The Appalachian Valley and Piedmont Regional Aquifer-System Analysis study (1988-1993) analyzed rock types in the 142,000-square-mile study area, identified hydrogeologic terranes, determined transmissivity distributions, determined the contribution of ground water to streamflow, modeled ground-water flow, described water quality, and identified areas suitable for the potential development of municipal and industrial ground-water supplies. Ground-water use in the Valley and Ridge, the Blue Ridge, and the Piedmont Physiographic Provinces exceeds 1.7 billion gallons per day.
Thirty-three rock types in the study area were analyzed, and the rock types with similar water-yielding characteristics were combined and mapped as 10 hydrogeologic terranes. Based on well records, the interquartile ranges of estimated transmissivities are between 180 to 17,000 feet squared per day (ft2/d) for five hydrologic terranes in the Valley and Ridge; between 9 to 350 ft2/d for two terranes in the Blue Ridge; and between 9 to 1,400 ft2/d for three terranes in the Piedmont Physiographic Province. Based on streamflow records, the interquartile ranges of estimated transmissivities for all three physiographic provinces are between 290 and 2,900 ft2/d. The mean ground-water contribution to streams from 157 drainage basins ranges from 32 to 94 percent of mean streamflow with a median of 67 percent. In three small areas in two of the physiographic provinces, more than 54 percent of ground-water flow was modeled as shallow and local. Although ground-water chemical composition in the three physiographic provinces is distinctly different, the water generally is not highly mineralized, with a median dissolved-solids concentration of 164 milligrams per liter, and is mostly calcium, magnesium, and bicarbonate. Based on aquifer properties and current pumpage, areas favorable for the development of municipal and industrial ground-water supplies are underlain by alluvium of glacial origin near the northeastern part of the study area, by clay-free carbonate rocks primarily in the Valley and Ridge Physiographic Province, and by siliciclastic rocks in the three northernmost Mesozoic basins.
","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/pp1422A","usgsCitation":"Swain, L.A., Mesko, T.O., and Hollyday, E.F., 2004, Summary of the hydrogeology of the Valley and Ridge, Blue Ridge, and Piedmont Physiographic Provinces in the eastern United States: U.S. Geological Survey Professional Paper 1422, vi, 23 p., https://doi.org/10.3133/pp1422A.","productDescription":"vi, 23 p.","costCenters":[],"links":[{"id":184915,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":5796,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/pp/pp1422A/","linkFileType":{"id":5,"text":"html"}},{"id":344113,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/pp/pp1422A/PDF/pp1422A.pdf","text":"Report","size":"7.07 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"country":"United States","state":"Alabama, Delaware, Georgia, Maryland, New Jersey, North Carolina, Pennsylvania, South Carolina, Tennessee, Virginia, West Virginia","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.916015625,\n 41.04621681452063\n ],\n [\n -75.0146484375,\n 41.68932225997044\n ],\n [\n -75.34423828125,\n 41.88592102814744\n ],\n [\n -75.87158203125,\n 41.902277040963696\n ],\n [\n -76.75048828125,\n 41.65649719441145\n ],\n [\n -78.24462890625,\n 40.91351257612758\n ],\n [\n -80.04638671875,\n 39.8928799002948\n ],\n [\n -80.6396484375,\n 39.07890809706475\n ],\n [\n -82.5732421875,\n 37.38761749978395\n ],\n [\n -84.48486328124999,\n 36.686041276581925\n ],\n [\n -85.078125,\n 36.54494944148322\n ],\n [\n -86.15478515625,\n 36.2265501474709\n ],\n [\n -87.07763671875,\n 35.817813158696616\n ],\n [\n -87.64892578125,\n 35.31736632923788\n ],\n [\n -87.69287109375,\n 34.52466147177172\n ],\n [\n -87.73681640625,\n 33.94335994657882\n ],\n [\n -87.56103515625,\n 33.247875947924385\n ],\n [\n -87.20947265625,\n 32.84267363195431\n ],\n [\n -86.33056640625,\n 32.91648534731439\n ],\n [\n -84.287109375,\n 33.44977658311846\n ],\n [\n -81.93603515625,\n 34.415973384481866\n ],\n [\n -80.15625,\n 35.62158189955968\n ],\n [\n -79.013671875,\n 36.98500309285596\n ],\n [\n -77.62939453125,\n 38.25543637637947\n ],\n [\n -76.79443359375,\n 39.36827914916014\n ],\n [\n -75.78369140625,\n 39.757879992021756\n ],\n [\n -75.3662109375,\n 39.9434364619742\n ],\n [\n -74.68505859374999,\n 40.212440718286466\n ],\n [\n -74.15771484375,\n 40.66397287638688\n ],\n [\n -73.916015625,\n 41.04621681452063\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b00e4b07f02db69814e","contributors":{"authors":[{"text":"Swain, Lindsay A.","contributorId":7323,"corporation":false,"usgs":true,"family":"Swain","given":"Lindsay","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":257885,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mesko, Thomas O.","contributorId":81498,"corporation":false,"usgs":true,"family":"Mesko","given":"Thomas","email":"","middleInitial":"O.","affiliations":[],"preferred":false,"id":257887,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hollyday, Este F.","contributorId":27089,"corporation":false,"usgs":true,"family":"Hollyday","given":"Este","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":257886,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":53296,"text":"ofr20041042 - 2004 - A new streamflow-routing (SFR1) package to simulate stream-aquifer interaction with MODFLOW-2000","interactions":[],"lastModifiedDate":"2020-02-05T19:53:30","indexId":"ofr20041042","displayToPublicDate":"2004-09-01T00:00:00","publicationYear":"2004","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":"2004-1042","title":"A new streamflow-routing (SFR1) package to simulate stream-aquifer interaction with MODFLOW-2000","docAbstract":"The increasing concern for water and its quality require improved methods to evaluate the interaction between streams and aquifers and the strong influence that streams can have on the flow and transport of contaminants through many aquifers. For this reason, a new Streamflow-Routing (SFR1) Package was written for use with the U.S. Geological Survey's MODFLOW-2000 ground-water flow model. The SFR1 Package is linked to the Lake (LAK3) Package, and both have been integrated with the Ground-Water Transport (GWT) Process of MODFLOW-2000 (MODFLOW-GWT). SFR1 replaces the previous Stream (STR1) Package, with the most important difference being that stream depth is computed at the midpoint of each reach instead of at the beginning of each reach, as was done in the original Stream Package. This approach allows for the addition and subtraction of water from runoff, precipitation, and evapotranspiration within each reach. Because the SFR1 Package computes stream depth differently than that for the original package, a different name was used to distinguish it from the original Stream (STR1) Package.\r\n\r\nThe SFR1 Package has five options for simulating stream depth and four options for computing diversions from a stream. The options for computing stream depth are: a specified value; Manning's equation (using a wide rectangular channel or an eight-point cross section); a power equation; or a table of values that relate flow to depth and width. Each stream segment can have a different option. Outflow from lakes can be computed using the same options. Because the wetted perimeter is computed for the eight-point cross section and width is computed for the power equation and table of values, the streambed conductance term no longer needs to be calculated externally whenever the area of streambed changes as a function of flow. The concentration of solute is computed in a stream network when MODFLOW-GWT is used in conjunction with the SFR1 Package. The concentration of a solute in a stream reach is based on a mass-balance approach and accounts for exchanges with (inputs from or losses to) ground-water systems.\r\n\r\nTwo test examples are used to illustrate some of the capabilities of the SFR1 Package. The first test simulation was designed to illustrate how pumping of ground water from an aquifer connected to streams can affect streamflow, depth, width, and streambed conductance using the different options. The second test simulation was designed to illustrate solute transport through interconnected lakes, streams, and aquifers. Because of the need to examine time series results from the model simulations, the Gage Package first described in the LAK3 documentation was revised to include time series results of selected variables (streamflows, stream depth and width, streambed conductance, solute concentrations, and solute loads) for specified stream reaches.\r\n\r\nThe mass-balance or continuity approach for routing flow and solutes through a stream network may not be applicable for all interactions between streams and aquifers. The SFR1 Package is best suited for modeling long-term changes (months to hundreds of years) in ground-water flow and solute concentrations using averaged flows in streams. The Package is not recommended for modeling the transient exchange of water between streams and aquifers when the objective is to examine short-term (minutes to days) effects caused by rapidly changing streamflows.","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20041042","usgsCitation":"Prudic, D.E., Konikow, L.F., and Banta, E., 2004, A new streamflow-routing (SFR1) package to simulate stream-aquifer interaction with MODFLOW-2000: U.S. Geological Survey Open-File Report 2004-1042, 104 p., https://doi.org/10.3133/ofr20041042.","productDescription":"104 p.","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":175092,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":5024,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.water.usgs.gov/ofr2004-1042/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd495ee4b0b290850ef1bb","contributors":{"authors":[{"text":"Prudic, David E. deprudic@usgs.gov","contributorId":3430,"corporation":false,"usgs":true,"family":"Prudic","given":"David","email":"deprudic@usgs.gov","middleInitial":"E.","affiliations":[{"id":465,"text":"Nevada Water Science Center","active":true,"usgs":true}],"preferred":true,"id":247210,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Konikow, Leonard F. 0000-0002-0940-3856 lkonikow@usgs.gov","orcid":"https://orcid.org/0000-0002-0940-3856","contributorId":158,"corporation":false,"usgs":true,"family":"Konikow","given":"Leonard","email":"lkonikow@usgs.gov","middleInitial":"F.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":247209,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Banta, Edward R.","contributorId":49820,"corporation":false,"usgs":true,"family":"Banta","given":"Edward R.","affiliations":[],"preferred":false,"id":247211,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":53380,"text":"sir20045030 - 2004 - Estimating the Magnitude and Frequency of Floods in Small Urban Streams in South Carolina, 2001","interactions":[],"lastModifiedDate":"2017-01-13T10:02:56","indexId":"sir20045030","displayToPublicDate":"2004-09-01T00:00:00","publicationYear":"2004","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":"2004-5030","title":"Estimating the Magnitude and Frequency of Floods in Small Urban Streams in South Carolina, 2001","docAbstract":"The magnitude and frequency of floods at 20 streamflowgaging stations on small, unregulated urban streams in or near South Carolina were estimated by fitting the measured wateryear peak flows to a log-Pearson Type-III distribution. The period of record (through September 30, 2001) for the measured water-year peak flows ranged from 11 to 25 years with a mean and median length of 16 years. The drainage areas of the streamflow-gaging stations ranged from 0.18 to 41 square miles.\n\nBased on the flood-frequency estimates from the 20 streamflow-gaging stations (13 in South Carolina; 4 in North Carolina; and 3 in Georgia), generalized least-squares regression was used to develop regional regression equations. These equations can be used to estimate the 2-, 5-, 10-, 25-, 50-, 100-, 200-, and 500-year recurrence-interval flows for small urban streams in the Piedmont, upper Coastal Plain, and lower Coastal Plain physiographic provinces of South Carolina. The most significant explanatory variables from this analysis were mainchannel length, percent impervious area, and basin development factor. Mean standard errors of prediction for the regression equations ranged from -25 to 33 percent for the 10-year recurrence-interval flows and from -35 to 54 percent for the 100-year recurrence-interval flows.\n\nThe U.S. Geological Survey has developed a Geographic Information System application called StreamStats that makes the process of computing streamflow statistics at ungaged sites faster and more consistent than manual methods. This application was developed in the Massachusetts District and ongoing work is being done in other districts to develop a similar application using streamflow statistics relative to those respective States. Considering the future possibility of implementing StreamStats in South Carolina, an alternative set of regional regression equations was developed using only main channel length and impervious area. This was done because no digital coverages are currently available for basin development factor and, therefore, it could not be included in the StreamStats application. The average mean standard error of prediction for the alternative equations was 2 to 5 percent larger than the standard errors for the equations that contained basin development factor.\n\nFor the urban streamflow-gaging stations in South Carolina, measured water-year peak flows were compared with those from an earlier urban flood-frequency investigation. The peak flows from the earlier investigation were computed using a rainfall-runoff model. At many of the sites, graphical comparisons indicated that the variance of the measured data was much less than the variance of the simulated data. Several statistical tests were applied to compare the variances and the means of the measured and simulated data for each site. The results indicated that the variances were significantly different for 11 of the 13 South Carolina streamflow-gaging stations. For one streamflow-gaging station, the test for normality, which is one of the assumptions of the data when comparing variances, indicated that neither the measured data nor the simulated data were distributed normally; therefore, the test for differences in the variances was not used for that streamflow-gaging station. Another statistical test was used to test for statistically significant differences in the means of the measured and simulated data. The results indicated that for 5 of the 13 urban streamflowgaging stations in South Carolina there was a statistically significant difference in the means of the two data sets.\n\nFor comparison purposes and to test the hypothesis that there may have been climatic differences between the period in which the measured peak-flow data were measured and the period for which historic rainfall data were used to compute the simulated peak flows, 16 rural streamflow-gaging stations with long-term records were reviewed using similar techniques as those used for the measured an","language":"ENGLISH","doi":"10.3133/sir20045030","usgsCitation":"Feaster, T., and Guimaraes, W.B., 2004, Estimating the Magnitude and Frequency of Floods in Small Urban Streams in South Carolina, 2001: U.S. Geological Survey Scientific Investigations Report 2004-5030, 68 p., https://doi.org/10.3133/sir20045030.","productDescription":"68 p.","costCenters":[{"id":13634,"text":"South Atlantic Water Science 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Iowa","interactions":[],"lastModifiedDate":"2016-02-03T12:20:13","indexId":"sir20045130","displayToPublicDate":"2004-09-01T00:00:00","publicationYear":"2004","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":"2004-5130","title":"Simulation of ground-water flow in the Cedar River alluvial aquifer flow system, Cedar Rapids, Iowa","docAbstract":"The Cedar River alluvial aquifer is the primary source of municipal water in the Cedar Rapids, Iowa, area. Since 1992, the U.S. Geological Survey, in cooperation with the City of Cedar Rapids, has investigated the hydrogeology and water quality of the Cedar River alluvial aquifer. This report describes a detailed analysis of the ground-water flow system in the alluvial aquifer, particularly near well field areas.
\nThe ground-water flow system in the Cedar Rapids area consists of two main components, the unconsolidated Quaternary deposits and the underlying carbonate bedrock that has a variable fracture density. Quaternary deposits consist of eolian sand, loess, alluvium, and glacial till. Devonian and Silurian bedrock aquifers overlie the Maquoketa Shale (Formation) of Ordovician age, a regional confining unit.
\nGround-water and surface-water data were collected during the study to better define the hydrogeology of the Cedar River alluvial aquifer and Devonian and Silurian aquifers. Stream stage and discharge, ground-water levels, and estimates of aquifer hydraulic properties were used to develop a conceptual ground-water flow model and to construct and calibrate a model of the flow system. This model was used to quantify the movement of water between the various components of the aluvial aquifer flow system and provide an improved understanding of the hydrology of the alluvial aquifer.
\nGround-water flow was simulated for the Cedar River alluvial aquifer and the Devonian and Silurian aquifers using the three-dimensional finite-difference ground-water flow model MODFLOW. The model was discretized into 223 rows and 354 columns of cells. Areal cell sizes range from about 50 feet on a side near the Cedar River and the Cedar Rapids municipal wells to 1,500 feet on a side near the model boundaries and farthest away from the Cedar Rapids municipal well fields. The model is separated into five layers to account for the various hydrogeologic units in the model area.
\nModel results indicate that the primary sources of inflow to the modeled area are infiltration from the Cedar River (53.0 percent) and regional flow in the glacial and bedrock materials (34.1 percent). The primary sources of outflow from the modeled area are discharge to the Cedar River (45.4 percent) and pumpage (44.8 percent). Current steady-state pumping rates have increased the flow of water from the Cedar River to the alluvial aquifer by 43.8 cubic feet per second. Steady-state and transient hypothetical pumpage scenarios were used to show the relation between changes in pumpage and changes in infiltration of water from the Cedar River. Results indicate that more than 99 percent of the water discharging from municipal wells infiltrates from the Cedar River, that the time required for induced river recharge to equilibrate with municipal pumpage may be 150 days or more, and that ground-water availability in the Cedar Rapids area will not be significantly affected by doubling current pumpage as long as there is sufficient flow in the Cedar River to provide recharge.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20045130","collaboration":"Prepared in cooperation with the City of Cedar Rapids","usgsCitation":"Turco, M.J., and Buchmiller, R.C., 2004, Simulation of ground-water flow in the Cedar River alluvial aquifer flow system, Cedar Rapids, Iowa: U.S. Geological Survey Scientific Investigations Report 2004-5130, 39 p.; 15 figs.; 9 tables, https://doi.org/10.3133/sir20045130.","productDescription":"39 p.; 15 figs.; 9 tables","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":351,"text":"Iowa Water Science Center","active":true,"usgs":true}],"links":[{"id":182151,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":5872,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.water.usgs.gov/sir20045130/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Iowa","city":"Cedar Rapids","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91.71833038330078,\n 42.05031239367958\n ],\n [\n -91.80416107177734,\n 41.99241540282406\n ],\n [\n -91.70459747314452,\n 41.92501515881273\n ],\n [\n -91.6208267211914,\n 41.98297345197973\n ],\n [\n -91.71833038330078,\n 42.05031239367958\n ]\n ]\n ]\n }\n }\n ]\n}","tableOfContents":"Abstract
Introduction
Purpose and Scope
Description of Study Area
Acknowledgments
Methods of Investigation
Surface-Water Measurements
Well Construction and Nomenclature
Ground-Water Measurements
Aquifer Properties
Hydrogeology
Geology and Water-Bearing Characteristics
Surface Water
Ground Water
Simulation of Ground-Water Flow
Model Description and Boundary Conditions
Model Parameters
Model Calibration
Steady-State Calibration
Transient Calibration
Sensitivity Analysis
Model Limitations
Steady-State Results and Hypothetical Pumping Scenarios
Transient Results and Hypothetical Pumping Scenarios
Summary
References
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. The primary objectives of this program are the near real time seismic monitoring of active, potentially hazardous, Alaskan volcanoes and the investigation of seismic processes associated with active volcanism. This catalog presents the calculated earthquake hypocenter and phase arrival data, and changes in the seismic monitoring program for the period January 1 through December 31, 2003.
The AVO seismograph network was used to monitor the seismic activity at twenty-seven volcanoes within Alaska in 2003. These include Mount Wrangell, Mount Spurr, Redoubt Volcano, Iliamna Volcano, Augustine Volcano, Katmai volcanic cluster (Snowy Mountain, Mount Griggs, Mount Katmai, Novarupta, Trident Volcano, Mount Mageik, Mount Martin), Aniakchak Crater, Mount Veniaminof, Pavlof Volcano, Mount Dutton, Isanotski Peaks, Shishaldin Volcano, Fisher Caldera, Westdahl Peak, Akutan Peak, Makushin Volcano, Okmok Caldera, Great Sitkin Volcano, Kanaga Volcano, Tanaga Volcano, and Mount Gareloi. Monitoring highlights in 2003 include: continuing elevated seismicity at Mount Veniaminof in January-April (volcanic unrest began in August 2002), volcanogenic seismic swarms at Shishaldin Volcano throughout the year, and low-level tremor at Okmok Caldera throughout the year. Instrumentation and data acquisition highlights in 2003 were the installation of subnetworks on Tanaga and Gareloi Islands, the installation of broadband installations on Akutan Volcano and Okmok Caldera, and the establishment of telemetry for the Okmok Caldera subnetwork. AVO located 3911 earthquakes in 2003.
This catalog includes: (1) a description of instruments deployed in the field and their locations; (2) a description of earthquake detection, recording, analysis, and data archival systems; (3) a description of velocity models used for earthquake locations; (4) a summary of earthquakes located in 2003; 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 2003.
","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20041234","usgsCitation":"Dixon, J.P., Stihler, S.D., Power, J.A., Tytgat, G., Moran, S.C., Sanchez, J.J., McNutt, S.R., Estes, S., and Paskievitch, J., 2004, Catalog of earthquake hypocenters at Alaskan volcanoes: January 1 through December 31, 2003 (Version 1.0): U.S. Geological Survey Open-File Report 2004-1234, 69 p., https://doi.org/10.3133/ofr20041234.","productDescription":"69 p.","costCenters":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true}],"links":[{"id":431665,"rank":22,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_68844.htm","text":"Katmai volcanic cluster","linkFileType":{"id":5,"text":"html"}},{"id":431664,"rank":21,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_68849.htm","text":"Unimak Island","linkFileType":{"id":5,"text":"html"}},{"id":431657,"rank":14,"type":{"id":36,"text":"NGMDB 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smoran@usgs.gov","orcid":"https://orcid.org/0000-0001-7308-9649","contributorId":548,"corporation":false,"usgs":true,"family":"Moran","given":"Seth","email":"smoran@usgs.gov","middleInitial":"C.","affiliations":[{"id":615,"text":"Volcano Hazards Program","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":257996,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Sanchez, John J.","contributorId":36219,"corporation":false,"usgs":true,"family":"Sanchez","given":"John","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":258000,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McNutt, Stephen R.","contributorId":38133,"corporation":false,"usgs":true,"family":"McNutt","given":"Stephen","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":258001,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Estes, Steve","contributorId":55881,"corporation":false,"usgs":true,"family":"Estes","given":"Steve","email":"","affiliations":[],"preferred":false,"id":258002,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Paskievitch, John","contributorId":74050,"corporation":false,"usgs":true,"family":"Paskievitch","given":"John","affiliations":[],"preferred":false,"id":258004,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":57817,"text":"sir20045073 - 2004 - Ground-water and surface-water flow and estimated water budget for Lake Seminole, southwestern Georgia and northwestern Florida","interactions":[],"lastModifiedDate":"2017-01-13T10:07:49","indexId":"sir20045073","displayToPublicDate":"2004-09-01T00:00:00","publicationYear":"2004","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":"2004-5073","title":"Ground-water and surface-water flow and estimated water budget for Lake Seminole, southwestern Georgia and northwestern Florida","docAbstract":"Lake Seminole is a 37,600-acre impoundment formed at the confluence of the Flint and Chattahoochee Rivers along the Georgia?Florida State line. Outflow from Lake Seminole through Jim Woodruff Lock and Dam provides headwater to the Apalachicola River, which is a major supply of freshwater, nutrients, and detritus to ecosystems downstream. These rivers,together with their tributaries, are hydraulically connected to karst limestone units that constitute most of the Upper Floridan aquifer and to a chemically weathered residuum of undifferentiated overburden. \r\n\r\nThe ground-water flow system near Lake Seminole consists of the Upper Floridan aquifer and undifferentiated overburden. The aquifer is confined below by low-permeability sediments of the Lisbon Formation and, generally, is semiconfined above by undifferentiated overburden. Ground-water flow within the Upper Floridan aquifer is unconfined or semiconfined and discharges at discrete points by springflow or diffuse leakage into streams and other surface-water bodies. The high degree of connectivity between the Upper Floridan aquifer and surface-water bodies is limited to the upper Eocene Ocala Limestone and younger units that are in contact with streams in the Lake Seminole area. The impoundment of Lake Seminole inundated natural stream channels and other low-lying areas near streams and raised the water-level altitude of the Upper Floridan aquifer near the lake to nearly that of the lake, about 77 feet.\r\n\r\nSurface-water inflow from the Chattahoochee and Flint Rivers and Spring Creek and outflow to the Apalachicola River through Jim Woodruff Lock and Dam dominate the water budget for Lake Seminole. About 81 percent of the total water-budget inflow consists of surface water; about 18 percent is ground water, and the remaining 1 percent is lake precipitation. Similarly, lake outflow consists of about 89 percent surface water, as flow to the Apalachicola River through Jim Woodruff Lock and Dam, about 4 percent ground water, and about 2 percent lake evaporation. Measurement error and uncertainty in flux calculations cause a flow imbalance of about 4 percent between inflow and outflow water-budget components. Most of this error can be attributed to errors in estimating ground-water discharge from the lake, which was calculated using a ground-water model calibrated to October 1986 conditions for the entire Apalachicola?Chattahoochee?Flint River Basin and not just the area around Lake Seminole. \r\n\r\nEvaporation rates were determined using the preferred, but mathematically complex, energy budget and five empirical equations: Priestley-Taylor, Penman, DeBruin-Keijman, Papadakis, and the Priestley-Taylor used by the Georgia Automated Environmental Monitoring Network. Empirical equations require a significant amount of data but are relatively easy to calculate and compare well to long-term average annual (April 2000?March 2001) pan evaporation, which is 65 inches. Calculated annual lake evaporation, for the study period, using the energy-budget method was 67.2 inches, which overestimated long-term average annual pan evaporation by 2.2 inches. The empirical equations did not compare well with the energy-budget method during the 18-month study period, with average differences in computed evaporation using each equation ranging from 8 to 26 percent. The empirical equations also compared poorly with long-term average annual pan evaporation, with average differences in evaporation ranging from 3 to 23 percent. Energy budget and long-term average annual pan evaporation estimates did compare well, with only a 3-percent difference between estimates. Monthly evaporation estimates using all methods ranged from 0.7 to 9.5 inches and were lowest during December 2000 and highest during May 2000. Although the energy budget is generally the preferred method, the dominance of surface water in the Lake Seminole water budget makes the method inaccurate and difficult to use, because surface water makes up m","language":"ENGLISH","doi":"10.3133/sir20045073","usgsCitation":"Dalton, M.S., Aulenbach, B.T., and Torak, L.J., 2004, Ground-water and surface-water flow and estimated water budget for Lake Seminole, southwestern Georgia and northwestern Florida (Online Only): U.S. Geological Survey Scientific Investigations Report 2004-5073, 49 p., https://doi.org/10.3133/sir20045073.","productDescription":"49 p.","onlineOnly":"Y","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":184914,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":5795,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.water.usgs.gov/sir2004-5073/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Florida, Georgia","otherGeospatial":"Lake Seminole","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -86.484375,\n 28.998531814051795\n ],\n [\n -86.484375,\n 32.731840896865684\n ],\n [\n -83.43017578125,\n 32.731840896865684\n ],\n [\n -83.43017578125,\n 28.998531814051795\n ],\n [\n -86.484375,\n 28.998531814051795\n ]\n ]\n ]\n }\n }\n ]\n}","edition":"Online Only","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ab0e4b07f02db66d423","contributors":{"authors":[{"text":"Dalton, Melinda S. 0000-0002-2929-5573 msdalton@usgs.gov","orcid":"https://orcid.org/0000-0002-2929-5573","contributorId":267,"corporation":false,"usgs":true,"family":"Dalton","given":"Melinda","email":"msdalton@usgs.gov","middleInitial":"S.","affiliations":[{"id":509,"text":"Office of the Associate Director for Water","active":true,"usgs":true},{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":257882,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aulenbach, Brent T. 0000-0003-2863-1288 btaulenb@usgs.gov","orcid":"https://orcid.org/0000-0003-2863-1288","contributorId":3057,"corporation":false,"usgs":true,"family":"Aulenbach","given":"Brent","email":"btaulenb@usgs.gov","middleInitial":"T.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":257884,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Torak, Lynn J. ljtorak@usgs.gov","contributorId":401,"corporation":false,"usgs":true,"family":"Torak","given":"Lynn","email":"ljtorak@usgs.gov","middleInitial":"J.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":257883,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":57816,"text":"sir20045077 - 2004 - Simulated effects of impoundment of lake seminole on ground-water flow in the upper Floridan Aquifer in southwestern Georgia and adjacent parts of Alabama and Florida","interactions":[],"lastModifiedDate":"2017-01-31T08:41:43","indexId":"sir20045077","displayToPublicDate":"2004-09-01T00:00:00","publicationYear":"2004","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":"2004-5077","title":"Simulated effects of impoundment of lake seminole on ground-water flow in the upper Floridan Aquifer in southwestern Georgia and adjacent parts of Alabama and Florida","docAbstract":"Hydrologic implications of the impoundment of Lake Seminole in southwest Georgia and its effect on components of the surface- and ground-water flow systems of the lower Apalachicola?Chattahoochee?Flint (ACF) River Basin were investigated using a ground-water model. Comparison of simulation results of postimpoundment drought conditions (October 1986) with results of hypothetical preimpoundment conditions (a similar drought prior to 1955) provides a qualitative measure of the changes in hydraulic head and ground-water flow to and from streams and Lake Seminole, and across State lines caused by the impoundment.\r\n\r\nBased on the simulation results, the impoundment of Lake Seminole changed ground-water flow directions within about 20?30 miles of the lake, reducing the amount of ground water flowing from Florida to Georgia southeast of the lake. Ground-water storage was increased by the impoundment, as indicated by a simulated increase of as much as 26 feet in the water level in the Upper Floridan aquifer. The impoundment of Lake Seminole caused changes to simulated components of the ground-water budget, including reduced discharge from the Upper Floridan aquifer to streams (315 million gallons per day); reduced recharge from or increased discharge to regional ground-water flow at external model boundaries (totaling 183 million gallons per day); and reduced recharge from or increased discharge to the undifferentiated overburden (totaling 129 million gallons per day).","language":"ENGLISH","doi":"10.3133/sir20045077","usgsCitation":"Jones, L.E., and Torak, L.J., 2004, Simulated effects of impoundment of lake seminole on ground-water flow in the upper Floridan Aquifer in southwestern Georgia and adjacent parts of Alabama and Florida: U.S. Geological Survey Scientific Investigations Report 2004-5077, 18 p., https://doi.org/10.3133/sir20045077.","productDescription":"18 p.","costCenters":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":184913,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":5794,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.water.usgs.gov/sir2004-5077/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Alabama, Florida, Georgia","otherGeospatial":"Upper Floridan Aquifer ","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -86.385498046875,\n 29.017748018496047\n ],\n [\n -86.385498046875,\n 33.4955977448657\n ],\n [\n -82.72705078125,\n 33.4955977448657\n ],\n [\n -82.72705078125,\n 29.017748018496047\n ],\n [\n -86.385498046875,\n 29.017748018496047\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b01e4b07f02db6984d6","contributors":{"authors":[{"text":"Jones, L. Elliott 0000-0002-7394-2053 lejones@usgs.gov","orcid":"https://orcid.org/0000-0002-7394-2053","contributorId":44569,"corporation":false,"usgs":true,"family":"Jones","given":"L.","email":"lejones@usgs.gov","middleInitial":"Elliott","affiliations":[],"preferred":false,"id":257881,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Torak, Lynn J. ljtorak@usgs.gov","contributorId":401,"corporation":false,"usgs":true,"family":"Torak","given":"Lynn","email":"ljtorak@usgs.gov","middleInitial":"J.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"preferred":true,"id":257880,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":56765,"text":"sir20045078 - 2004 - A Comparison of Forest Survey Data with Forest Dynamics Simulators FORCLIM and ZELIG along Climatic Gradients in the Pacific Northwest","interactions":[],"lastModifiedDate":"2012-02-02T00:11:48","indexId":"sir20045078","displayToPublicDate":"2004-09-01T00:00:00","publicationYear":"2004","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":"2004-5078","title":"A Comparison of Forest Survey Data with Forest Dynamics Simulators FORCLIM and ZELIG along Climatic Gradients in the Pacific Northwest","docAbstract":"Two forest dynamics simulators are compared along climatic gradients in the Pacific Northwest. The ZELIG and FORCLIM models are tested against forest survey data from western Oregon. Their ability to generate accurate patterns of forest basal area and species composition is evaluated for series of sites with contrasting climate. Projections from both models approximate the basal area and composition patterns for three sites along the elevation gradient at H.J. Andrews Experimental Forest in the western Cascade Range. The ZELIG model is somewhat more accurate than FORCLIM at the two low-elevation sites. Attempts to project forest composition along broader climatic gradients reveal limitations of ZELIG, however. For example, ZELIG is less accurate than FORCLIM at projecting the average composition of a west Cascades ecoregion selected for intensive analysis. Also, along a gradient consisting of several sites on an east to west transect at 44.1oN latitude, both the FORCLIM model and the actual data show strong changes in composition and total basal area, but the ZELIG model shows a limited response. ZELIG does not simulate the declines in forest basal area and the diminished dominance of mesic coniferous species east of the Cascade crest. We conclude that ZELIG is suitable for analyses of certain sites for which it has been calibrated. FORCLIM can be applied in analyses involving a range of climatic conditions without requiring calibration for specific sites.","language":"ENGLISH","doi":"10.3133/sir20045078","usgsCitation":"Busing, R.T., and Solomon, A.M., 2004, A Comparison of Forest Survey Data with Forest Dynamics Simulators FORCLIM and ZELIG along Climatic Gradients in the Pacific Northwest: U.S. Geological Survey Scientific Investigations Report 2004-5078, 16 p., https://doi.org/10.3133/sir20045078.","productDescription":"16 p.","costCenters":[],"links":[{"id":5647,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.water.usgs.gov/sir2004-5078/","linkFileType":{"id":5,"text":"html"}},{"id":173878,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53cd494fe4b0b290850ef0ab","contributors":{"authors":[{"text":"Busing, Richard T.","contributorId":13303,"corporation":false,"usgs":true,"family":"Busing","given":"Richard","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":255731,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Solomon, Allen M.","contributorId":20394,"corporation":false,"usgs":true,"family":"Solomon","given":"Allen","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":255732,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":57784,"text":"sir20045031 - 2004 - Simulation of ground-water flow, surface-water flow, and a deep sewer tunnel system in the Menomonee Valley, Milwaukee, Wisconsin","interactions":[],"lastModifiedDate":"2015-11-16T12:14:24","indexId":"sir20045031","displayToPublicDate":"2004-09-01T00:00:00","publicationYear":"2004","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":"2004-5031","title":"Simulation of ground-water flow, surface-water flow, and a deep sewer tunnel system in the Menomonee Valley, Milwaukee, Wisconsin","docAbstract":"Numerical models were constructed for simulation of ground-water flow in the Menomonee Valley Brownfield, in Milwaukee, Wisconsin. An understanding of ground-water flow is necessary to develop an efficient program to sample ground water for contaminants. Models were constructed in a stepwise fashion, beginning with a regional, single-layer, analytic-element model (GFLOW code) that provided boundary conditions for a local, eight layer, finite-difference model (MODFLOW code) centered on the Menomonee Valley Brownfield. The primary source of ground water to the models is recharge over the model domains; primary sinks for ground water within the models are surface-water features and the Milwaukee Metropolitan Sewerage District Inline Storage System (ISS). Calibration targets were hydraulic heads, surface-water fluxes, vertical gradients, and ground-water infiltration to the ISS. Simulation of ground-water flow by use of the MODFLOW model indicates that about 73 percent of recharge within the MODFLOW domain circulates to the ISS and 27 percent discharges to gaining surface-water bodies. In addition, infiltration to the ISS comes from the following sources: 36 percent from recharge within the model domain, 45 percent from lateral flow into the domain, 15 percent from Lake Michigan, and 4 percent from other surface-water bodies. Particle tracking reveals that the median traveltime from the recharge point to surface-water features is 8 years; the median time to the ISS is 255 years. The traveltimes to the ISS are least over the northern part of the valley, where dolomite is near the land surface. The distribution of traveltimes in the MODFLOW simulation is greatly influenced by the effective porosity values assigned to the various lithologies.
","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/sir20045031","collaboration":"In cooperation with the U.S. Environmental Protection Agency, Region 5, and City of Milwaukee, Wisconsin","usgsCitation":"Dunning, C.P., Feinstein, D.T., Hunt, R.J., and Krohelski, J.T., 2004, Simulation of ground-water flow, surface-water flow, and a deep sewer tunnel system in the Menomonee Valley, Milwaukee, Wisconsin: U.S. Geological Survey Scientific Investigations Report 2004-5031, vi, 40 p., https://doi.org/10.3133/sir20045031.","productDescription":"vi, 40 p.","numberOfPages":"48","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":677,"text":"Wisconsin Water Science Center","active":true,"usgs":true}],"links":[{"id":182239,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":5742,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.water.usgs.gov/sir2004-5031/","linkFileType":{"id":5,"text":"html"}},{"id":311359,"rank":101,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2004/5031/pdf/2004-5031_Menomonee.pdf"}],"scale":"48","country":"United States","state":"Wisconsin","city":"Milwaukee","otherGeospatial":"Menominee Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.97697067260742,\n 42.995607893370135\n ],\n [\n -87.97697067260742,\n 43.059857997098916\n ],\n [\n -87.87895202636719,\n 43.059857997098916\n ],\n [\n -87.87895202636719,\n 42.995607893370135\n ],\n [\n -87.97697067260742,\n 42.995607893370135\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e49f7e4b07f02db5f246f","contributors":{"authors":[{"text":"Dunning, C. P.","contributorId":35792,"corporation":false,"usgs":true,"family":"Dunning","given":"C.","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":257777,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Feinstein, D. T.","contributorId":47328,"corporation":false,"usgs":true,"family":"Feinstein","given":"D.","email":"","middleInitial":"T.","affiliations":[],"preferred":false,"id":257779,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hunt, R. J.","contributorId":40164,"corporation":false,"usgs":true,"family":"Hunt","given":"R.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":257778,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Krohelski, J. T.","contributorId":59046,"corporation":false,"usgs":true,"family":"Krohelski","given":"J.","email":"","middleInitial":"T.","affiliations":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"preferred":false,"id":257780,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":57820,"text":"sir20045087 - 2004 - Regional ground-water-flow models of surficial sand and gravel aquifers along the Mississippi River between Brainerd and St. Cloud, central Minnesota","interactions":[],"lastModifiedDate":"2016-04-08T10:43:08","indexId":"sir20045087","displayToPublicDate":"2004-09-01T00:00:00","publicationYear":"2004","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":"2004-5087","title":"Regional ground-water-flow models of surficial sand and gravel aquifers along the Mississippi River between Brainerd and St. Cloud, central Minnesota","docAbstract":"This report documents regional ground-waterflow models constructed by the U.S. Geological Survey in cooperation with the Minnesota Department of Health (MDH) to satisfy the requirements of their Source Water Protection Plan (SWPP). Steady-state single-layer ground-water-flow models were constructed with the computer program MODFLOW to simulate flow in surficial sand and gravel aquifers along the Mississippi River between Brainerd and St. Cloud in central Minnesota. The hydrogeologic data that were used to construct the models were compiled from available sources.
\nCalibrated values of horizontal hydraulic conductivity and areal recharge for the aquifer in a northern model area were 70 m/d and 3.0x10-4 m/d, respectively. This model was sensitive to net areal recharge, vertical hydraulic conductivity of perennial streambed sediments, and horizontal hydraulic conductivity. The major source of net inflow to the model was from edge boundary cells. The major source of net outflow was ground-water discharge to perennial and ephemeral streams.
\nCalibrated values of horizontal hydraulic conductivity and areal recharge for the aquifer in a southern model area were 70 m/d and 6.0x10-4 m/d, respectively. This model was sensitive mostly to horizontal hydraulic conductivity. Net areal recharge and ground-water discharge to perennial streams were the major sources of net inflow and outflow, respectively.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20045087","usgsCitation":"Ruhl, J.F., and Cowdery, T., 2004, Regional ground-water-flow models of surficial sand and gravel aquifers along the Mississippi River between Brainerd and St. Cloud, central Minnesota: U.S. Geological Survey Scientific Investigations Report 2004-5087, iv, 21 p., https://doi.org/10.3133/sir20045087.","productDescription":"iv, 21 p.","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"links":[{"id":319904,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20045087.JPG"},{"id":5798,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.water.usgs.gov/sir20045087/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Minnesota","city":"Brainerd, St. Cloud","otherGeospatial":"Mississippi","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.53460693359374,\n 46.300457387911614\n ],\n [\n -94.06356811523438,\n 46.30330363797423\n ],\n [\n -94.06494140625,\n 45.916765867649005\n ],\n [\n -94.11712646484375,\n 45.917721261594224\n ],\n [\n -94.11849975585938,\n 45.50345949537662\n ],\n [\n -94.46731567382812,\n 45.50345949537662\n ],\n [\n -94.46731567382812,\n 45.920587344733654\n ],\n [\n -94.53048706054688,\n 45.917721261594224\n ],\n [\n -94.53460693359374,\n 46.300457387911614\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a69e4b07f02db63baae","contributors":{"authors":[{"text":"Ruhl, J. F.","contributorId":81866,"corporation":false,"usgs":true,"family":"Ruhl","given":"J.","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":257889,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cowdery, T.K.","contributorId":92658,"corporation":false,"usgs":true,"family":"Cowdery","given":"T.K.","affiliations":[],"preferred":false,"id":257890,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":54269,"text":"sir20045066 - 2004 - Summary and Comparison of Multiphase Streambed Scour Analysis at Selected Bridge Sites in Alaska","interactions":[],"lastModifiedDate":"2018-04-21T13:44:04","indexId":"sir20045066","displayToPublicDate":"2004-09-01T00:00:00","publicationYear":"2004","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":"2004-5066","title":"Summary and Comparison of Multiphase Streambed Scour Analysis at Selected Bridge Sites in Alaska","docAbstract":"The U.S. Geological Survey and the Alaska Department of Transportation and Public Facilities undertook a cooperative multiphase study of streambed scour at selected bridges in Alaska beginning in 1994. Of the 325 bridges analyzed for susceptibility to scour in the preliminary phase, 54 bridges were selected for a more intensive analysis that included site investigations. Cross-section geometry and hydraulic properties for each site in this study were determined from field surveys and bridge plans. Water-surface profiles were calculated for the 100- and 500-year floods using the Hydrologic Engineering Center?s River Analysis System and scour depths were calculated using methods recommended by the Federal Highway Administration.\r\n\r\nComputed contraction-scour depths for the 100- and 500-year recurrence-interval discharges exceeded 5 feet at six bridges, and pier-scour depths exceeded 10 feet at 24 bridges. Complex pier-scour computations were made at 10 locations where the computed contraction-scour depths would expose pier footings. Pressure scour was evaluated at three bridges where the modeled flood water-surface elevations intersected the bridge structure.\r\n\r\nSite investigation at the 54 scour-critical bridges was used to evaluate the effectiveness of the preliminary scour analysis. Values for channel-flow angle of attack and approach-channel width were estimated from bridge survey plans for the preliminary study and were measured during a site investigation for this study. These two variables account for changes in scour depths between the preliminary analysis and subsequent reanalysis for most sites. Site investigation is needed for best estimates of scour at bridges with survey plans that indicate a channel-flow angle of attack and for locations where survey plans did not include sufficient channel geometry upstream of the bridge.","language":"ENGLISH","doi":"10.3133/sir20045066","usgsCitation":"Conaway, J.S., 2004, Summary and Comparison of Multiphase Streambed Scour Analysis at Selected Bridge Sites in Alaska: U.S. Geological Survey Scientific Investigations Report 2004-5066, 34 p.; 10 illus.; 8 tables, https://doi.org/10.3133/sir20045066.","productDescription":"34 p.; 10 illus.; 8 tables","costCenters":[],"links":[{"id":178036,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":5381,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.water.usgs.gov/sir20045066","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b05e4b07f02db699703","contributors":{"authors":[{"text":"Conaway, Jeffrey S. 0000-0002-3036-592X jconaway@usgs.gov","orcid":"https://orcid.org/0000-0002-3036-592X","contributorId":2026,"corporation":false,"usgs":true,"family":"Conaway","given":"Jeffrey","email":"jconaway@usgs.gov","middleInitial":"S.","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":249707,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":54144,"text":"wri034300 - 2004 - Water use, ground-water recharge and availability, and quality of water in the Greenwich area, Fairfield County, Connecticut and Westchester County, New York, 2000-2002","interactions":[],"lastModifiedDate":"2017-08-15T11:32:04","indexId":"wri034300","displayToPublicDate":"2004-09-01T00:00:00","publicationYear":"2004","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":342,"text":"Water-Resources Investigations Report","code":"WRI","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"2003-4300","title":"Water use, ground-water recharge and availability, and quality of water in the Greenwich area, Fairfield County, Connecticut and Westchester County, New York, 2000-2002","docAbstract":"Ground-water budgets were developed for 32 small basin-based zones in the Greenwich area of southwestern Connecticut, where crystalline-bedrock aquifers supply private wells, to determine the status of residential ground-water consumption relative to rates of ground-water recharge and discharge. Estimated residential ground-water withdrawals for small basins (averaging 1.7 square miles (mi2)) ranged from 0 to 0.16 million gallons per day per square mile (Mgal/d/mi2). To develop these budgets, residential ground-water withdrawals were estimated using multiple-linear regression models that relate water use from public water supply to data on residential property characteristics. Average daily water use of households with public water supply ranged from 219 to 1,082 gallons per day (gal/d).
A steady-state finite-difference ground-water- flow model was developed to track water budgets, and to estimate optimal values for hydraulic conductivity of the bedrock (0.05 feet per day) and recharge to the overlying till deposits (6.9 inches) using nonlinear regression. Estimated recharge rates to the small basins ranged from 3.6 to 7.5 inches per year (in/yr) and relate to the percentage of the basin underlain by coarse- grained glacial stratified deposits. Recharge was not applied to impervious areas to account for the effects of urbanization. Net residential ground-water consumption was estimated as ground-water withdrawals increased during the growing season, and ranged from 0 to 0.9 in/yr.
Long-term average stream base flows simulated by the ground-water-flow model were compared to calculated values of average base flow and low flow to determine if base flow was substantially reduced in any of the basins studied. Three of the 32 basins studied had simulated base flows less than 3 in/yr, as a result of either ground-water withdrawals or reduced recharge due to urbanization. A water-availability criteria of the difference between the 30-day 2-year low flow and the recharge rate for each basin was explored as a method to rate the status of water consumption in each basin. Water consumption ranged from 0 to 14.3 percent of available water based on this criteria for the 32 basins studied.
Base-flow water quality was related to the amount of urbanized area in each basin sampled. Concentrations of total nitrogen and phosphorus, chloride, indicator bacteria, and the number of pesticide detections increased with basin urbanization, which ranged from 18 to 63 percent of basin area.
","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/wri034300","collaboration":"Prepared in cooperation with the town of Greenwich, Connecticut","usgsCitation":"Mullaney, J.R., 2004, Water use, ground-water recharge and availability, and quality of water in the Greenwich area, Fairfield County, Connecticut and Westchester County, New York, 2000-2002: U.S. Geological Survey Water-Resources Investigations Report 2003-4300, vi, 64 p., https://doi.org/10.3133/wri034300.","productDescription":"vi, 64 p.","costCenters":[],"links":[{"id":181453,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":344857,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/wri/wri034300/GreenwichCT03-4300.pdf","text":"Report","size":"2.68 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":5590,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/wri/wri034300/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Connecticut, New York","county":"Fairfield County, Westchester County","otherGeospatial":"Greenwich area","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.75,\n 40.9\n ],\n [\n -73.5,\n 40.9\n ],\n [\n -73.5,\n 41.2\n ],\n [\n -73.75,\n 41.2\n ],\n [\n -73.75,\n 40.9\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e49a1e4b07f02db5be166","contributors":{"authors":[{"text":"Mullaney, John R. 0000-0003-4936-5046 jmullane@usgs.gov","orcid":"https://orcid.org/0000-0003-4936-5046","contributorId":1957,"corporation":false,"usgs":true,"family":"Mullaney","given":"John","email":"jmullane@usgs.gov","middleInitial":"R.","affiliations":[{"id":466,"text":"New England Water Science Center","active":true,"usgs":true},{"id":196,"text":"Connecticut Water Science Center","active":true,"usgs":true}],"preferred":true,"id":249321,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":54029,"text":"wri034047 - 2004 - Development and Application of Watershed Regressions for Pesticides (WARP) for Estimating Atrazine Concentration Distributions in Streams","interactions":[],"lastModifiedDate":"2012-02-02T00:11:55","indexId":"wri034047","displayToPublicDate":"2004-09-01T00:00:00","publicationYear":"2004","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":342,"text":"Water-Resources Investigations Report","code":"WRI","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"2003-4047","title":"Development and Application of Watershed Regressions for Pesticides (WARP) for Estimating Atrazine Concentration Distributions in Streams","docAbstract":"Regression models were developed for predicting atrazine concentration distributions in rivers and streams, using the Watershed Regressions for Pesticides (WARP) methodology. Separate regression equations were derived for each of nine percentiles of the annual distribution of atrazine concentrations and for the annual time-weighted mean atrazine concentration. In addition, seasonal models were developed for two specific periods of the year--the high season, when the highest atrazine concentrations are expected in streams, and the low season, when concentrations are expected to be low or undetectable. Various nationally available watershed parameters were used as explanatory variables, including atrazine use intensity, soil characteristics, hydrologic parameters, climate and weather variables, land use, and agricultural management practices. Concentration data from 112 river and stream stations sampled as part of the U.S. Geological Survey's National Water-Quality Assessment and National Stream Quality Accounting Network Programs were used for computing the concentration percentiles and mean concentrations used as the response variables in regression models. Tobit regression methods, using maximum likelihood estimation, were used for developing the models because some of the concentration values used for the response variables were censored (reported as less than a detection threshold). Data from 26 stations not used for model development were used for model validation.\r\n\r\n The annual models accounted for 62 to 77 percent of the variability in concentrations among the 112 model development stations. Atrazine use intensity (the amount of atrazine used in the watershed divided by watershed area) was the most important explanatory variable in all models, but additional watershed parameters significantly increased the amount of variability explained by the models. Predicted concentrations from all 10 models were within a factor of 10 of the observed concentrations at most model development and model validation stations. Results for the two sets of seasonal models were similar. Concentration distributions derived from the seasonal-model predictions provided additional information compared to distributions derived from the annual models.","language":"ENGLISH","doi":"10.3133/wri034047","usgsCitation":"Larson, S., Crawford, C.G., and Gilliom, R.J., 2004, Development and Application of Watershed Regressions for Pesticides (WARP) for Estimating Atrazine Concentration Distributions in Streams: U.S. Geological Survey Water-Resources Investigations Report 2003-4047, 81 p., https://doi.org/10.3133/wri034047.","productDescription":"81 p.","costCenters":[],"links":[{"id":174400,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":5472,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.water.usgs.gov/wri034047/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4aa7e4b07f02db6672d8","contributors":{"authors":[{"text":"Larson, Steven J.","contributorId":29845,"corporation":false,"usgs":true,"family":"Larson","given":"Steven J.","affiliations":[],"preferred":false,"id":248969,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Crawford, Charles G. 0000-0003-1653-7841 cgcrawfo@usgs.gov","orcid":"https://orcid.org/0000-0003-1653-7841","contributorId":1064,"corporation":false,"usgs":true,"family":"Crawford","given":"Charles","email":"cgcrawfo@usgs.gov","middleInitial":"G.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":248968,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gilliom, Robert J. rgilliom@usgs.gov","contributorId":488,"corporation":false,"usgs":true,"family":"Gilliom","given":"Robert","email":"rgilliom@usgs.gov","middleInitial":"J.","affiliations":[{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true}],"preferred":true,"id":248967,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":54146,"text":"sir20045046 - 2004 - Hydrologic and geochemical evaluation of aquifer storage recovery in the Santee Limestone/Black Mingo Aquifer, Charleston, South Carolina, 1998-2002","interactions":[],"lastModifiedDate":"2020-02-09T15:42:11","indexId":"sir20045046","displayToPublicDate":"2004-09-01T00:00:00","publicationYear":"2004","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":"2004-5046","displayTitle":"Hydrologic and Geochemical Evaluation of Aquifer Storage Recovery in the Santee Limestone/Black Mingo Aquifer, Charleston, South Carolina, 1998-2002","title":"Hydrologic and geochemical evaluation of aquifer storage recovery in the Santee Limestone/Black Mingo Aquifer, Charleston, South Carolina, 1998-2002","docAbstract":"The hydrologic and geochemical effects of aquifer storage recovery were evaluated to determine the potential for supplying the city of Charleston, South Carolina, with large quantities of potable water during emergencies, such as earthquakes, hurricanes, or hard freezes. An aquifer storage recovery system, including a production well and three observation wells, was installed at a site located on the Charleston peninsula. The focus of this study was the 23.2-meter thick Tertiary-age carbonate and sand aquifer of the Santee Limestone and the Black Mingo Group, the northernmost equivalent of the Floridan aquifer system. Four cycles of injection, storage, and recovery were conducted between October 1999 and February 2002. Each cycle consisted of injecting between 6.90 and 7.19 million liters of water for storage periods of 1, 3, or 6 months. The volume of recovered water that did not exceed the U.S. Environmental Protection Agency secondary standard for chloride (250 milligrams per liter) varied from 1.48 to 2.46 million liters, which is equivalent to 21 and 34 percent of the total volume injected for the individual tests. Aquifer storage recovery testing occurred within two productive zones of the brackish Santee Limestone/Black Mingo aquifer. The individual productive zones were determined to be approximately 2 to 4 meters thick, based on borehole geophysical logs, electromagnetic flow-meter testing, and specific-conductance profiles collected within the observation wells. A transmissivity and storage coefficient of 37 meters squared per day and 3 x 10-5, respectively, were determined for the Santee Limestone/Black Mingo aquifer. Water-quality and sediment samples collected during this investigation documented baseline aquifer and injected water quality, aquifer matrix composition, and changes in injected/aquifer water quality during injection, storage, and recovery. A total of 193 water-quality samples were collected and analyzed for physical properties, major and minor ions, and nutrients. The aquifer and treated surface water were sodiumchloride and calcium/sodium-bicarbonate water types, respectively. Forty-five samples were collected and analyzed for total trihalomethane. Total trihalomethane data collected during aquifer storage recovery cycle 4 indicated that this constituent would not restrict the use of recovered water for drinking-water purposes. Analysis of six sediment samples collected from a cored well located near the aquifer storage recovery site showed that quartz and calcite were the dominant minerals in the Santee Limestone/Black Mingo aquifer. Estimated cation exchange capacity ranged from 12 to 36 milliequivalents per 100 grams in the lower section of the aquifer. A reactive transport model was developed that included two 2-meter thick layers to describe each of the production zones. The four layers composing the production zones were assigned porosities ranging from 0.1 to 0.3 and hydraulic conductivities ranging from 1 to 8.4 meters per day. Specific storage of the aquifer and confining units was estimated to be 1.5 x 10-5 meter-1. Longitudinal dispersivity of all layers was specified to be 0.5 meter. Leakage through the confining unit was estimated to be minimal and, therefore, not used in the reactive transport modeling. Inverse geochemical modeling indicates that mixing, cation exchange, and calcite dissolution are the dominant reactions that occur during aquifer storage recovery testing in the Santee Limestone/Black Mingo aquifer. Potable water injected into the Santee Limestone/Black Mingo aquifer evolved chemically by mixing with brackish background water and reaction with calcite and cation exchangers in the sediment. Reactive-transport model simulations indicated that the calcite and exchange reactions could be treated as equilibrium processes.
","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/sir20045046","usgsCitation":"Petkewich, M.D., Parkhurst, D.L., Conlon, K.J., Campbell, B.G., and Mirecki, J.E., 2004, Hydrologic and geochemical evaluation of aquifer storage recovery in the Santee Limestone/Black Mingo Aquifer, Charleston, South Carolina, 1998-2002: U.S. Geological Survey Scientific Investigations Report 2004-5046, 92 p., https://doi.org/10.3133/sir20045046.","productDescription":"92 p.","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true},{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true}],"links":[{"id":184845,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":5592,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.water.usgs.gov/sir20045046/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"South Carolina","city":"Charleston","otherGeospatial":"Santee Limestone/Black Mingo Aquifer","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.6451416015625,\n 32.41706632846282\n ],\n [\n -80.6451416015625,\n 33.211116472416855\n ],\n [\n -79.31579589843749,\n 33.211116472416855\n ],\n [\n -79.31579589843749,\n 32.41706632846282\n ],\n [\n -80.6451416015625,\n 32.41706632846282\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a29e4b07f02db6118d7","contributors":{"authors":[{"text":"Petkewich, Matthew D. 0000-0002-5749-6356 mdpetkew@usgs.gov","orcid":"https://orcid.org/0000-0002-5749-6356","contributorId":982,"corporation":false,"usgs":true,"family":"Petkewich","given":"Matthew","email":"mdpetkew@usgs.gov","middleInitial":"D.","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":true,"id":249325,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Parkhurst, David L. 0000-0003-3348-1544 dlpark@usgs.gov","orcid":"https://orcid.org/0000-0003-3348-1544","contributorId":1088,"corporation":false,"usgs":true,"family":"Parkhurst","given":"David","email":"dlpark@usgs.gov","middleInitial":"L.","affiliations":[{"id":5044,"text":"National Research Program - Central Branch","active":true,"usgs":true}],"preferred":true,"id":249327,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Conlon, Kevin J. 0000-0003-0798-368X kjconlon@usgs.gov","orcid":"https://orcid.org/0000-0003-0798-368X","contributorId":2561,"corporation":false,"usgs":true,"family":"Conlon","given":"Kevin","email":"kjconlon@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":249328,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Campbell, Bruce G. 0000-0003-4800-6674 bcampbel@usgs.gov","orcid":"https://orcid.org/0000-0003-4800-6674","contributorId":995,"corporation":false,"usgs":true,"family":"Campbell","given":"Bruce","email":"bcampbel@usgs.gov","middleInitial":"G.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":559,"text":"South Carolina Water Science Center","active":true,"usgs":true}],"preferred":true,"id":249326,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Mirecki, June E.","contributorId":93577,"corporation":false,"usgs":true,"family":"Mirecki","given":"June","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":249329,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":56935,"text":"sir20045084 - 2004 - Sources of mercury in sediments, water, and fish of the lakes of Whatcom County, Washington","interactions":[],"lastModifiedDate":"2012-02-02T00:12:20","indexId":"sir20045084","displayToPublicDate":"2004-09-01T00:00:00","publicationYear":"2004","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":"2004-5084","title":"Sources of mercury in sediments, water, and fish of the lakes of Whatcom County, Washington","docAbstract":"Concerns about mercury (Hg) contamination in Lake Whatcom, Washington, were raised in the late 1990s after a watershed protection survey reported elevated concentrations of Hg in smallmouth bass. The U.S. Geological Survey, the Whatcom County Health Department, and the Washington State Department of Ecology (Ecology) cooperated to develop a study to review existing data and collect new data that would lead to a better understanding of Hg deposition to Lake Whatcom and other lakes in Whatcom County, Washington.\r\n\r\nA simple atmospheric deposition model was developed that allowed comparisons of the deposition of Hg to the surfaces of each lake. Estimates of Hg deposition derived from the model indicated that the most significant deposition of Hg would have occurred to the lakes north of the City of Bellingham. These lakes were in the primary wind pattern of two municipal waste incinerators. Of all the lakes examined, basin 1 of Lake Whatcom would have been most affected by the Hg emissions from the chlor-alkali plant and the municipal sewage-sludge incinerator in the City of Bellingham. The length-adjusted concentrations of Hg in largemouth and smallmouth bass were not related to estimated deposition rates of Hg to the lakes from local atmospheric sources.\r\n\r\nTotal Hg concentrations in the surface sediments of Lake Whatcom are affected by the sedimentation of fine-grained particles, whereas organic carbon regulates the concentration of methyl-Hg in the surface sediments of the lake. Hg concentrations in dated sediment core samples indicate that increases in Hg sedimentation were largest during the first half of the 20th century. Increases in Hg sedimentation were smaller after the chlor-alkali plant and the incinerators began operating between 1964 and 1984. Analysis of sediments recently deposited in basin 1 of Lake Whatcom, Lake Terrell, and Lake Samish indicates a decrease in Hg sedimentation.\r\n\r\nConcentrations of Hg in Seattle precipitation and in tributary waters were used to calculate current (2002-03) loadings of Hg to Lake Whatcom. Hg in tributaries contributed 59 percent of the total Hg, whereas non-local atmospheric deposition was estimated to have contributed 41 percent of the 303 grams of Hg entering Lake Whatcom each year. However, these inputs cannot be verified without a better understanding of the sources of sediment to Lake Whatcom.","language":"ENGLISH","doi":"10.3133/sir20045084","usgsCitation":"Paulson, A.J., 2004, Sources of mercury in sediments, water, and fish of the lakes of Whatcom County, Washington: U.S. Geological Survey Scientific Investigations Report 2004-5084, 111 p., https://doi.org/10.3133/sir20045084.","productDescription":"111 p.","costCenters":[],"links":[{"id":5703,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.water.usgs.gov/sir20045084/","linkFileType":{"id":5,"text":"html"}},{"id":184930,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e49e6e4b07f02db5e7604","contributors":{"authors":[{"text":"Paulson, Anthony J. 0000-0002-2358-8834 apaulson@usgs.gov","orcid":"https://orcid.org/0000-0002-2358-8834","contributorId":5236,"corporation":false,"usgs":true,"family":"Paulson","given":"Anthony","email":"apaulson@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":255940,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":57160,"text":"sir20045053 - 2004 - Vertical gradients in water chemistry and age in the southern High Plains Aquifer, Texas, 2002","interactions":[],"lastModifiedDate":"2020-02-10T06:29:28","indexId":"sir20045053","displayToPublicDate":"2004-09-01T00:00:00","publicationYear":"2004","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":"2004-5053","displayTitle":"Vertical Gradients in Water Chemistry and Age in the Southern High Plains Aquifer, Texas, 2002","title":"Vertical gradients in water chemistry and age in the southern High Plains Aquifer, Texas, 2002","docAbstract":"The southern High Plains aquifer is the primary source of water used for domestic, industrial, and irrigation purposes in parts of New Mexico and Texas. Despite the aquifer's importance to the overall economy of the southern High Plains, fundamental ground-water characteristics, such as vertical gradients in water chemistry and age, remain poorly defined. As part of the U.S. Geological Survey's National Water-Quality Assessment Program, water samples from nested, short-screen monitoring wells installed in the southern High Plains aquifer at two locations (Castro and Hale Counties, Texas) were analyzed for field parameters, major ions, nutrients, trace elements, dissolved organic carbon, pesticides, stable and radioactive isotopes, and dissolved gases to evaluate vertical gradients in water chemistry and age in the aquifer. Tritium measurements indicate that recent (post-1953) recharge was present near the water table and that deeper water was recharged before 1953. Concentrations of dissolved oxygen were largest (2.6 to 5.6 milligrams per liter) at the water table and decreased with depth below the water table. The smallest concentrations were less than 0.5 milligram per liter. The largest major-ion concentrations generally were detected at the water table because of the effects of overlying agricultural activities, as indicated by postbomb tritium concentrations and elevated nitrate and pesticide concentrations at the water table. Below the zone of agricultural influence, major-ion concentrations exhibited small increases with depth and distance along flow paths because of rock/water interactions and mixing with water from the underlying aquifer in rocks of Cretaceous age. The concentration increases primarily were accounted for by dissolved sodium, bicarbonate, chloride, and sulfate. \r\n\r\nNitrite plus nitrate concentrations at the water table were 2.0 to 6.1 milligrams per liter as nitrogen, and concentrations substantially decreased with depth in the aquifer to a maximum concentration of 0.55 milligram per liter as nitrogen. Dissolved-gas and nitrogen-isotope data from the deep wells in Castro County indicate that denitrification occurred in the aquifer, removing 74 to more than 97 percent of the nitrate originally present in recharge. There was no evidence of denitrification in the deep part of the aquifer in Hale County. After correcting for denitrification effects, the background concentration of nitrate in water recharged before 1953 ranged from 0.4 to 3.2 milligrams per liter as nitrogen, with an average of 1.6 milligrams per liter as nitrogen. The d15N composition of background nitrate at the time of recharge was estimated to range from 9.6 to 12.3 per mil. \r\n\r\nMass-balance models indicate that the decreases in dissolved oxygen and nitrate concentrations and small increases in major-ion concentrations along flow paths can be accounted for by small amounts of silicate-mineral and calcite dissolution; SiO2, goethite, and clay-mineral precipitation; organic-carbon and pyrite oxidation; denitrification; and cation exchange. Mass-balance models for some wells also required mixing with water from the underlying aquifer in rocks of Cretaceous age to achieve mole and isotope balances. Carbon mass transfers identified in the models were used to adjust radiocarbon ages of water samples recharged before 1953. Adjusted radiocarbon ages ranged from less than 1,000 to 9,000 carbon-14 years before present. Radiocarbon ages were more sensitive to uncertainties in the carbon-14 content of recharge than uncertainties in carbon mass transfers, leading to 1-sigma uncertainties of about ?2,000 years in the adjusted ages. Despite these relatively large uncertainties in adjusted radiocarbon ages, it appears that deep water in the aquifer was considerably older (at least 1,000 years) than water near the water table.\r\n\r\nThere was essentially no change in ground-water age with depth in deeper parts of the aquifer, indicating that water in that ","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/sir20045053","usgsCitation":"McMahon, P., Böhlke, J., and Lehman, T., 2004, Vertical gradients in water chemistry and age in the southern High Plains Aquifer, Texas, 2002: U.S. Geological Survey Scientific Investigations Report 2004-5053, 53 p., https://doi.org/10.3133/sir20045053.","productDescription":"53 p.","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":180688,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"},{"id":5638,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.water.usgs.gov/sir2004-5053/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Texas","otherGeospatial":"Southern High Plains Aquifer","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -103.040771484375,\n 36.18665862660454\n ],\n [\n -103.0517578125,\n 31.970803930433096\n ],\n [\n -102.974853515625,\n 31.541089879585808\n ],\n [\n -102.65625,\n 31.44741029142872\n ],\n [\n -100.8984375,\n 31.531726144517158\n ],\n [\n -100.78857421875,\n 31.886886525780806\n ],\n [\n -100.75561523437499,\n 32.61161640317033\n ],\n [\n -100.81054687499999,\n 33.128351191631566\n ],\n [\n -100.777587890625,\n 33.715201644740844\n ],\n [\n -100.6787109375,\n 34.1890858311724\n ],\n [\n -100.557861328125,\n 34.69646117272349\n ],\n [\n -100.601806640625,\n 35.03899204678081\n ],\n [\n -100.75561523437499,\n 35.460669951495305\n ],\n [\n -100.8544921875,\n 35.567980458012094\n ],\n [\n -101.00830078125,\n 35.85343961959182\n ],\n [\n -101.173095703125,\n 36.12900165569652\n ],\n [\n -101.370849609375,\n 36.36822190085111\n ],\n [\n -101.72241210937499,\n 36.4566360115962\n ],\n [\n -102.3046875,\n 36.47872381162464\n ],\n [\n -102.469482421875,\n 36.48314061639213\n ],\n [\n -102.6397705078125,\n 36.47872381162464\n ],\n [\n -102.74414062499999,\n 36.43454191900892\n ],\n [\n -102.9364013671875,\n 36.29741818650811\n ],\n [\n -103.040771484375,\n 36.18665862660454\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a13e4b07f02db6021d7","contributors":{"authors":[{"text":"McMahon, P.B. 0000-0001-7452-2379","orcid":"https://orcid.org/0000-0001-7452-2379","contributorId":10762,"corporation":false,"usgs":true,"family":"McMahon","given":"P.B.","affiliations":[],"preferred":false,"id":256296,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Böhlke, J.K. 0000-0001-5693-6455","orcid":"https://orcid.org/0000-0001-5693-6455","contributorId":96696,"corporation":false,"usgs":true,"family":"Böhlke","given":"J.K.","affiliations":[],"preferred":false,"id":256298,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lehman, T.M.","contributorId":87621,"corporation":false,"usgs":true,"family":"Lehman","given":"T.M.","email":"","affiliations":[],"preferred":false,"id":256297,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":54270,"text":"sir20045001 - 2004 - Modeling Streamflow and Water Temperature in the North Santiam and Santiam Rivers, Oregon, 2001-02","interactions":[],"lastModifiedDate":"2017-02-07T09:20:08","indexId":"sir20045001","displayToPublicDate":"2004-09-01T00:00:00","publicationYear":"2004","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":"2004-5001","title":"Modeling Streamflow and Water Temperature in the North Santiam and Santiam Rivers, Oregon, 2001-02","docAbstract":"To support the development of a total maximum daily load (TMDL) for water temperature in the Willamette Basin, the laterally averaged, two-dimensional model CE-QUAL-W2 was used to construct a water temperature and streamflow model of the Santiam and North Santiam Rivers. The rivers were simulated from downstream of Detroit and Big Cliff dams to the confluence with the Willamette River. Inputs to the model included bathymetric data, flow and temperature from dam releases, tributary flow and temperature, and meteorologic data. The model was calibrated for the period July 1 through November 21, 2001, and confirmed with data from April 1 through October 31, 2002. Flow calibration made use of data from two streamflow gages and travel-time and river-width data. Temperature calibration used data from 16 temperature monitoring locations in 2001 and 5 locations in 2002. A sensitivity analysis was completed by independently varying input parameters, including point-source flow, air temperature, flow and water temperature from dam releases, and riparian shading. Scenario analyses considered hypothetical river conditions without anthropogenic heat inputs, with restored riparian vegetation, with minimum streamflow from the dams, and with a more-natural seasonal water temperature regime from dam releases.","language":"ENGLISH","doi":"10.3133/sir20045001","usgsCitation":"Sullivan, A.B., and Roundsk, S.A., 2004, Modeling Streamflow and Water Temperature in the North Santiam and Santiam Rivers, Oregon, 2001-02: U.S. Geological Survey Scientific Investigations Report 2004-5001, 44 p., https://doi.org/10.3133/sir20045001.","productDescription":"44 p.","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":5382,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.water.usgs.gov/sir20045001","linkFileType":{"id":5,"text":"html"}},{"id":178104,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a29e4b07f02db611b1f","contributors":{"authors":[{"text":"Sullivan, Annett B. 0000-0001-7783-3906 annett@usgs.gov","orcid":"https://orcid.org/0000-0001-7783-3906","contributorId":56317,"corporation":false,"usgs":true,"family":"Sullivan","given":"Annett","email":"annett@usgs.gov","middleInitial":"B.","affiliations":[],"preferred":false,"id":249709,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Roundsk, Stewart A.","contributorId":55272,"corporation":false,"usgs":true,"family":"Roundsk","given":"Stewart","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":249708,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":57730,"text":"fs20043091 - 2004 - Linking selenium sources to ecosystems: San Francisco Bay-Delta Model","interactions":[],"lastModifiedDate":"2020-02-09T16:53:38","indexId":"fs20043091","displayToPublicDate":"2004-09-01T00:00:00","publicationYear":"2004","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":"2004-3091","title":"Linking selenium sources to ecosystems: San Francisco Bay-Delta Model","docAbstract":"Marine sedimentary rocks of the Coast Ranges contribute selenium to soil, surface water, and ground water in the western San Joaquin Valley, California. Irrigation funnels selenium into a network of subsurface drains and canals. Proposals to build a master drain (i.e., San Luis Drain) to discharge into the San Francisco Bay-Delta Estuary remain as controversial today as they were in the 1950s, when drainage outside the San Joaquin Valley was first considered. An existing 85-mile portion of the San Luis Drain was closed in 1986 after fish mortality and deformities in ducks, grebes and coots were discovered at Kesterson National Wildlife Refuge, the temporary terminus of the drain. A 28-mile portion of the drain now conveys drainage from 100,000 acres into the San Joaquin River and eventually into the Bay-Delta. If the San Luis Drain is extended directly to the Bay-Delta, as is now being proposed as an alternative to sustain agriculture, it could receive drainage from an estimated one-million acres of farmland affected by rising water tables and increasing salinity. In addition to agricultural sources, oil refineries also discharge selenium to the Bay-Delta, although those discharges have declined in recent years. To understand the effects of changing selenium inputs, scientists have developed the Bay-Delta Selenium Model.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20043091","usgsCitation":"Presser, T.S., and Luoma, S.N., 2004, Linking selenium sources to ecosystems: San Francisco Bay-Delta Model: U.S. Geological Survey Fact Sheet 2004-3091, 4 p., https://doi.org/10.3133/fs20043091.","productDescription":"4 p.","costCenters":[{"id":589,"text":"Toxic Substances Hydrology Program","active":true,"usgs":true}],"links":[{"id":5981,"rank":99,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.water.usgs.gov/fs2004-3091/","linkFileType":{"id":5,"text":"html"}},{"id":338509,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2004/3091/coverthb2.jpg"},{"id":338426,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2004/3091/pdf/FS2004-3091.pdf","text":"Report","size":"1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2004-3091"}],"country":"United States","state":"California","otherGeospatial":"San Francisco Bay delta","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -123.211669921875,\n 37.34395908944491\n ],\n [\n -120.73974609374999,\n 37.34395908944491\n ],\n [\n -120.73974609374999,\n 38.40194908237822\n ],\n [\n -123.211669921875,\n 38.40194908237822\n ],\n [\n -123.211669921875,\n 37.34395908944491\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b15e4b07f02db6a5082","contributors":{"authors":[{"text":"Presser, Theresa S. 0000-0001-5643-0147 tpresser@usgs.gov","orcid":"https://orcid.org/0000-0001-5643-0147","contributorId":2467,"corporation":false,"usgs":true,"family":"Presser","given":"Theresa","email":"tpresser@usgs.gov","middleInitial":"S.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":687765,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Luoma, Samuel N. 0000-0001-5443-5091 snluoma@usgs.gov","orcid":"https://orcid.org/0000-0001-5443-5091","contributorId":2287,"corporation":false,"usgs":true,"family":"Luoma","given":"Samuel","email":"snluoma@usgs.gov","middleInitial":"N.","affiliations":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"preferred":true,"id":687766,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":57752,"text":"sir20045121 - 2004 - Evaluation of conceptual models of natural organic matter (humus) from a consideration of the chemical and biochemical processes of humification","interactions":[],"lastModifiedDate":"2012-02-02T00:12:33","indexId":"sir20045121","displayToPublicDate":"2004-09-01T00:00:00","publicationYear":"2004","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":"2004-5121","title":"Evaluation of conceptual models of natural organic matter (humus) from a consideration of the chemical and biochemical processes of humification","docAbstract":"Natural organic matter (NOM) has been studied for more than 200 years because of its importance in enhancing soil fertility, soil structure, and water-holding capacity and as a carbon sink in the global carbon cycle. Two different types of models have been proposed for NOM: (1) the humic polymer models and (2) the molecular aggregate models. In the humic polymer models, NOM molecules are depicted as large (humic) polymers that have unique chemical structures that are different from those of the precursor plant degradation products. In the molecular aggregate models, NOM is depicted as being composed of molecular aggregates (supramolecular aggregates) of plant degradation products held together by non-covalent bonds. The preponderance of evidence favors the supramolecular aggregate models. These models were developed by studying the properties of NOM extracted from soils and natural waters, and as such, they provide only a very generalized picture of the structure of NOM aggregates in soils and natural waters prior to extraction. A compartmental model, in which the structure of the NOM in each of the compartments is treated separately, should provide a more accurate representation of NOM in soil and sediment systems. The proposed NOM compartments are: (1) partially degraded plant tissue, (2) biomass from microorganisms, (3) organic coatings on mineral grains, (4) pyrolytic carbon, (5) organic precipitates, and (6) dissolved organic matter (DOM) in interstitial water. Within each of these compartments there are NOM supramolecular aggregates that will be dissolved by the solvent systems that are used by researchers for extraction of NOM from soils and sediments. In natural water systems DOM may be considered as existing in two subcompartments: (1) truly dissolved DOM and (2) colloidal DOM.","language":"ENGLISH","doi":"10.3133/sir20045121","usgsCitation":"Wershaw, R.L., 2004, Evaluation of conceptual models of natural organic matter (humus) from a consideration of the chemical and biochemical processes of humification: U.S. Geological Survey Scientific Investigations Report 2004-5121, 49 p., https://doi.org/10.3133/sir20045121.","productDescription":"49 p.","costCenters":[],"links":[{"id":5995,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.water.usgs.gov/sir20045121/","linkFileType":{"id":5,"text":"html"}},{"id":182574,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/usgs_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e49fee4b07f02db5f7519","contributors":{"authors":[{"text":"Wershaw, Robert L. rwershaw@usgs.gov","contributorId":4856,"corporation":false,"usgs":true,"family":"Wershaw","given":"Robert","email":"rwershaw@usgs.gov","middleInitial":"L.","affiliations":[],"preferred":true,"id":257696,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70176639,"text":"70176639 - 2004 - The rising tide of ocean diseases: Unsolved problems and research priorities","interactions":[],"lastModifiedDate":"2016-09-23T11:29:13","indexId":"70176639","displayToPublicDate":"2004-09-01T00:00:00","publicationYear":"2004","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1701,"text":"Frontiers in Ecology and the Environment","active":true,"publicationSubtype":{"id":10}},"title":"The rising tide of ocean diseases: Unsolved problems and research priorities","docAbstract":"New studies have detected a rising number of reports of diseases in marine organisms such as corals, molluscs, turtles, mammals, and echinoderms over the past three decades. Despite the increasing disease load, microbiological, molecular, and theoretical tools for managing disease in the world's oceans are under-developed. Review of the new developments in the study of these diseases identifies five major unsolved problems and priorities for future research: (1) detecting origins and reservoirs for marine diseases and tracing the flow of some new pathogens from land to sea; (2) documenting the longevity and host range of infectious stages; (3) evaluating the effect of greater taxonomic diversity of marine relative to terrestrial hosts and pathogens; (4) pinpointing the facilitating role of anthropogenic agents as incubators and conveyors of marine pathogens; (5) adapting epidemiological models to analysis of marine disease.
","language":"English","publisher":"Ecological Society of America","doi":"10.1890/1540-9295(2004)002[0375:TRTOOD]2.0.CO;2","usgsCitation":"Harvell, D., Aronson, R., Baron, N., Connell, J., Dobson, A.P., Ellner, S., Gerber, L.R., Kim, K., Kuris, A.M., McCallum, H., Lafferty, K.D., McKay, B., Porter, J., Pascual, M., Smith, G., Sutherland, K., and Ward, J., 2004, The rising tide of ocean diseases: Unsolved problems and research priorities: Frontiers in Ecology and the Environment, v. 2, no. 7, p. 375-382, https://doi.org/10.1890/1540-9295(2004)002[0375:TRTOOD]2.0.CO;2.","productDescription":"8 p.","startPage":"375","endPage":"382","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":478024,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://hdl.handle.net/2027.42/117033","text":"External Repository"},{"id":328901,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"2","issue":"7","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"57fe932ee4b0824b2d14c982","contributors":{"authors":[{"text":"Harvell, Drew","contributorId":149982,"corporation":false,"usgs":false,"family":"Harvell","given":"Drew","email":"","affiliations":[{"id":17869,"text":"Department of Ecology & Evolutionary Biology, Cornell University, Ithaca, NY 14853","active":true,"usgs":false}],"preferred":false,"id":649444,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Aronson, Richard","contributorId":174847,"corporation":false,"usgs":false,"family":"Aronson","given":"Richard","affiliations":[],"preferred":false,"id":649445,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Baron, Nancy","contributorId":174848,"corporation":false,"usgs":false,"family":"Baron","given":"Nancy","email":"","affiliations":[],"preferred":false,"id":649446,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Connell, Joseph","contributorId":174849,"corporation":false,"usgs":false,"family":"Connell","given":"Joseph","affiliations":[],"preferred":false,"id":649447,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dobson, Andrew P.","contributorId":63693,"corporation":false,"usgs":true,"family":"Dobson","given":"Andrew","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":649448,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ellner, Steve","contributorId":174850,"corporation":false,"usgs":false,"family":"Ellner","given":"Steve","email":"","affiliations":[],"preferred":false,"id":649449,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gerber, Leah 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We hypothesize that the evolutionary stability of mutualism can depend on how benefits and costs to one mutualist vary with the population density of its partner, and that stability can be maintained if a mutualist can influence demographic rates and regulate the population density of its partner. We test this hypothesis in a model of mutualism with key features of senita cactus (Pachycereus schottii) – senita moth (Upiga virescens) interactions, in which benefits of pollination and costs of larval seed consumption to plant fitness depend on pollinator density. We show that plants can maximize their fitness by allocating resources to the production of excess flowers at the expense of fruit. Fruit abortion resulting from excess flower production reduces pre–adult survival of the pollinating seed–consumer, and maintains its density beneath a threshold that would destabilize the mutualism. Such a strategy of excess flower production and fruit abortion is convergent and evolutionarily stable against invasion by cheater plants that produce few flowers and abort few to no fruit. This novel mechanism of achieving evolutionarily stable mutualism, namely interspecific population regulation, is qualitatively different from other mechanisms invoking partner choice or selective rewards, and may be a general process that helps to preserve mutualistic interactions in nature.
","language":"English","publisher":"The Royal Society Publishing","doi":"10.1098/rspb.2004.2789","usgsCitation":"Holland, J.N., DeAngelis, D., and Schultz, S.T., 2004, Evolutionary stability of mutualism: interspecific population regulation as an evolutionarily stable strategy: Proceedings of the Royal Society B, v. 271, no. 1550, p. 1807-1814, https://doi.org/10.1098/rspb.2004.2789.","productDescription":"8 p.","startPage":"1807","endPage":"1814","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":478025,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/1691799","text":"External Repository"},{"id":313946,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"271","issue":"1550","noUsgsAuthors":false,"publicationDate":"2004-09-07","publicationStatus":"PW","scienceBaseUri":"568e48ffe4b0e7a44bc4194d","contributors":{"authors":[{"text":"Holland, J. 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Investigations of atmospheric forcing and oceanic response (including wave generation and propagation, water-mass formation, stratification, and circulation), suspended material, bottom boundary layer dynamics, bottom sediment, and small-scale stratigraphy were performed by European and North American researchers participating in several projects. The goal of EuroSTRATAFORM researchers is to improve our ability to understand and simulate the physical processes that deliver sediment to the marine environment and generate stratigraphic signatures. Scientists involved in the Po and Apennine Sediment Transport and Accumulation (PASTA) experiment benefited from other major research programs including ACE (Adriatic Circulation Experiment), DOLCE VITA (Dynamics of Localized Currents and Eddy Variability in the Adriatic), EACE (the Croatian East Adriatic Circulation Experiment project), WISE (West Istria Experiment), and ADRICOSM (Italian nowcasting and forecasting) studies.","language":"English","publisher":"Oceanography Society","publisherLocation":"Washington, D.C.","doi":"10.5670/oceanog.2004.04","usgsCitation":"Sherwood, C.R., Book, J.W., Carniel, S., Cavaleri, L., Chiggiato, J., Das, H., Doyle, J.D., Harris, C.K., Niedoroda, A.W., Perkins, H., Poulain, P., Pullen, J., Reed, C.W., Russo, A., Sclavo, M., Signell, R.P., Traykovski, P.A., and Warner, J., 2004, Sediment dynamics in the Adriatic Sea investigated with coupled models: Oceanography, v. 17, no. 4, p. 58-69, 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Only about 165 genuine impact structures have been identified to date (Table 1.1). Even so, the number is steadily increasing at the rate of ∼3–5 per year (Grieve et al. 1995; Earth Impact Database at http://www.unb.ca/passc/Impact/Database/). In stark contrast, most other rocky planets and satellites of our solar system are pockmarked by thousands to hundreds of thousands of impact features (Beatty et al. 1999). Nevertheless, impact specialists acknowledge that Earth, too, has undergone billions of years of bolide bombardment (Melosh 1989; Schoenberg et al. 2002). The most intense bombardment, however, took place during Earth’s earliest history (∼3.8–4 Ga; Ryder 1990; Cohen et al. 2000; Ryder et al. 2000). Traces of most terrestrial impacts have been completely erased or strongly altered by the dynamic processes of a thick atmosphere, deep ocean, and mobile crust, a combination unique to our planet. Planetary geologists now recognize that processes associated with bolide impacts are fundamental to planetary accretion and surface modification (Melosh 1989; Peucker-Ehrenbrink and Schmitz 2001). Incoming meteorites may have been primary sources for Earth’s water, and, perhaps, even organic life as we know it (Thomas et al. 1997; Kring 2000). There is little doubt that impacts played a major role in the evolution of Earth’s biota (Ryder et al. 1996; Hart 1996).","language":"English","publisher":"Springer","doi":"10.1007/978-3-642-18900-5","usgsCitation":"Poag, C.W., Koeberl, C., and Reimold, W.U., 2004, The Chesapeake Bay Crater: Geology and geophysics of a Late Eocene submarine impact structure, 522 p., https://doi.org/10.1007/978-3-642-18900-5.","productDescription":"522 p.","costCenters":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"links":[{"id":292883,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Maryland; Virginia","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -76.6311,36.9075 ], [ -76.6311,39.5704 ], [ -75.6353,39.5704 ], [ -75.6353,36.9075 ], [ -76.6311,36.9075 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"53f85993e4b03f038c5c193c","contributors":{"authors":[{"text":"Poag, C. 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The MRIB is composed of a categorization scheme, a metadata database, and a specialized software backend, capable of drawing together information from remote sources without modifying their original format or content. Twelve facets are used to classify information: location, geologic time, feature type, biota, discipline, research method, hot topics, project, agency, author, content type, and file type. The MRIB approach allows easy and flexible organization of large or growing document collections for which centralized repositories would be impractical. Geographic searching based on the gazetteer and map interface is the centerpiece of the MRIB distributed geolibrary. The MRIB is one of a very few digital libraries that employ georeferencing -- a fundamentally different way to structure information from the traditional author/title/subject/keyword approach employed by most digital libraries. 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These conditions were revealed by nearly 300 km of streamer resistivity surveys, utilizing a towed multichannel cable system. Zones of high resistivity displayed by inversion modeling were confirmed by vibradrilling investigations to correspond to fresh ground water occurrences. Fresh water lenses extended from a few hundred meters up to 2 km from shore. Along the western margins of coastal bays in areas associated with fine-grained surficial sediments, high-resistivity layers were widespread and were especially pronounced near tidal creeks. Fresh ground water layers were less common along the eastern barrier-bar margins of the bays, where sediments were typically sandy. Mid-bay areas in Chincoteague Bay, Maryland, did not show evidence of fresh water. Indian River Bay, Delaware, showed complex subsurface salinity relationships, including an area with possible hypersaline brines. The new streamer resistivity system paired with vibradrilling in these investigations provides a powerful approach to recovering information required for extension of hydrologic modeling of shallow coastal aquifer systems into offshore areas.","language":"English","publisher":"Wiley","doi":"10.1111/j.1745-6584.2004.tb02643.x","usgsCitation":"Manheim, F., Krantz, D.E., and Bratton, J.F., 2004, Studying ground water under Delmarva coastal bays using electrical resistivity: Ground Water, v. 42, no. 7, p. 1052-1068, https://doi.org/10.1111/j.1745-6584.2004.tb02643.x.","productDescription":"17 p.","startPage":"1052","endPage":"1068","costCenters":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":478028,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/j.1745-6584.2004.tb02643.x","text":"Publisher Index Page"},{"id":292853,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Delaware, Maryland, Virginia","otherGeospatial":"Delmarva Peninsula","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -75.419907,37.865355 ], [ -75.419907,38.820557 ], [ -75.069246,38.820557 ], [ -75.069246,37.865355 ], [ -75.419907,37.865355 ] ] ] } } ] }","volume":"42","issue":"7","noUsgsAuthors":false,"publicationDate":"2006-03-24","publicationStatus":"PW","scienceBaseUri":"53f85991e4b03f038c5c192e","contributors":{"authors":[{"text":"Manheim, Frank T. 0000-0003-4005-4524","orcid":"https://orcid.org/0000-0003-4005-4524","contributorId":45294,"corporation":false,"usgs":true,"family":"Manheim","given":"Frank T.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":false,"id":499142,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Krantz, David E.","contributorId":9238,"corporation":false,"usgs":true,"family":"Krantz","given":"David","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":499141,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"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":499143,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}