWS serves the area as the primary drainage feature, a waterway transportation corridor, and recreational waterbody. The CAWS was constructed by the Metropolitan Water Reclamation District of Greater Chicago (MWRDGC). Completion of the Chicago Sanitary and Ship Canal (initial portion of the CAWS) in 1900 breached a low drainage divide and resulted in a diversion of water from the Lake Michigan Basin. A U.S. Supreme Court decree (Consent Decree 388 U.S. 426 [1967] Modified 449 U.S. 48 [1980]) limits the annual diversion from Lake Michigan. While the State of Illinois is responsible for the diversion, the MWRDGC regulates and maintains water level and water quality within the CAWS by using several waterway control structures. The operation and control of water levels in the CAWS results in a very complex hydraulic setting characterized by highly unsteady flows. The complexity leads to unique gaging requirements and monitoring issues. This report provides a general discussion of the complex hydraulic setting within the CAWS and quantifies this information with examples of data collected at a range of flow conditions from U.S. Geological Survey streamflow gaging stations and other locations within the CAWS. Monitoring to address longstanding issues of waterway operation, as well as current (2014) emerging issues such as wastewater disinfection and the threat from aquatic invasive species, is included in the discussion.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155115","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency– Great Lakes Restoration Initiative","usgsCitation":"Duncker, J.J. and Johnson, K.K., 2015, Hydrology of and current monitoring issues for the Chicago Area Waterway\nSystem, northeastern Illinois: U.S. Geological Survey Scientific Investigations Report 2015–5115, 48 p., https://dx.doi.\norg/10.3133/sir20155115.","productDescription":"vi, 48 p.","numberOfPages":"58","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-038442","costCenters":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true}],"links":[{"id":310678,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5115/sir20155115.pdf","text":"Report","size":"9.07 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5115"},{"id":310677,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5115/coverthb.jpg"}],"country":"United States","state":"Illinois","city":"Chicago","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -88.099365234375,\n 41.57847058443442\n ],\n [\n -88.099365234375,\n 42.18579390537848\n ],\n [\n -87.47039794921874,\n 42.18579390537848\n ],\n [\n -87.47039794921874,\n 41.57847058443442\n ],\n [\n -88.099365234375,\n 41.57847058443442\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Illinois Water Science Center
U.S. Geological Survey
405 N. Goodwin Avenue
Urbana, IL 61801
http://il.water.usgs.gov/
About 35 million years ago, during late Eocene time, a 2-mile-wide asteroid or comet smashed into Earth in what is now the lower Chesapeake Bay in Virginia. The oceanic impact vaporized, melted, fractured, and (or) displaced the target rocks and sediments and sent billions of tons of water, sediments, and rocks into the air. Glassy particles of solidified melt rock rained down as far away as Texas and the Caribbean. Models suggest that even up to 50 miles away the velocity of the intensely hot air blast was greater than 1,500 miles per hour, and ground shaking was equivalent to an earthquake greater than magnitude 8.0 on the Richter scale. Large tsunamis affected most of the North Atlantic basin. The Chesapeake Bay impact structure is among the 20 largest known impact structures on Earth.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20153071","usgsCitation":"Powars, D.S., Edwards, L.E., Gohn, G.S., and Horton, J.W., Jr., 2015, The Chesapeake Bay impact structure: U.S. Geological Survey Fact Sheet 2015–3071, 2 p., https://dx.doi.org/10.3133/fs20153071.","productDescription":"2 p.","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-069422","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":310712,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://dx.doi.org/10.3133/gip159","text":"General Information Product 159 - Bookmark","size":"348 KB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2015-3071"},{"id":310711,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2015/3071/fs20153071.pdf","text":"Report","size":"1.55 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2015-3071"},{"id":310710,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2015/3071/coverthb.jpg"}],"country":"United States","state":"Virginia","otherGeospatial":"Chesapeake Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.003173828125,\n 36.641977814705946\n ],\n [\n -77.003173828125,\n 37.79676317682161\n ],\n [\n -75.0531005859375,\n 37.79676317682161\n ],\n [\n -75.0531005859375,\n 36.641977814705946\n ],\n [\n -77.003173828125,\n 36.641977814705946\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Eastern Geology and Paleoclimate Science Center
U.S. Geological Survey
926A National Center
12201 Sunrise Valley Drive
Reston, VA 20192
http://geology.er.usgs.gov/egpsc
About 35 million years ago, a 2-mile-wide meteorite smashed into Earth in what is now the lower Chesapeake Bay in Virginia. The oceanic impact vaporized, melted, fractured, and displaced rocks and sediments and sent billions of tons of water, sediments, and rocks into the air. Glassy particles of solidified melt rock rained down as far away as Texas and the Caribbean. Large tsunamis affected most of the North Atlantic basin. The resulting impact structure is more than 53 miles wide and has a 23-mile-wide, filled central crater surrounded by collapsed sediments. Now buried by hundreds of feet of younger sediments, the Chesapeake Bay impact structure is among the 20 largest known impact structures on Earth.
\nSince its discovery in the early 1990s, scientists have conducted deep drilling and geophysical surveys of the impact structure to find out more about its size, composition, structure, age, and biological effects and to understand its lingering influences on the regional groundwater system. These efforts culminated in the drilling of a 1-mile-deep, continuously sampled corehole in 2005 by an international group of scientists and agencies.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/gip159","issn":"2332–3531","isbn":"2332–354X","usgsCitation":"Powars, D.S., Edwards, L.E., Gohn, G.S., and Horton, J.W., Jr., 2015, Chesapeake Bay impact structure—A blast from the past: U.S. Geological Survey General Information Product 159, 2 p., https://dx.doi.org/10.3133/gip159.","productDescription":"2 p.","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-069162","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":310647,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/gip/0159/gip159.pdf","text":"Report","size":"346 KB","linkFileType":{"id":1,"text":"pdf"},"description":"GIP 159","linkHelpText":"Chesapeake Bay Impact Structure: A Blast from the Past - Bookmark"},{"id":310648,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://dx.doi.org/10.3133/fs20153071","text":"Fact Sheet 2015-3071","size":"1.56 MB","linkFileType":{"id":1,"text":"pdf"},"description":"GIP 159"},{"id":310646,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/gip/0159/coverthb.jpg"}],"country":"United States","otherGeospatial":"Chesapeake Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -77.003173828125,\n 36.641977814705946\n ],\n [\n -77.003173828125,\n 37.79676317682161\n ],\n [\n -75.0531005859375,\n 37.79676317682161\n ],\n [\n -75.0531005859375,\n 36.641977814705946\n ],\n [\n -77.003173828125,\n 36.641977814705946\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Eastern Geology and Paleoclimate Science Center
U.S. Geological Survey
926A National Center
12201 Sunrise Valley Drive
Reston, VA 20192
http://geology.er.usgs.gov/egps
The recent commercial availability of in-situ optical sensors, together with new techniques for data collection and analysis, provides the opportunity to monitor a wide range of water-quality constituents over time scales during which environmental conditions actually change. Traditional approaches for data collection (daily to monthly discrete samples) are often limited by high sample collection, processing, and analytical costs, difficult site access, and logistical challenges, particularly for long-term sampling at a large number of sites. Optical sensors that continuously measure constituents in the environment by absorbance or fluorescence properties (Figure 1) have had a long history of use in oceanography for measuring highly resolved concentrations and fluxes of organic matter, nutrients, and algal material. However, much of the work using commercially-available optical sensors in rivers and streams has taken place in only the last few years. Figure 1. [NOT SHOWN] Optical sensor technology is now sufficiently developed to warrant broader application for research and monitoring in coastal and freshwater systems, and the United States Geological Survey (a U.S. science agency) is now using these sensors in a variety of research and monitoring programs to better understand water quality in-situ and in real-time. Examples are numerous and range from the applications of nitrate sensors for calculating loads to estuaries susceptible to hypoxia (Pellerin et al., 2014) to the use of fluorometers to estimate methymercury fluxes (Bergamaschi et al., 2011) and disinfection byproduct formation (Carpenter et al., 2013). Transmitting these data in real-time provides information that can be used for early trend detection, help identify monitoring gaps critical for water management, and provide science-based decision support across a range of issues related to water quality, freshwater ecosystems, and human health. Despite the value of these sensors, collecting data that meet high-quality standards requires investment in and adherence to tested and established methods and protocols for sensor operation and data management (Pellerin et al., 2013). For example, optical sensor measurements can be strongly influenced by a variety of matrix effects, including water temperature, inner filtering from highly colored water, and scattering of light by suspended particles (Downing et al., 2012). Characterizing and correcting sensors for these effects – as well as the continued development of common methodologies and protocols for sensor use – will be critical to ensuring comparable measurements across sites and over time. In addition, collaborative efforts such as the Nutrient Sensor Challenge (www.nutrients-challenge.org) will continue to accelerate the development, production and use of affordable, reliable and accurate sensors for a range of environments. REFERENCES Bergamaschi .B.A., Fleck J.A., Downing B.D., Boss E., Pellerin B.A., Ganju N.K., Schoellhamer D.H., Byington A.A., Heim W.A., Stephenson M., Fujii R. (2011), Methyl mercury dynamics in a tidal wetland quantified using in situ optical measurements. Limnology and Oceanography, 56(4): 1355-1371. Carpenter K.D., Kraus T.E.C., Goldman J.H., Saraceno J., Downing B.D., Bergamaschi B.A., McGhee G., Triplett T. (2013), Sources and Characteristics of Organic Matter in the Clackamas River, Oregon, Related to the Formation of Disinfection By-products in Treated Drinking Water: U.S. Geological Survey Scientific Investigations Report 2013–5001, 78 p. Downing .B.D., Pellerin B.A., Bergamaschi B.A., Saraceno J., Kraus T.E.K. (2012), Seeing the light: The effects of particles, temperature and inner filtering on in situ CDOM fluorescence in rivers and streams. Limnology and Oceanography: Methods, 10: 767-775. Pellerin B.A., Bergamaschi B.A., Downing B.D., Saraceno J., Garrett J.D., Olsen L.D. (2013), Optical Techniques for the Determination of Nitrate in En
","conferenceTitle":"The SMART water grid International conference","conferenceDate":"October 27-28, 2015","conferenceLocation":"Incheon, South Korea","language":"English","usgsCitation":"Pellerin, B., 2015, Applications of optical sensors for high-frequency water-quality monitoring and research, The SMART water grid International conference, Incheon, South Korea, October 27-28, 2015, 1 p.","productDescription":"1 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-068720","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":311184,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":307561,"type":{"id":15,"text":"Index Page"},"url":"https://www.swgic.org/sub/information/schedule.htm"}],"publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5643233ce4b0aafbcd017fcb","contributors":{"authors":[{"text":"Pellerin, Brian A. 0000-0003-3712-7884 bpeller@usgs.gov","orcid":"https://orcid.org/0000-0003-3712-7884","contributorId":147077,"corporation":false,"usgs":true,"family":"Pellerin","given":"Brian","email":"bpeller@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true}],"preferred":true,"id":570189,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70156292,"text":"70156292 - 2015 - Simulating maize yield and bomass with spatial variability of soil field capacity","interactions":[],"lastModifiedDate":"2016-01-06T10:35:22","indexId":"70156292","displayToPublicDate":"2015-10-27T17:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":684,"text":"Agronomy Journal","active":true,"publicationSubtype":{"id":10}},"title":"Simulating maize yield and bomass with spatial variability of soil field capacity","docAbstract":"Spatial variability in field soil properties is a challenge for system modelers who use single representative values, such as means, for model inputs, rather than their distributions. In this study, the root zone water quality model (RZWQM2) was first calibrated for 4 yr of maize (Zea mays L.) data at six irrigation levels in northern Colorado and then used to study spatial variability of soil field capacity (FC) estimated in 96 plots on maize yield and biomass. The best results were obtained when the crop parameters were fitted along with FCs, with a root mean squared error (RMSE) of 354 kg ha–1 for yield and 1202 kg ha–1 for biomass. When running the model using each of the 96 sets of field-estimated FC values, instead of calibrating FCs, the average simulated yield and biomass from the 96 runs were close to measured values with a RMSE of 376 kg ha–1 for yield and 1504 kg ha–1 for biomass. When an average of the 96 FC values for each soil layer was used, simulated yield and biomass were also acceptable with a RMSE of 438 kg ha–1 for yield and 1627 kg ha–1 for biomass. Therefore, when there are large numbers of FC measurements, an average value might be sufficient for model inputs. However, when the ranges of FC measurements were known for each soil layer, a sampled distribution of FCs using the Latin hypercube sampling (LHS) might be used for model inputs.
","language":"English","publisher":"American Society of Agronomy","publisherLocation":"Madison, WI","doi":"10.2134/agronj2015.0206","usgsCitation":"Ma, L., Ahuja, L., Trout, T., Nolan, B.T., and Malone, R.W., 2015, Simulating maize yield and bomass with spatial variability of soil field capacity: Agronomy Journal, v. 108, no. 1, p. 171-184, https://doi.org/10.2134/agronj2015.0206.","productDescription":"14 p.","startPage":"171","endPage":"184","numberOfPages":"14","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060069","costCenters":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"links":[{"id":313916,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"108","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"568e492ae4b0e7a44bc41a6a","contributors":{"authors":[{"text":"Ma, Liwang","contributorId":6751,"corporation":false,"usgs":false,"family":"Ma","given":"Liwang","affiliations":[{"id":6622,"text":"US Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":583050,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ahuja, Lajpat","contributorId":100275,"corporation":false,"usgs":true,"family":"Ahuja","given":"Lajpat","email":"","affiliations":[],"preferred":false,"id":583051,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Trout, Thomas","contributorId":95785,"corporation":false,"usgs":true,"family":"Trout","given":"Thomas","email":"","affiliations":[],"preferred":false,"id":583052,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nolan, Bernard T. 0000-0002-6945-9659 btnolan@usgs.gov","orcid":"https://orcid.org/0000-0002-6945-9659","contributorId":2190,"corporation":false,"usgs":true,"family":"Nolan","given":"Bernard","email":"btnolan@usgs.gov","middleInitial":"T.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true}],"preferred":true,"id":568542,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Malone, Robert W.","contributorId":10347,"corporation":false,"usgs":false,"family":"Malone","given":"Robert","email":"","middleInitial":"W.","affiliations":[{"id":6622,"text":"US Department of Agriculture","active":true,"usgs":false}],"preferred":false,"id":583053,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70158608,"text":"ds964 - 2015 - Public-supply water use in Kansas, 2013","interactions":[],"lastModifiedDate":"2016-02-24T10:29:28","indexId":"ds964","displayToPublicDate":"2015-10-27T14:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"964","title":"Public-supply water use in Kansas, 2013","docAbstract":"This report, prepared by the U.S. Geological Survey in cooperation with the Kansas Department of Agriculture’s Division of Water Resources, presents derivative statistics of water used by Kansas public-supply systems in 2013. The published statistics from the previous 4 years (2009–12) are also shown with the 2013 statistics and are used to calculate a 5-year average. An overall Kansas average and regional averages also are calculated and presented.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds964","collaboration":"Prepared in cooperation with the Kansas Department of Agriculture’s Division of Water Resources","usgsCitation":"Lanning-Rush, J.L., and Eslick, P.J., 2015, Public-supply water use in Kansas, 2013: U.S. Geological Survey Data\nSeries 964, 46 p., https://dx.doi.org/10.3133/ds964.","productDescription":"Report: iii, 46 p.; 2 Appendixes","numberOfPages":"54","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2013-01-01","temporalEnd":"2013-12-31","ipdsId":"IP-067633","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":310291,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/0964/coverthb.jpg"},{"id":310299,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/0964/downloads/appendix2-non_primary_mun.pdf","text":"Appendix 2","size":"33.8 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4821 Quail Crest Place
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http://ks.water.usgs.gov
Decline of sugar maple in North American forests has been attributed to changes in soil calcium (Ca) and nitrogen (N) by acidic precipitation. Although N is an essential and usually a limiting factor in forests, atmospheric N deposition may cause N-saturation leading to loss of soil Ca. Such changes can affect carbon gain and growth of sugar maple trees and seedlings. We applied a 22 factorial arrangement of N and dolomitic limestone containing Ca and Magnesium (Mg) to 12 forest plots in the Catskill Mountain region of NY, USA. To quantify the short-term effects, we measured photosynthetic-light responses of sugar maple mature trees and seedlings two or three times during two summers. We estimated maximum net photosynthesis (An-max) and its related light intensity (PAR at An-max), apparent quantum efficiency (Aqe), and light compensation point (LCP). To quantify the long-term effects, we measured basal area of living mature trees before and 4 and 8 years after treatment applications. Soil and foliar chemistry variables were also measured. Dolomitic limestone increased Ca, Mg, and pH in the soil Oe horizon. Mg was increased in the B horizon when comparing the plots receiving N with those receiving CaMg. In mature trees, foliar Ca and Mg concentrations were higher in the CaMg and N+CaMg plots than in the reference or N plots; foliar Ca concentration was higher in the N+CaMg plots compared with the CaMg plots, foliar Mg was higher in the CaMg plots than the N+CaMg plots; An-max was maximized due to N+CaMg treatment; Aqe decreased by N addition; and PAR at An-max increased by N or CaMg treatments alone, but the increase was maximized by their combination. No treatment effect was detected on basal areas of living mature trees four or eight years after treatment applications. In seedlings, An-max was increased by N+CaMg addition. The reference plots had an open herbaceous layer, but the plots receiving N had a dense monoculture of common woodfern in the forest floor, which can impede seedling survival.
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Based on a well-replicated dendrochronological network of range-centered populations in the Adirondack Mountains (USA), which encompassed a wide gradient of soil fertility, we observed that the majority of sugar maple trees exhibited negative growth trends in the last several decades, regardless of age, diameter, or soil fertility. Such growth patterns were unexpected, given recent warming and increased moisture availability, as well as reduced acidic deposition, which should have favored growth. Mean basal area increment was greater on base-rich soils, but these stands also experienced sharp reductions in growth. Growth sensitivity of sugar maple to temperature and precipitation was non-stationary during the last century, with overall weaker relationships than expected. Given the favorable competitive status and age structure of the Adirondack sugar maple populations sampled, evidence of widespread growth reductions raises concern over this ecologically and economically important tree. Further study will be needed to establish whether growth declines of sugar maple are occurring more widely across its range.
A series of 10 digital flood-inundation maps were developed for a 3.3-mile reach of the North River in Colrain, Charlemont, and Shelburne, Massachusetts, by the U.S. Geological Survey in cooperation with the Federal Emergency Management Agency. The coverage of the maps extends from the confluence of the East and West Branch North Rivers to the Deerfield River. Peak-flow estimates at the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities were computed for the reach from updated flood-frequency analyses. These peak flows were routed through a one-dimensional step-backwater hydraulic model to obtain the corresponding peak water-surface elevations and to place the tropical storm Irene flood of August 28, 2011, into historical context. The hydraulic model was calibrated by using the current [2015] stage-discharge relation at the U.S. Geological Survey streamgage North River at Shattuckville, MA (station number 01169000), and from documented high-water marks from the tropical storm Irene flood, which had a peak flow with approximately a 0.2-percent annual exceedance probability.
\nA hydraulic model was used to compute water-surface profiles for 10 flood stages referenced to the streamgage and ranging from 6.6 feet (ft; 464.5 ft North American Vertical Datum of 1988 [which is approximately bankfull]) to 18.3 ft (476.2 ft North American Vertical Datum of 1988 [which is the stage of the 0.2-percent annual exceedance probability peak flow and exceeds the maximum recorded water level at the streamgage and the National Weather Service major flood stage of 13.0 ft]. The mapped stages of 6.6 to 18.3 ft were selected to match the stages of flows for bankfull; the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities; and an incremental stage of 17.0 ft. The simulated water-surface profiles were combined with a geographic information system digital elevation model derived from light detection and ranging (lidar) data with a 0.5-ft vertical accuracy to create a set of flood-inundation maps.
\nThe availability of the flood-inundation maps, combined with information regarding near-real-time stage from the U.S. Geological Survey North River at Shattuckville, MA streamgage can provide emergency management personnel and residents with information that is critical for flood response activities, such as evacuations and road closures, and postflood recovery efforts. The flood-inundation maps are nonregulatory, but provide Federal, State, and local agencies and the public with estimates of the potential extent of flooding during selected peak-flow events. Introduction
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155108","collaboration":"Prepared in cooperation with the Federal Emergency Management Agency","usgsCitation":"Bent, G.C., Lombard, P.J., and Dudley, R.W., 2015, Flood-inundation maps for the North River in Colrain, Charlemont, and Shelburne, Massachusetts, from the confluence of the East and West Branch North Rivers to the Deerfield River: U.S. Geological Survey Scientific Investigations Report 2015–5108, 16 p., appendixes, https://dx.doi.org/10.3133/sir20155108.","productDescription":"Report: v, 15 p.; Appendixes: 1-2; Application site; Metadata; Spacial data","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-061968","costCenters":[{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true}],"links":[{"id":310349,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5108/sir20155108.pdf","text":"Report","size":"4.54 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5108"},{"id":310384,"rank":6,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sir/2015/5108/attachments/sir20155108_flood-inundation-gis.zip","text":"Flood Inundation - GIS","size":"4.64 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2015-5108"},{"id":310385,"rank":7,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sir/2015/5108/attachments/sir20155108_flood-inundation-gis-metadata.xml","text":"Flood Inundation - GIS Metadata (xml)","size":"12.5 KB","description":"SIR 2015-5108"},{"id":310386,"rank":8,"type":{"id":4,"text":"Application Site"},"url":"https://wimcloud.usgs.gov/apps/FIM/FloodInundationMapper.html","text":"Flood Inundation Mapper","linkFileType":{"id":5,"text":"html"}},{"id":310383,"rank":5,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5108/attachments/sir20155108_appendix2-shapefiles.zip","text":"Appendix 2 - Shapefiles","size":"31 KB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2015-5108"},{"id":310382,"rank":4,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sir/2015/5108/attachments/sir20155108_appendix2-metadata.xml","text":"Appendix 2 - Metadata (xml)","size":"11.8 KB","description":"SIR 2015-5108"},{"id":310350,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5108/attachments/sir20155108_app1.xlsx","text":"Appendix 1","size":"13.4 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"SIR 2015-5108"},{"id":310629,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5108/images/coverthb.jpg"}],"country":"United States","state":"Massachusetts","city":"Colrain, Charlemont, Shelburne, Shattuckville","otherGeospatial":"North River, Deerfield River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.0810546875,\n 42.285437007491545\n ],\n [\n -72.421875,\n 42.285437007491545\n ],\n [\n -72.421875,\n 42.70665956351041\n ],\n [\n -73.0810546875,\n 42.70665956351041\n ],\n [\n -73.0810546875,\n 42.285437007491545\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New England Water Science Center
U.S. Geological Survey
10 Bearfoot Road
Northborough, MA 01532
Or visit our Web site at
http://newengland.water.usgs.gov/
Collecting physical bedload measurements is an expensive and time-consuming endeavor that rarely captures the spatial and temporal variability of sediment transport. Technological advances can improve monitoring of sediment transport by filling in temporal gaps between physical sampling periods. We have developed a low-cost hydrophone recording system designed to record the sediment-generated noise (SGN) resulting from collisions of coarse particles (generally larger than 4 mm) in gravel-bedded rivers. The sound level of the signal recorded by the hydrophone is assumed to be proportional to the magnitude of bedload transport as long as the acoustic frequency of the SGN is known, the grain-size distribution of the bedload is assumed constant, and the frequency band of the ambient noise is known and can be excluded from the analysis. Each system has two hydrophone heads and samples at half-hour intervals. Ten systems were deployed on the San Joaquin River, California, and its tributaries for ten months during water year 2014, and two systems were deployed during a flood event on the Gunnison River, Colorado in 2014. A mobile hydrophone system was also tested at both locations to collect longitudinal profiles of SGN. Physical samples of bedload were not collected in this study. In lieu of physical measurements, several audio recordings from each site were aurally reviewed to confirm the presence or absence of SGN, and hydraulic data were compared to historical measurements of bedload transport or transport capacity estimates to verify if hydraulic conditions during the study would likely produce bedload transport. At one site on the San Joaquin River, the threshold of movement was estimated to have occurred around 30 m 3 /s based on SGN data. During the Gunnison River flood event, continuous data showed clockwise hysteresis, indicating that bedload transport was generally less at any given streamflow discharge during the recession limb of the hydrograph. Spatial variability in transport was also detected in the longitudinal profiles audibly and using signal processing algorithms. These experiments demonstrate the ability of hydrophone technology to capture the temporal and spatial variability of sediment transport, which may be missed when samples are collected using conventional methods.
","conferenceTitle":"3rd Joint Federal Interagency Conference","conferenceDate":"April 19-23, 2015","conferenceLocation":"Reno, NV","language":"English","publisher":"Joint Federal Interagency Conference","usgsCitation":"Marineau, M.D., Minear, J., and Wright, S., 2015, Using hydrophones as a surrogate monitoring technique to detect temporal and spatial variability in bedload transport, 3rd Joint Federal Interagency Conference, Reno, NV, April 19-23, 2015, 12 p.","productDescription":"12 p.","ipdsId":"IP-060794","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":342079,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Colorado","otherGeospatial":"Gunnison River, San Joaquin River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.083333,\n 37.1\n ],\n [\n -120.083333,\n 36.683333\n ],\n [\n -119.683333,\n 36.683333\n ],\n [\n -119.683333,\n 37.1\n ],\n [\n -120.083333,\n 37.1\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.458333,\n 38.925\n ],\n [\n -108.25,\n 38.925\n ],\n [\n -108.25,\n 38.7\n ],\n [\n -108.458333,\n 38.7\n ],\n [\n -108.458333,\n 38.925\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"59366daae4b0f6c2d0d7d62e","contributors":{"authors":[{"text":"Marineau, Mathieu D. 0000-0002-6568-0743 mmarineau@usgs.gov","orcid":"https://orcid.org/0000-0002-6568-0743","contributorId":4954,"corporation":false,"usgs":true,"family":"Marineau","given":"Mathieu","email":"mmarineau@usgs.gov","middleInitial":"D.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":548731,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Minear, J. Toby","contributorId":9938,"corporation":false,"usgs":true,"family":"Minear","given":"J. Toby","affiliations":[],"preferred":false,"id":548732,"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":548733,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70157439,"text":"sir20155139 - 2015 - Groundwater chemistry in the vicinity of the Puna Geothermal Venture Power Plant, Hawai‘i, after two decades of production","interactions":[],"lastModifiedDate":"2015-10-27T09:14:28","indexId":"sir20155139","displayToPublicDate":"2015-10-26T16:00:00","publicationYear":"2015","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":"2015-5139","title":"Groundwater chemistry in the vicinity of the Puna Geothermal Venture Power Plant, Hawai‘i, after two decades of production","docAbstract":"We report chemical data for selected shallow wells and coastal springs that were sampled in 2014 to determine whether geothermal power production in the Puna area over the past two decades has affected the characteristics of regional groundwater. The samples were analyzed for major and minor chemical species, trace metals of environmental concern, stable isotopes of water, and two organic compounds (pentane and isopropanol) that are injected into the deep geothermal reservoir at the power plant. Isopropanol was not detected in any of the groundwaters; confirmed detection of pentane was restricted to one monitoring well near the power plant at a low concentration not indicative of source. Thus, neither organic compound linked geothermal operations to groundwater contamination, though chemical stability and transport velocity questions exist for both tracers. Based on our chemical analysis of geothermal fluid at the power plant and on many similar results from commercially analyzed samples, we could not show that geothermal constituents in the groundwaters we sampled came from the commercially developed reservoir. Our data are consistent with a long-held view that heat moves by conduction from the geothermal reservoir into shallow groundwaters through a zone of low permeability rock that blocks passage of geothermal water. The data do not rule out all impacts of geothermal production on groundwater. Removal of heat during production, for example, may be responsible for minor changes that have occurred in some groundwater over time, such as the decline in temperature of one monitoring well near the power plant. Such indirect impacts are much harder to assess, but point out the need for an ongoing groundwater monitoring program that should include the coastal springs down-gradient from the power plant.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155139","usgsCitation":"Evans, W., Bergfeld, D., Sutton, A., Lee, R., and Lorenson, T., 2015, Groundwater chemistry in the vicinity of the Puna Geothermal Venture Power Plant, Hawai‘i, after two decades of production: U.S. Geological Survey Scientific Investigations Report 2015-5139, v, 26 p., https://doi.org/10.3133/sir20155139.","productDescription":"v, 26 p.","numberOfPages":"36","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2014-01-01","temporalEnd":"2014-12-31","ipdsId":"IP-068405","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":310658,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5139/coverthb.jpg"},{"id":310659,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5139/sir20155139.pdf","text":"Report","size":"2.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5139"}],"country":"United States","state":"Hawaii","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -154.98310089111328,\n 19.34289288466279\n ],\n [\n -154.99408721923828,\n 19.51255069063782\n ],\n [\n -154.918212890625,\n 19.581463883128308\n ],\n [\n -154.8028564453125,\n 19.52484721904625\n ],\n [\n -154.81761932373047,\n 19.47533181665073\n ],\n [\n -154.98310089111328,\n 19.34289288466279\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"NRP staff, National Research Program
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Coastal communities are uniquely vulnerable to sea-level rise (SLR) and severe storms such as hurricanes. These events enhance the dispersion and concentration of natural and anthropogenic chemicals and pathogenic microorganisms that could adversely affect the health and resilience of coastal communities and ecosystems in coming years. The U.S. Geological Survey has developed a strategy to define baseline and post-event sediment-bound environmental health (EH) stressors (hereafter referred to as the Sediment-Bound Contaminant Resiliency and Response [SCoRR] strategy). A tiered, multimetric approach will be used to (1) identify and map contaminant sources and potential exposure pathways for human and ecological receptors, (2) define the baseline mixtures of EH stressors present in sediments and correlations of relevance, (3) document post-event changes in EH stressors present in sediments, and (4) establish and apply metrics to quantify changes in coastal resilience associated with sediment-bound contaminants. Integration of this information provides a means to improve assessment of the baseline status of a complex system and the significance of changes in contaminant hazards due to storm-induced (episodic) and SLR (incremental) disturbances. This report describes the purpose and design of the SCoRR strategy and the methods used to construct a decision support tool to identify candidate sampling stations vulnerable to contaminants that may be mobilized by coastal storms.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151188A","collaboration":"Toxic Substances Hydrology Program","usgsCitation":"Reilly, T.J., Jones, D.K., Focazio, M.J., Aquino, K.C., Carbo, C.L., Kaufhold, E.E., Zinecker, E.K., Benzel, W.M., Fisher, S.C., Griffin, D.W., Iwanowicz, L.R., Loftin, K.A. and Schill, W.B., 2015, Strategy to evaluate persistent contaminant hazards resulting from sea-level rise and storm-derived disturbances—Study design and methodology for station prioritization: U.S. Geological Survey Open-File Report 2015–1188A, 20 p., https://dx.doi.org/10.3133/ofr20151188A.","productDescription":"Report: vi, 20 p.; 3 Appendixes","numberOfPages":"30","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-066315","costCenters":[{"id":470,"text":"New Jersey Water Science Center","active":true,"usgs":true}],"links":[{"id":438671,"rank":7,"type":{"id":30,"text":"Data 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Toxic Substances Hydrology Program
12201 Sunrise Valley Drive
Reston, Virginia 20192
http://www.usgs.gov/envirohealth/
A series of maps that describe the distribution and texture of sea-floor sediments and physiographic zones of Massachusetts State waters from Nahant to Salisbury, Massachusetts, including western Massachusetts Bay, have been produced by using high-resolution geophysical data (interferometric and multibeam swath bathymetry, lidar bathymetry, backscatter intensity, and seismic reflection profiles), sediment samples, and bottom photographs. These interpretations are intended to aid statewide efforts to inventory and manage coastal and marine resources, link with existing data interpretations, and provide information for research focused on coastal evolution and environmental change. Marine geologic mapping of the inner continental shelf of Massachusetts is a statewide cooperative effort of the U.S. Geological Survey and the Massachusetts Office of Coastal Zone Management.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151153","collaboration":"Prepared in cooperation with the Massachusetts Office of Coastal Zone Management","usgsCitation":"Pendleton, E.A., Barnhardt, W.A., Baldwin, W.E., Foster, D.S., Schwab, W.C., Andrews, B.D., and Ackerman, S.D., 2015, Sea-floor texture and physiographic zones of the inner continental shelf from Salisbury to Nahant, Massachusetts, including the Merrimack Embayment and Western Massachusetts Bay: U.S. Geological Survey Open-File Report 2015–1153, 36 p., 1 appendix, https://dx.doi.org/10.3133/ofr20151153.","productDescription":"vi, 36 p.; HTML Documet","numberOfPages":"46","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-057824","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":309391,"rank":3,"type":{"id":2,"text":"Additional Report Piece"},"url":"https://pubs.usgs.gov/of/2015/1153/index.html","text":"Report HTML","description":"OFR 2015-1153"},{"id":308684,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1153/ofr20151153.pdf","text":"Report","size":"2.02 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2015-1153"},{"id":308683,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2015/1153/images/coverthb.jpg"}],"country":"United States","state":"Massachusetts","city":"Nahant, Salisbury","otherGeospatial":"Massachusetts Bay, Merrimack Embayment","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.95794677734374,\n 42.407234661551875\n ],\n [\n -70.95794677734374,\n 42.84777884235988\n ],\n [\n -70.56106567382812,\n 42.84777884235988\n ],\n [\n -70.56106567382812,\n 42.407234661551875\n ],\n [\n -70.95794677734374,\n 42.407234661551875\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Woods Hole Coastal and Marine Science Center
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384 Woods Hole Road
Quissett Campus
Woods Hole, MA 0254
http://woodshole.er.usgs.gov/
Chambers Lake is a manmade reservoir on Birch Run, a tributary to West Branch Brandywine Creek in Chester County, Pennsylvania. The lake was created in 1994 after the completion of Multi-Purpose Dam PA-436F (Hibernia Dam), which was built under the Watershed Protection & Flood Control Prevention Act (U.S. Soil Conservation Service, 1991). Hibernia dam is 1,700 feet upstream from the confluence of Birch Run with West Branch Brandywine Creek. The primary objectives for Hibernia Dam were to provide (1) flood control, (2) a supplemental source of water supply for the greater City of Coatesville public water system, and (3) recreational opportunities. The drainage basin of Chambers Lake encompasses approximately 4.5 square miles, and the lake covers a surface area of about 95 acres at normal pool, which is at an elevation of 579.2 feet above the North American Vertical Datum of 1988 (NAVD 88) [580.0 feet above the National Geodetic Vertical Datum of 1929 (NGVD 29)]. The crest of the auxiliary spillway of the dam is 586.6 feet above NAVD 88. The elevation of the auxiliary spillway is important to this investigation because this elevation defines the flood storage capacity of Chambers Lake. Water levels exceeding this elevation are routed through the auxiliary spillway and flow through adjoining woodland to Birch Run.
\nThe U.S. Geological Survey (USGS), in cooperation with Chester County Water Resources Authority (CCWRA) and the County of Chester, surveyed the bathymetry and selected above-water features of Chambers Lake in September 2014. The purpose of the survey was to develop an accurate representation of the surface of the bottom of Chambers Lake and to determine the stage area and reservoir-storage capacity relation as of September 2014. CCWRA is responsible for operation of the dam and water-supply reservoir. Since construction, CCWRA has used a stage–storage capacity relation developed from the original survey conducted in the 1990s to estimate the volume of water available for water supply and the available flood storage. The bathymetric mapping effort was initiated due to interest in potential changes in current (2014) storage capacity when compared to the stage–storage capacity relation developed during design. The generated bathymetric surface may serve as a baseline to which temporal changes in storage capacity, owing to sedimentation and other factors, can be compared. In addition, these data will improve the overall accuracy of the stage–storage capacity table that CCWRA uses for reservoir and flood management operations.
\nThis report describes the methods used to create a bathymetric map of Chambers Lake for the computation of reservoir storage capacity as of September 2014. The product is a bathymetric map and a table showing the storage capacity of the reservoir at 2-foot increments from minimum usable elevation up to full capacity at the crest of the auxiliary spillway.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3346","collaboration":"Prepared in cooperation with the Chester County Water Resources Authority","usgsCitation":"Gyves, M.C., 2015, Bathymetry and capacity of Chambers Lake, Chester County, Pennsylvania: U.S. Geological Survey Scientific Investigations Map 3346, https://dx.doi.org/10.3133/sim3346.","productDescription":"1 Sheet: 38 x 36 inches ; Spatial Data","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-062894","costCenters":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"links":[{"id":310602,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sim/3346/coverthb.jpg"},{"id":310604,"rank":3,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sim/3346/sim3346_spatial_data.zip","text":"Spatial Data","size":"13.1 MB","description":"SIM 3346"},{"id":310603,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sim/3346/sim3346.pdf","text":"Report","size":"1.71 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIM 3346"}],"country":"United States","state":"Pennsylvania","county":"Chester County","otherGeospatial":"Chambers Lake","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -75.86523056030273,\n 40.02781160777367\n ],\n [\n -75.86523056030273,\n 40.03622367578228\n ],\n [\n -75.84815025329588,\n 40.03622367578228\n ],\n [\n -75.84815025329588,\n 40.02781160777367\n ],\n [\n -75.86523056030273,\n 40.02781160777367\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Pennsylvania Water Science Center
215 Limekiln Road
New Cumberland, PA 17070
http://pa.water.usgs.gov/
Decreasing trends in acidic deposition levels over the past several decades have led to partial chemical recovery of surface waters. However, depletion of soil Ca from acidic deposition has slowed surface water recovery and led to the impairment of both aquatic and terrestrial ecosystems. Nevertheless, documentation of acidic deposition effects on soils has been limited, and little is known regarding soil responses to ongoing acidic deposition decreases. In this study, resampling of soils in eastern Canada and the northeastern U.S. was done at 27 sites exposed to reductions in wet SO42– deposition of 5.7–76%, over intervals of 8–24 y. Decreases of exchangeable Al in the O horizon and increases in pH in the O and B horizons were seen at most sites. Among all sites, reductions in SO42– deposition were positively correlated with ratios (final sampling/initial sampling) of base saturation (P < 0.01) and negatively correlated with exchangeable Al ratios (P < 0.05) in the O horizon. However, base saturation in the B horizon decreased at one-third of the sites, with no increases. These results are unique in showing that the effects of acidic deposition on North American soils have begun to reverse.
","language":"English","publisher":"American Chemical Society","publisherLocation":"Easton, PA","doi":"10.1021/acs.est.5b02904","collaboration":"New York State Energy Research and Development Authority; USGS","usgsCitation":"Lawrence, G.B., Hazlett, P.W., Fernandez, I.J., , O., Bailey, S.W., Shortle, W.C., Smith, K.T., and Antidormi, M.R., 2015, Declining acidic deposition begins reversal of forest-soil acidification in the northeastern U.S. and eastern Canada: Environmental Science & Technology, v. 49, no. 22, p. 13103-13111, https://doi.org/10.1021/acs.est.5b02904.","productDescription":"9 p.","startPage":"13103","endPage":"13111","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067512","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":312540,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":312539,"type":{"id":15,"text":"Index 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glawrenc@usgs.gov","orcid":"https://orcid.org/0000-0002-8035-2350","contributorId":867,"corporation":false,"usgs":true,"family":"Lawrence","given":"Gregory","email":"glawrenc@usgs.gov","middleInitial":"B.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":582919,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hazlett, Paul W.","contributorId":101177,"corporation":false,"usgs":true,"family":"Hazlett","given":"Paul","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":582920,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fernandez, Ivan J.","contributorId":80174,"corporation":false,"usgs":true,"family":"Fernandez","given":"Ivan","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":582921,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":" Ouimet","contributorId":140810,"corporation":false,"usgs":false,"given":"Ouimet","email":"","affiliations":[{"id":13582,"text":"Director of Forestry Research, Dept of Natural Resources & Wildlife, Quebec, Canada","active":true,"usgs":false}],"preferred":false,"id":582922,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Bailey, Scott W. 0000-0002-9160-156X","orcid":"https://orcid.org/0000-0002-9160-156X","contributorId":36840,"corporation":false,"usgs":true,"family":"Bailey","given":"Scott","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":582923,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Shortle, Walter C.","contributorId":64130,"corporation":false,"usgs":true,"family":"Shortle","given":"Walter","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":582924,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Smith, Kevin T.","contributorId":58512,"corporation":false,"usgs":true,"family":"Smith","given":"Kevin","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":582925,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Antidormi, Michael R. 0000-0002-3967-1173 mantidormi@usgs.gov","orcid":"https://orcid.org/0000-0002-3967-1173","contributorId":150722,"corporation":false,"usgs":true,"family":"Antidormi","given":"Michael","email":"mantidormi@usgs.gov","middleInitial":"R.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":582926,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70173836,"text":"70173836 - 2015 - Habitat selection and survival of pronghorn fawns at the Carrizo Plain National Monument, California","interactions":[],"lastModifiedDate":"2016-06-24T12:57:04","indexId":"70173836","displayToPublicDate":"2015-10-22T18:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1153,"text":"California Fish and Game","active":true,"publicationSubtype":{"id":10}},"title":"Habitat selection and survival of pronghorn fawns at the Carrizo Plain National Monument, California","docAbstract":"On the Carrizo Plain National Monument (CPNM), California, little is\nknown about survival rates and habitat characteristics of pronghorn fawns\n(Antilocapra americana). A marked decline in pronghorn numbers on the\nCPNM (from approximately 200 to <30 individuals from 1989 to 2011)\nprompted a study of fawn habitat use and fawn survival from 2009 to\n2011. Only 45 fawns were born during this period. We attached GPS\ncollars to 44% of these fawns (<5 days-of-age). We then used the locations\nof collared fawns to develop two separate binary logistic regression\nmodels to explore the best combination of micro- and macrohabitat-scale\nenvironmental variables for predicting (1) fawn habitat selection and\n(2) fawn survival. Model results for habitat selection showed that fawn\nlocations were associated with increased concealment at close distances (5\nm and 50 m) and decreased concealment at far distances (100 m). Fawn\nlocations were on lower sloped terrain and closer to available drinking\nwater and saltbush (Atriplex spp.). Model results for fawn survival showed\nthat increased survival time was associated with higher sloped terrain,\nproximity to available drinking water and saltbush, and increased distance\nfrom high-use roads. Collectively, these results demonstrate that fawn\nhabitat selection is scale-dependent and likely influenced by the combined\nspatio-temporal needs of both females and their young. The results of this\nstudy can be used to inform critical management actions on the CPNM.","language":"English","publisher":"California Department of Fish and Wildlife","usgsCitation":"Johnson, D.R., Longshore, K.M., Lowrey, C.E., and Thompson, D., 2015, Habitat selection and survival of pronghorn fawns at the Carrizo Plain National Monument, California: California Fish and Game, v. 101, no. 4, p. 267-279.","productDescription":"12 p.","startPage":"267","endPage":"279","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070598","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":324368,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":324367,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://www.wildlife.ca.gov/Publications/Journal/Contents"}],"country":"United States","state":"California","otherGeospatial":"Carrizo Plain National 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Center","active":true,"usgs":true}],"preferred":true,"id":638594,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Longshore, Kathleen M. 0000-0001-6621-1271 longshore@usgs.gov","orcid":"https://orcid.org/0000-0001-6621-1271","contributorId":2677,"corporation":false,"usgs":true,"family":"Longshore","given":"Kathleen","email":"longshore@usgs.gov","middleInitial":"M.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":false,"id":638593,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lowrey, Chris E. 0000-0001-5084-7275 clowrey@usgs.gov","orcid":"https://orcid.org/0000-0001-5084-7275","contributorId":3225,"corporation":false,"usgs":true,"family":"Lowrey","given":"Chris","email":"clowrey@usgs.gov","middleInitial":"E.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":638595,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Thompson, Daniel B.","contributorId":97829,"corporation":false,"usgs":true,"family":"Thompson","given":"Daniel B.","affiliations":[],"preferred":false,"id":638596,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70157183,"text":"sir20155127 - 2015 - Characteristics of sediment transport at selected sites along the Missouri River, 2011–12","interactions":[],"lastModifiedDate":"2015-10-22T15:08:55","indexId":"sir20155127","displayToPublicDate":"2015-10-22T15:00:00","publicationYear":"2015","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":"2015-5127","title":"Characteristics of sediment transport at selected sites along the Missouri River, 2011–12","docAbstract":"Extreme flooding in the Missouri River in 2011, followed by a year of more typical streamflows in 2012, allowed the sediment-transport regime to be compared between the unprecedented conditions of 2011 and the year immediately following the flooding. As part of a cooperative effort between the U.S. Geological Survey and the U.S. Army Corps of Engineers, this report follows up U.S. Geological Survey Scientific Investigations Report 2013–5006 by comparing sediment transport between years and among sampling sites spanning the Garrison Segment in North Dakota, the Gavins Point Segment downstream from Lewis and Clark Lake, and a part of the Channelized Segment along the Nebraska-Iowa border. Suspended sediment, bed material, bedload, and streamflow data from June 2011 through November 2012 were designated as “measured” total loads, wash loads, and bed-material loads; and, alternatively, were applied to the Modified-Einstein Procedure to compute sediment loads that were designated as “estimated” total loads.
\nBeyond the expected result that sediment loads were much lower during typical streamflows than those measured during the flooding, the measured data indicated some localized sediment-transport processes for further examination. Extreme and prolonged flooding can temporarily deplete sediment supplies locally, and evidence indicating such depletion was present at some sites. Unexpectedly high bed-material loads in the Gavins Point Segment may reflect episodic bar erosion just upstream from the sampling site. The relative contribution of bedload was typically 10 percent or less of the total load during the flooding. Following the flooding, this relative amount increased at some sites but not others, the reasons for which are possibly related to differences in stream velocity. Ultimately, the bedload decreased as it entered the Channelized Segment because of increased velocity and the turbulent mixing ability of the river as compared to the Gavins Point Segment. This turbulent mixing may also convert bed-material load into wash load, thereby rendering those sediments unavailable for creating sandbars and other bedforms. Though some of the sampling data support this premise, it was not consistently manifested by differences between the sediment load of the two segments during typical-streamflow conditions.
\nThe Modified-Einstein Procedure tended to predict greater total-sediment loads when compared to measured values. These differences may be the result of sediment deficits in the Missouri River that lead to an overprediction by the Modified-Einstein Procedure, the unsampled zone above the streambed that leads to an underprediction by the suspended sampler, or general uncertainty in the sampling approach. The differences between total-sediment load obtained through measurements and that estimated from applied theoretical procedures such as the Modified-Einstein Procedure pose a challenge for reliably characterizing total-sediment transport. Though it is not clear which of the two techniques is more accurate, the general tendency of the two to be within an order of magnitude of one another may be adequate for many sediment studies.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155127","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Omaha District","usgsCitation":"Rus, D.L., Galloway, J.M., and Alexander, J.S., 2015, Characteristics of sediment transport at selected sites along the Missouri River, 2011–12: U.S. Geological Survey Scientific Investigations Report 2015–5127, 34 p., https://dx.doi.org/10.3133/sir20155127.","productDescription":"v, 34 p.","numberOfPages":"44","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2011-01-01","temporalEnd":"2012-12-31","ipdsId":"IP-055952","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":310206,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5127/coverthb.jpg"},{"id":310207,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5127/sir20155127.pdf","text":"Report","size":"1.34 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5127"}],"country":"United States","state":"Iowa, Kansas, Missouri, Nebraska, North Dakota, South Dakota","otherGeospatial":"Missouri River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.087890625,\n 38.685509760012\n ],\n [\n -93.42773437499999,\n 40.613952441166596\n ],\n [\n -95.2734375,\n 43.51668853502909\n ],\n [\n -97.18505859374999,\n 45.90529985724796\n ],\n [\n -101.162109375,\n 47.90161354142077\n ],\n [\n -102.9638671875,\n 47.79839667295524\n ],\n [\n -101.62353515625,\n 43.992814500489914\n ],\n [\n -97.53662109375,\n 41.77131167976407\n ],\n [\n -94.9658203125,\n 38.5825261593533\n ],\n [\n -92.08740234375,\n 38.16911413556086\n ],\n [\n -90,\n 38.444984668894705\n ],\n [\n -90.087890625,\n 38.685509760012\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Nebraska Water Science Center
U.S. Geological Survey
5231 South 19th Street
Lincoln, Nebraska 68512
http://ne.water.usgs.gov/
The U.S. Geological Survey (USGS) has the critical role of providing scientific information to improve the understanding and management of the Chesapeake Bay ecosystem. The USGS works with Federal, State, and academic science partners to provide research and monitoring, and communicate results of these activities to enhance ecosystem management for both the Chesapeake and other National ecosystems. The USGS Chesapeake Science Strategy was prepared to guide science activities to address the Chesapeake Bay Watershed Agreement (2014–2025), to support the Department of the Interior (DOI) involvement in the Bay restoration efforts, and align with the USGS Mission Area (MA) Science strategies.
\nThe Chesapeake Bay is our Nation’s largest estuary, and provides critical goods and services to the people, fish, and wildlife that use the 64,000-square-mile watershed. The Chesapeake Bay watershed contains over 3,600 species of fish, wildlife, and plants and provides spawning grounds for many ecologically and economically important species including striped bass and blue crabs. The Bay watershed lies in the heart of the Atlantic Flyway and has 29 species of waterfowl, about 1 million of which winter in the region. The size of the Chesapeake seafood harvest is third in the Nation, only behind the Atlantic and Pacific Oceans. Along with agricultural production, tourism, and recreation, the estimated economic value of the services from the Chesapeake Bay watershed is about $100 billion annually. However, the health of the Bay ecosystem began to decline at the beginning of the 20th century due to overfishing and increasing human population and associated land change.
\nThe Chesapeake Bay Program (CBP) is the Federal-State cooperative effort that started in 1983 to restore the Bay and watershed. Given the ecological and economic importance of the Chesapeake ecosystem, President Obama issued an Executive Order (EO) in 2009 for increased Federal leadership in the CBP to enhance the pace of restoration, and the supporting strategy was released in 2010. The EO directed the Federal Government, including the U.S. Department of the Interior (DOI), represented by the National Park Service (NPS), the U.S. Fish & Wildlife Service (FWS), and the USGS, to expand its efforts and increase leadership to restore the Bay and its watershed. The USGS and other Federal agencies expanded their activities in 2011 to meet the President’s Chesapeake EO. Since the EO was released, there have been several important changes in the USGS, DOI, and the CBP including: (1) the Chesapeake Bay Watershed Agreement, (2) increased DOI leadership in the CBP, and (3) the release of the USGS MA science strategies. The EO strategy served as a foundation for the Chesapeake Bay Watershed Agreement that was signed in 2014 by the CBP Partners, and has goals and outcomes to be met by 2025.
\nThe USGS developed the Chesapeake Science Strategy to guide our activities to address the Chesapeake Bay Watershed Agreement, DOI leadership in the CBP, and USGS MA strategies. Improving the understanding of fish and wildlife population and health, and the factors affecting their condition is the emphasis of the Strategy. The science focuses on documenting the critical ecosystem connections in the Chesapeake, and providing implications to enhance decision making for restoration and conservation activities.
\nThe revised Strategy has four themes that address 7 of the 10 goals in the Chesapeake Bay Watershed Agreement:
\nThe structure and function of biological communities of the Bay and its watershed are extremely complex and are affected by a variety of stressors and conditions. To better define the issues being addressed, the USGS has developed cross-cutting questions that define some of the most important scientific challenges where multiple disciplines and collaborators are needed to address an issue. The initial questions include:
\nChesapeake Bay Coordinator
Northeast Region
U.S. Geological Survey
12201 Sunrise Valley Drive, Mail Stop 953
Reston, VA 20192
http://chesapeake.usgs.gov
To better understand suspended-sediment transport in a tidal slough adjacent to a large wetland restoration project, we deployed continuously measuring temperature, salinity, depth, turbidity, and velocity sensors in 2010 at a near-bottom location in Alviso Slough (Alviso, California, USA). Alviso Slough is the downstream reach of the Guadalupe River and flows into the far southern end of San Francisco Bay. River flow is influenced by the Mediterranean climate, with high flows (∼90 m3 s−1) correlated to episodic winter storms and low base flow (∼0.85 m3 s−1) during the summer. Storms and associated runoff have a large influence on sediment flux for brief periods, but the annual peak sediment concentrations in the slough, which occur in April and May, are similar to the rest of this part of the bay and are not directly related to peak discharge events. Strong spring tides promote a large upstream sediment flux as a front associated with the passage of a salt wedge during flood tide. Neap tides do not have flood-directed fronts, but a front seen sometimes during ebb tide appears to be associated with the breakdown of stratification in the slough. During neap tides, stratification likely suppresses sediment transport during weaker flood and ebb tides. The slough is flood dominant during spring tides, and ebb dominant during neap tides. Extreme events in landward (salt wedge) and bayward (rainfall events) suspended-sediment flux account for 5.0 % of the total sediment flux in the slough and only 0.55 % of the samples. The remaining 95 % of the total sediment flux is due to tidal transport, with an imbalance in the daily tidal transport producing net landward flux. Overall, net sediment transport during this study was landward indicating that sediment in the sloughs may not be flushed to the bay and are available for sedimentation in the adjacent marshes and ponds.
","language":"English","publisher":"Springer","publisherLocation":"Berlin","doi":"10.1007/s10236-015-0876-0","collaboration":"California State Coastal Conservancy; US Army Corps of Engineers; the Regional Monitoring Program for Water Quality in San Francisco Bay; USGS Priority Ecosystems Science Program; Santa Clara Valley Water District","usgsCitation":"Shellenbarger, G., Downing-Kunz, M.A., and Schoellhamer, D., 2015, Suspended-sediment dynamics in the tidal reach of a San Francisco Bay tributary: Ocean Dynamics, v. 65, no. 11, p. 1477-1488, https://doi.org/10.1007/s10236-015-0876-0.","startPage":"1477","endPage":"1488","numberOfPages":"12","ipdsId":"IP-062309","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":328852,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California","city":"Alviso","otherGeospatial":"Alviso Slough","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.05741882324219,\n 37.397846264696724\n ],\n [\n -122.05741882324219,\n 37.47036222875846\n ],\n [\n -121.94412231445314,\n 37.47036222875846\n ],\n [\n -121.94412231445314,\n 37.397846264696724\n ],\n [\n -122.05741882324219,\n 37.397846264696724\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"65","issue":"11","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationDate":"2015-09-18","publicationStatus":"PW","scienceBaseUri":"57f7ee36e4b0bc0bec09e90d","contributors":{"authors":[{"text":"Shellenbarger, Gregory gshellen@usgs.gov","contributorId":174805,"corporation":false,"usgs":true,"family":"Shellenbarger","given":"Gregory","email":"gshellen@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":649294,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Downing-Kunz, Maureen A. 0000-0002-4879-0318 mdowning-kunz@usgs.gov","orcid":"https://orcid.org/0000-0002-4879-0318","contributorId":3690,"corporation":false,"usgs":true,"family":"Downing-Kunz","given":"Maureen","email":"mdowning-kunz@usgs.gov","middleInitial":"A.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":649295,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Schoellhamer, David H. 0000-0001-9488-7340 dschoell@usgs.gov","orcid":"https://orcid.org/0000-0001-9488-7340","contributorId":631,"corporation":false,"usgs":true,"family":"Schoellhamer","given":"David H.","email":"dschoell@usgs.gov","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":649296,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70157499,"text":"ds965 - 2015 - Topographic and hydrographic survey data for the São Francisco River near Torrinha, Bahia, Brazil, 2014","interactions":[],"lastModifiedDate":"2015-10-22T08:25:52","indexId":"ds965","displayToPublicDate":"2015-10-21T16:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"965","title":"Topographic and hydrographic survey data for the São Francisco River near Torrinha, Bahia, Brazil, 2014","docAbstract":"Navigable inland waterways, including lakes, rivers, and reservoirs, are important transportation routes for people and goods in Brazil. Natural and anthropogenic effects coupled with recent severe droughts have led to decreased inland waterway navigation. The Company for Development of the São Francisco and Parnaíba River Valleys (CODEVASF) has recognized the decrease in waterway navigation and is investing resources to help restore selected reaches of the São Francisco River for navigation. In 2011, CODEVASF signed an agreement with the U.S. Army Corps of Engineers (USACE) seeking technical assistance and engineering expertise in waterway navigation and bank stabilization. The Torrinha-Itacoatiara study reach near Torrinha, Bahia was 1 of 12 conceptual waterway navigation improvement feasibility studies and was the focus of this study. The U.S. Geological Survey, in cooperation with the USACE and CODEVASF, collected topographic and hydrographic data from May 22 to June 12, 2014, to provide baseline data for supporting computational streamflow models.
\nThis report presents the surveying techniques and data-processing methods used to collect, process, and disseminate topographic and hydrographic data. All standard and non‑standard data-collection methods, techniques, and data process methods were documented. Additional discussion describes the quality-assurance and quality-control elements used in this study, along with the limitations for the Torrinha-Itacoatiara study reach data. The topographic and hydrographic geospatial data are published along with associated metadata.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds965","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers and the Company for Development of the São Francisco and Parnaiba River Valleys","usgsCitation":"Fosness, R.L., and Dietsch, B.J., 2015, Topographic and hydrographic survey data for the São Francisco River near Torrinha, Bahia, Brazil, 2014: U.S. Geological Survey Data Series 965, 28 p., https://dx.doi.org/10.3133/ds965.","productDescription":"Report: vi, 28 p.; GIS Datasets","numberOfPages":"38","onlineOnly":"Y","additionalOnlineFiles":"Y","temporalStart":"2014-05-22","temporalEnd":"2014-06-12","ipdsId":"IP-063788","costCenters":[{"id":343,"text":"Idaho Water Science Center","active":true,"usgs":true}],"links":[{"id":310182,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/0965/coverthb.jpg"},{"id":310183,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0965/ds0965.pdf","text":"Report","size":"7.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 965 PDF"},{"id":310308,"rank":3,"type":{"id":28,"text":"Dataset"},"url":"https://pubs.usgs.gov/ds/0965/ds0965_table3.html","text":"GIS Datasets","linkFileType":{"id":5,"text":"html"},"description":"GIS Datasets","linkHelpText":"Metadata, preview illustrations, and compressed geospatial data sets for the Torrinha-Itacoatiara feasibility study, São Francisco River near Torrinha, Bahia, Brazil, 2014."}],"country":"Brazil","state":"Bahia","city":"Torrinha","otherGeospatial":"São Francisco River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -43.385009765625,\n -11.549998444541838\n ],\n [\n -43.385009765625,\n -10.992423823549997\n ],\n [\n -42.9290771484375,\n -10.992423823549997\n ],\n [\n -42.9290771484375,\n -11.549998444541838\n ],\n [\n -43.385009765625,\n -11.549998444541838\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Idaho Water Science Center
U.S. Geological Survey
230 Collins Road
Boise, Idaho 83702
http://id.water.usgs.gov
The Yakima River Basin in south-central Washington has a long history of irrigated agriculture and a more recent history of large-scale livestock operations, both of which may contribute nutrients to the groundwater system. Nitrate concentrations in water samples from shallow groundwater wells in the lower Yakima River Basin exceeded the U.S. Environmental Protection Agency drinking-water standard, generating concerns that current applications of fertilizer and animal waste may be exceeding the rate at which plants can uptake nutrients, and thus contributing to groundwater contamination.
\nThe U.S. Geological Survey (USGS) recently completed a regional scale transient three-dimensional groundwater-flow model of the Yakima River Basin using MODFLOW-2000. The model was used with the USGS particle-tracking code MODPATH to generate advective flowpaths and associated travel times. Analyses used particle backtracking in time from September 2001 through 504 monthly stress periods to October 1959 or until pathlines terminated at a model boundary. The particle starting locations were assigned to 1,000 foot square computational model cells containing one or more of the 121 sampling locations with measured nitrate concentrations greater than the U.S. Environmental Protection Agency drinking-water standard for nitrate (10 milligrams per liter [mg/L]). Of the 2,403 particles, the simulated pathlines for 2,080 reached the water table within the 42-year simulation period, thus identifying the predicted recharge areas for those particles. The median horizontal straight-line distance was 13,194 feet between starting and ending locations for these particles and the median time-of-travel for particles that intersected the water table was 984 days. Well to water-table travel times for 75.4 percent of the particles were less than the average travel time of 3,749 days. Predicted recharge locations for all particles, including those that did not reach the water table in 42 years, were between 50 feet and 34 miles horizontal distance from their starting locations, with a median distance of less than 3 miles away.
\nGeneralized groundwater-flow directions in unconsolidated basin-fill deposits were towards the Yakima River, which acts as a local sink for shallow groundwater, and roughly parallel to topographic gradients. Particles backtracked from more shallow aquifer locations traveled shorter distances before reaching the water table than particles from deeper locations. Flowpaths for particles starting at wells completed in the basalt units underlying the basin-fill deposits sometimes were different than for wells with similar lateral locations but more shallow depths. In cases where backtracking particles reached geologic structures simulated as flow barriers, abrupt changes in direction in some particle pathlines suggest significant changes in simulated hydraulic gradients that may not accurately reflect actual conditions. Most groundwater wells sampled had associated zones of contribution within the Toppenish/Benton subbasin between the well and the nearest subbasin margin, but interpretation of these results for any specific well is likely to be complicated by the assumptions and simplifications inherent in the model construction process. Delineated zones of contribution for individual wells are sensitive to the depths assigned to the screened interval of the well, resulting in simulated areal extents of the zones of contribution to a discharging well that are elongated in the direction of groundwater flow.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155149","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Bachmann, M.P., 2015, Particle tracking for selected groundwater wells in the lower Yakima River Basin, Washington: U.S. Geological Survey Scientific Investigations Report 2015-5149, 33 p., https://dx.doi.org/10.3133/sir20155149.","productDescription":"v, 33 p.","numberOfPages":"44","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-066526","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":310287,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5149/coverthb.jpg"},{"id":310288,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5149/sir20155149.pdf","text":"Report","size":"13.5MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015-5149 Report PDF"}],"country":"United States","state":"Washington","otherGeospatial":"Yakima River Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -120.95947265624999,\n 45.935870621190546\n ],\n [\n -120.95947265624999,\n 46.58529390583601\n ],\n [\n -119.53125,\n 46.58529390583601\n ],\n [\n -119.53125,\n 45.935870621190546\n ],\n [\n -120.95947265624999,\n 45.935870621190546\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
http://wa.water.usgs.gov
The Albuquerque Basin, located in central New Mexico, is about 100 miles long and 25–40 miles wide. The basin is hydrologically defined as the extent of consolidated and unconsolidated deposits of Tertiary and Quaternary age that encompasses the structural Rio Grande Rift. Drinking-water supplies throughout the basin were obtained solely from groundwater resources until December 2008, when treatment and distribution of surface water from the Rio Grande through the San Juan-Chama Drinking Water Project began. A 20-percent population increase in the basin from 1990 to 2000 and a 22-percent population increase from 2000 to 2010 resulted in an increased demand for water.
An initial network of wells was established by the U.S. Geological Survey (USGS) in cooperation with the City of Albuquerque from April 1982 through September 1983 to monitor changes in groundwater levels throughout the basin. This network consisted of 6 wells with analog-to-digital recorders and 27 wells where water levels were measured monthly in 1983. The network currently (2014) consists of 125 wells and piezometers. (A piezometer is a specialized well open to a specific depth in the aquifer, often of small diameter and nested with other piezometers open to different depths.) The USGS, in cooperation with the Albuquerque Bernalillo County Water Utility Authority, currently (2014) measures and reports water levels from the 125 wells and piezometers in the network; this report presents water-level data collected by USGS personnel at those 125 sites through water year 2014 (October 1, 2013, to September 30, 2014).
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds963","collaboration":"Prepared in cooperation with the Albuquerque Bernalillo County Water Utility Authority","usgsCitation":"Beman, J.E., 2015, Water-level data for the Albuquerque Basin and adjacent areas, central New Mexico, period of record through September 30, 2014 (ver. 1.1, August 2021): U.S. Geological Survey Data Series 963, 42 p., https://doi.org/10.3133/ds963.","productDescription":"iii, 42 p.","numberOfPages":"49","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-063333","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":388362,"rank":1,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0963/ds963.pdf","text":"Report","size":"5.12 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 963"},{"id":388363,"rank":2,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/ds/0963/versionHist.txt","text":"Version History","size":"535 B","linkFileType":{"id":2,"text":"txt"},"description":"DS 963 Version History"},{"id":388485,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/0963/coverthb2.jpg"}],"country":"United States","state":"New Mexico","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -108.03955078125,\n 34.252676117101515\n ],\n [\n -108.03955078125,\n 36.20882309283712\n ],\n [\n -106.23779296875,\n 36.20882309283712\n ],\n [\n -106.23779296875,\n 34.252676117101515\n ],\n [\n -108.03955078125,\n 34.252676117101515\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.1: August 2021","contact":"Director, New Mexico Water Science Center
U.S. Geological Survey
6700 Edith Blvd. NE
Albuquerque, NM 87113
","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"publishedDate":"2015-10-21","revisedDate":"2021-08-25","noUsgsAuthors":false,"publicationDate":"2015-10-21","publicationStatus":"PW","scienceBaseUri":"5628a91ee4b0d158f5926bf9","contributors":{"authors":[{"text":"Beman, Joseph E. 0000-0002-0689-029X jebeman@usgs.gov","orcid":"https://orcid.org/0000-0002-0689-029X","contributorId":2619,"corporation":false,"usgs":true,"family":"Beman","given":"Joseph","email":"jebeman@usgs.gov","middleInitial":"E.","affiliations":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"preferred":true,"id":572772,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70159179,"text":"ofr20151201 - 2015 - Preliminary peak stage and streamflow data at selected USGS streamgaging stations for the South Carolina flood of October 2015","interactions":[],"lastModifiedDate":"2024-10-24T16:43:35.91342","indexId":"ofr20151201","displayToPublicDate":"2015-10-20T17:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1201","title":"Preliminary peak stage and streamflow data at selected USGS streamgaging stations for the South Carolina flood of October 2015","docAbstract":"
Heavy rainfall occurred across South Carolina during October 1–5, 2015, as a result of an upper atmospheric low-pressure system that funneled tropical moisture from Hurricane Joaquin into the State. The storm caused major flooding from the central to the coastal areas of South Carolina. Almost 27 inches of rain fell near Mount Pleasant in Charleston County during this period. U.S. Geological Survey streamgages recorded peaks of record at 17 locations, and 15 other locations had peaks that ranked in the top 5 for the period of record. During the October 2015 flood event, U.S. Geological Survey personnel made about 140 streamflow measurements at 86 locations to verify, update, or extend existing rating curves, which are used to compute streamflow from monitored river stage.
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U.S. Geological Survey
720 Gracern Road
Columbia, SC 29210
http://sc.water.usgs.gov
Watershed-scale monitoring, field aeration experiments, and geochemical equilibrium and kinetic modeling were conducted to evaluate interdependent changes in pH, dissolved CO2, O2, and Fe(II) concentrations that typically take place downstream of net-alkaline, circumneutral coal-mine drainage (CMD) outfalls and during aerobic treatment of such CMD. The kinetic modeling approach, using PHREEQC, accurately simulates observed variations in pH, Fe(II) oxidation, alkalinity consumption, and associated dissolved gas concentrations during transport downstream of the CMD outfalls (natural attenuation) and during 6-h batch aeration tests on the CMD using bubble diffusers (enhanced attenuation). The batch aeration experiments demonstrated that aeration promoted CO2 outgassing, thereby increasing pH and the rate of Fe(II) oxidation. The rate of Fe(II) oxidation was accurately estimated by the abiotic homogeneous oxidation rate law −d[Fe(II)]/dt = k1·[O2]·[H+]−2·[Fe(II)] that indicates an increase in pH by 1 unit at pH 5–8 and at constant dissolved O2 (DO) concentration results in a 100-fold increase in the rate of Fe(II) oxidation. Adjusting for sample temperature, a narrow range of values for the apparent homogeneous Fe(II) oxidation rate constant (k1′) of 0.5–1.7 times the reference value of k1 = 3 × 10−12 mol/L/min (for pH 5–8 and 20 °C), reported by Stumm and Morgan (1996), was indicated by the calibrated models for the 5-km stream reach below the CMD outfalls and the aerated CMD. The rates of CO2 outgassing and O2ingassing in the model were estimated with first-order asymptotic functions, whereby the driving force is the gradient of the dissolved gas concentration relative to equilibrium with the ambient atmosphere. Although the progressive increase in DO concentration to saturation could be accurately modeled as a kinetic function for the conditions evaluated, the simulation of DO as an instantaneous equilibrium process did not affect the model results for Fe(II) or pH. In contrast, the model results for pH and Fe(II) were sensitive to the CO2 mass transfer rate constant (kL,CO2a). The value of kL,CO2a estimated for the stream (0.010 min−1) was within the range for the batch aeration experiments (0–0.033 min−1). These results indicate that the abiotic homogeneous Fe(II) oxidation rate law, with adjustments for variations in temperature and CO2 outgassing rate, may be applied to predict changes in aqueous iron and pH for net-alkaline, ferruginous waters within a stream (natural conditions) or a CMD treatment system (engineered conditions).
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