Eutrophication of coastal waters due to nonpoint source land-derived nitrogen (N) loads is a worldwide phenomenon and perhaps the greatest agent of change altering coastal ecology (National Research Council, 2000; Howarth and others, 2000). Within the United States, a majority of estuaries have been determined to be moderately to severely impaired by eutrophication associated with increasing nutrient loads (Bricker and others, 1999).
In coastal watersheds with soils of high hydraulic conductivity and permeable coastal sediments, ground water is a major route of transport of freshwater and its solutes from land to sea. Freshwater flowing downgradient from aquifers may either discharge from a seepage face near the intertidal zone, or flow directly into the sea as submarine ground-water discharge (SGD) (fig. 1). In the coastal aquifer, entrainment of saline pore water occurs prior to discharge, producing a gradient in ground-water salinity from land to sea, referred to as a subterranean estuary (Moore, 1999). In addition, processes including density-driven flow and tidal pumping create brackish and saline ground-water circulation. Hence, submarine ground-water discharge often consists of a substantial amount of recirculating seawater. Mixing of fresh and saline ground waters in the context of coastal sediments may alter the chemical composition of the discharging fluid. Depending on the biogeochemical setting, removal of fixed N due to processes leading to N2 (dinitrogen gas) production in the nearshore aquifer and subterranean estuary may significantly attenuate land-derived N loads; or, processes such as ion exchange and tidal pumping in the subterranean estuary may substantially accelerate the transport of both land-derived and sediment re-mineralized N to estuarine water columns.
As emphasized by Burnett and others (2001, 2002), a fundamental problem in evaluating the importance of ground-water discharge in marine geochemical budgets is the difficulty of collecting samples across the salinity gradients of coastal aquifers. In addition, locating and quantifying rates of submarine ground-water discharge remains a challenge due to the diffuse and spatially and temporally heterogeneous nature of discharge. As a result, with regard to the study of biogeochemical cycles and chemical loads to coastal waters, the seepage face and subterranean estuary are relatively new and under-studied zones in the aquatic cascade from watershed to sea. Processes occurring in those zones must be understood and considered for proper modeling and management of coastal water resources.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20063110","usgsCitation":"Kroeger, K.D., Swarzenski, P.W., Crusius, J., Bratton, J.F., and Charette, M.A., 2006, Submarine ground-water discharge: nutrient loading and nitrogen transformations: U.S. Geological Survey Fact Sheet 2006-3110, 4 p., https://doi.org/10.3133/fs20063110.","productDescription":"4 p.","costCenters":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"links":[{"id":125095,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2006_3110.jpg"},{"id":9353,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2006/3110/","linkFileType":{"id":5,"text":"html"}},{"id":293248,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2006/3110/pdf/FS2006-3110.pdf","text":"Report","size":"296.37 kB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b05e4b07f02db699bed","contributors":{"authors":[{"text":"Kroeger, Kevin D. 0000-0002-4272-2349 kkroeger@usgs.gov","orcid":"https://orcid.org/0000-0002-4272-2349","contributorId":1603,"corporation":false,"usgs":true,"family":"Kroeger","given":"Kevin","email":"kkroeger@usgs.gov","middleInitial":"D.","affiliations":[{"id":41100,"text":"Coastal and Marine Hazards and Resources Program","active":true,"usgs":true}],"preferred":true,"id":289746,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Swarzenski, Peter W. 0000-0003-0116-0578 pswarzen@usgs.gov","orcid":"https://orcid.org/0000-0003-0116-0578","contributorId":1070,"corporation":false,"usgs":true,"family":"Swarzenski","given":"Peter","email":"pswarzen@usgs.gov","middleInitial":"W.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":289745,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Crusius, John 0000-0003-2554-0831 jcrusius@usgs.gov","orcid":"https://orcid.org/0000-0003-2554-0831","contributorId":2155,"corporation":false,"usgs":true,"family":"Crusius","given":"John","email":"jcrusius@usgs.gov","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":119,"text":"Alaska Science Center Geology Minerals","active":true,"usgs":true}],"preferred":true,"id":289747,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bratton, John F. 0000-0003-0376-4981 jbratton@usgs.gov","orcid":"https://orcid.org/0000-0003-0376-4981","contributorId":92757,"corporation":false,"usgs":true,"family":"Bratton","given":"John","email":"jbratton@usgs.gov","middleInitial":"F.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":289749,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Charette, Matthew A.","contributorId":92355,"corporation":false,"usgs":true,"family":"Charette","given":"Matthew","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":289748,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":79338,"text":"sir20065222 - 2006 - Hydrologic Characteristics of a Managed Wetland and a Natural Riverine Wetland along the Kankakee River in Northwestern Indiana","interactions":[],"lastModifiedDate":"2016-05-09T11:06:35","indexId":"sir20065222","displayToPublicDate":"2006-11-17T00:00:00","publicationYear":"2006","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":"2006-5222","title":"Hydrologic Characteristics of a Managed Wetland and a Natural Riverine Wetland along the Kankakee River in Northwestern Indiana","docAbstract":"Characteristics of ground-water/surface-water interactions were identified at a managed wetland (Hog Marsh) and a natural riverine wetland (LaSalle) located on the north and south sides, respectively, of the Kankakee River in northwestern Indiana. Hog Marsh covers about 390 hectares of the Grand Kankakee Marsh County Park. LaSalle covers about 100 hectares of the LaSalle State Fish and Wildlife Area, and is about 20 kilometers downstream of Hog Marsh. Hydrologic characteristics of the two wetlands were investigated using data from 1997 to 1999 for 22 wells adjacent to the Kankakee River in northwestern Indiana. Surface-water levels at the managed wetland were controlled by a system of channels, levees, and managed flooding. Surface-water levels at the natural riverine wetland were not controlled. Ground-water levels in the unconfined surficial aquifer beneath the two wetlands were analyzed by assessing water-level fluctuations. Fifteen wells at Hog Marsh and seven wells at LaSalle were monitored. The interquartile range in ground-water levels away from the river at Hog Marsh fluctuated less (from 0.4 to 0.7 meters) than all ground-water levels in the same aquifer beneath LaSalle (from 0.9 to 1.0 meters). The difference in the range of water-level fluctuation probably is attributable to the managed flooding of Hog Marsh units, which tends to maintain somewhat uniform water levels in that wetland. Ground-water-flow directions along a vertical section through the unconfined surficial aquifer at the managed wetland were more variable than those at the natural riverine wetland. During winter and spring, when flow in the Kankakee River is high, flow is from the Kankakee River into the adjacent surficial aquifer and towards a 2-meter-wide Brown Ditch on the north side of Hog Marsh. Water levels in Brown Ditch remain lower than those in the Kankakee River during this period. From June to December, when flow in the Kankakee River is moderate to low, a flow divide developed near the center of the managed wetland. Ground-water flow south of the divide is to the Kankakee River; north of the divide, it is toward Brown Ditch. Slight ground-water mounding near the center of the managed wetland is accentuated by water-management practices that intentionally flood that area. Ground-water flow in the surficial aquifer at the natural riverine wetland was not impeded by ditches or managed flooding, and a simple flow-through system from areas south of the Kankakee River to the river was observed. A ground-water flow model was constructed along a representative cross section through the surficial aquifer at the managed wetland and calibrated using data collected at the site. A no-flow boundary was used beneath the Kankakee River, and head-dependent boundaries were used along the north end of the model and at the base of the model. The model simulations indicated that artificial controls on the managed-wetland hydrology create sites of recharge to and discharge from the surficial aquifer that are absent at the natural riverine wetland. The steady-state flow simulation represented flow conditions following a 4-month period of no changes in hydrologic stresses. The simulation results indicated that flow paths originating from flooded areas near the center of the managed wetland are sources of aquifer recharge during the managed-flooding period. Brown Ditch captured almost all of the ground water north of the managed wetland. The simulated water budget along a well transect indicated that 88 percent of inflow to the surficial aquifer beneath the managed wetland was from a distribution channel and from flooding in the management units. These modeling results identify differences in flow patterns between the managed and natural riverine wetlands in addition to those identified by the water-level data. Results of transient simulations indicated that surface water from the Kankakee River penetrated only about 2 to 3 meters into the surficial aquif
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20065222","usgsCitation":"Arihood, L.D., Bayless, E.R., and Sidle, W.C., 2006, Hydrologic Characteristics of a Managed Wetland and a Natural Riverine Wetland along the Kankakee River in Northwestern Indiana: U.S. Geological Survey Scientific Investigations Report 2006-5222, vi, 78 p., https://doi.org/10.3133/sir20065222.","productDescription":"vi, 78 p.","startPage":"1","endPage":"78","numberOfPages":"84","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"links":[{"id":195561,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20065222.GIF"},{"id":8830,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2006/5222/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Indiana","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.27762222290039,\n 41.21750015595371\n ],\n [\n -87.27762222290039,\n 41.226086473772526\n ],\n [\n -87.2720217704773,\n 41.226086473772526\n ],\n [\n -87.2720217704773,\n 41.21750015595371\n ],\n [\n -87.27762222290039,\n 41.21750015595371\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ae1e4b07f02db688a64","contributors":{"authors":[{"text":"Arihood, Leslie D. 0000-0001-5792-3699 larihood@usgs.gov","orcid":"https://orcid.org/0000-0001-5792-3699","contributorId":2357,"corporation":false,"usgs":true,"family":"Arihood","given":"Leslie","email":"larihood@usgs.gov","middleInitial":"D.","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true},{"id":346,"text":"Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":289683,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bayless, E. Randall 0000-0002-0357-3635","orcid":"https://orcid.org/0000-0002-0357-3635","contributorId":42586,"corporation":false,"usgs":true,"family":"Bayless","given":"E.","email":"","middleInitial":"Randall","affiliations":[{"id":35860,"text":"Ohio-Kentucky-Indiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":289684,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sidle, William C.","contributorId":47885,"corporation":false,"usgs":true,"family":"Sidle","given":"William","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":289685,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":79393,"text":"ofr20061026 - 2006 - Salinity and temperature tolerance experiments on selected Florida Bay mollusks","interactions":[],"lastModifiedDate":"2025-04-18T15:06:41.473995","indexId":"ofr20061026","displayToPublicDate":"2006-11-17T00:00:00","publicationYear":"2006","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":"2006-1026","title":"Salinity and temperature tolerance experiments on selected Florida Bay mollusks","docAbstract":"The ultimate goal of the Comprehensive Everglades Restoration Plan (CERP) is to restore and preserve the unique ecosystems of South Florida, including the estuaries. Understanding the effect of salinity and temperature changes, beyond typical oscillations, on the biota of South Florida's estuaries is a necessary component of achieving the goal of restoring the estuaries. The U.S. Geological Survey has been actively involved in researching the history of the South Florida Ecosystem, to provide targets, performance measures, and baseline data for restoration managers. These experiments addressed two aspects of ecosystem history research: 1) determining the utility of using molluscan shells as recorders of change in water chemistry parameters, primarily salinity, and 2) enhancing our in situ observations on modern assemblages by exceeding typically observed aquatic conditions. This set of experiments expanded our understanding of the effects of salinity, temperature and other water chemistry parameters on the reproduction, growth and overall survivability of key species of mollusks used in interpreting sediment core data. Observations on mollusks, plants and microbes made as part of these experiments have further refined our knowledge and understanding of the effects of ecosystem feedback and the role salinity and temperature play in ecosystem stability. The results have demonstrated the viability of several molluscan species as indicators of atypical salinity, and possibly temperature, modulations. For example Cerithium muscarum and Bulla striata demonstrated an ability to withstand a broad salinity and temperature range, with reproduction occurring in atypically high salinities and temperatures. These experiments also provided calibration data for the shell biogeochemistry of Chione cancellata and the possible use of this species as a water chemistry recorder. Observations made in the mesocosms, on a scale not normally observable in the field, have led to new questions about the influence of salinity on the localized ecosystem. The next phase of these experiments; to calibrate growth rate and reproductive viability in atypical salinities is currently underway.","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20061026","usgsCitation":"Salinity and Temperature Tolerance Experiments on Selected Florida Bay Mollusks; 2006; OFR; 2006-1026; Murray, James B.; Wingard, G. Lynn","productDescription":"59 p.","numberOfPages":"59","costCenters":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true}],"links":[{"id":192351,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2006/1026/coverthb.jpg"},{"id":8893,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2006/1026/ofr2006-1026.pdf","text":"Report","size":"62.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2006-1026"}],"country":"United States","state":"Florida","otherGeospatial":"Florida Bay","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -80.35211958760377,\n 25.331996734474302\n ],\n [\n -81.54167471125137,\n 25.331996734474302\n ],\n [\n -81.54167471125137,\n 24.58719181605028\n ],\n [\n -80.35211958760377,\n 24.58719181605028\n ],\n [\n -80.35211958760377,\n 25.331996734474302\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Caribbean-Florida Water Science Center
U.S. Geological Survey
3321 College Avenue
Davie, FL 33314
Results of ground-water sampling from 255 wells and 19 springs in 11 studies done by the U.S. Geological Survey National Water-Quality Assessment (NAWQA) Program within the Piedmont Aquifer System (PAS) were analyzed to determine the factors affecting occurrence and distribution of selected contaminants. The contaminants, which were selected on the basis of potential human-health effects, included nitrate, pesticides, volatile organic compounds (VOCs), and radon.
The PAS was subdivided on the basis of the general rock type of the aquifers into three areas for the study—crystalline, carbonate, and siliciclastic. The 11 studies were designed to areally represent an individual aquifer rock type and overall are representative of the PAS in their distribution; 7 studies are in the crystalline-rock aquifers, 3 studies are in the siliciclasticrock aquifers, and 1 study is in the carbonate-rock aquifers. Four of the studies were focused on land use, 1 in an agricultural area and 3 in urban areas. The remaining studies had wells representing a range of land-use types.
Analysis of results of nitrate sampling indicated that in 8 of the 10 areas where nitrate concentrations were measured, median concentrations of nitrate were below 3 mg/L (milligrams per liter); 2 of the 10 areas had statistically significant higher median concentrations when compared to the other 8 areas. The agricultural land-use study in the carbonate-rock aquifer in the Lower Susquehanna River Basin had the highest median nitrate concentration (11 mg/L), and 60 percent of the wells sampled exceeded the U.S. Environmental Protection Agency (USEPA) Maximum Contaminant Level (MCL) of 10 mg/L. The major aquifer study in the crystalline-rock aquifer of the Lower Susquehanna River Basin Study Unit had the second-highest median nitrate concentration. Nitrate concentrations were positively correlated to the percentage of agricultural land use around the well, the total input of nitrogen from all sources, dissolved oxygen concentration, lithology, depth to water, and soil-matrix characteristics. A linear regression model was used to determine that increases in the percentage of agricultural land use, the input of nitrogen from all sources, and dissolved oxygen were the most significant variables affecting increased concentration of nitrate. A logistic regression model was used to determine that those same factors were the most significant variables affecting whether or not the nitrate concentration would exceed 4 mg/L.
Of the analysis of samples from 253 wells and 19 springs for 47 pesticides, no sample had a pesticide concentration that exceeded any USEPA MCL. The most frequently detected pesticide was desethyl atrazine, a degradation product of atrazine; the detection frequency was 47 percent. Other frequently detected pesticides included atrazine, metolachlor, simazine, alachlor, prometon, and dieldrin. Detection frequency was affected by the analytical reporting limits; the frequency of detection was somewhat lower when all pesticides were censored to the highest common detection limit. Source factors such as agricultural land use (for agricultural herbicides), urban land use (for insecticides), and the application rate were found to have positive statistical correlations with pesticide concentration. Transport factors such as depth to water and percentage of well-drained soils, sand, or silt typically were positively correlated with higher pesticide concentrations.
Sampling for VOCs was conducted in 187 wells and 19 springs that were sampled for 59 VOCs. There were 137 detections of VOCs above the common censoring limit of 0.2 µg/L. The most frequently detected VOCs were chloroform, a trihalomethane, and methyl-tert butyl ether (MTBE), a fuel oxygenate. Seventy-nine wells had at least one VOC detected. The detections were related to land use and well depth. Kendall’s tau correlations indicated a significant positive correlation between chloroform concentration and urban land use, leaking underground storage tanks, population density, and well depth. MTBE concentrations also were positively correlated to urban land use, leaking underground storage tanks, population density, and well depth.
Radon was sampled at 205 sites. The subdivisions used for analysis of other contaminants were not adequate for analysis of radon because radon varies on the basis of variations in mineralogy that are not reflected by the general lithologic categories used for the rest of the studies. Concentrations of radon were highest in areas where the crystalline-rock aquifers had felsic mineralogy, and the lowest concentrations of radon were in areas where the crystalline-rocks aquifer had mafic mineralogy. Water from wells in siliciclastic-rock aquifers had concentrations of radon lower than that in the felsic crystalline-rock aquifers. More than 90 percent of the wells sampled for radon exceeded the proposed MCL of 300 pCi/L (picoCuries per liter); however, only 13 percent of those wells had concentrations in water that exceeded the alternative maximum contaminant level (AMCL), a higher level that can be used by municipalities addressing other sources of radon exposure.
Overall, concentrations of constituents were related to land-use factors for nitrate, pesticides, VOCs, and to aquifer lithology for radon. None of the 47 pesticides or 59 VOCs analyzed exceeded the MCLs where those constituents were sampled. Concentrations exceeded the MCL for nitrate in 11 percent of the wells sampled. Nearly 91 percent of the wells sampled exceeded the proposed MCL for radon. Additional sampling in selected areas would improve overall understanding of the PAS and increase the possibility of creating predictive models of ground-water quality in this area.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20065104","usgsCitation":"Lindsey, B., Falls, W.F., Ferrari, M., Zimmerman, T.M., Harned, D.A., Sadorf, E.M., and Chapman, M.J., 2006, Factors affecting occurrence and distribution of selected contaminants in ground water from selected areas in the Piedmont Aquifer System, Eastern United States, 1993-2003: U.S. Geological Survey Scientific Investigations Report 2006-5104, x, 72 p.; 28 figs.; 22 tables, https://doi.org/10.3133/sir20065104.","productDescription":"x, 72 p.; 28 figs.; 22 tables","temporalStart":"1993-01-01","temporalEnd":"2003-12-31","costCenters":[],"links":[{"id":191253,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":8812,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2006/5104/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Alabama, Delaware, Georgia, Maryland, New Jersey, New York, North Carolina, Pennsylvania, South Carolina, Virginia","otherGeospatial":"Piedmont Aquifer System","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"properties\":{},\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-87.4072265625,32.47269502206151],[-87.802734375,32.10118973232094],[-85.517578125,31.952162238024975],[-83.1005859375,32.54681317351514],[-82.2216796875,32.91648534731439],[-81.298828125,33.46810795527896],[-80.68359375,33.8339199536547],[-80.244140625,34.379712580462204],[-78.134765625,35.06597313798418],[-77.7392578125,35.85343961959182],[-78.22265625,36.63316209558658],[-77.7392578125,37.579412513438385],[-75.76171875,39.842286020743394],[-73.916015625,40.81380923056958],[-74.44335937499999,41.47566020027821],[-75.7177734375,40.97989806962013],[-78.046875,39.470125122358176],[-78.57421875,38.92522904714054],[-79.2333984375,38.13455657705411],[-80.1123046875,37.26530995561875],[-80.8154296875,36.4566360115962],[-81.5625,35.60371874069731],[-81.6064453125,35.137879119634185],[-82.9248046875,34.379712580462204],[-83.3642578125,34.34343606848294],[-84.1552734375,34.125447565116126],[-85.4296875,33.7243396617476],[-86.66015624999999,33.137551192346145],[-87.4072265625,32.47269502206151]]]}}]}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a06e4b07f02db5f8860","contributors":{"authors":[{"text":"Lindsey, Bruce D. 0000-0002-7180-4319 blindsey@usgs.gov","orcid":"https://orcid.org/0000-0002-7180-4319","contributorId":434,"corporation":false,"usgs":true,"family":"Lindsey","given":"Bruce D.","email":"blindsey@usgs.gov","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":false,"id":289656,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Falls, W. Fred 0000-0003-2928-9795 wffalls@usgs.gov","orcid":"https://orcid.org/0000-0003-2928-9795","contributorId":2562,"corporation":false,"usgs":true,"family":"Falls","given":"W.","email":"wffalls@usgs.gov","middleInitial":"Fred","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":false,"id":289661,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ferrari, Matthew J.","contributorId":67082,"corporation":false,"usgs":true,"family":"Ferrari","given":"Matthew J.","affiliations":[],"preferred":false,"id":289662,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Zimmerman, Tammy M. 0000-0003-0842-6981 tmzimmer@usgs.gov","orcid":"https://orcid.org/0000-0003-0842-6981","contributorId":2359,"corporation":false,"usgs":true,"family":"Zimmerman","given":"Tammy","email":"tmzimmer@usgs.gov","middleInitial":"M.","affiliations":[{"id":532,"text":"Pennsylvania Water Science Center","active":true,"usgs":true}],"preferred":false,"id":289660,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Harned, Douglas A. daharned@usgs.gov","contributorId":1295,"corporation":false,"usgs":true,"family":"Harned","given":"Douglas","email":"daharned@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":289657,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sadorf, Eric M. emsadorf@usgs.gov","contributorId":2245,"corporation":false,"usgs":true,"family":"Sadorf","given":"Eric","email":"emsadorf@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":true,"id":289659,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Chapman, Melinda J. 0000-0003-4021-0320 mjchap@usgs.gov","orcid":"https://orcid.org/0000-0003-4021-0320","contributorId":1597,"corporation":false,"usgs":true,"family":"Chapman","given":"Melinda","email":"mjchap@usgs.gov","middleInitial":"J.","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":476,"text":"North Carolina Water Science Center","active":true,"usgs":true}],"preferred":true,"id":289658,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":79323,"text":"sir20065071 - 2006 - Estimation of nonpoint-source loads of total nitrogen, total phosphorous, and total suspended solids in the Black, Belle, and Pine River basins, Michigan, by use of the PLOAD model","interactions":[],"lastModifiedDate":"2017-02-06T09:28:20","indexId":"sir20065071","displayToPublicDate":"2006-11-16T00:00:00","publicationYear":"2006","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":"2006-5071","title":"Estimation of nonpoint-source loads of total nitrogen, total phosphorous, and total suspended solids in the Black, Belle, and Pine River basins, Michigan, by use of the PLOAD model","docAbstract":"The Lake St. Clair Regional Monitoring Project partners planned a 3-year assessment study of the surface water in the Lake St. Clair drainage basins in Michigan. This study included water-quality monitoring and analysis, collection of discrete (grab) and automatic water-quality samples, monitoring of bacteria, and the creation of a database to store all relevant data collected from past and future field-data-collection programs.
In cooperation with the Lake St. Clair Monitoring Project, the U.S. Geological Survey assessed nonpoint-source loads of nutrients and total suspended solids in the Black, Belle, and Pine River basins. The principal tool for the assessment study was the USEPA’s PLOAD model, a simplified GIS-based numerical program that generates gross estimates of pollutant loads. In this study, annual loads were computed for each watershed using the USEPA’s Simple Method, which is based on scientific studies showing a correlation between different land-use types and loading rates.
The two land-use data sets used in the study (representing 1992 and 2001) show a maximum of 0.02-percent change in any of the 15 land use categories between the two timeframes. This small change in land use is reflected in the PLOAD results of the study area between the two time periods. PLOAD model results for the 2001 land-use data include total-nitrogen loads from the Black, Belle, and Pine River basins of approximately 495,599 lb/yr, 156,561 lb/yr, and 121,212 lb/yr, respectively; total-phosphorus loads of 80,777 lb/yr, 25,493 lb/yr, and 19,655 lb/yr, respectively; and total-suspended-solids loads of 5,613,282 lb/yr, 1,831,045 lb/yr, and 1,480,352 lb/yr, respectively. The subbasins in the Black, Belle, and Pine River basin with comparatively high loads are characterized by comparatively high percentages of industrial, commercial, transportation, or residential land use.
The results from the PLOAD model provide useful information about the approximate average annual loading rates from the three study basins. In particular, the results identify subbasins with comparatively high loading rates per square mile. This could aid water-resources managers and planners in evaluation of the effectiveness of public expenditures for water-quality improvements, assessment of progress towards achieving established water-quality goals, and planning of preventive actions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20065071","collaboration":"In cooperation with the Lake St. Clair Regional Monitoring Project","usgsCitation":"Syed, A.U., and Jodoin, R.S., 2006, Estimation of nonpoint-source loads of total nitrogen, total phosphorous, and total suspended solids in the Black, Belle, and Pine River basins, Michigan, by use of the PLOAD model: U.S. Geological Survey Scientific Investigations Report 2006-5071, v, 42 p., https://doi.org/10.3133/sir20065071.","productDescription":"v, 42 p.","numberOfPages":"47","costCenters":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"links":[{"id":194533,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20065071.JPG"},{"id":8810,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2006/5071/ ","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Michigan","otherGeospatial":"Black River basin, Belle River basin, Pine River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -83.533333,\n 42.166667\n ],\n [\n -83.533333,\n 43.55\n ],\n [\n -82.283333,\n 43.55\n ],\n [\n -82.283333,\n 42.166667\n ],\n [\n -83.533333,\n 42.166667\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a0ae4b07f02db5fbc36","contributors":{"authors":[{"text":"Syed, Atiq U.","contributorId":14898,"corporation":false,"usgs":true,"family":"Syed","given":"Atiq","email":"","middleInitial":"U.","affiliations":[],"preferred":false,"id":289655,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jodoin, Richard S. rsjodoin@usgs.gov","contributorId":2533,"corporation":false,"usgs":true,"family":"Jodoin","given":"Richard","email":"rsjodoin@usgs.gov","middleInitial":"S.","affiliations":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"preferred":true,"id":289654,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":79321,"text":"sir20065275 - 2006 - Effects of Proposed Additional Ground-Water Withdrawals from the Mississippi River Valley Alluvial Aquifer on Water Levels in Lonoke County, Arkansas","interactions":[],"lastModifiedDate":"2012-02-10T00:11:44","indexId":"sir20065275","displayToPublicDate":"2006-11-16T00:00:00","publicationYear":"2006","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":"2006-5275","title":"Effects of Proposed Additional Ground-Water Withdrawals from the Mississippi River Valley Alluvial Aquifer on Water Levels in Lonoke County, Arkansas","docAbstract":"The Grand Prairie Water Users Association, located in Lonoke County, Arkansas, plans to increase ground-water withdrawals from the Mississippi River Valley alluvial aquifer from their current (2005) rate of about 400 gallons per minute to 1,400 gallons per minute (2,016,000 gallons per day). The effect of pumping from a proposed well was simulated using a digital model of ground-water flow. The proposed additional withdrawals were added to an existing pumping cell specified in the model, with increased pumping beginning in 2005, and specified to pump at a total combined rate of 2,016,000 gallons per day for a period of 46 years. In addition, pumping from wells owned by Cabot Water Works, located about 2 miles from the proposed pumping, was added to the model beginning in 2001 and continuing through to the end of 2049. \r\n\r\nSimulated pumping causes a cone of depression to occur in the alluvial aquifer with a maximum decline in water level of about 8.5 feet in 46 years in the model cell of the proposed well compared to 1998 withdrawals. However, three new dry model cells occur south of the withdrawal well after 46 years. This total water-level decline takes into account the cumulative effect of all wells pumping in the vicinity, although the specified pumping rate from all other model cells in 2005 is less than for actual conditions in 2005. After 46 years with the additional pumping, the water-level altitude in the pumped model cell was about 177.4 feet, which is 41.7 feet higher than 135.7 feet, the altitude corresponding to half of the original saturated thickness of the alluvial aquifer (a metric used to determine if the aquifer should be designated as a Critical Ground-Water Area (Arkansas Natural Resources Commission, 2006)).","language":"ENGLISH","doi":"10.3133/sir20065275","usgsCitation":"Czarnecki, J.B., 2006, Effects of Proposed Additional Ground-Water Withdrawals from the Mississippi River Valley Alluvial Aquifer on Water Levels in Lonoke County, Arkansas: U.S. Geological Survey Scientific Investigations Report 2006-5275, iv, 6 p., https://doi.org/10.3133/sir20065275.","productDescription":"iv, 6 p.","numberOfPages":"10","onlineOnly":"Y","costCenters":[],"links":[{"id":194648,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":8808,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2006/5275/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -93,32.5 ], [ -93,37 ], [ -89,37 ], [ -89,32.5 ], [ -93,32.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a4ae4b07f02db624d67","contributors":{"authors":[{"text":"Czarnecki, John B. jczarnec@usgs.gov","contributorId":2555,"corporation":false,"usgs":true,"family":"Czarnecki","given":"John","email":"jczarnec@usgs.gov","middleInitial":"B.","affiliations":[],"preferred":true,"id":289652,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":79330,"text":"ofr20061121 - 2006 - Surface-Water Quantity and Quality of the Upper Milwaukee River, Cedar Creek, and Root River Basins, Wisconsin, 2004","interactions":[],"lastModifiedDate":"2012-02-02T00:14:20","indexId":"ofr20061121","displayToPublicDate":"2006-11-16T00:00:00","publicationYear":"2006","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":"2006-1121","title":"Surface-Water Quantity and Quality of the Upper Milwaukee River, Cedar Creek, and Root River Basins, Wisconsin, 2004","docAbstract":"The U.S. Geological Survey, in cooperation with the Southeastern Wisconsin Regional Planning Commission (SEWRPC), collected discharge and water-quality data at nine sites in previously monitored areas of the upper Milwaukee River, Cedar Creek, and Root River Basins, in Wisconsin from May 1 through November 15, 2004. The data were collected for calibration of hydrological models that will be used to simulate how various management strategies will affect the water quality of streams. The data also will support SEWRPC and Milwaukee Metropolitan Sewerage District (MMSD) managers in development of the SEWRPC Regional Water Quality Management Plan and the MMSD 2020 Facilities Plan. These management plans will provide a scientific basis for future management decisions regarding development and maintenance of public and private waste-disposal systems.\r\n\r\nIn May 2004, parts of the study area received over 13 inches of precipitation (3.06 inches is normal). In June 2004, most of the study area received between 7 and 11 inches of rainfall (3.56 inches is normal). This excessive rainfall caused flooding throughout the study area and resultant high discharges were measured at all nine monitoring sites. For example, the mean daily discharge recorded at the Cedar Creek site on May 27, 2004, was 2,120 cubic feet per second. This discharge ranked ninth of the largest 10 mean daily discharges in the 75-year record, and was the highest discharge recorded since March 30, 1960. Discharge records from continuous monitoring on the Root River Canal near Franklin since October 1, 1963, indicated that the discharge recorded on May 23, 2004, ranked second highest on record, and was the highest discharge recorded since March 4, 1974.\r\n\r\nWater-quality samples were taken during two base-flow events and six storm events at each of the nine sites. Analysis of water-quality data indicated that most concentrations of dissolved oxygen, biological oxygen demand, fecal coliform bacteria, chloride, suspended solids, nitrate plus nitrite nitrogen, ammonia nitrogen, Kjeldahl nitrogen, total phosphorus, dissolved orthophosphorus, total copper, particulate mercury, dissolved mercury, particulate methylmercury, dissolved methylmercury, and total zinc were below U.S. Environmental Protection Agency (USEPA) and State of Wisconsin water-quality standards at all sites, with the exception of dissolved oxygen at the Kewaskum, Farmington, Root River Canal, Root River Racine, and Root River Mouth sites. Each of these sites had from several days to several weeks of daily average dissolved oxygen concentrations below the 5 milligrams per liter State of Wisconsin standard for aquatic life. The lowest dissolved oxygen concentrations were measured at the heavily urbanized Root River Mouth site in downtown Racine, Wisconsin, where elevated concentrations of ammonia may have contributed to oxygen consumption during oxidation of ammonia to nitrate. Additionally, the maximum concentrations of copper in several Root River samples exceeded draft USEPA Ambient Water-Quality Criteria (U.S. Environmental Protection Agency, 2003) for acute toxicity to several species of aquatic organisms.\r\n\r\nSubstantial water-quality changes were not correlated with hydrologic changes at any of the nine sites. Base-flow water-quality was generally indistinguishable from that sampled during storm events. The sparsely developed upper Milwaukee River and Cedar Creek Basins had relatively low ranges of contamination for all laboratory-reported parameters. For all nine sites, the highest reported concentrations of chloride (216 mg/L), total phosphorus (0.627 mg/L), ortho-phosphorus (0.136 mg/L), nitrate plus nitrate (9.32 mg/L), and copper (38 ?g/L) were reported for samples collected at the Root River Canal site. The highest concentrations of fecal coliforms (3,600 colonies per 100 mL) and Escherichia coli (2,300 colonies per 100 mL) were reported in samples collected at Kewaskum. The highest concentrations of s","language":"ENGLISH","doi":"10.3133/ofr20061121","usgsCitation":"Hall, D.W., 2006, Surface-Water Quantity and Quality of the Upper Milwaukee River, Cedar Creek, and Root River Basins, Wisconsin, 2004: U.S. Geological Survey Open-File Report 2006-1121, viii, 52 p.; 28 figs.; 14 tables, https://doi.org/10.3133/ofr20061121.","productDescription":"viii, 52 p.; 28 figs.; 14 tables","numberOfPages":"60","temporalStart":"2004-05-01","temporalEnd":"2004-11-15","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":194891,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":8819,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2006/1121/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ae5e4b07f02db68acf3","contributors":{"authors":[{"text":"Hall, David W.","contributorId":39362,"corporation":false,"usgs":true,"family":"Hall","given":"David","email":"","middleInitial":"W.","affiliations":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"preferred":false,"id":289672,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":79316,"text":"ofr20061215 - 2006 - Magnetotelluric Data, Rainier Mesa/Shoshone Mountain, Nevada Test Site, Nevada","interactions":[],"lastModifiedDate":"2012-02-02T00:14:20","indexId":"ofr20061215","displayToPublicDate":"2006-11-15T00:00:00","publicationYear":"2006","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":"2006-1215","title":"Magnetotelluric Data, Rainier Mesa/Shoshone Mountain, Nevada Test Site, Nevada","docAbstract":"Introduction: \r\nThe United States Department of Energy (DOE) and the National Nuclear Security Administration (NNSA) at their Nevada Site Office (NSO) are addressing ground-water contamination resulting from historical underground nuclear testing through the Environmental Management (EM) program and, in particular, the Underground Test Area (UGTA) project.\r\n\r\nDuring 2005, the U.S. Geological Survey (USGS), in cooperation with the DOE and NNSA-NSO, collected and processed data from twenty-six magnetotelluric (MT) and audio-magnetotelluric (AMT) sites at the Nevada Test Site. The 2005 data stations were located on and near Rainier Mesa and Shoshone Mountain to assist in characterizing the pre-Tertiary geology in those areas. These new stations extend the area of the hydrogeologic study previously conducted in Yucca Flat. The MT data presented in this report will help refine what is known about the character, thickness, and lateral extent of pre Tertiary confining units. Subsequent interpretation will include a three dimensional (3 D) character analysis and a two-dimensional (2 D) resistivity model. The purpose of this report is to release the MT sounding data. No interpretation of the data is included here. \r\n","language":"ENGLISH","doi":"10.3133/ofr20061215","usgsCitation":"Williams, J.M., Sampson, J.A., Rodriguez, B.D., and Asch, T., 2006, Magnetotelluric Data, Rainier Mesa/Shoshone Mountain, Nevada Test Site, Nevada (Version 1.0): U.S. Geological Survey Open-File Report 2006-1215, iii, 243 p., https://doi.org/10.3133/ofr20061215.","productDescription":"iii, 243 p.","numberOfPages":"246","onlineOnly":"Y","costCenters":[],"links":[{"id":194890,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":8799,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2006/1215/","linkFileType":{"id":5,"text":"html"}}],"edition":"Version 1.0","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a80e4b07f02db6493bf","contributors":{"authors":[{"text":"Williams, Jackie M.","contributorId":11217,"corporation":false,"usgs":true,"family":"Williams","given":"Jackie","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":289639,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sampson, Jay A.","contributorId":13939,"corporation":false,"usgs":true,"family":"Sampson","given":"Jay","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":289640,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rodriguez, Brian D. 0000-0002-2263-611X brod@usgs.gov","orcid":"https://orcid.org/0000-0002-2263-611X","contributorId":836,"corporation":false,"usgs":true,"family":"Rodriguez","given":"Brian","email":"brod@usgs.gov","middleInitial":"D.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":289638,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Asch, Theodore H.","contributorId":83617,"corporation":false,"usgs":true,"family":"Asch","given":"Theodore H.","affiliations":[],"preferred":false,"id":289641,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":79317,"text":"ofr20061328 - 2006 - Reserve Growth in Oil Fields of West Siberian Basin, Russia","interactions":[],"lastModifiedDate":"2018-08-28T16:20:39","indexId":"ofr20061328","displayToPublicDate":"2006-11-15T00:00:00","publicationYear":"2006","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":"2006-1328","title":"Reserve Growth in Oil Fields of West Siberian Basin, Russia","docAbstract":"Although reserve (or field) growth has proven to be an important factor contributing to new reserves in mature petroleum basins, it is still a poorly understood phenomenon. Limited studies show that the magnitude of reserve growth is controlled by several major factors, including (1) the reserve booking and reporting requirements in each country, (2) improvements in reservoir characterization and simulation, (3) application of enhanced oil recovery techniques, and (4) the discovery of new and extensions of known pools in discovered fields. Various combinations of these factors can affect the estimates of proven reserves in particular fields and may dictate repeated estimations of reserves during a field's life. This study explores the reserve growth in the 42 largest oil fields in the West Siberian Basin, which contain about 55 percent of the basin's total oil reserves.\r\n\r\nThe West Siberian Basin occupies a vast swampy plain between the Ural Mountains and the Yenisey River, and extends offshore into the Kara Sea; it is the richest petroleum province in Russia. About 600 oil and gas fields with original reserves of 144 billion barrels of oil (BBO) and more than 1,200 trillion cubic feet of gas (TCFG) have been discovered. The principal oil reserves and most of the oil fields are in the southern half of the basin, whereas the northern half contains mainly gas reserves.\r\n\r\nSedimentary strata in the basin consist of Upper Triassic through Tertiary clastic rocks. Most oil is produced from Neocomian (Lower Cretaceous) marine to deltaic sandstone reservoirs, although substantial oil reserves are also in the marine Upper Jurassic and continental to paralic Lower to Middle Jurassic sequences. The majority of oil fields are in structural traps, which are gentle, platform-type anticlines with closures ranging from several tens of meters to as much as 150 meters (490 feet). Fields producing from stratigraphic traps are generally smaller except for the giant Talin field which contains oil in Jurassic river-valley sandstones. Principal source rocks are organic-rich marine shales of the Volgian (uppermost Jurassic) Bazhenov Formation, which is 30-50 m (98- 164 feet) thick. Bazhenov-derived oils are mostly of medium gravity, and contain 0.8-1.3 percent sulfur and 2-5 percent paraffin. Oils in the Lower to Middle Jurassic clastics were sourced from lacustrine and estuarine shales of the Toarcian Togur Bed. These oils are medium to low gravity, with low sulfur (less than 0.25 percent) and high paraffin (commonly to 10 percent) contents.\r\n\r\nAmong the 42 fields analyzed for reserve growth, 30 fields are located in the Middle Ob region, which includes the Samotlor field with reserves of more than 25 BBO and the Fedorov field with reserves of about 5 BBO. Data used in the study include year of discovery, year of first production, annual and cumulative production, and remaining reserves reported by Russian reserve categories (A+B+C1 and C2) in January of each year. Correlation of these Russian resource categories to U.S. categories of the Society of Petroleum Engineers classification is complex and somewhat uncertain.\r\n\r\nReserve growth in oil fields of West Siberia was calculated using a newly developed Group Growth method, which requires that the total reserve (proven reserve plus cumulative production) of individual fields with an equal length of reserve record be added together starting with discovery year or the first production year. Then the annual growth factor (AGF), which is the ratio of total reserves of two consecutive years, is calculated for all years. Once AGFs have been calculated, the cumulative growth factor (CGF) is calculated by multiplying the AGFs of all the previous years. The CGF data are used to develop reserve growth models.\r\n\r\nThe West Siberian oil fields show a 13-fold reserve growth 20 years after the discovery year and only about a 2-fold growth after the first production year. This difference is attributed to extensive exploration and field delineation activities between the discovery and the first production years. Because of uncertainty in the length of evaluation time and in reported reserves during this initial period, reserve growth based on the first production year is more reliable for model development. However, reserve growth models based both on discovery year and first production year show rapid growth in the first few years and slower growth in the following years. In contrast, the reserve growth patterns for the conterminous United States and offshore Gulf of Mexico show a steady reserve increase throughout the productive lives of the fields. The different reserve booking requirements and the lack of capital investment for improved reservoir management and production technologies in West Siberian fields relative to U.S. fields are the probable causes for the difference in growth patterns.\r\n\r\nReserve growth models based on the first production year predict that the reserve growth potential in the 42 largest oil fields of West Siberia over a five-year period (1998-2003) ranges from 270-330 million barrels or 0.34-0.42 percent per year. For a similar five-year period (1996-2001), models for the conterminous United States predict a growth of 0.54-0.75 percent per year.\r\n\r\nThis abstract presents the contents of a poster prepared for the AAPG Hedberg Research Conference on Understanding World Oil Resources, November 12-17, 2006 - Colorado Springs, Colorado. A paper 'Reserve Growth in Oil Fields of West Siberian Basin, Russia' was published in Natural Resources Research, v. 12, no. 2, June, 2003.","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20061328","usgsCitation":"Verma, M., and Ulmishek, G.F., 2006, Reserve Growth in Oil Fields of West Siberian Basin, Russia (Version 1.0): U.S. Geological Survey Open-File Report 2006-1328, 96.0 x 42.0 inches, https://doi.org/10.3133/ofr20061328.","productDescription":"96.0 x 42.0 inches","onlineOnly":"Y","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":192544,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":8800,"rank":100,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2006/1328/","text":"Index Page","linkFileType":{"id":5,"text":"html"}},{"id":356881,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2006/1328/pdf/of06-1328poster.pdf","text":"Poster","size":"11 MB"}],"edition":"Version 1.0","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a28e4b07f02db61126f","contributors":{"authors":[{"text":"Verma, Mahendra K. mverma@usgs.gov","contributorId":1027,"corporation":false,"usgs":true,"family":"Verma","given":"Mahendra K.","email":"mverma@usgs.gov","affiliations":[{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":289642,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ulmishek, Gregory F.","contributorId":48971,"corporation":false,"usgs":true,"family":"Ulmishek","given":"Gregory","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":289643,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":79310,"text":"ofr20061183 - 2006 - Using packrat middens to assess how grazing influences vegetation change in Glen Canyon National Recreation Area, Utah","interactions":[],"lastModifiedDate":"2024-12-17T14:20:32.324373","indexId":"ofr20061183","displayToPublicDate":"2006-11-02T00:00:00","publicationYear":"2006","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":"2006-1183","title":"Using packrat middens to assess how grazing influences vegetation change in Glen Canyon National Recreation Area, Utah","docAbstract":"The fossil and sub-fossil plant macrofossils and pollen\r\ngrains found in packrat middens can serve as important proxies\r\nfor climate and vegetation change in the arid Southwestern\r\nUnited States. A new application for packrat midden research\r\nis in understanding post-settlement vegetation changes caused\r\nby the grazing of domesticated animals. This work examines\r\na series of 27 middens from Glen Canyon National Recreation\r\nArea (GLCA), spanning from 995 yr BP to the present, which\r\ndetail vegetation during the periods just prior to, and following,\r\nthe introduction of domesticated grazers. By comparing\r\nmiddens deposited before and after the start of grazing by\r\ndomesticated sheep and cattle, the effect on the native plant\r\ncommunities through time can be determined. This analysis of\r\nchange through time is augmented by measurements of change\r\nthrough space by contrasting contemporaneous middens from\r\nnearby similar grazed and ungrazed sites. These comparisons\r\nare only made possible by the presence of inaccessible\r\nungrazed areas surrounded by steep cliffs.\r\nMultivariate ordinations of the plant assemblages from\r\npackrat middens demonstrated that even though all middens\r\nwere selected from similar geologic substrates, soils, and\r\nvegetation type, their primary variability was site-to-site. This\r\nsuggests that selecting comparable grazed versus ungrazed\r\nstudy treatments would be difficult, and that two similar sites\r\nseveral kilometers apart should not be assumed to have been\r\nthe same prior to grazing without pre-grazing data. But, the\r\nchanges through time on grazed areas, as well as the differences\r\nbetween grazed and ungrazed areas in the diversity of\r\ncertain taxonomic groups, both suggest that grazing by domesticated\r\nungulates has had a noticeable effect on the vegetation.\r\nThe changes seen through time suggested that grazing lowered\r\nthe number of taxa recorded and lessened the pre-existing\r\ndifferences within sites, homogenizing the resultant plant\r\nassociations.\r\nLate Holocene pre-settlement middens, and modern\r\nmiddens from ungrazed areas, contained more native grasses, skunkbush sumac (Rhus trilobata), blackbrush (Coleogyne\r\nramosissima), winterfat (Krascheninnikovia lanata), Utah serviceberry\r\n(Amelanchier utahensis), and roundleaf buffaloberry\r\n(Shepherdia rotundifolia) than modern middens from grazed\r\nareas. Pollen data supported the macrofossil data, recording\r\ndecreases in pollen of the goosefoot family (Chenopodiaceae),\r\ngrass family (Poaceae), and globemallow (Sphaeralcea spp.)\r\nfrom pre- to post-settlement.","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20061183","usgsCitation":"Fisher, J.F., Cole, K.L., and Anderson, R.S., 2006, Using packrat middens to assess how grazing influences vegetation change in Glen Canyon National Recreation Area, Utah: U.S. Geological Survey Open-File Report 2006-1183, vi, 55 p., https://doi.org/10.3133/ofr20061183.","productDescription":"vi, 55 p.","numberOfPages":"61","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":194750,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":8794,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2006/1183/report.pdf","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Utah","otherGeospatial":"Glen Canyon National Recreation Area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.31204963537535,\n 37.7008801723826\n ],\n [\n -111.31204963537535,\n 37.12695480528001\n ],\n [\n -110.52613833423678,\n 37.12695480528001\n ],\n [\n -110.52613833423678,\n 37.7008801723826\n ],\n [\n -111.31204963537535,\n 37.7008801723826\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a14e4b07f02db602e8b","contributors":{"authors":[{"text":"Fisher, Jessica F.","contributorId":84464,"corporation":false,"usgs":true,"family":"Fisher","given":"Jessica","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":289626,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cole, Kenneth L.","contributorId":48533,"corporation":false,"usgs":true,"family":"Cole","given":"Kenneth","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":289625,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Anderson, R. Scott","contributorId":47041,"corporation":false,"usgs":true,"family":"Anderson","given":"R.","email":"","middleInitial":"Scott","affiliations":[],"preferred":false,"id":289624,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":5224706,"text":"5224706 - 2006 - Prevalence of Ehrlichia, Borrelia, and Rickettsial agents in Amblyomma americanum (Acari: Ixodidae) collected from nine states","interactions":[],"lastModifiedDate":"2023-12-04T21:03:57.207149","indexId":"5224706","displayToPublicDate":"2006-11-01T12:18:31","publicationYear":"2006","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2385,"text":"Journal of Medical Entomology","active":true,"publicationSubtype":{"id":10}},"displayTitle":"Prevalence of Ehrlichia, Borrelia, and Rickettsial agents in Amblyomma americanum (Acari: Ixodidae) collected from nine states","title":"Prevalence of Ehrlichia, Borrelia, and Rickettsial agents in Amblyomma americanum (Acari: Ixodidae) collected from nine states","docAbstract":"Ambyomma antericanum (L.) (Acari: Ixodidae) is an aggressive tick that feeds on humans during all postembryonic life stages. In many regions of the United States, it is the tick most commonly found attached to humans. Public health interest has grown recently, due to the recognition of new human pathogens transmitted by A. antericanum and the expanding distribution of the tick. A. americanum is a vector of several bacteria pathogenic to humans. Ehrlichia chaffeensis and Ehrlichia ewingii cause moderate-to-severe febrile illness. 'Rickettsia amblyommii,' a member of the spotted fever group Rickettsia, also has recently been implicated as a possible human pathogen based on serologic evidence from persons recovering from illness after a tick bite. We have determined the prevalence of infection of Ehrlichia chaffeensis, E. ewingii, 'Borrelia lonestari,' and R. amblyommii within A. americanum ticks from 29 sites in nine states. Overall infection prevalences were 4.7% for E. chaffeensis (range, 0-27%), 3.5% for E. ewingii (range, 0-18.6%), 2.5% for B. lonestari (range, 0-12.2%), and 41.2% for R. amblyommii (range, 0-84.0%). In addition, 87 ticks (4.3%) were infected with two or more bacteria. This report documents new distribution records for E. ewingii, B. lonestari, and R. amblyommii and underscores the nonhomogeneous distribution of pathogen foci of infection. Additional surveillance throughout the range of A. antericanum is warranted to increase physician and public awareness of the risk of disease to humans from exposure to the agents transmitted by this tick.","language":"English","publisher":"Oxford Academic","doi":"10.1093/jmedent/43.6.1261","usgsCitation":"Mixson, T., Campbell, S., Gill, J., Ginsberg, H.S., Reichard, M., Schultz, T., and Dasch, G., 2006, Prevalence of Ehrlichia, Borrelia, and Rickettsial agents in Amblyomma americanum (Acari: Ixodidae) collected from nine states: Journal of Medical Entomology, v. 43, no. 6, p. 1261-1268, https://doi.org/10.1093/jmedent/43.6.1261.","productDescription":"8 p.","startPage":"1261","endPage":"1268","numberOfPages":"8","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":489991,"rank":2,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://digitalcommons.uri.edu/pls_facpubs/162","text":"External Repository"},{"id":201867,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.er.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"43","issue":"6","noUsgsAuthors":false,"publicationDate":"2006-11-01","publicationStatus":"PW","scienceBaseUri":"4f4e4aaae4b07f02db668fb9","contributors":{"authors":[{"text":"Mixson, T.R.","contributorId":49489,"corporation":false,"usgs":true,"family":"Mixson","given":"T.R.","email":"","affiliations":[],"preferred":false,"id":342437,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Campbell, S.R.","contributorId":15721,"corporation":false,"usgs":true,"family":"Campbell","given":"S.R.","email":"","affiliations":[],"preferred":false,"id":342433,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gill, J.S.","contributorId":76046,"corporation":false,"usgs":true,"family":"Gill","given":"J.S.","email":"","affiliations":[],"preferred":false,"id":342438,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Ginsberg, Howard S. 0000-0002-4933-2466 hginsberg@usgs.gov","orcid":"https://orcid.org/0000-0002-4933-2466","contributorId":3204,"corporation":false,"usgs":true,"family":"Ginsberg","given":"Howard","email":"hginsberg@usgs.gov","middleInitial":"S.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":342434,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Reichard, M.V.","contributorId":48286,"corporation":false,"usgs":true,"family":"Reichard","given":"M.V.","email":"","affiliations":[],"preferred":false,"id":342436,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Schultz, T.L.","contributorId":100505,"corporation":false,"usgs":true,"family":"Schultz","given":"T.L.","email":"","affiliations":[],"preferred":false,"id":342439,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Dasch, G.A.","contributorId":33027,"corporation":false,"usgs":true,"family":"Dasch","given":"G.A.","email":"","affiliations":[],"preferred":false,"id":342435,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":79263,"text":"sir20065187 - 2006 - Simulation of Water Levels and Salinity in the Rivers and Tidal Marshes in the Vicinity of the Savannah National Wildlife Refuge, Coastal South Carolina and Georgia","interactions":[],"lastModifiedDate":"2017-01-12T10:26:13","indexId":"sir20065187","displayToPublicDate":"2006-10-30T00:00:00","publicationYear":"2006","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":"2006-5187","title":"Simulation of Water Levels and Salinity in the Rivers and Tidal Marshes in the Vicinity of the Savannah National Wildlife Refuge, Coastal South Carolina and Georgia","docAbstract":"The Savannah Harbor is one of the busiest ports on the East Coast of the United States and is located downstream from the Savannah National Wildlife Refuge, which is one of the Nation?s largest freshwater tidal marshes. The Georgia Ports Authority and the U.S. Army Corps of Engineers funded hydrodynamic and ecological studies to evaluate the potential effects of a proposed deepening of Savannah Harbor as part of the Environmental Impact Statement. These studies included a three-dimensional (3D) model of the Savannah River estuary system, which was developed to simulate changes in water levels and salinity in the system in response to geometry changes as a result of the deepening of Savannah Harbor, and a marsh-succession model that predicts plant distribution in the tidal marshes in response to changes in the water-level and salinity conditions in the marsh. Beginning in May 2001, the U.S. Geological Survey entered into cooperative agreements with the Georgia Ports Authority to develop empirical models to simulate the water level and salinity of the rivers and tidal marshes in the vicinity of the Savannah National Wildlife Refuge and to link the 3D hydrodynamic river-estuary model and the marsh-succession model. \r\n\r\nFor the development of these models, many different databases were created that describe the complexity and behaviors of the estuary. The U.S. Geological Survey has maintained a network of continuous streamflow, water-level, and specific-conductance (field measurement to compute salinity) river gages in the study area since the 1980s and a network of water-level and salinity marsh gages in the study area since 1999. The Georgia Ports Authority collected water-level and salinity data during summer 1997 and 1999 and collected continuous water-level and salinity data in the marsh and connecting tidal creeks from 1999 to 2002. Most of the databases comprise time series that differ by variable type, periods of record, measurement frequency, location, and reliability. \r\n\r\nUnderstanding freshwater inflows, tidal water levels, and specific conductance in the rivers and marshes is critical to enhancing the predictive capabilities of a successful marsh succession model. Data-mining techniques, including artificial neural network (ANN) models, were applied to address various needs of the ecology study and to integrate the riverine predictions from the 3D model to the marsh-succession model. ANN models were developed to simulate riverine water levels and specific conductance in the vicinity of the tidal marshes for the full range of historical conditions using data from the river gaging networks. ANN models were also developed to simulate the marsh water levels and pore-water salinities using data from the marsh gaging networks. Using the marsh ANN models, the continuous marsh network was hindcasted to be concurrent with the long-term riverine network. The hindcasted data allow ecologists to compute hydrologic parameters?such as hydroperiods and exposure frequency?to help analyze historical vegetation data.\r\n\r\nTo integrate the 3D hydrodynamic model, the marsh-succession model, and various time-series databases, a decision support system (DSS) was developed to support the various needs of regulatory and scientific stakeholders. The DSS required the development of a spreadsheet application that integrates the database, 3D hydrodynamic model output, and ANN riverine and marsh models into a single package that is easy to use and can be readily disseminated. The DSS allows users to evaluate water-level and salinity response for different hydrologic conditions. Savannah River streamflows can be controlled by the user as constant flow, a percentage of historical flows, a percentile daily flow hydrograph, or as a user-specified hydrograph. The DSS can also use output from the 3D model at stream gages near the Savannah National Wildlife Refuge to simulate the effects in the tidal marshes. The DSS is distributed with a two-dimensional (","language":"ENGLISH","doi":"10.3133/sir20065187","usgsCitation":"Conrads, P., Roehl, E.A., Daamen, R.C., and Kitchens, W.M., 2006, Simulation of Water Levels and Salinity in the Rivers and Tidal Marshes in the Vicinity of the Savannah National Wildlife Refuge, Coastal South Carolina and Georgia: U.S. Geological Survey Scientific Investigations Report 2006-5187, x, 134 p., https://doi.org/10.3133/sir20065187.","productDescription":"x, 134 p.","numberOfPages":"144","onlineOnly":"Y","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":194571,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":8742,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2006/5187/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Georgia, South Carolina","otherGeospatial":"Savannah National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.51031494140625,\n 31.811062019751912\n ],\n [\n -81.51031494140625,\n 32.55607364492026\n ],\n [\n -80.60531616210938,\n 32.55607364492026\n ],\n [\n -80.60531616210938,\n 31.811062019751912\n ],\n [\n -81.51031494140625,\n 31.811062019751912\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a7ee4b07f02db648602","contributors":{"authors":[{"text":"Conrads, Paul 0000-0003-0408-4208 pconrads@usgs.gov","orcid":"https://orcid.org/0000-0003-0408-4208","contributorId":764,"corporation":false,"usgs":true,"family":"Conrads","given":"Paul","email":"pconrads@usgs.gov","affiliations":[{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":false,"id":289517,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roehl, Edwin A.","contributorId":89242,"corporation":false,"usgs":true,"family":"Roehl","given":"Edwin","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":289519,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Daamen, Ruby C.","contributorId":105391,"corporation":false,"usgs":true,"family":"Daamen","given":"Ruby","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":289520,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kitchens, Wiley M. kitchensw@usgs.gov","contributorId":2851,"corporation":false,"usgs":true,"family":"Kitchens","given":"Wiley","email":"kitchensw@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":true,"id":289518,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":79264,"text":"sir20065211 - 2006 - Characterization of dissolved solids in water resources of agricultural lands near Manila, Utah, 2004-05","interactions":[],"lastModifiedDate":"2017-01-27T12:19:07","indexId":"sir20065211","displayToPublicDate":"2006-10-30T00:00:00","publicationYear":"2006","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":"2006-5211","title":"Characterization of dissolved solids in water resources of agricultural lands near Manila, Utah, 2004-05","docAbstract":"Agricultural lands near Manila, Utah, have been identified as contributing dissolved solids to Flaming Gorge Reservoir. Concentrations of dissolved solids in water resources of agricultural lands near Manila, Utah, ranged from 35 to 7,410 milligrams per liter. The dissolved-solids load in seeps and drains in the study area that discharge to Flaming Gorge Reservoir ranged from less than 0.1 to 113 tons per day. The most substantial source of dissolved solids discharging from the study area to the reservoir was Birch Spring Draw. The mean daily dissolved-solids load near the mouth of Birch Spring Draw was 65 tons per day.
The estimated annual dissolved-solids load imported to the study area by Sheep Creek and Peoples Canals is 1,330 and 13,200 tons, respectively. Daily dissolved-solid loads discharging to the reservoir from the study area, less the amount of dissolved solids imported by canals, for the period July 1, 2004, to June 30, 2005, ranged from 72 to 241 tons per day with a mean of 110 tons per day. The estimated annual dissolved-solids load discharging to the reservoir from the study area, less the amount of dissolved solids imported by canals, for the same period was 40,200 tons. Of this 40,200 tons of dissolved solids, about 9,000 tons may be from a regional source that is not associated with agricultural activities. The salt-loading factor is 3,670 milligrams per liter or about 5.0 tons of dissolved solids per acre-foot of deep percolation in Lucerne Valley and 1,620 milligrams per liter or 2.2 tons per acre-foot in South Valley.
The variation of δ87Sr with strontium concentration indicates some general patterns that help to define a conceptual model of the processes affecting the concentration of strontium and the δ87Sr isotopic ratio in area waters. As excess irrigation water percolates through soils derived from Mancos Shale, the δ87Sr isotopic ratio (0.21 to 0.69 permil) approaches one that is typical of deep percolation from irrigation on Mancos Shale. The boron concentration and δ11B value for the water sample from Antelope Wash, being distinctly different from water samples from other sites, is evidence that water in Antelope Wash may contain a substantial component of regional ground-water flow.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20065211","collaboration":"Prepared in cooperation with the Natural Resources Conservation Service","usgsCitation":"Gerner, S.J., Spangler, L., Kimball, B.A., and Naftz, D.L., 2006, Characterization of dissolved solids in water resources of agricultural lands near Manila, Utah, 2004-05 (Version 2.0, Revised June 2007): U.S. Geological Survey Scientific Investigations Report 2006-5211, vi, 36 p., https://doi.org/10.3133/sir20065211.","productDescription":"vi, 36 p.","numberOfPages":"42","onlineOnly":"Y","temporalStart":"2004-07-01","temporalEnd":"2005-06-30","costCenters":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"links":[{"id":194653,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":8743,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2006/5211/","linkFileType":{"id":5,"text":"html"}},{"id":334164,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2006/5211/PDF/SIR2006_5211.pdf"},{"id":334165,"rank":4,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/sir/2006/5211/PDF/Errata_SIR2006_5211.pdf","text":"Revision History"}],"country":"United States","state":"Utah","city":"Manila","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -109.9,40.916666666666664 ], [ -109.9,41.11666666666667 ], [ -109.6,41.11666666666667 ], [ -109.6,40.916666666666664 ], [ -109.9,40.916666666666664 ] ] ] } } ] }","edition":"Version 2.0, Revised June 2007","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e49f7e4b07f02db5f1ccb","contributors":{"authors":[{"text":"Gerner, Steven J. 0000-0002-5701-1304 sjgerner@usgs.gov","orcid":"https://orcid.org/0000-0002-5701-1304","contributorId":972,"corporation":false,"usgs":true,"family":"Gerner","given":"Steven","email":"sjgerner@usgs.gov","middleInitial":"J.","affiliations":[{"id":610,"text":"Utah Water Science Center","active":true,"usgs":true}],"preferred":true,"id":289521,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Spangler, L.E.","contributorId":54230,"corporation":false,"usgs":true,"family":"Spangler","given":"L.E.","email":"","affiliations":[],"preferred":false,"id":289523,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kimball, B. A.","contributorId":87583,"corporation":false,"usgs":false,"family":"Kimball","given":"B.","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":289524,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Naftz, D. L.","contributorId":40624,"corporation":false,"usgs":true,"family":"Naftz","given":"D.","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":289522,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":79267,"text":"sir20065160 - 2006 - Simulation of Streamflow and Water Quality to Determine Fecal Coliform and Nitrate Concentrations and Loads in the Mad River Basin, Ohio","interactions":[],"lastModifiedDate":"2012-03-08T17:16:19","indexId":"sir20065160","displayToPublicDate":"2006-10-30T00:00:00","publicationYear":"2006","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":"2006-5160","title":"Simulation of Streamflow and Water Quality to Determine Fecal Coliform and Nitrate Concentrations and Loads in the Mad River Basin, Ohio","docAbstract":"The Hydrological Simulation Program Fortran (HSPF) was used to simulate the concentrations and loads of fecal coliform and nitrate for streams in the Mad River Basin in west-central Ohio during the period 1999 through 2003. The Mad River Basin was divided into subbasins that were defined either by the 14-digit Hydrologic Unit (HU) boundaries or by streamflow-gaging-station locations used in the model. Model calibration and simulation processes required the formation of nine meteorologic zones to input meteorologic time-series data and water-quality data.\r\n\r\nSources of fecal coliform and nitrate from wastewater-treatment discharges and combined sewer overflow discharges (CSOs) within the City of Springfield were point sources simulated in the model. Failing septic systems and cattle with direct access to streams were nonpoint sources included in the study but treated in the model as point sources. Other nonpoint sources were addressed by adjusting interflow and ground-water concentrations in the subsurface and maximum storage capacities and accumulation rates of the simulated constituents on the land surface for each meteorologic zone. Simulation results from the calibrated model show that several HUs exceeded the water-quality standard of 1,000 colony-forming units per 100 mL for fecal coliform based on the maximum 30-day geometric mean. Most HUs with high fecal coliform counts were within or downstream from the City of Springfield. No water-quality standard has been set for instream nitrate concentrations; however, the Ohio Environmental Protection Agency (Ohio EPA) considered a concentration of 5 mg/L or greater to be of concern. Simulation results indicate that several HUs in the agricultural areas of the basin exceeded this level.\r\n\r\nThe calibrated model was modified to create scenarios that simulated loads of fecal coliform and nitrate that were either reduced or eliminated from selected sources. The revised models included the elimination of failing septic systems, elimination of direct access of cattle to streams, decrease in fecal coliform loads from the CSOs and selected wastewater-treatment facilities, and decrease in nitrate loads from land surfaces. The fecal coliform source-reduction model decreased the fecal coliform concentrations below a target concentration of 1,000 colonies per 100 milliliters for all HU outlets and decreased the load at the mouth of the Mad River by 73 percent. The nitrate source-reduction model decreased some HU mean concentrations to 5 milligrams per liter or less and decreased the load at the mouth of the Mad River by 52 percent. Other reduction scenarios may be run by Ohio EPA with the intent of identifying a management strategy that will attain a target concentration for the Mad River Basin.\r\n","language":"ENGLISH","doi":"10.3133/sir20065160","usgsCitation":"Reutter, D., Puskas, B.M., and Jagucki, M.L., 2006, Simulation of Streamflow and Water Quality to Determine Fecal Coliform and Nitrate Concentrations and Loads in the Mad River Basin, Ohio: U.S. Geological Survey Scientific Investigations Report 2006-5160, viii, 94 p., https://doi.org/10.3133/sir20065160.","productDescription":"viii, 94 p.","numberOfPages":"102","temporalStart":"1999-01-01","temporalEnd":"2003-01-01","costCenters":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"links":[{"id":191965,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":8746,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2006/5160/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4afee4b07f02db697847","contributors":{"authors":[{"text":"Reutter, David C. dreutter@usgs.gov","contributorId":5441,"corporation":false,"usgs":true,"family":"Reutter","given":"David C.","email":"dreutter@usgs.gov","affiliations":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"preferred":true,"id":289533,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Puskas, Barry M.","contributorId":59889,"corporation":false,"usgs":true,"family":"Puskas","given":"Barry","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":289534,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jagucki, Martha L. 0000-0003-3798-8393 mjagucki@usgs.gov","orcid":"https://orcid.org/0000-0003-3798-8393","contributorId":1794,"corporation":false,"usgs":true,"family":"Jagucki","given":"Martha","email":"mjagucki@usgs.gov","middleInitial":"L.","affiliations":[{"id":513,"text":"Ohio Water Science Center","active":true,"usgs":true}],"preferred":true,"id":289532,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":79268,"text":"ofr20061251 - 2006 - The National Assessment of Shoreline Change: A GIS compilation of vector shorelines and associated shoreline change data for the sandy shorelines of the California coast","interactions":[],"lastModifiedDate":"2021-08-16T21:46:44.331249","indexId":"ofr20061251","displayToPublicDate":"2006-10-30T00:00:00","publicationYear":"2006","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":"2006-1251","title":"The National Assessment of Shoreline Change: A GIS compilation of vector shorelines and associated shoreline change data for the sandy shorelines of the California coast","docAbstract":"Introduction\r\n\r\nThe Coastal and Marine Geology Program of the U.S. Geological Survey has generated a comprehensive data clearinghouse of digital vector shorelines and shoreline change rates for the sandy shoreline along the California open coast. These data, which are presented herein, were compiled as part of the U.S. Geological Survey's National Assessment of Shoreline Change Project.\r\n\r\nBeach erosion is a chronic problem along many open-ocean shores of the United States. As coastal populations continue to grow and community infrastructures are threatened by erosion, there is increased demand for accurate information including rates and trends of shoreline migration. There is also a critical need for shoreline change data that is consistent from one coastal region to another. One purpose of this work is to develop standard, repeatable methods for mapping and analyzing shoreline movement so that periodic, systematic, and internally consistent updates of shorelines and shoreline change rates can be made at a National Scale.\r\n\r\nThis data compilation for open-ocean, sandy shorelines of the California coast is one in a series that already includes the Gulf of Mexico and the Southeast Atlantic Coast (Morton et al., 2004; Morton et al., 2005) and will eventually cover Washington, Oregon, and parts of Hawaii and Alaska. Short- and long-term shoreline change evaluations are determined by comparing the positions of three historical shorelines digitized from maps, with a modern shoreline derived from LIDAR (light detection and ranging) topographic surveys. Historical shorelines generally represent the following time-periods: 1850s-1880s, 1920s-1930s, and late 1940s-1970s. The most recent shoreline is from data collected between 1997 and 2002. Long-term rates of change are calculated by linear regression using all four shorelines. Short-term rates of change are end-point rate calculations using the two most recent shorelines. Please refer to our full report on shoreline change of the California coastline at http://pubs.usgs.gov/of/2006/1219/ for additional information regarding methods and results (Hapke et al., 2006).\r\n\r\nData in this report are organized into downloadable layers by region (Northern, Central and Southern California) and are provided as vector datasets with metadata. Vector shorelines may represent a compilation of data from one or more sources and these sources are included in the dataset metadata. This project employs the Environmental Systems Research Institute's (ESRI) ArcGIS as it's GIS mapping tool and contains several data layers (shapefiles) that are used to create a geographic view of the California Coast. These vector data form a basemap comprised of polygon and line themes that include a U.S. coastline (1:80,000), U.S. cities, and state boundaries.","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20061251","usgsCitation":"Hapke, C.J., and Reid, D., 2006, The National Assessment of Shoreline Change: A GIS compilation of vector shorelines and associated shoreline change data for the sandy shorelines of the California coast (Version 1.1, Revised 2007): U.S. Geological Survey Open-File Report 2006-1251, HTML Document, https://doi.org/10.3133/ofr20061251.","productDescription":"HTML Document","additionalOnlineFiles":"Y","costCenters":[{"id":645,"text":"Western Coastal and Marine Geology","active":false,"usgs":true}],"links":[{"id":192428,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":387953,"rank":4,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_78137.htm"},{"id":8747,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2006/1251/"},{"id":8748,"rank":1000,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/of/2006/1219/"}],"scale":"80000","country":"United States","state":"California","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -124.4111,32.5353 ], [ -124.4111,42 ], [ -117.1203,42 ], [ -117.1203,32.5353 ], [ -124.4111,32.5353 ] ] ] } } ] }","edition":"Version 1.1, Revised 2007","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ac7e4b07f02db67b14e","contributors":{"authors":[{"text":"Hapke, Cheryl J. 0000-0002-2753-4075 chapke@usgs.gov","orcid":"https://orcid.org/0000-0002-2753-4075","contributorId":2981,"corporation":false,"usgs":true,"family":"Hapke","given":"Cheryl","email":"chapke@usgs.gov","middleInitial":"J.","affiliations":[{"id":6676,"text":"USGS (retired)","active":true,"usgs":false}],"preferred":true,"id":289535,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reid, David","contributorId":63888,"corporation":false,"usgs":true,"family":"Reid","given":"David","email":"","affiliations":[],"preferred":false,"id":289536,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":79284,"text":"ofr20061264 - 2006 - Catalog of earthquake hypocenters at Alaskan volcanoes: January 1 through December 31, 2005","interactions":[],"lastModifiedDate":"2022-12-08T23:16:11.872359","indexId":"ofr20061264","displayToPublicDate":"2006-10-30T00:00:00","publicationYear":"2006","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":"2006-1264","title":"Catalog of earthquake hypocenters at Alaskan volcanoes: January 1 through December 31, 2005","docAbstract":"The Alaska Volcano Observatory (AVO), a cooperative program of the U.S. Geological Survey, the Geophysical Institute of the University of Alaska Fairbanks, and the Alaska Division of Geological and Geophysical Surveys, has maintained seismic monitoring networks at historically active volcanoes in Alaska since 1988 (Figure 1). The primary objectives of the seismic program are the real-time seismic monitoring of active, potentially hazardous, Alaskan volcanoes and the investigation of seismic processes associated with active volcanism. This catalog presents calculated earthquake hypocenters and seismic phase arrival data, and details changes in the seismic monitoring program for the period January 1 through December 31, 2005.
The AVO seismograph network was used to monitor the seismic activity at thirty-two volcanoes within Alaska in 2005 (Figure 1). The network was augmented by two new subnetworks to monitor the Semisopochnoi Island volcanoes and Little Sitkin Volcano. Seismicity at these volcanoes was still being studied at the end of 2005 and has not yet been added to the list of permanently monitored volcanoes in the AVO weekly update. Following an extended period of monitoring to determine the background seismicity at the Mount Peulik, Ukinrek Maars, and Korovin Volcano, formal monitoring of these volcanoes began in 2005. AVO located 9,012 earthquakes in 2005.
Monitoring highlights in 2005 include: (1) seismicity at Mount Spurr remaining above background, starting in February 2004, through the end of the year and into 2006; (2) an increase in seismicity at Augustine Volcano starting in May 2005, and continuing through the end of the year into 2006; (3) volcanic tremor and seismicity related to low-level strombolian activity at Mount Veniaminof in January to March and September; and (4) a seismic swarm at Tanaga Volcano in October and November.
This catalog includes: (1) descriptions and locations of seismic instrumentation deployed in the field in 2005; (2) a description of earthquake detection, recording, analysis, and data archival systems; (3) a description of seismic velocity models used for earthquake locations; (4) a summary of earthquakes located in 2005; and (5) an accompanying UNIX tar-file with a summary of earthquake origin times, hypocenters, magnitudes, phase arrival times, and location quality statistics; daily station usage statistics; and all HYPOELLIPSE files used to determine the earthquake locations in 2005.
","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20061264","usgsCitation":"Dixon, J.P., Stihler, S.D., Power, J.A., Tytgat, G., Estes, S., and McNutt, S.R., 2006, Catalog of earthquake hypocenters at Alaskan volcanoes: January 1 through December 31, 2005 (Version 1.0): U.S. Geological Survey Open-File Report 2006-1264, HTML Document, https://doi.org/10.3133/ofr20061264.","productDescription":"HTML Document","additionalOnlineFiles":"Y","temporalStart":"2005-01-01","temporalEnd":"2005-12-31","costCenters":[{"id":121,"text":"Alaska Volcano Observatory","active":false,"usgs":true},{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"links":[{"id":410202,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_78271.htm","linkFileType":{"id":5,"text":"html"}},{"id":8766,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2006/1264/","linkFileType":{"id":5,"text":"html"}},{"id":190862,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20061264.JPG"}],"country":"United States","state":"Alaska","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -143.25,\n 50\n ],\n [\n -143.25,\n 62.333\n ],\n [\n -179.9,\n 62.333\n ],\n [\n -179.9,\n 50\n ],\n [\n -143.25,\n 50\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Version 1.0","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e49e3e4b07f02db5e5a27","contributors":{"authors":[{"text":"Dixon, James P. 0000-0002-8478-9971 jpdixon@usgs.gov","orcid":"https://orcid.org/0000-0002-8478-9971","contributorId":3163,"corporation":false,"usgs":true,"family":"Dixon","given":"James","email":"jpdixon@usgs.gov","middleInitial":"P.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":289578,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stihler, Scott D.","contributorId":31373,"corporation":false,"usgs":true,"family":"Stihler","given":"Scott","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":289579,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Power, John A. 0000-0002-7233-4398 jpower@usgs.gov","orcid":"https://orcid.org/0000-0002-7233-4398","contributorId":2768,"corporation":false,"usgs":true,"family":"Power","given":"John","email":"jpower@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":289577,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Tytgat, Guy","contributorId":71152,"corporation":false,"usgs":true,"family":"Tytgat","given":"Guy","email":"","affiliations":[],"preferred":false,"id":289582,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Estes, Steve","contributorId":55881,"corporation":false,"usgs":true,"family":"Estes","given":"Steve","email":"","affiliations":[],"preferred":false,"id":289581,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"McNutt, Stephen R.","contributorId":38133,"corporation":false,"usgs":true,"family":"McNutt","given":"Stephen","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":289580,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":79276,"text":"sir20065174 - 2006 - Water-quality changes caused by riverbank filtration between the Missouri River and three pumping wells of the Independence, Missouri, well field 2003-05","interactions":[],"lastModifiedDate":"2023-04-05T21:26:18.686729","indexId":"sir20065174","displayToPublicDate":"2006-10-30T00:00:00","publicationYear":"2006","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":"2006-5174","title":"Water-quality changes caused by riverbank filtration between the Missouri River and three pumping wells of the Independence, Missouri, well field 2003-05","docAbstract":"Riverbank filtration substantially improves the source-water quality of the Independence, Missouri well field. Coliform bacteria, Cryptosporidium, Giardia, viruses and selected constituents were analyzed in water samples from the Missouri River, two vertical wells, and a collector well.\r\n\r\nTotal coliform bacteria, Cryptosporidium, Giardia, and total culturable viruses were detected in the Missouri River, but were undetected in samples from wells. Using minimum reporting levels for non-detections in well samples, minimum log removals were 4.57 for total coliform bacteria, 1.67 for Cryptosporidium, 1.67 for Giardia, and 1.15 for total culturable virus. Ground-water flow rates between the Missouri River and wells were calculated from water temperature profiles and ranged between 1.2 and 6.7 feet per day. Log removals based on sample pairs separated by the traveltime between the Missouri River and wells were infinite for total coliform bacteria (minimum detection level equal to zero), between 0.8 and 3.5 for turbidity, between 1.5 and 2.1 for Giardia, and between 0.4 and 2.6 for total culturable viruses. Cryptosporidium was detected once in the Missouri River but no corresponding well samples were available. No clear relation was evident between changes in water quality in the Missouri River and in wells for almost all constituents. Results of analyses for organic wastewater compounds and the distribution of dissolved oxygen, specific conductance, and temperature in the Missouri River indicate water quality on the south side of the river was moderately influenced by the south bank inflows to the river upstream from the Independence well field.","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/sir20065174","usgsCitation":"Kelly, B.P., and Rydlund, P.H., 2006, Water-quality changes caused by riverbank filtration between the Missouri River and three pumping wells of the Independence, Missouri, well field 2003-05 (Version 1.0): U.S. Geological Survey Scientific Investigations Report 2006-5174, vi, 48 p., https://doi.org/10.3133/sir20065174.","productDescription":"vi, 48 p.","numberOfPages":"54","temporalStart":"2003-10-01","temporalEnd":"2005-09-30","costCenters":[],"links":[{"id":190714,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":415303,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_86823.htm","linkFileType":{"id":5,"text":"html"}},{"id":8757,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2006/5174/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Missouri","city":"Independence","otherGeospatial":"Missouri River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -94.5,\n 39.1833\n ],\n [\n -94.5,\n 39.1167\n ],\n [\n -94.35,\n 39.1167\n ],\n [\n -94.35,\n 39.1833\n ],\n [\n -94.5,\n 39.1833\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","edition":"Version 1.0","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e48cfe4b07f02db545d97","contributors":{"authors":[{"text":"Kelly, Brian P. 0000-0001-6378-2837 bkelly@usgs.gov","orcid":"https://orcid.org/0000-0001-6378-2837","contributorId":897,"corporation":false,"usgs":true,"family":"Kelly","given":"Brian","email":"bkelly@usgs.gov","middleInitial":"P.","affiliations":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true},{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":289554,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Rydlund, Paul H. Jr. 0000-0001-9461-9944 prydlund@usgs.gov","orcid":"https://orcid.org/0000-0001-9461-9944","contributorId":3840,"corporation":false,"usgs":true,"family":"Rydlund","given":"Paul","suffix":"Jr.","email":"prydlund@usgs.gov","middleInitial":"H.","affiliations":[{"id":396,"text":"Missouri Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true},{"id":502,"text":"Office of Surface Water","active":true,"usgs":true}],"preferred":true,"id":289555,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":79278,"text":"fs20063120 - 2006 - Ground-water modeling of the Death Valley Region, Nevada and California","interactions":[],"lastModifiedDate":"2017-07-13T10:58:22","indexId":"fs20063120","displayToPublicDate":"2006-10-30T00:00:00","publicationYear":"2006","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2006-3120","title":"Ground-water modeling of the Death Valley Region, Nevada and California","docAbstract":"The Death Valley regional ground-water flow system (DVRFS) of southern Nevada and eastern California covers an area of about 100,000 square kilometers and contains very complex geology and hydrology. Using a computer model to represent the complex system, the U.S. Geological Survey simulated ground-water flow in the Death Valley region for use with U.S. Department of Energy projects in southern Nevada. The model was created to help address contaminant cleanup activities associated with the underground nuclear testing conducted from 1951 to 1992 at the Nevada Test Site and to support the licensing process for the proposed geologic repository for high-level nuclear waste at Yucca Mountain, Nevada. \r\n","language":"English","publisher":"U.S. Geological Society","publisherLocation":"Henderson, NV","doi":"10.3133/fs20063120","usgsCitation":"Belcher, W., Faunt, C., Sweetkind, D.S., Blainey, J., San Juan, C.A., Laczniak, R.J., and Hill, M.C., 2006, Ground-water modeling of the Death Valley Region, Nevada and California (Version 1.0): U.S. Geological Survey Fact Sheet 2006-3120, 6 p., https://doi.org/10.3133/fs20063120.","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":125001,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2006_3120.jpg"},{"id":8759,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2006/3120/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"California, Nevada","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -118.10302734374999,\n 35.02999636902566\n ],\n [\n -114.7412109375,\n 35.02999636902566\n ],\n [\n -114.7412109375,\n 38.324420427006544\n ],\n [\n -118.10302734374999,\n 38.324420427006544\n ],\n [\n -118.10302734374999,\n 35.02999636902566\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Version 1.0","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ab0e4b07f02db66d5bd","contributors":{"authors":[{"text":"Belcher, W.R.","contributorId":30667,"corporation":false,"usgs":true,"family":"Belcher","given":"W.R.","email":"","affiliations":[],"preferred":false,"id":289559,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Faunt, C.C. 0000-0001-5659-7529","orcid":"https://orcid.org/0000-0001-5659-7529","contributorId":103314,"corporation":false,"usgs":true,"family":"Faunt","given":"C.C.","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":289565,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sweetkind, D. 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J.","contributorId":46104,"corporation":false,"usgs":true,"family":"Laczniak","given":"R.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":289561,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Hill, M. C.","contributorId":48993,"corporation":false,"usgs":true,"family":"Hill","given":"M.","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":289562,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":79254,"text":"ofr20061329 - 2006 - Preliminary geologic map of the White Sulphur Springs 30' x 60' Quadrangle, Montana","interactions":[],"lastModifiedDate":"2020-06-25T15:45:18.068126","indexId":"ofr20061329","displayToPublicDate":"2006-10-30T00:00:00","publicationYear":"2006","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":"2006-1329","displayTitle":"Preliminary Geologic Map of the White Sulphur Springs 30' x 60' Quadrangle, Montana","title":"Preliminary geologic map of the White Sulphur Springs 30' x 60' Quadrangle, Montana","docAbstract":"The geologic map of the White Sulphur Springs quadrangle, scale 1:100,000, was made as part of the Montana Investigations Project to provide new information on the stratigraphy, structure, and geologic history of the geologically complex area in west-central Montana. The quadrangle encompasses about 4,235 km2 (1,635 mi2), across part of the Smith River basin, the west end of the Little Belt Mountains, the Castle Mountains, and the upper parts of the basins of the North Forks of the Smith and Musselshell Rivers and the Judith River. Geologically the quadrangle extends across the eastern part of the Helena structural salient in the Rocky Mountain thrust belt, a segment of the Lewis and Clark tectonic zone, west end of the ancestral central Montana uplift, and the southwest edge of the Judith basin.\r\n\r\nRocks and sediments in the White Sulphur Springs quadrangle are assigned to 88 map units on the basis of rock or sediment type and age. The oldest rock exposed is Neoarchean diorite that is infolded with Paleoproterozoic metamorphic rocks including gneiss, diorite, granite, amphibolite, schist, and mixed metamorphic rock types. A thick succession of the Mesoproterozoic Belt Supergroup unconformably overlies the metamorphic rocks and, in turn, is overlain unconformably by Phanerozoic sedimentary and volcanic rocks. Across most of the quadrangle, the pre-Tertiary stratigraphic succession is intruded by Eocene dikes, sills, and plutons. The central part of the Little Belt Mountains is generally underlain by laccoliths and sheet-like bodies of quartz monzonite or dacite. Oligocene andesitic basalt flows in the western and southern part of the quadrangle document both the configuration of the late Eocene erosional surfaces and the extent of extensional faulting younger than early Oligocene in the area.\r\n\r\nPliocene, Miocene, and Oligocene strata, mapped as 11 units, consist generally of interbedded sand, gravel, and tuffaceous sedimentary rock. Quaternary and Quaternary-Tertiary sediments rest across the older Cenozoic deposits and across all older rocks. The Quaternary and Quaternary-Tertiary deposits generally are gravels that mantle broad erosional surfaces on the flanks of the mountains, gravels in stream channels, and colluvium and landslide deposits on hill sides. Glacial deposits, representing at least two stages of glaciation, are present in the northern part of the Little Belt Mountains.\r\n\r\nThe geologic structure of much of the northwest part of the quadrangle is a broad uplift, in the core of which the Paleoproterozoic and Neoarchean metamorphic rocks are exposed. Down plunge to the east, the succession of Phanerozoic sedimentary rocks define an east-trending arch, cored locally by Mesoproterozoic strata of the Belt Supergroup. The north flank of the arch dips steeply north as a monocline. Stratigraphic relations among Mississippian, Pennsylvanian, and Jurassic strata document the recurrent uplift and erosion on that north flank. The broader arch of the Little Belt Mountains reflects the west plunge of the ancestral Central Montana uplift.\r\n\r\nThe eastern extension of the Lewis and Clark tectonic zone is exposed in the southern half of the quadrangle where the Volcano Valley fault zone curves from west to southeast as a reverse fault along which the latest movement is up on the south side. The fault zone ends in an anticline in the south-central margin of the quadrangle. Stratigraphic overlap of Phanerozoic strata over the truncated edges of Mesoproterozoic units documents that the area of the eastern terminus of the fault zone was tectonically recurrently active.\r\n\r\nNortheast trending strike-slip faults displace Mesoproterozoic rocks in the northwest and south-central parts of the quadrangle. Several of those faults are overlain unconformably by the Middle Cambrian Flathead Sandstone. Other north-east and west-trending faults across the central part of the quadrangle are intruded by middle Eocene plutons. You","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20061329","usgsCitation":"Reynolds, M.W., and Brandt, T.R., 2006, Preliminary geologic map of the White Sulphur Springs 30' x 60' Quadrangle, Montana (Version 1.1): U.S. Geological Survey Open-File Report 2006-1329, 1 Map: 69.69 x 29.45 inches; HTML Document, https://doi.org/10.3133/ofr20061329.","productDescription":"1 Map: 69.69 x 29.45 inches; HTML Document","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":190597,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":8728,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2006/1329/","linkFileType":{"id":5,"text":"html"}},{"id":110682,"rank":700,"type":{"id":15,"text":"Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_78152.htm","linkFileType":{"id":5,"text":"html"},"description":"78152"}],"scale":"1","country":"United States","state":"Montana","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -111,46.5 ], [ -111,47 ], [ -110,47 ], [ -110,46.5 ], [ -111,46.5 ] ] ] } } ] }","edition":"Version 1.1","publicComments":"Version 1.1 is released to (a) revise on the basis of new fossil evidence the Cretaceous stratigraphy and nomenclature for strata the southeast part of the quadrangle, and (b) modify several line and polygon codes.","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4acce4b07f02db67e530","contributors":{"authors":[{"text":"Reynolds, Mitchell W. 0000-0002-9966-3896 mwreynol@usgs.gov","orcid":"https://orcid.org/0000-0002-9966-3896","contributorId":4641,"corporation":false,"usgs":true,"family":"Reynolds","given":"Mitchell","email":"mwreynol@usgs.gov","middleInitial":"W.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":289492,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brandt, Theodore R. 0000-0002-7862-9082 tbrandt@usgs.gov","orcid":"https://orcid.org/0000-0002-7862-9082","contributorId":1267,"corporation":false,"usgs":true,"family":"Brandt","given":"Theodore","email":"tbrandt@usgs.gov","middleInitial":"R.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":289491,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":79256,"text":"ofr20061299 - 2006 - Inversion of Gravity Data to Define the Pre-Cenozoic Surface and Regional Structures Possibly Influencing Groundwater Flow in the Rainier Mesa Region, Nye County, Nevada","interactions":[],"lastModifiedDate":"2012-02-10T00:11:41","indexId":"ofr20061299","displayToPublicDate":"2006-10-30T00:00:00","publicationYear":"2006","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":"2006-1299","title":"Inversion of Gravity Data to Define the Pre-Cenozoic Surface and Regional Structures Possibly Influencing Groundwater Flow in the Rainier Mesa Region, Nye County, Nevada","docAbstract":"A three-dimensional inversion of gravity data from the Rainier Mesa area and surrounding regions reveals a topographically complex pre-Cenozoic basement surface. This model of the depth to pre-Cenozoic basement rocks is intended for use in a 3D hydrogeologic model being constructed for the Rainier Mesa area. Prior to this study, our knowledge of the depth to pre-Cenozoic basement rocks was based on a regional model, applicable to general studies of the greater Nevada Test Site area but inappropriate for higher resolution modeling of ground-water flow across the Rainier Mesa area. The new model incorporates several changes that lead to significant improvements over the previous regional view. First, the addition of constraining wells, encountering old volcanic rocks lying above but near pre-Cenozoic basement, prevents modeled basement from being too shallow. Second, an extensive literature and well data search has led to an increased understanding of the change of rock density with depth in the vicinity of Rainier Mesa. The third, and most important change, relates to the application of several depth-density relationships in the study area instead of a single generalized relationship, thereby improving the overall model fit. In general, the pre-Cenozoic basement surface deepens in the western part of the study area, delineating collapses within the Silent Canyon and Timber Mountain caldera complexes, and shallows in the east in the Eleana Range and Yucca Flat regions, where basement crops out. In the Rainier Mesa study area, basement is generally shallow (< 1 km). The new model identifies previously unrecognized structures within the pre-Cenozoic basement that may influence ground-water flow, such as a shallow basement ridge related to an inferred fault extending northward from Rainier Mesa into Kawich Valley. ","language":"ENGLISH","doi":"10.3133/ofr20061299","usgsCitation":"Hildenbrand, T.G., Phelps, G., and Mankinen, E.A., 2006, Inversion of Gravity Data to Define the Pre-Cenozoic Surface and Regional Structures Possibly Influencing Groundwater Flow in the Rainier Mesa Region, Nye County, Nevada (Version 1.0): U.S. Geological Survey Open-File Report 2006-1299, 28 p., https://doi.org/10.3133/ofr20061299.","productDescription":"28 p.","numberOfPages":"28","costCenters":[{"id":314,"text":"Geophysics Unit of Menlo Park, CA (GUMP)","active":false,"usgs":true}],"links":[{"id":190630,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":8730,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2006/1299/","linkFileType":{"id":5,"text":"html"}},{"id":8733,"rank":9999,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2006/1299/version_history.txt","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -116.5,36.5 ], [ -116.5,37.5 ], [ -116,37.5 ], [ -116,36.5 ], [ -116.5,36.5 ] ] ] } } ] }","edition":"Version 1.0","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e48eae4b07f02db55519b","contributors":{"authors":[{"text":"Hildenbrand, Thomas G.","contributorId":61787,"corporation":false,"usgs":true,"family":"Hildenbrand","given":"Thomas","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":289500,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Phelps, Geoffrey A.","contributorId":17262,"corporation":false,"usgs":true,"family":"Phelps","given":"Geoffrey A.","affiliations":[],"preferred":false,"id":289499,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mankinen, Edward A. 0000-0001-7496-2681 emank@usgs.gov","orcid":"https://orcid.org/0000-0001-7496-2681","contributorId":1054,"corporation":false,"usgs":true,"family":"Mankinen","given":"Edward","email":"emank@usgs.gov","middleInitial":"A.","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":289498,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":79286,"text":"ofr20061293 - 2006 - Reconnaissance investigation of Caribbean extreme wave deposits — Preliminary observations, interpretations, and research directions","interactions":[],"lastModifiedDate":"2022-09-01T21:11:32.69718","indexId":"ofr20061293","displayToPublicDate":"2006-10-30T00:00:00","publicationYear":"2006","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":"2006-1293","title":"Reconnaissance investigation of Caribbean extreme wave deposits — Preliminary observations, interpretations, and research directions","docAbstract":"This report presents an overview of preliminary geological investigations and recommended future research activities in the Caribbean region pertaining to coastal hazards with an emphasis on establishing tsunami risk for U.S. territories. Fieldwork was conducted in March 2006 on the islands of Bonaire, Puerto Rico, and Guadeloupe to evaluate the stratigraphic records of extreme wave deposits as possible indicators of paleotsunami recurrence. Morphological, sedimentological, and stratigraphic evidence indicate that shore-parallel coral rubble deposits composed of coarse clasts and sand that are 10s of meters wide and several meters thick are depositional complexes that have accumulated for a few centuries or millennia, and are not entirely the result of one or a few tsunamis as previously reported. The origins of boulder fields on elevated rock platforms of the Caribbean islands are more complicated than the origins of ridge complexes because boulder fields can be constructed by either storm waves or tsunamis. What is needed now for more conclusive interpretations is a systematic sedimentological approach to deposit analysis and a set of criteria for distinguishing between coarse clast storm and tsunami deposits. Assembling more field data from other Caribbean islands, analyzing stratigraphic deposits on Puerto Rico and Bonaire, and investigating boulder field deposits resulting from a historical tsunami can accomplish this. Also needed are improved sediment transport models for coarse clasts that can be used to estimate the competence and capacity of tsunamis and storms waves and to determine whether a deposit likely was created by a tsunami or extreme storm. Improved models may also be useful for reconstructing the magnitude of extreme wave events.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20061293","usgsCitation":"Morton, R., Richmond, B.M., Jaffe, B.E., and Gelfenbaum, G., 2006, Reconnaissance investigation of Caribbean extreme wave deposits — Preliminary observations, interpretations, and research directions (Version 1.0): U.S. Geological Survey Open-File Report 2006-1293, ii, 41 p., https://doi.org/10.3133/ofr20061293.","productDescription":"ii, 41 p.","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"links":[{"id":324711,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20061293.GIF"},{"id":406100,"rank":4,"type":{"id":36,"text":"NGMDB Index 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1.0","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a74e4b07f02db64472a","contributors":{"authors":[{"text":"Morton, Robert A.","contributorId":88333,"corporation":false,"usgs":true,"family":"Morton","given":"Robert A.","affiliations":[],"preferred":false,"id":289592,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Richmond, Bruce M. 0000-0002-0056-5832 brichmond@usgs.gov","orcid":"https://orcid.org/0000-0002-0056-5832","contributorId":2459,"corporation":false,"usgs":true,"family":"Richmond","given":"Bruce","email":"brichmond@usgs.gov","middleInitial":"M.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":289590,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jaffe, Bruce E. 0000-0002-8816-5920 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California","interactions":[],"lastModifiedDate":"2018-09-19T18:53:15","indexId":"sir20065259","displayToPublicDate":"2006-10-30T00:00:00","publicationYear":"2006","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":"2006-5259","title":"The Effectiveness of Cattlemans Detention Basin, South Lake Tahoe, California","docAbstract":"Lake Tahoe (Nevada-California) has been designated as an 'outstanding national water resource' by the U.S. Environmental Protection Agency, in part, for its exceptional clarity. Water clarity in Lake Tahoe, however, has been declining at a rate of about one foot per year for more than 35 years. To decrease the amount of sediment and nutrients delivered to the lake by way of alpine streams, wetlands and stormwater detention basins have been installed at several locations around the lake. Although an improvement in stormwater and snowmelt runoff quality has been measured, the effectiveness of the detention basins for increasing the clarity of Lake Tahoe needs further study. It is possible that poor ground-water quality conditions exist beneath the detention basins and adjacent wetlands and that the presence of the basins has altered ground-water flow paths to nearby streams. A hydrogeochemical and ground-water flow modeling study was done at Cattlemans detention basin, situated adjacent to Cold Creek, a tributary to Lake Tahoe, to determine whether the focusing of storm and snowmelt runoff into a confined area has (1) modified the ground-water flow system beneath the detention basin and affected transport of sediment and nutrients to nearby streams and (2) provided an increased source of solutes which has changed the distribution of nutrients and affected nutrient transport rates beneath the basin.\r\n\r\nResults of slug tests and ground-water flow modeling suggest that ground water flows unrestricted northwest across the detention basin through the meadow. The modeling also indicates that seasonal flow patterns and flow direction remain similar from year to year under transient conditions. Model results imply that about 34 percent (0.004 ft3/s) of the total ground water within the model area originates from the detention basin. Of the 0.004 ft3/s, about 45 percent discharges to Cold Creek within the modeled area downstream of the detention basin. The remaining 55 percent of ground water is either consumed by evapotranspiration, is discharged to Cold Creek outside the modeled area downstream of the detention basin, or is discharged directly to Lake Tahoe. Of the 45 percent discharging to Cold Creek, about 9 percent enters directly downstream of the detention basin and 36 percent enters further downstream.\r\n\r\nGeochemical and microbial data suggest that a seasonal variation of chemical constituents and microbe population size is present at most wells. The geochemical data also indicate that construction of Cattlemans detention basin has not substantially changed the composition of the ground water in the area. High concentrations of ammonia, iron, and dissolved organic carbon, low concentrations of sulfate and nitrate, and large populations of sulfate-reducing microbes imply that the major geochemical process controlling nutrient concentrations beneath the detention basin is sulfate reduction. High concentrations of total nitrogen indicate that oxidation of organic carbon is a second important geochemical process occurring beneath the basin. The influx of surface runoff during spring 2002 apparently provided sufficient oxidized organic carbon to produce iron-reducing conditions and an increase in reduced iron, sulfate, and iron-reducing microorganisms. The increase in recharge of oxygenated water to the ground water system beneath the basin in future intervals of increased recharge may eventually redistribute nutrients and speed up transport of dissolved nutrients from the ground water system to Cold Creek.\r\n","language":"ENGLISH","doi":"10.3133/sir20065259","usgsCitation":"Green, J., 2006, The Effectiveness of Cattlemans Detention Basin, South Lake Tahoe, California: U.S. Geological Survey Scientific Investigations Report 2006-5259, viii, 81 p.; 32 figs.; 19 tables; Excel file, https://doi.org/10.3133/sir20065259.","productDescription":"viii, 81 p.; 32 figs.; 19 tables; Excel file","numberOfPages":"89","onlineOnly":"Y","temporalStart":"2001-01-01","temporalEnd":"2005-12-31","costCenters":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"links":[{"id":8754,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2006/5259/","linkFileType":{"id":5,"text":"html"}},{"id":194572,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ac9e4b07f02db67c9c6","contributors":{"editors":[{"text":"Green, Jena M.","contributorId":78033,"corporation":false,"usgs":true,"family":"Green","given":"Jena M.","affiliations":[],"preferred":false,"id":745700,"contributorType":{"id":2,"text":"Editors"},"rank":1}],"authors":[{"text":"Green, Jena M.","contributorId":78033,"corporation":false,"usgs":true,"family":"Green","given":"Jena M.","affiliations":[],"preferred":false,"id":289551,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":79257,"text":"ofr20061235 - 2006 - Evaluation of some software measuring displacements using GPS in real-time","interactions":[],"lastModifiedDate":"2019-04-08T10:46:35","indexId":"ofr20061235","displayToPublicDate":"2006-10-30T00:00:00","publicationYear":"2006","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":"2006-1235","title":"Evaluation of some software measuring displacements using GPS in real-time","docAbstract":"For the past decade, the USGS has been monitoring deformation at various locations in the western United States using continuous GPS. The main focus of these measurements are estimates of displacement averaged over one day. Essentially, these consist of recording at 30 seconds intervals the carrier-frequency phase-data (equivalent to travel-time) between a GPS receiver and the GPS satellite network. In turn, these observations, which are converted to pseudo—ranges, are processed using one of the “research grade” programs (GIPSY, Zumberge et al., or GAMIT, wwwgpsg.mit.edu/~simon/gtgk) to estimate the position of the GPS receiver averaged over 24 hours. However, it is possible and desirable to estimate the position of the receiver (actually the antenna) more frequently and to do this within a few seconds of the time actual measurement (known as real-time). A recent example, the 2004 Magnitude 6, Parkfield, California earthquake, demonstrated that having GPS estimates of position more frequently than simply a daily average is required if one requires discrimination between co-seismic and post-seismic deformation (Langbein et al., 2006). The high-rate estimates of position obtained at Parkfield show that post-seismic deformation started less than one-hour after the mainshock and that this deformation was roughly the same magnitude as the co-seismic deformation. The high-rate solutions for Parkfield were done by others including Yehuda Bock at UCSD and Kristine Larson at U. of Colorado, but not the USGS.
The Parkfield experience points out the need for an in-house capability by the USGS to be able to accurately measure co-seismic displacements and other rapid, deformation signals using GPS. This applies to both the Earthquake and Volcano Hazard programs. Although at many locations where we monitor deformation, we have strainmeters and tiltmeters in addition to GPS which, in principle, are far more sensitive to rapid deformation over periods of less than a day (Langbein and Bock, 2004). But, not all locales include strain and tiltmeters. Thus, having the capability to extract signals with periods of less than a day is desirable since the distribution of GPS is more extensive than strain and tilt.
At both Parkfield and Long Valley, the USGS has been using other software packages to process the GPS data at sub-daily intervals and in real-time. The underlying goal of these types of measurements is to detect any deformation event as it evolves; the 24 hour processing might not provide timely results if such a deformation event is precursory to a geologic hazard (an earthquake for Parkfield and either a volcanic event or an earthquake for Long Valley).
In Long Valley, We use the software package called 3DTracker (http://www.3dtracker.com, http://www.condorearth.com) to estimate the changes of in position of a remote site relative to a “fixed” site. The 3DTracker software uses double difference GPS code measurements and receiversatellite-time triple differences from one epoch to the next of the GPS phase data (a proxy for travel-time measurements) and employs a Kalman filter to obtain stability in the estimate of position. That is, the estimate of the current position depends upon the estimate of the prior position. Hence, a time series of position looks fairly smooth depending upon the coefficient selected for the Kalman filter. With triple differences, the sometimes troublesome initial integer cycle ambiguity terms cancel (number of wavelengths between the receiver and each satellite), but only the incremental change in position is calculated. This triple difference Kalman filter solution is slow to converge and less accurate than a double difference (e.g., RTD, Track) solution, but it is robust and computationally efficient (Remondi and Brown, 2000). 3D-Tracker allows use of various single-frequency and dual-frequency GPS phase and code observables including the ionospheric-free combinations (known as LC or L3 and P(L3)) formed from an linear combination of the L1 and L2 carrier phase and code data. The lowest noise observable is the L1 carrier, but it is biased by ionospheric refraction that has amplitudes of about 1 to 10 ppm. This results in a systematic scale error in the relative positions. The L3 phase noise is about 3 times greater than the L1 phase noise, but it is generally used to solve for all but the shortest baselines (< 5 km). In addition, the software does output the position changes is a standard format that can be used for other analysis.
At Parkfield, we use the software package called RTD (http://www.geodetics.com). The RTD software has been described in the literature (Bock et al., 2000) but basically, it estimates the position without the constraint of a Kalman filter. It uses double differences (in our studies the LC or ionospheric free observable is used) and the integer ambiguities are resolved independently for each 1-second measurement; Most GPS software that use double-differences require several epochs of measurements to resolve the integer ambiguities. The data files use a proprietary format and can not be read by me or others; rather, Yehuda Bock at UCSD (and author of RTD) translates these files into a standard format that can be read by me.
Recently, Tom Herring of MIT has modified the GAMIT software to process kinematically GPS data (www-gpsg.mit.edu/~simon/gtgk/tutorial/Lecture_13.pdf). At this time, the software, known as TRACK, does not process the observations in real-time. Consequently, the latency between the time of the observation and the time when a position estimate is available depends upon the frequency that the data are downloaded and the speed of actually processing the observations; there could be a delay of an hour or two before the a position estimates are available. Unlike RTD and 3DTracker, TRACK comes with GAMIT (which is distributed freely) and is currently operating in a test mode at the USGS office in Pasadena. The LC or ionosphere free observable is used in our TRACK solutions.
JPL has a version of their GIPSY software called “Real-time GIPSY (RTG)” (gipsy.jpl.nasa.gov/orms/rtg), which, like TRACK, can process the pseudo-range data “off—line”. However, this software is not freely distributed. Instead, at least one company, NAVCOM, has teamed with JPL to integrate RTG with GPS receivers and telemetry that yields positions in realtime.
Kristine Larson of University of Colorado has modified the original GIPSY to estimate positions kinematically. Again, like TRACK, the positions are estimated off—line. Much of her research is described in Larson et al. (2003), and Choi et al. (2004).
For Long Valley, out of the 17 GPS sites, we monitor 5 baselines within the caldera at 5 second intervals relative to the Bald Mountain site at the edge of the caldera using 3DTracker. The baseline measurement using 3DTracker consists of determination of the 3 dimensional positions of the 5 remote points (GPS receivers) relative to a GPS site at Bald. A second, independent system collects and downloads once a day the 30-second data used for the 24-hour solutions for the 12 sites not monitored with 3DTracker. For the sites monitored with 3DTracker, the pseudo—range data are decimated to 30 seconds and converted to a form used for the 24-hour solutions. Both sets of telemetry employ 900 MHz spread spectrum radios which require line of site between all of the links. The telemetry for the 3DTracker sites require a dedicated radios at each end and intermediate repeaters as needed, while the telemetry required for the other sites use a single master radio, repeaters as needed, and a radio at each remote site. (The 5 sites being monitored with 3DTracker require 13 radios.)
At Parkfield, RTD is used to measure the position changes all 12 baselines at 1 second intervals relative to a site, Pomm, adjacent to the San Andreas Fault. The complete RTD package (hardware and software) collects all of the data and determines the position of each site relative to Pomm. In addition, the system stores both the 1-second and 30-second pseudo-range data for later downloading which are ultimately used in the 24-hour solutions. To do this, each site has a 2.4 GHz radio and a telemetry buffer. The telemetry buffer holds 24-hours of data (in the event that the telemetry link is broken) and converts the RS232 data stream from the GPS receiver into a form compatible with an IP (Internet protocol) network connection. In contrast with the Long Valley system, the telemetry link for GPS at Parkfield consists of a single radio at each remote sites and a single radio at the central site. Although position estimates are produced within 1-second of the observations, these results are not immediately available because there is no high speed Internet connection to Parkfield. Instead, the data are stored on a removable disk and sent to UCSD once per month.
Below, I describe the results of a simple experiment to examine the response of some of these systems to simulated deformation that could be an analogue of a tectonic or volcanic event. In many engineering applications, the system response is tested by inputting a step to the system and measuring the output of the system. Essentially, this is what I've done. The experiment described below moves the GPS antenna from its original position to a new position within 1 second; the software tracks the translation. These measurements were conducted in August 2004 with the RTD software at Parkfield, and twice in Long Valley. The first Long Valley test was conducted in September 2004 using 3DTracker on a single baseline. The test was repeated in September 2005 using 3DTracker on two baselines and, importantly, saving the RINEX files of the data so that the data could be replayed through 3DTracker using other options in the program and, using other software packages including TRACK.
In addition, we observed a short-term event at the Three Sisters volcano in Oregon. This event was snow melt at a remote GPS site which gave an apparent 15 cm displacement in vertical in less than one-day. 3DTracker is used to monitor this site, and the event was captured with this software. In addition, with the assistance of others, I got additional estimates of position using other software packages; those results are presented.
Finally, the precision of both 3DTracker and RTD are compared using a power spectrum. Those results would suggest that 3DTracker using appropriate Kalman filter coefficients would have better precision than RTD; instead, the lower noise level from 3DTracker is a result of smoothing from the Kalman filter.
Given the results described in this report, high-rate GPS is certainly capable of accurately measuring displacements of 1 centimeter with a high degree of statistical confidence. Plotting these results show that the time of the displacement can be visually determined to that of the sampling interval of the data. However, especially with small amplitude signals, any of the software packages can yield erroneous deformation “signals” that are either due excess travel-time of the GPS carrier frequency from multipath or a limitation in the software. Thus, the time series of displacements must be viewed with caution and knowledge of external circumstances that might cause a change in position.
The casual reader should continue with the next section describing the methods then jump to the last two sections for the discussion and conclusions. I have made some recommendations there.
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