The laboratory for analysis of low-ionic-strength water at the U.S. Geological Survey (USGS) Water Science Center in Troy, N.Y., analyzes samples collected by USGS projects throughout the Northeast. The laboratory's quality-assurance program is based on internal and interlaboratory quality-assurance samples and quality-control procedures that were developed to ensure proper sample collection, processing, and analysis. The quality-assurance and quality-control data were stored in the laboratory's Lab Master data-management system, which provides efficient review, compilation, and plotting of data. This report presents and discusses results of quality-assurance and quality control samples analyzed from July 2003 through June 2005.
Results for the quality-control samples for 20 analytical procedures were evaluated for bias and precision. Control charts indicate that data for five of the analytical procedures were occasionally biased for either high-concentration or low-concentration samples but were within control limits; these procedures were: acid-neutralizing capacity, total monomeric aluminum, pH, silicon, and sodium. Seven of the analytical procedures were biased throughout the analysis period for the high-concentration sample, but were within control limits; these procedures were: dissolved organic carbon, chloride, nitrate (ion chromatograph), nitrite, silicon, sodium, and sulfate. The calcium and magnesium procedures were biased throughout the analysis period for the low-concentration sample, but were within control limits. The total aluminum and specific conductance procedures were biased for the high-concentration and low-concentration samples, but were within control limits.
Results from the filter-blank and analytical-blank analyses indicate that the procedures for 17 of 18 analytes were within control limits, although the concentrations for blanks were occasionally outside the control limits. The data-quality objective was not met for dissolved organic carbon.
Sampling and analysis precision are evaluated herein in terms of the coefficient of variation obtained for triplicate samples in the procedures for 18 of the 22 analytes. At least 85 percent of the samples met data-quality objectives for all analytes except total monomeric aluminum (82 percent of samples met objectives), total aluminum (77 percent of samples met objectives), chloride (80 percent of samples met objectives), fluoride (76 percent of samples met objectives), and nitrate (ion chromatograph) (79 percent of samples met objectives). The ammonium and total dissolved nitrogen did not meet the data-quality objectives.
Results of the USGS interlaboratory Standard Reference Sample (SRS) Project indicated good data quality over the time period, with ratings for each sample in the satisfactory, good, and excellent ranges or less than 10 percent error. The P-sample (low-ionic-strength constituents) analysis had one marginal and two unsatisfactory ratings for the chloride procedure. The T-sample (trace constituents)analysis had two unsatisfactory ratings and one high range percent error for the aluminum procedure. The N-sample (nutrient constituents) analysis had one marginal rating for the nitrate procedure.
Results of Environment Canada's National Water Research Institute (NWRI) program indicated that at least 84 percent of the samples met data-quality objectives for 11 of the 14 analytes; the exceptions were ammonium, total aluminum, and acid-neutralizing capacity. The ammonium procedure did not meet data quality objectives in all studies. Data-quality objectives were not met in 23 percent of samples analyzed for total aluminum and 45 percent of samples analyzed acid-neutralizing capacity.
Results from blind reference-sample analyses indicated that data-quality objectives were met by at least 86 percent of the samples analyzed for calcium, chloride, fluoride, magnesium, pH, potassium, sodium, and sulfate. Data-quality objectives were not met by samples analyzed for fluoride.
","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20091233","usgsCitation":"Lincoln, T.A., Horan-Ross, D.A., McHale, M.R., and Lawrence, G.B., 2009, Quality-assurance data for routine water analyses by the U.S. Geological Survey laboratory in Troy, New York - July 2003 through June 2005: U.S. Geological Survey Open-File Report 2009-1233, iv, 35 p., https://doi.org/10.3133/ofr20091233.","productDescription":"iv, 35 p.","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2003-07-01","temporalEnd":"2005-06-30","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":125646,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2009_1233.jpg"},{"id":13348,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2009/1233/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ac9e4b07f02db67c59c","contributors":{"authors":[{"text":"Lincoln, Tricia A. tarenga@usgs.gov","contributorId":3803,"corporation":false,"usgs":true,"family":"Lincoln","given":"Tricia","email":"tarenga@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":304236,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Horan-Ross, Debra A. dhross@usgs.gov","contributorId":3809,"corporation":false,"usgs":true,"family":"Horan-Ross","given":"Debra","email":"dhross@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":304237,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McHale, Michael R. 0000-0003-3780-1816 mmchale@usgs.gov","orcid":"https://orcid.org/0000-0003-3780-1816","contributorId":1735,"corporation":false,"usgs":true,"family":"McHale","given":"Michael","email":"mmchale@usgs.gov","middleInitial":"R.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":304235,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lawrence, Gregory B. 0000-0002-8035-2350 glawrenc@usgs.gov","orcid":"https://orcid.org/0000-0002-8035-2350","contributorId":867,"corporation":false,"usgs":true,"family":"Lawrence","given":"Gregory","email":"glawrenc@usgs.gov","middleInitial":"B.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":304234,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":98116,"text":"fs20093103 - 2009 - Stormwater runoff: What it is and why it is important in Johnson County, Kansas","interactions":[],"lastModifiedDate":"2023-05-05T19:02:13.984993","indexId":"fs20093103","displayToPublicDate":"2010-01-16T00:00:00","publicationYear":"2009","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":"2009-3103","title":"Stormwater runoff: What it is and why it is important in Johnson County, Kansas","docAbstract":"Stormwater runoff is a leading contributor to pollution in streams, rivers, and lakes in Johnson County, Kansas, and nationwide. Because stormwater runoff contains pollutants from many different sources, decreasing pollution from stormwater runoff is a challenging task. It requires cooperation from residents, businesses, and municipalities. An important step in protecting streams from stormwater pollution is understanding watershed processes, stormwater characteristics, and their combined effects on streams and water quality.","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/fs20093103","collaboration":"Prepared in cooperation with the Johnson County Stormwater Management Program","usgsCitation":"Rasmussen, T.J., and Schmidt, H., 2009, Stormwater runoff: What it is and why it is important in Johnson County, Kansas: U.S. Geological Survey Fact Sheet 2009-3103, 2 p., https://doi.org/10.3133/fs20093103.","productDescription":"2 p.","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":125629,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2009_3103.jpg"},{"id":416785,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_90295.htm","linkFileType":{"id":5,"text":"html"}},{"id":13355,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2009/3103/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Kansas","county":"Johnson County","geographicExtents":"{\"type\":\"FeatureCollection\",\"features\":[{\"type\":\"Feature\",\"geometry\":{\"type\":\"Polygon\",\"coordinates\":[[[-94.6075,39.0437],[-94.6075,39.0399],[-94.6082,38.8463],[-94.6084,38.8341],[-94.6102,38.7376],[-95.0572,38.7395],[-95.0558,38.9816],[-95.0477,38.9778],[-95.0383,38.9771],[-95.0312,38.9773],[-95.0292,38.9813],[-95.0271,38.9881],[-95.0249,38.9962],[-95.0189,38.9987],[-95.0135,38.9991],[-95.0077,38.998],[-94.9946,38.9976],[-94.9899,38.997],[-94.9841,38.995],[-94.9789,38.9926],[-94.9755,38.9885],[-94.9704,38.9851],[-94.9645,38.9832],[-94.9575,38.982],[-94.9527,38.9828],[-94.9479,38.9845],[-94.9448,38.9871],[-94.9423,38.9898],[-94.9386,38.9933],[-94.9367,38.9964],[-94.9335,38.9995],[-94.9264,38.9998],[-94.9217,38.9996],[-94.9176,38.9977],[-94.9209,38.9919],[-94.923,38.9856],[-94.9207,38.9837],[-94.9164,38.9859],[-94.9115,38.9889],[-94.9078,38.9924],[-94.9014,39.0022],[-94.8989,39.0053],[-94.8945,39.0102],[-94.8919,39.0155],[-94.891,39.021],[-94.8875,39.0313],[-94.8824,39.0379],[-94.8768,39.0441],[-94.8681,39.052],[-94.8631,39.0564],[-94.8488,39.0578],[-94.8318,39.0546],[-94.8131,39.0486],[-94.8038,39.0456],[-94.7197,39.0435],[-94.6693,39.0433],[-94.6075,39.0437]]]},\"properties\":{\"name\":\"Johnson\",\"state\":\"KS\"}}]}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b28e4b07f02db6b15f5","contributors":{"authors":[{"text":"Rasmussen, Teresa J. 0000-0002-7023-3868 rasmuss@usgs.gov","orcid":"https://orcid.org/0000-0002-7023-3868","contributorId":3336,"corporation":false,"usgs":true,"family":"Rasmussen","given":"Teresa","email":"rasmuss@usgs.gov","middleInitial":"J.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":304218,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schmidt, Heather C.","contributorId":99668,"corporation":false,"usgs":true,"family":"Schmidt","given":"Heather C.","affiliations":[],"preferred":false,"id":304219,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":98118,"text":"ofr20091257 - 2009 - Groundwater Quality in Central New York, 2007","interactions":[],"lastModifiedDate":"2012-03-08T17:16:29","indexId":"ofr20091257","displayToPublicDate":"2010-01-16T00:00:00","publicationYear":"2009","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":"2009-1257","title":"Groundwater Quality in Central New York, 2007","docAbstract":"Water samples were collected from 7 production wells and 28 private residential wells in central New York from August through December 2007 and analyzed to characterize the chemical quality of groundwater. Seventeen wells are screened in sand and gravel aquifers, and 18 are finished in bedrock aquifers. The wells were selected to represent areas of greatest groundwater use and to provide a geographical sampling from the 5,799-square-mile study area. Samples were analyzed for 6 physical properties and 216 constituents, including nutrients, major inorganic ions, trace elements, radionuclides, pesticides, volatile organic compounds, phenolic compounds, organic carbon, and 4 types of bacteria.\r\n\r\nResults indicate that groundwater used for drinking supply is generally of acceptable quality, although concentrations of some constituents or bacteria exceeded at least one drinking-water standard at several wells. The cations detected in the highest concentrations were calcium, magnesium, and sodium; anions detected in the highest concentrations were bicarbonate, chloride, and sulfate. The predominant nutrients were nitrate and ammonia, but no nutrients exceeded Maximum Contaminant Levels (MCLs). The trace elements barium, boron, lithium, and strontium were detected in every sample; the trace elements present in the highest concentrations were barium, boron, iron, lithium, manganese, and strontium. Fifteen pesticides, including seven pesticide degradates, were detected in water from 17 of the 35 wells, but none of the concentrations exceeded State or Federal MCLs. Sixteen volatile organic compounds were detected in water from 15 of the 35 wells.\r\n\r\nNine analytes and three types of bacteria were detected in concentrations that exceeded Federal and State drinking-water standards, which typically are identical. One sample had a water color that exceeded the U.S. Environmental Protection Agency (USEPA) Secondary Maximum Contaminant Level (SMCL) and the New York State MCL of 10 color units. Sulfate concentrations exceeded the USEPA SMCL and the New York State MCL of 250 milligrams per liter (mg/L) in two samples, and chloride concentrations exceeded the USEPA SMCL and the New York State MCL of 250 mg/L in two samples. Sodium concentrations exceeded the USEPA Drinking Water Health Advisory of 60 mg/L in eight samples. Iron concentrations exceeded the USEPA SMCL and the New York State MCL of 300 micrograms per liter (ug/L) in 10 filtered samples. Manganese exceeded the USEPA SMCL of 50 ug/L in 10 filtered samples and the New York State MCL of 300 ug/L in 1 filtered sample. Barium exceeded the MCL of 2,000 ug/L in one sample, and aluminum exceeded the SMCL of 50 ug/L in three samples. Radon-222 exceeded the proposed USEPA MCL of 300 picocuries per liter in 12 samples. One sample from a private residential well had a trichloroethene concentration of 50.8 ug/L, which exceeded the MCL of 5 ug/L. Any detection of coliform bacteria indicates a potential violation of New York State health regulations; total coliform bacteria were detected in 19 samples, and fecal coliform bacteria were detected in one sample. The plate counts for heterotrophic bacteria exceeded the MCL (500 colony-forming units per milliliter) in three samples.","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20091257","collaboration":"Prepared in cooperation with the New York State Department of Environmental Conservation","usgsCitation":"Eckhardt, D., Reddy, J., and Shaw, S.B., 2009, Groundwater Quality in Central New York, 2007: U.S. Geological Survey Open-File Report 2009-1257, vi, 39 p., https://doi.org/10.3133/ofr20091257.","productDescription":"vi, 39 p.","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2007-08-01","temporalEnd":"2007-12-31","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":125636,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2009_1257.jpg"},{"id":13358,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2009/1257/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -78,42 ], [ -78,44 ], [ -75,44 ], [ -75,42 ], [ -78,42 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a90e4b07f02db655990","contributors":{"authors":[{"text":"Eckhardt, David A.V.","contributorId":80233,"corporation":false,"usgs":true,"family":"Eckhardt","given":"David A.V.","affiliations":[],"preferred":false,"id":304223,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Reddy, J.E.","contributorId":32943,"corporation":false,"usgs":true,"family":"Reddy","given":"J.E.","email":"","affiliations":[],"preferred":false,"id":304221,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shaw, Stephen B.","contributorId":40700,"corporation":false,"usgs":true,"family":"Shaw","given":"Stephen","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":304222,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":98114,"text":"sir20095125 - 2009 - Water Withdrawals, Use, and Trends in Florida, 2005","interactions":[],"lastModifiedDate":"2012-02-10T00:11:53","indexId":"sir20095125","displayToPublicDate":"2010-01-16T00:00:00","publicationYear":"2009","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":"2009-5125","title":"Water Withdrawals, Use, and Trends in Florida, 2005","docAbstract":"In 2005, the total amount of water withdrawals in Florida was estimated at 18,359 million gallons per day (Mgal/d). Saline water accounted for 11,486 Mgal/d (63 percent), and freshwater accounted for 6,873 Mgal/d (37 percent). Groundwater accounted for 4,247 Mgal/d (62 percent) of freshwater withdrawals, and surface water accounted for the remaining 2,626 Mgal/d (38 percent). Surface water accounted for nearly all (99.9 percent) saline-water withdrawals. An additional 660 Mgal/d of reclaimed wastewater was used in Florida during 2005. The largest amount of freshwater was withdrawn from Palm Beach County, and the largest amount of saline water was withdrawn from Pasco County.\r\n\r\nFresh groundwater provided drinking water (public supplied and self-supplied) for 16.19 million people (90 percent of Florida's population), and fresh surface water provided drinking water for 1.73 million people (10 percent). The majority of groundwater withdrawals (nearly 60 percent) in 2005 was obtained from the Floridan aquifer system which is present throughout the entire State. The majority of fresh surface-water withdrawals (59 percent) came from the southern Florida hydrologic unit subregion and is associated with Lake Okeechobee and the canals in the Everglades Agricultural Area of Glades, Hendry, and Palm Beach Counties, as well as the Caloosahatchee River and its tributaries in the agricultural areas of Collier, Glades, Hendry, and Lee Counties.\r\n\r\nOverall, agricultural irrigation accounted for 40 percent of the total freshwater withdrawals (ground and surface), followed by public supply with 37 percent. Public supply accounted for 52 percent of groundwater withdrawals, followed by agricultural self-supplied (31 percent), ommercial-industrial-mining self-supplied (8.5 percent), recreational irrigation and domestic self-supplied (4 percent each), and power generation (0.5 percent). Agricultural self-supplied accounted for 56 percent of fresh surface-water withdrawals, followed by power generation (20.5 percent), public supply (13 percent), recreational irrigation (6 percent), and commercial-industrial self-supplied (4.5 percent). Power generation accounted for nearly all (99.9 percent) saline-water withdrawals.\r\n\r\nOf the 17.92 million people who resided in Florida during 2005, 41 percent (7.36 million people) resided in the South Florida Water Management District (SFWMD), followed by the St. Johns River Water Management District (SJRWMD) and the Southwest Florida Water Management District (SWFWMD) with 25 percent each (4.46 and 4.44 million people, respectively), the Northwest Florida Water Management District (NWFWMD) with 7.5 percent (1.34 million people), and the Suwannee River Water Management District (SRWMD) with 1.5 percent (0.32 million people). The largest amount of freshwater withdrawals was from the SFWMD, which was one-half (50 percent) of the State's total freshwater withdrawals, followed by the SJRWMD (19 percent), SWFWMD (16 percent), NWFWMD (10 percent), and SRWMD (5 percent). \r\n\r\nBetween 1950 and 2005, the population of Florida increased by 15.15 million (550 percent), and the total water withdrawals (fresh and saline) increased 15,700 Mgal/d (600 percent). More recently, total withdrawals decreased 1,790 Mgal/d (9 percent) between 2000 and 2005, but the total population increased by 1.94 million (12 percent). Between 1990 and 2005, saline-water withdrawals increased 1,120 Mgal/d (11 percent), whereas between 2000 and 2005, saline-water withdrawals decreased 470 Mgal/d (4 percent). Between 1990 and 2005, freshwater withdrawals decreased 710 Mgal/d (9 percent), whereas between 2000 and 2005, freshwater withdrawals decreased 1,320 Mgal/d (16 percent). \r\n\r\nThe use of highly mineralized groundwater as a source of supply, primarily for public supply, also has increased in Florida. This water, referred as nonpotable water, increased from just less than 2 Mgal/d in 1970, to 142 Mgal/d in 2005. Nonpotable water is treated to meet drin","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/sir20095125","isbn":"9781411326040","collaboration":"Prepared in cooperation with the Florida Department of Environmental Protection","usgsCitation":"Marella, R.L., 2009, Water Withdrawals, Use, and Trends in Florida, 2005: U.S. Geological Survey Scientific Investigations Report 2009-5125, viii, 49 p., https://doi.org/10.3133/sir20095125.","productDescription":"viii, 49 p.","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2005-01-01","temporalEnd":"2005-12-31","costCenters":[{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"links":[{"id":125624,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2009_5125.jpg"},{"id":13353,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2009/5125/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -88,24 ], [ -88,31.5 ], [ -79.5,31.5 ], [ -79.5,24 ], [ -88,24 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b00e4b07f02db697fb8","contributors":{"authors":[{"text":"Marella, Richard L. 0000-0003-4861-9841 rmarella@usgs.gov","orcid":"https://orcid.org/0000-0003-4861-9841","contributorId":2443,"corporation":false,"usgs":true,"family":"Marella","given":"Richard","email":"rmarella@usgs.gov","middleInitial":"L.","affiliations":[{"id":27821,"text":"Caribbean-Florida Water Science Center","active":true,"usgs":true},{"id":5051,"text":"FLWSC-Orlando","active":true,"usgs":true}],"preferred":true,"id":304213,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":98112,"text":"fs20093028 - 2009 - An estimate of recoverable heavy oil resources of the Orinoco Oil Belt, Venezuela","interactions":[],"lastModifiedDate":"2018-08-28T15:36:04","indexId":"fs20093028","displayToPublicDate":"2010-01-16T00:00:00","publicationYear":"2009","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":"2009-3028","title":"An estimate of recoverable heavy oil resources of the Orinoco Oil Belt, Venezuela","docAbstract":"The Orinoco Oil Belt Assessment Unit of the La Luna-Quercual Total Petroleum System encompasses approximately 50,000 km2 of the East Venezuela Basin Province that is underlain by more than 1 trillion barrels of heavy oil-in-place. As part of a program directed at estimating the technically recoverable oil and gas resources of priority petroleum basins worldwide, the U.S. Geological Survey estimated the recoverable oil resources of the Orinoco Oil Belt Assessment Unit. This estimate relied mainly on published geologic and engineering data for reservoirs (net oil-saturated sandstone thickness and extent), petrophysical properties (porosity, water saturation, and formation volume factors), recovery factors determined by pilot projects, and estimates of volumes of oil-in-place. The U.S. Geological Survey estimated a mean volume of 513 billion barrels of technically recoverable heavy oil in the Orinoco Oil Belt Assessment Unit of the East Venezuela Basin Province; the range is 380 to 652 billion barrels. The Orinoco Oil Belt Assessment Unit thus contains one of the largest recoverable oil accumulations in the world.\r\n","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/fs20093028","usgsCitation":"Schenk, C.J., Cook, T.A., Charpentier, R., Pollastro, R.M., Klett, T., Tennyson, M., Kirschbaum, M.A., Brownfield, M.E., and Pitman, J.K., 2009, An estimate of recoverable heavy oil resources of the Orinoco Oil Belt, Venezuela: U.S. Geological Survey Fact Sheet 2009-3028, 4 p., https://doi.org/10.3133/fs20093028.","productDescription":"4 p.","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":125643,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2009_3028.jpg"},{"id":13351,"rank":100,"type":{"id":15,"text":"Index 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Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":304204,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Cook, Troy A.","contributorId":52519,"corporation":false,"usgs":true,"family":"Cook","given":"Troy","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":304210,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Charpentier, Ronald R. charpentier@usgs.gov","contributorId":934,"corporation":false,"usgs":true,"family":"Charpentier","given":"Ronald R.","email":"charpentier@usgs.gov","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":304205,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pollastro, Richard M.","contributorId":25100,"corporation":false,"usgs":true,"family":"Pollastro","given":"Richard","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":304208,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Klett, Timothy R. 0000-0001-9779-1168 tklett@usgs.gov","orcid":"https://orcid.org/0000-0001-9779-1168","contributorId":709,"corporation":false,"usgs":true,"family":"Klett","given":"Timothy R.","email":"tklett@usgs.gov","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":304202,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tennyson, Marilyn E. 0000-0002-5166-2421 tennyson@usgs.gov","orcid":"https://orcid.org/0000-0002-5166-2421","contributorId":1433,"corporation":false,"usgs":true,"family":"Tennyson","given":"Marilyn E.","email":"tennyson@usgs.gov","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":false,"id":304206,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Kirschbaum, Mark A.","contributorId":25112,"corporation":false,"usgs":true,"family":"Kirschbaum","given":"Mark","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":304209,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Brownfield, Michael E. 0000-0003-3633-1138 mbrownfield@usgs.gov","orcid":"https://orcid.org/0000-0003-3633-1138","contributorId":1548,"corporation":false,"usgs":true,"family":"Brownfield","given":"Michael","email":"mbrownfield@usgs.gov","middleInitial":"E.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":304207,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Pitman, Janet K. 0000-0002-0441-779X jpitman@usgs.gov","orcid":"https://orcid.org/0000-0002-0441-779X","contributorId":767,"corporation":false,"usgs":true,"family":"Pitman","given":"Janet","email":"jpitman@usgs.gov","middleInitial":"K.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":304203,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":98111,"text":"sir20095207 - 2009 - Water Levels and Selected Water-Quality Conditions in the Sparta-Memphis Aquifer (Middle Claiborne Aquifer) in Arkansas, Spring-Summer 2007","interactions":[],"lastModifiedDate":"2012-02-10T00:11:53","indexId":"sir20095207","displayToPublicDate":"2010-01-16T00:00:00","publicationYear":"2009","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":"2009-5207","title":"Water Levels and Selected Water-Quality Conditions in the Sparta-Memphis Aquifer (Middle Claiborne Aquifer) in Arkansas, Spring-Summer 2007","docAbstract":"The U.S. Geological Survey in cooperation with the Arkansas Natural Resources Commission and the Arkansas Geological Survey has monitored water levels in the Sparta Sand of Claiborne Group and Memphis Sand of Claiborne Group (herein referred to as the Sparta Sand and the Memphis Sand, respectively), since the 1920s. Groundwater withdrawals have increased while water levels have declined since monitoring was initiated. Herein, aquifers in the Sparta Sand and Memphis Sand will be referred to as the Sparta-Memphis aquifer throughout Arkansas. During the spring of 2007, 309 water levels were measured in wells completed in the Sparta-Memphis aquifer. During the summer of 2007, 129 water-quality samples were collected and measured for temperature and specific conductance and 102 were collected and analyzed for chloride from wells completed in the Sparta-Memphis aquifer.\r\n\r\nWater-level measurements collected in wells screened in the Sparta-Memphis aquifer were used to produce a regional potentiometric-surface map. The regional direction of groundwater flow in the Sparta-Memphis aquifer is generally to the south-southeast in the northern half of Arkansas and to the east and south in the southern half of Arkansas, away from the outcrop area except where affected by large ground-water withdrawals. The highest water-level altitude measured in the Sparta-Memphis aquifer was 326 feet above National Geodetic Vertical Datum of 1929, located in Grant County in the outcrop at the western boundary of the study area; the lowest water-level altitude was 161 feet below National Geodetic Vertical Datum of 1929 in Union County near the southern boundary of the study area.\r\n\r\nEight cones of depression (generally represented by closed contours) are located in the following counties: Bradley, Drew, and Ashley; Calhoun; Cleveland; Columbia; Crittenden; Arkansas, Jefferson, and Lincoln; Cross and Poinsett; and Union. Two large depressions are shown on the 2007 potentiometric-surface map, centered in Jefferson and Union Counties, as a result of large withdrawals for industrial and public supplies. The depression centered in Jefferson County deepened and expanded in recent years into Arkansas and Prairie Counties as a result of large withdrawals for irrigation and public supply. The area enclosed within the 40-foot contour has expanded on the 2007 potentiometric-surface map when compared with the 2005 potentiometric-surface map. In 2003, the depression in Union County was elongated east and west and beginning to coalesce with the depression in Columbia County. The deepest measurement during 2007 in the center of the depression in Union County has risen 38 feet since 2003. The area enclosed by the deepest contour, 160 feet below National Geodetic Vertical Datum of 1929, on the 2007 potentiometric-surface map is less than 10 percent of the area on the 2005 potentiometric-surface map. A broad depression in western Poinsett and Cross Counties was first shown in the 1995 potentiometric-surface map caused by withdrawals for irrigation extending north to the Poinsett-Craighead County line, and south into Cross County. \r\n\r\nA water-level difference map was constructed using the difference between water-level measurements made during 2003 and 2007 from 283 wells. The difference in water level between 2003 and 2007 ranged from -49.8 to 60.0 feet. Areas with a general rise in water levels are shown in northern Arkansas, Columbia, southern Jefferson, and most of Union Counties. In the area around west-central Union County, water levels rose as much as 60.0 feet with water levels in 15 wells rising 20 feet or more, which is an average annual rise of 5 feet or more. Water levels generally declined throughout most of the rest of Arkansas.\r\n\r\nHydrographs from 157 wells were constructed with a minimum of 25 years of water-level measurements. During the period 1983-2007, the county mean annual water level rose in Calhoun, Columbia, Hot Spring, and Lafayette Counties. Mean an","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/sir20095207","collaboration":"Prepared in cooperation with the Arkansas Natural Resources Commission and the Arkansas Geological Survey","usgsCitation":"Schrader, T., 2009, Water Levels and Selected Water-Quality Conditions in the Sparta-Memphis Aquifer (Middle Claiborne Aquifer) in Arkansas, Spring-Summer 2007: U.S. Geological Survey Scientific Investigations Report 2009-5207, iv, 24 p. , https://doi.org/10.3133/sir20095207.","productDescription":"iv, 24 p. ","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2007-02-01","temporalEnd":"2007-04-30","costCenters":[{"id":129,"text":"Arkansas Water Science Center","active":true,"usgs":true}],"links":[{"id":125642,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2009_5207.jpg"},{"id":13350,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2009/5207/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -95,32.5 ], [ -95,37 ], [ -89.5,37 ], [ -89.5,32.5 ], [ -95,32.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e478fe4b07f02db48a13f","contributors":{"authors":[{"text":"Schrader, T.P.","contributorId":56300,"corporation":false,"usgs":true,"family":"Schrader","given":"T.P.","email":"","affiliations":[],"preferred":false,"id":304201,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":98104,"text":"sir20095261 - 2009 - Travel Times, Streamflow Velocities, and Dispersion Rates in the Yellowstone River, Montana","interactions":[],"lastModifiedDate":"2012-03-08T17:16:29","indexId":"sir20095261","displayToPublicDate":"2010-01-15T00:00:00","publicationYear":"2009","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":"2009-5261","title":"Travel Times, Streamflow Velocities, and Dispersion Rates in the Yellowstone River, Montana","docAbstract":"The Yellowstone River is a vital natural resource to the residents of southeastern Montana and is a primary source of water for irrigation and recreation and the primary source of municipal water for several cities. The Yellowstone River valley is the primary east-west transportation corridor through southern Montana. This complex of infrastructure makes the Yellowstone River especially vulnerable to accidental spills from various sources such as tanker cars and trucks. In 2008, the U.S. Geological Survey (USGS), in cooperation with the Montana Department of Environmental Quality, initiated a dye-tracer study to determine instream travel times, streamflow velocities, and dispersion rates for the Yellowstone River from Lockwood to Glendive, Montana. The purpose of this report is to describe the results of this study and summarize data collected at each of the measurement sites between Lockwood and Glendive. This report also compares the results of this study to estimated travel times from a transport model developed by the USGS for a previous study. For this study, Rhodamine WT dye was injected at four locations in late September and early October 2008 during reasonably steady streamflow conditions. Streamflows ranged from 3,490 to 3,770 cubic feet per second upstream from the confluence of the Bighorn River and ranged from 6,520 to 7,570 cubic feet per second downstream from the confluence of the Bighorn River.\r\n\r\nMean velocities were calculated for each subreach between measurement sites for the leading edge, peak concentration, centroid, and trailing edge at 10 percent of the peak concentration. Calculated velocities for the centroid of the dye plume for subreaches that were completely laterally mixed ranged from 1.83 to 3.18 ft/s within the study reach from Lockwood Bridge to Glendive Bridge. The mean of the completely mixed centroid velocity for the entire study reach, excluding the subreach between Forsyth Bridge and Cartersville Dam, was 2.80 ft/s. Longitudinal dispersion rates of the dye plume for this study ranged from 0.06 ft/s for the subreach upstream from Forsyth Bridge to 2.25 ft/s for the subreach upstream from Calyspo Bridge for subreaches where the dye was completely laterally mixed. A relation was determined between travel time of the peak concentration and time for the dye plume to pass a site (duration). This relation can be used to estimate when the receding concentration of a potential contaminant reaches 10 percent of its peak concentration for accidental spills into the Yellowstone River.\r\n\r\nData from this dye-tracer study were used to evaluate velocity and concentration estimates from a transport model developed as part of an earlier USGS study. Comparison of the estimated and calculated velocities for the study reach indicate that the transport model estimates the velocities of the Yellowstone River between Huntley Bridge and Glendive Bridge with reasonable accuracy. Velocities of the peak concentration of the dye plume calculated for this study averaged 10 percent faster than the most probable velocities and averaged 12 percent slower than the maximum probable velocities estimated from the transport model. Peak Rhodamine WT dye concentrations were consistently lower than the transport model estimates except for the most upstream subreach of each dye injection. The most upstream subreach of each dye injection is expected to have a higher concentration because of incomplete lateral mixing. Lower measured peak concentrations for all other sites were expected because Rhodamine WT dye deteriorates when exposed to sunlight and will sorb onto the streambanks and stream bottom.\r\n\r\nVelocity-streamflow relations developed by using routine streamflow measurements at USGS gaging stations and the transport model can be used to estimate mean streamflow velocities throughout a range of streamflows. The variation in these velocity-streamflow relations emphasizes the uncertainty in estimating the mean streamflow veloc","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/sir20095261","isbn":"9781411326606","collaboration":"Prepared in cooperation with the Montana Department of Environmental Quality","usgsCitation":"McCarthy, P., 2009, Travel Times, Streamflow Velocities, and Dispersion Rates in the Yellowstone River, Montana: U.S. Geological Survey Scientific Investigations Report 2009-5261, Report: vi, 26 p.; 4 Appendixes (xls), https://doi.org/10.3133/sir20095261.","productDescription":"Report: vi, 26 p.; 4 Appendixes (xls)","onlineOnly":"N","additionalOnlineFiles":"Y","temporalStart":"2008-09-15","temporalEnd":"2008-10-15","costCenters":[{"id":400,"text":"Montana Water Science Center","active":false,"usgs":true}],"links":[{"id":125630,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2009_5261.jpg"},{"id":13341,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2009/5261/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -109,45 ], [ -109,47.5 ], [ -104,47.5 ], [ -104,45 ], [ -109,45 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a4ce4b07f02db626af7","contributors":{"authors":[{"text":"McCarthy, Peter 0000-0002-2396-7463 pmccarth@usgs.gov","orcid":"https://orcid.org/0000-0002-2396-7463","contributorId":2504,"corporation":false,"usgs":true,"family":"McCarthy","given":"Peter","email":"pmccarth@usgs.gov","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":304177,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":98107,"text":"sir20095233 - 2009 - Evaluation of catchment delineation methods for the medium-resolution National Hydrography Dataset","interactions":[],"lastModifiedDate":"2017-03-29T14:23:27","indexId":"sir20095233","displayToPublicDate":"2010-01-15T00:00:00","publicationYear":"2009","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":"2009-5233","title":"Evaluation of catchment delineation methods for the medium-resolution National Hydrography Dataset","docAbstract":"Different methods for determining catchments (incremental drainage areas) for stream segments of the medium-resolution (1:100,000-scale) National Hydrography Dataset (NHD) were evaluated by the U.S. Geological Survey (USGS), in cooperation with the U.S. Environmental Protection Agency (USEPA). The NHD is a comprehensive set of digital spatial data that contains information about surface-water features (such as lakes, ponds, streams, and rivers) of the United States. The need for NHD catchments was driven primarily by the goal to estimate NHD streamflow and velocity to support water-quality modeling. The application of catchments for this purpose also demonstrates the broader value of NHD catchments for supporting landscape characterization and analysis.\n\nFive catchment delineation methods were evaluated. Four of the methods use topographic information for the delineation of the NHD catchments. These methods include the Raster Seeding Method; two variants of a method first used in a USGS New England study-one used the Watershed Boundary Dataset (WBD) and the other did not-termed the 'New England Methods'; and the Outlet Matching Method. For these topographically based methods, the elevation data source was the 30-meter (m) resolution National Elevation Dataset (NED), as this was the highest resolution available for the conterminous United States and Hawaii. The fifth method evaluated, the Thiessen Polygon Method, uses distance to the nearest NHD stream segments to determine catchment boundaries.\n\nCatchments were generated using each method for NHD stream segments within six hydrologically and geographically distinct Subbasins to evaluate the applicability of the method across the United States. The five methods were evaluated by comparing the resulting catchments with the boundaries and the computed area measurements available from several verification datasets that were developed independently using manual methods.\n\nThe results of the evaluation indicated that the two New England Methods provided the most accurate catchment boundaries. The New England Method with the WBD provided the most accurate results. The time and cost to implement and apply these automated methods were also considered in ultimately selecting the methods used to produce NHD catchments for the conterminous United States and Hawaii.\n\nThis study was conducted by a joint USGS-USEPA team during the 2-year period that ended in September 2004. During the following 2-year period ending in the fall of 2006, the New England Methods were used to produce NHD catchments as part of a multiagency effort to generate the NHD streamflow and velocity estimates for a suite of integrated geospatial products known as 'NHDPlus.'","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20095233","collaboration":"Prepared in cooperation with the U.S. Environmental Protection Agency","usgsCitation":"Johnston, C.M., Dewald, T.G., Bondelid, T., Worstell, B.B., McKay, L., Rea, A., Moore, R.B., and Goodall, J.L., 2009, Evaluation of catchment delineation methods for the medium-resolution National Hydrography Dataset: U.S. Geological Survey Scientific Investigations Report 2009-5233, x, 89 p., https://doi.org/10.3133/sir20095233.","productDescription":"x, 89 p.","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":468,"text":"New Hampshire-Vermont Water Science Center","active":false,"usgs":true}],"links":[{"id":125649,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2009_5233.jpg"},{"id":13346,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2009/5233/","linkFileType":{"id":5,"text":"html"}},{"id":338662,"rank":3,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2009/5233/pdf/sir2009-5233.pdf"}],"country":"United States","otherGeospatial":"New England","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -125,23 ], [ -125,50 ], [ -65,50 ], [ -65,23 ], [ -125,23 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a09e4b07f02db5fb018","contributors":{"authors":[{"text":"Johnston, Craig M. cmjohnst@usgs.gov","contributorId":1814,"corporation":false,"usgs":true,"family":"Johnston","given":"Craig","email":"cmjohnst@usgs.gov","middleInitial":"M.","affiliations":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":304185,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dewald, Thomas G.","contributorId":97600,"corporation":false,"usgs":true,"family":"Dewald","given":"Thomas","email":"","middleInitial":"G.","affiliations":[],"preferred":false,"id":304191,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Bondelid, Timothy R.","contributorId":90420,"corporation":false,"usgs":true,"family":"Bondelid","given":"Timothy R.","affiliations":[],"preferred":false,"id":304190,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Worstell, Bruce B. 0000-0001-8927-3336 worstell@usgs.gov","orcid":"https://orcid.org/0000-0001-8927-3336","contributorId":1815,"corporation":false,"usgs":true,"family":"Worstell","given":"Bruce","email":"worstell@usgs.gov","middleInitial":"B.","affiliations":[{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":304186,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"McKay, Lucinda D.","contributorId":90010,"corporation":false,"usgs":true,"family":"McKay","given":"Lucinda D.","affiliations":[],"preferred":false,"id":304189,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Rea, Alan","contributorId":41018,"corporation":false,"usgs":true,"family":"Rea","given":"Alan","affiliations":[],"preferred":false,"id":304187,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Moore, Richard B. rmoore@usgs.gov","contributorId":1464,"corporation":false,"usgs":true,"family":"Moore","given":"Richard","email":"rmoore@usgs.gov","middleInitial":"B.","affiliations":[{"id":405,"text":"NH/VT office of New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":304184,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Goodall, Jonathan L.","contributorId":59535,"corporation":false,"usgs":true,"family":"Goodall","given":"Jonathan","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":304188,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":98102,"text":"ofr20091279 - 2009 - Hurricane Gustav: Observations and analysis of coastal change","interactions":[],"lastModifiedDate":"2023-12-07T14:34:51.14829","indexId":"ofr20091279","displayToPublicDate":"2010-01-15T00:00:00","publicationYear":"2009","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":"2009-1279","title":"Hurricane Gustav: Observations and analysis of coastal change","docAbstract":"Understanding storm-induced coastal change and forecasting these changes require knowledge of the physical processes associated with a storm and the geomorphology of the impacted coastline. The primary physical processes of interest are the wind field, storm surge, currents, and wave field. Not only does wind cause direct damage to structures along the coast, but it is ultimately responsible for much of the energy that is transferred to the ocean and expressed as storm surge, mean currents, and surface waves. Waves and currents are the processes most responsible for moving sediments in the coastal zone during extreme storm events. Storm surge, which is the rise in water level due to the wind, barometric pressure, and other factors, allows both waves and currents to attack parts of the coast not normally exposed to these processes.
Coastal geomorphology, including shapes of the shoreline, beaches, and dunes, is also a significant aspect of the coastal change observed during extreme storms. Relevant geomorphic variables include sand dune elevation, beach width, shoreline position, sediment grain size, and foreshore beach slope. These variables, in addition to hydrodynamic processes, can be used to predict coastal vulnerability to storms.
The U.S. Geological Survey (USGS) National Assessment of Coastal Change Hazards project (http://coastal.er.usgs.gov/hurricanes) strives to provide hazard information to those concerned about the Nation’s coastlines, including residents of coastal areas, government agencies responsible for coastal management, and coastal researchers. As part of the National Assessment, observations were collected to measure morphological changes associated with Hurricane Gustav, which made landfall near Cocodrie, Louisiana, on September 1, 2008. Methods of observation included oblique aerial photography, airborne topographic surveys, and ground-based topographic surveys. This report documents these data-collection efforts and presents qualitative and quantitative descriptions of hurricane-induced changes to the shoreline, beaches, dunes, and infrastructure in the region that was heavily impacted by Hurricane Gustav.
","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20091279","usgsCitation":"Doran, K., Stockdon, H.F., Plant, N.G., Sallenger, A., Guy, K.K., and Serafin, K.A., 2009, Hurricane Gustav: Observations and analysis of coastal change: U.S. Geological Survey Open-File Report 2009-1279, vii, 28 p., https://doi.org/10.3133/ofr20091279.","productDescription":"vii, 28 p.","onlineOnly":"N","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":595,"text":"U.S. Geological Survey","active":false,"usgs":true}],"links":[{"id":13339,"rank":3,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2009/1279/","linkFileType":{"id":5,"text":"html"}},{"id":403717,"rank":2,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_90304.htm","linkFileType":{"id":5,"text":"html"}},{"id":125626,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2009_1279.jpg"}],"country":"United States","state":"Alabama, Louisiana, Mississippi","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -91,\n 28.9167\n ],\n [\n -88,\n 28.9167\n ],\n [\n -88,\n 30.5\n ],\n [\n -91,\n 30.5\n ],\n [\n -91,\n 28.9167\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4affe4b07f02db697bfd","contributors":{"authors":[{"text":"Doran, Kara S. 0000-0001-8050-5727","orcid":"https://orcid.org/0000-0001-8050-5727","contributorId":33010,"corporation":false,"usgs":true,"family":"Doran","given":"Kara S.","affiliations":[],"preferred":false,"id":304173,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stockdon, Hilary F. 0000-0003-0791-4676 hstockdon@usgs.gov","orcid":"https://orcid.org/0000-0003-0791-4676","contributorId":2153,"corporation":false,"usgs":true,"family":"Stockdon","given":"Hilary","email":"hstockdon@usgs.gov","middleInitial":"F.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":true,"id":304170,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Plant, Nathaniel G. 0000-0002-5703-5672 nplant@usgs.gov","orcid":"https://orcid.org/0000-0002-5703-5672","contributorId":3503,"corporation":false,"usgs":true,"family":"Plant","given":"Nathaniel","email":"nplant@usgs.gov","middleInitial":"G.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"preferred":true,"id":304171,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sallenger, Asbury H. Jr.","contributorId":27458,"corporation":false,"usgs":true,"family":"Sallenger","given":"Asbury H.","suffix":"Jr.","affiliations":[],"preferred":false,"id":304172,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Guy, Kristy K. kguy@usgs.gov","contributorId":45010,"corporation":false,"usgs":true,"family":"Guy","given":"Kristy","email":"kguy@usgs.gov","middleInitial":"K.","affiliations":[],"preferred":false,"id":304174,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Serafin, Katherine A.","contributorId":84466,"corporation":false,"usgs":true,"family":"Serafin","given":"Katherine","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":304175,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":98101,"text":"ofr20091225 - 2009 - Natural offshore oil seepage and related tarball accumulation on the California coastline — Santa Barbara Channel and the southern Santa Maria Basin; source identification and inventory","interactions":[],"lastModifiedDate":"2022-06-09T20:25:10.852413","indexId":"ofr20091225","displayToPublicDate":"2010-01-14T00:00:00","publicationYear":"2009","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":"2009-1225","title":"Natural offshore oil seepage and related tarball accumulation on the California coastline — Santa Barbara Channel and the southern Santa Maria Basin; source identification and inventory","docAbstract":"Oil spillage from natural sources is very common in the waters of southern California. Active oil extraction and shipping is occurring concurrently within the region and it is of great interest to resource managers to be able to distinguish between natural seepage and anthropogenic oil spillage.
The major goal of this study was to establish the geologic setting, sources, and ultimate dispersal of natural oil seeps in the offshore southern Santa Maria Basin and Santa Barbara Basins. Our surveys focused on likely areas of hydrocarbon seepage that are known to occur between Point Arguello and Ventura, California.
Our approach was to 1) document the locations and geochemically fingerprint natural seep oils or tar; 2) geochemically fingerprint coastal tar residues and potential tar sources in this region, both onshore and offshore; 3) establish chemical correlations between offshore active seeps and coastal residues thus linking seep sources to oil residues; 4) measure the rate of natural seepage of individual seeps and attempt to assess regional natural oil and gas seepage rates; and 5) interpret the petroleum system history for the natural seeps.
To document the location of sub-sea oil seeps, we first looked into previous studies within and near our survey area. We measured the concentration of methane gas in the water column in areas of reported seepage and found numerous gas plumes and measured high concentrations of methane in the water column. The result of this work showed that the seeps were widely distributed between Point Conception east to the vicinity of Coal Oil Point, and that they by in large occur within the 3-mile limit of California State waters. Subsequent cruises used sidescan and high resolution seismic to map the seafloor, from just south of Point Arguello, east to near Gaviota, California. The results of the methane survey guided the exploration of the area west of Point Conception east to Gaviota using a combination of seismic instruments. The seafloor was mapped by sidescan sonar, and numerous lines of high -resolution seismic surveys were conducted over areas of interest.
Biomarker and stable carbon isotope ratios were used to infer the age, lithology, organic matter input, and depositional environment of the source rocks for 388 samples of produced crude oil, seep oil, and tarballs mainly from coastal California. These samples were used to construct a chemometric fingerprint (multivariate statistics) decision tree to classify 288 additional samples, including tarballs of unknown origin collected from Monterey and San Mateo County beaches after a storm in early 2007. A subset of 9 of 23 active offshore platform oils and one inactive platform oil representing a few oil reservoirs from the western Santa Barbara Channel were used in this analysis, and thus this model is not comprehensive and the findings are not conclusive. The platform oils included in this study are from west to east: Irene, Hildago, Harvest, Hermosa, Heritage, Harmony, Hondo, Holly, Platform A, and Hilda (now removed).
The results identify three “tribes” of 13C-rich oil samples inferred to originate from thermally mature equivalents of the clayey-siliceous, carbonaceous marl, and lower calcareous-siliceous members of the Monterey Formation. Tribe 1 contains four oil families having geochemical traits of clay-rich marine shale source rock deposited under suboxic conditions with substantial higher-plant input. Tribe 2 contains four oil families with intermediate traits, except for abundant 28,30-bisnorhopane, indicating suboxic to anoxic marine marl source rock with hemipelagic input. Tribe 3 contains five oil families with traits of distal marine carbonate source rock deposited under anoxic conditions with pelagic but little or no higher-plant input. Tribes 1 and 2 occur mainly south of Point Conception in paleogeographic settings where deep burial of the Monterey Formation source rock favored generation from all three members or their equivalents. In this area, oil from the clayey-siliceous and carbonaceous marl members (Tribes 1 and 2) may overwhelm that from the lower calcareous-siliceous member (Tribe 3) because the latter is thinner and less oil-prone than the overlying members. Tribe 3 occurs mainly north of Point Conception, where shallow burial caused preferential generation from the underlying lower calcareous-siliceous member or another unit with similar characteristics.
It is very desirable to be able to clearly distinguish the naturally occurring seep oils from the anthropogenically derived platform oils. Within the “training set” of oils and tars (388 samples), the biomarker parameters are sometimes sufficient to allow unique discrimination of individual platform oils. More often however, platform samples and seep samples with sources geographically close to each other are too similar to each other, with respect to the biomarker parameters, to definitively differentiate them on that basis alone. In some cases other parameters can be helpful. These other parameters are related to the degree of biogeochemical degradation or weathering that the oils or tars have experienced. These components include the typical oil distribution of n-alkane hydrocarbons and isoprenoids pristane and phytane. All of the platform oils in our sample set contain these components. On the other hand, the seep oils or tars have been exposed to significant biodegradation while in the near subsurface. The majority, but not all of seep oils or tars have been biodegraded up to or beyond the loss of n-alkanes and isoprenoids. Seep oils found in the vicinity of Coal Oil Point or Arroyo Burro are apparently the least weathered and are particularly likely to retain significant n-alkanes and isoprenoids. Therefore the combination of chemometric fingerprinting and the presence or absence of n-alkanes and isoprenoids help to differentiate anthropogenic production oils versus natural seeps oils and tars. The differentiation is not always definitive because of the close chemical similarity of some samples and the variability in the biodegradation progression. This is the case near Coal Oil Point, and near Platform A (Dos Cuadros Field) where seep oils and Platform Holly and Platform A oils are genetically very similar and cannot be definitively distinguished after a period of a few days of weathering. In contrast, oils from the Point Conception platforms can be distinguished on the basis of chemometric fingerprinting alone. In the middle of this spectrum are oils from Platforms Harmony, Heritage, and Hondo, where it is expected that oil weathering would take on the order of two weeks to a month to produce tarballs similar to those seen near Point Conception. In this case there is a much greater degree of weathering needed to proceed from produced oil to the biodegraded tar characteristic of tarball stranded on the beach.
Tar deposition on beaches was monitored as part of cooperative with the County of Santa Barbara Energy Division and the U.S. Geological Survey during 2001-2003. We found tar deposition varies on a seasonal basis. In general, tarballs accumulate at a faster rate or remain longer on all beaches during the summer and fall months. The reasons for this are unclear based on our limited observations, however we speculate that factors such as prevailing winds and currents combined with more quiescent wave conditions favors the accumulation and preservation of tarballs on the beach during the summer and fall months. In contrast, winter storms, with much greater wave action remove beach sand and other materials, and stormy seas tend to break up oil that might weather into tarballs. Natural seepage is affected by the spring/neap tidal cycle; however, the link to tar deposition is unclear. Longer periods of monitoring are needed to address the variability in the data and provide a more robust statistical analysis.
","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20091225","collaboration":"A study in cooperation with the Minerals Management Service and the Energy Division, County of Santa Barbara, California; Also released as MMS report 2009-030; This study was funded in part by the U. S. Department of the Interior, Minerals Management Service (MMS), through an Interagency Agreement No. 18985 with the U.S. Geological Survey, Western Coastal and Marine Geology Team, as part of the MMS Environmental Studies Program.","usgsCitation":"Lorenson, T., Hostettler, F.D., Rosenbauer, R.J., Peters, K., Dougherty, J.A., Kvenvolden, K.A., Gutmacher, C.E., Wong, F.L., and Normark, W.R., 2009, Natural offshore oil seepage and related tarball accumulation on the California coastline — Santa Barbara Channel and the southern Santa Maria Basin; source identification and inventory: U.S. Geological Survey Open-File Report 2009-1225, Report: iii, 116 p.; Appendixes, https://doi.org/10.3133/ofr20091225.","productDescription":"Report: iii, 116 p.; Appendixes","onlineOnly":"N","additionalOnlineFiles":"Y","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true},{"id":645,"text":"Western Coastal and Marine Geology","active":false,"usgs":true}],"links":[{"id":125640,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2009_1225.jpg"},{"id":402029,"rank":3,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_90302.htm"},{"id":13337,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2009/1225/","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"California","otherGeospatial":"Santa Barbara Channel, Santa Maria Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.014404296875,\n 34.134541681937364\n ],\n [\n -119.32250976562499,\n 34.134541681937364\n ],\n [\n -119.32250976562499,\n 35.146862906756304\n ],\n [\n -121.014404296875,\n 35.146862906756304\n ],\n [\n -121.014404296875,\n 34.134541681937364\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b00e4b07f02db6982ee","contributors":{"authors":[{"text":"Lorenson, T.D. tlorenson@usgs.gov","contributorId":2622,"corporation":false,"usgs":true,"family":"Lorenson","given":"T.D.","email":"tlorenson@usgs.gov","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true}],"preferred":false,"id":304163,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hostettler, Frances D. fdhostet@usgs.gov","contributorId":3383,"corporation":false,"usgs":true,"family":"Hostettler","given":"Frances","email":"fdhostet@usgs.gov","middleInitial":"D.","affiliations":[],"preferred":true,"id":304164,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rosenbauer, Robert J. brosenbauer@usgs.gov","contributorId":204,"corporation":false,"usgs":true,"family":"Rosenbauer","given":"Robert","email":"brosenbauer@usgs.gov","middleInitial":"J.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":304161,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Peters, Kenneth E.","contributorId":10897,"corporation":false,"usgs":true,"family":"Peters","given":"Kenneth E.","affiliations":[],"preferred":false,"id":304167,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dougherty, Jennifer A.","contributorId":6114,"corporation":false,"usgs":true,"family":"Dougherty","given":"Jennifer","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":304166,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kvenvolden, Keith A. kkvenvolden@usgs.gov","contributorId":3384,"corporation":false,"usgs":true,"family":"Kvenvolden","given":"Keith","email":"kkvenvolden@usgs.gov","middleInitial":"A.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":304165,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Gutmacher, Christina E.","contributorId":28272,"corporation":false,"usgs":true,"family":"Gutmacher","given":"Christina","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":304168,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Wong, Florence L. 0000-0002-3918-5896 fwong@usgs.gov","orcid":"https://orcid.org/0000-0002-3918-5896","contributorId":1990,"corporation":false,"usgs":true,"family":"Wong","given":"Florence","email":"fwong@usgs.gov","middleInitial":"L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":304162,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Normark, William R.","contributorId":69570,"corporation":false,"usgs":true,"family":"Normark","given":"William","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":304169,"contributorType":{"id":1,"text":"Authors"},"rank":9}]}} ,{"id":98098,"text":"sir20095270 - 2009 - Hydrogeologic Framework, Groundwater Movement, and Water Budget in Tributary Subbasins and Vicinity, Lower Skagit River Basin, Skagit and Snohomish Counties, Washington","interactions":[],"lastModifiedDate":"2012-03-08T17:16:29","indexId":"sir20095270","displayToPublicDate":"2010-01-09T00:00:00","publicationYear":"2009","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":"2009-5270","title":"Hydrogeologic Framework, Groundwater Movement, and Water Budget in Tributary Subbasins and Vicinity, Lower Skagit River Basin, Skagit and Snohomish Counties, Washington","docAbstract":"A study to characterize the groundwater-flow system in four tributary subbasins and vicinity of the lower Skagit River basin was conducted by the U.S. Geological Survey to assist Skagit County and the Washington State Department of Ecology in evaluating the effects of potential groundwater withdrawals and consumptive use on tributary streamflows.\r\n\r\nThis report presents information used to characterize the groundwater and surface-water flow system in the subbasins, and includes descriptions of the geology and hydrogeologic framework of the subbasins; groundwater recharge and discharge; groundwater levels and flow directions; seasonal groundwater-level fluctuations; interactions between aquifers and the surface-water system; and a water budget for the subbasins.\r\n\r\nThe study area covers about 247 mi2 along the Skagit River and its tributary subbasins (East Fork Nookachamps Creek, Nookachamps Creek, Carpenter Creek, and Fisher Creek) in southwestern Skagit County and northwestern Snohomish County, Washington. The geology of the area records a complex history of accretion along the continental margin, mountain building, deposition of terrestrial and marine sediments, igneous intrusion, and the repeated advance and retreat of continental glaciers. A simplified surficial geologic map was developed from previous mapping in the area, and geologic units were grouped into nine hydrogeologic units consisting of aquifers and confining units. A surficial hydrogeologic unit map was constructed and, with lithologic information from 296 drillers'logs, was used to produce unit extent and thickness maps and four hydrogeologic sections.\r\n\r\nGroundwater in unconsolidated aquifers generally flows towards the northwest and west in the direction of the Skagit River and Puget Sound. This generalized flow pattern is likely complicated by the presence of low-permeability confining units that separate discontinuous bodies of aquifer material and act as local groundwater-flow barriers. Groundwater-flow directions in the sedimentary aquifer likely reflect local topographic relief (radial flow from bedrock highs) and more regional westward flow from the mountains to the Puget Sound. The largest groundwater-level fluctuations observed during the monitoring period (October 2006 through September 2008) occurred in wells completed in the sedimentary aquifer, and ranged from about 3 to 27 feet. Water levels in wells completed in unconsolidated hydrogeologic units exhibited seasonal variations ranging from less than 1 to about 10 feet.\r\n\r\nSynoptic streamflow measurements made in August 2007 and June 2008 indicate a total groundwater discharge to creeks in the tributary subbasin area of about 13.15 and 129.6 cubic feet per second (9,520 and 93,830 acre-feet per year), respectively. Streamflow measurements illustrate a general pattern in which the upper reaches of creeks in the study area tended to gain flow from the groundwater system, and lower creek reaches tended to lose water. Large inflows from tributaries to major creeks in the study area suggest the presence of groundwater discharge from upland areas underlain by bedrock.\r\n\r\nThe groundwater system within the subbasins received an average (September 1, 2006 to August 31, 2008) of about 92,400 acre-feet or about 18 inches of recharge from precipitation a year. Most of this recharge (65 percent) discharges to creeks, and only about 3 percent is withdrawn from wells. The remaining groundwater recharge (32 percent) leaves the subbasin groundwater system as discharge to the Skagit River and Puget Sound.\r\n","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/sir20095270","collaboration":"Prepared in cooperation with the Skagit County Public Works Department, Washington State Department of Ecology, and Skagit County Public Utility District No. 1","usgsCitation":"Savoca, M.E., Johnson, K.H., Sumioka, S.S., Olsen, T.D., Fasser, E.T., and Huffman, R.L., 2009, Hydrogeologic Framework, Groundwater Movement, and Water Budget in Tributary Subbasins and Vicinity, Lower Skagit River Basin, Skagit and Snohomish Counties, Washington: U.S. Geological Survey Scientific Investigations Report 2009-5270, Report: viii, 47 p.; Plate 1 (43 x 28 inches); Plate 2 (42 x 30 inches), https://doi.org/10.3133/sir20095270.","productDescription":"Report: viii, 47 p.; Plate 1 (43 x 28 inches); Plate 2 (42 x 30 inches)","onlineOnly":"N","additionalOnlineFiles":"Y","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":125282,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2009_5270.jpg"},{"id":13334,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2009/5270/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -122.5,48.25 ], [ -122.5,48.5 ], [ -122,48.5 ], [ -122,48.25 ], [ -122.5,48.25 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a50e4b07f02db628e1c","contributors":{"authors":[{"text":"Savoca, Mark E. mesavoca@usgs.gov","contributorId":1961,"corporation":false,"usgs":true,"family":"Savoca","given":"Mark","email":"mesavoca@usgs.gov","middleInitial":"E.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":304149,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Kenneth H. johnson@usgs.gov","contributorId":3103,"corporation":false,"usgs":true,"family":"Johnson","given":"Kenneth","email":"johnson@usgs.gov","middleInitial":"H.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":304150,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sumioka, Steven S.","contributorId":8159,"corporation":false,"usgs":true,"family":"Sumioka","given":"Steven","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":304152,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Olsen, Theresa D. 0000-0003-4099-4057 tdolsen@usgs.gov","orcid":"https://orcid.org/0000-0003-4099-4057","contributorId":1644,"corporation":false,"usgs":true,"family":"Olsen","given":"Theresa","email":"tdolsen@usgs.gov","middleInitial":"D.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":304148,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fasser, Elisabeth T. 0000-0002-3945-6633 efasser@usgs.gov","orcid":"https://orcid.org/0000-0002-3945-6633","contributorId":3973,"corporation":false,"usgs":true,"family":"Fasser","given":"Elisabeth","email":"efasser@usgs.gov","middleInitial":"T.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":304151,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Huffman, Raegan L. 0000-0001-8523-5439 rhuffman@usgs.gov","orcid":"https://orcid.org/0000-0001-8523-5439","contributorId":1638,"corporation":false,"usgs":true,"family":"Huffman","given":"Raegan","email":"rhuffman@usgs.gov","middleInitial":"L.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":304147,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":98095,"text":"ofr20091232 - 2009 - Quality-Assurance Data for Routine Water Analyses by the U.S. Geological Survey Laboratory in Troy, New York - July 2001 Through June 2003","interactions":[],"lastModifiedDate":"2012-03-08T17:16:29","indexId":"ofr20091232","displayToPublicDate":"2010-01-07T00:00:00","publicationYear":"2009","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":"2009-1232","title":"Quality-Assurance Data for Routine Water Analyses by the U.S. Geological Survey Laboratory in Troy, New York - July 2001 Through June 2003","docAbstract":"The laboratory for analysis of low-ionic-strength water at the U.S. Geological Survey (USGS) Water Science Center in Troy, N.Y., analyzes samples collected by USGS projects throughout the Northeast. The laboratory's quality-assurance program is based on internal and interlaboratory quality-assurance samples and quality-control procedures that were developed to ensure proper sample collection, processing, and analysis. The quality-assurance and quality-control data were stored in the laboratory's Lab Master data-management system, which provides efficient review, compilation, and plotting of data. This report presents and discusses results of quality-assurance and quality control samples analyzed from July 2001 through June 2003.\r\n\r\nResults for the quality-control samples for 19 analytical procedures were evaluated for bias and precision. Control charts indicate that data for six of the analytical procedures were occasionally biased for either high-concentration or low-concentration samples but were within control limits; these procedures were: acid-neutralizing capacity, chloride, magnesium, nitrate (ion chromatography), potassium, and sodium. The calcium procedure was biased throughout the analysis period for the high-concentration sample, but was within control limits. The total monomeric aluminum and fluoride procedures were biased throughout the analysis period for the low-concentration sample, but were within control limits. The total aluminum, pH, specific conductance, and sulfate procedures were biased for the high-concentration and low-concentration samples, but were within control limits.\r\n\r\nResults from the filter-blank and analytical-blank analyses indicate that the procedures for 16 of 18 analytes were within control limits, although the concentrations for blanks were occasionally outside the control limits. The data-quality objective was not met for the dissolved organic carbon or specific conductance procedures.\r\nSampling and analysis precision are evaluated herein in terms of the coefficient of variation obtained for triplicate samples in the procedures for 18 of the 21 analytes. At least 90 percent of the samples met data-quality objectives for all procedures except total monomeric aluminum (83 percent of samples met objectives), total aluminum (76 percent of samples met objectives), ammonium (73 percent of samples met objectives), dissolved organic carbon (86 percent of samples met objectives), and nitrate (81 percent of samples met objectives). The data-quality objective was not met for the nitrite procedure.\r\n\r\nResults of the USGS interlaboratory Standard Reference Sample (SRS) Project indicated satisfactory or above data quality over the time period, with most performance ratings for each sample in the good-to-excellent range. The N-sample (nutrient constituents) analysis had one unsatisfactory rating for the ammonium procedure in one study. The T-sample (trace constituents) analysis had one unsatisfactory rating for the magnesium procedure and one marginal rating for the potassium procedure in one study and one unsatisfactory rating for the sodium procedure in another.\r\n\r\nResults of Environment Canada's National Water Research Institute (NWRI) program indicated that at least 90 percent of the samples met data-quality objectives for 10 of the 14 analytes; the exceptions were acid-neutralizing capacity, ammonium, dissolved organic carbon, and sodium. Data-quality objectives were not met in 37 percent of samples analyzed for acid-neutralizing capacity, 28 percent of samples analyzed for dissolved organic carbon, and 30 percent of samples analyzed for sodium. Results indicate a positive bias for the ammonium procedure in one study and a negative bias in another.\r\nResults from blind reference-sample analyses indicated that data-quality objectives were met by at least 90 percent of the samples analyzed for calcium, chloride, magnesium, pH, potassium, and sodium. Data-quality objectives were met by 78 percent of ","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20091232","usgsCitation":"Lincoln, T.A., Horan-Ross, D.A., McHale, M.R., and Lawrence, G.B., 2009, Quality-Assurance Data for Routine Water Analyses by the U.S. Geological Survey Laboratory in Troy, New York - July 2001 Through June 2003: U.S. Geological Survey Open-File Report 2009-1232, iv, 33 p., https://doi.org/10.3133/ofr20091232.","productDescription":"iv, 33 p.","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2001-07-01","temporalEnd":"2003-06-30","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":125861,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2009_1232.jpg"},{"id":13331,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2009/1232/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a69e4b07f02db63bfd2","contributors":{"authors":[{"text":"Lincoln, Tricia A. tarenga@usgs.gov","contributorId":3803,"corporation":false,"usgs":true,"family":"Lincoln","given":"Tricia","email":"tarenga@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":304134,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Horan-Ross, Debra A. dhross@usgs.gov","contributorId":3809,"corporation":false,"usgs":true,"family":"Horan-Ross","given":"Debra","email":"dhross@usgs.gov","middleInitial":"A.","affiliations":[],"preferred":true,"id":304135,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McHale, Michael R. 0000-0003-3780-1816 mmchale@usgs.gov","orcid":"https://orcid.org/0000-0003-3780-1816","contributorId":1735,"corporation":false,"usgs":true,"family":"McHale","given":"Michael","email":"mmchale@usgs.gov","middleInitial":"R.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":304133,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lawrence, Gregory B. 0000-0002-8035-2350 glawrenc@usgs.gov","orcid":"https://orcid.org/0000-0002-8035-2350","contributorId":867,"corporation":false,"usgs":true,"family":"Lawrence","given":"Gregory","email":"glawrenc@usgs.gov","middleInitial":"B.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":304132,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":98089,"text":"sir20095224 - 2009 - Riparian and Associated Habitat Characteristics Related to Nutrient Concentrations and Biological Responses of Small Streams in Selected Agricultural Areas, United States, 2003-04","interactions":[],"lastModifiedDate":"2012-03-08T17:16:29","indexId":"sir20095224","displayToPublicDate":"2010-01-06T00:00:00","publicationYear":"2009","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":"2009-5224","title":"Riparian and Associated Habitat Characteristics Related to Nutrient Concentrations and Biological Responses of Small Streams in Selected Agricultural Areas, United States, 2003-04","docAbstract":"Physical factors, including both in-stream and riparian habitat characteristics that limit biomass or otherwise regulate aquatic biological condition, have been identified by previous studies. However, linking the ecological significance of nutrient enrichment to habitat or landscape factors that could allow for improved management of streams has proved to be a challenge in many regions, including agricultural landscapes, where many ecological stressors are strong and the variability among watersheds typically is large. Riparian and associated habitat characteristics were sampled once during 2003-04 for an intensive ecological and nutrients study of small perennial streams in five contrasting agricultural landscapes across the United States to determine how biological communities and ecosystem processes respond to varying levels of nutrient enrichment. Nutrient concentrations were determined in stream water at two different sampling times per site and biological samples were collected once per site near the time of habitat characterization. Data for 141 sampling sites were compiled, representing five study areas, located in parts of the Delmarva Peninsula (Delaware and Maryland), Georgia, Indiana, Ohio, Nebraska, and Washington. This report examines the available data for riparian and associated habitat characteristics to address questions related to study-unit contrasts, spatial scale-related differences, multivariate correlation structure, and bivariate relations between selected habitat characteristics and either stream nutrient conditions or biological responses.\r\n\r\nRiparian and associated habitat characteristics were summarized and categorized into 22 groups of habitat variables, with 11 groups representing land-use and land-cover characteristics and 11 groups representing other riparian or in-stream habitat characteristics. Principal components analysis was used to identify a reduced set of habitat variables that describe most of the variability among the sampled sites. The habitat characteristics sampled within the five study units were compared statistically. Bivariate correlations between riparian habitat variables and either nutrient-chemistry or biological-response variables were examined for all sites combined, and for sites within each study area.\r\n\r\nNutrient concentrations were correlated with the extent of riparian cropland. For nitrogen species, these correlations were more frequently at the basin scale, whereas for phosphorus, they were about equally frequent at the segment and basin scales. Basin-level extents of riparian cropland and reach-level bank vegetative cover were correlated strongly with both total nitrogen and dissolved inorganic nitrogen (DIN) among multiple study areas, reflecting the importance of agricultural land-management and conservation practices for reducing nitrogen delivery from near-stream sources. When sites lacking segment-level wetlands were excluded, the negative correlation of riparian wetland extent with DIN among 49 sites was strong at the reach and segment levels. Riparian wetland vegetation thus may be removing dissolved nutrients from soil water and shallow groundwater passing through riparian zones. Other habitat variables that correlated strongly with nitrogen and phosphorus species included suspended sediment, light availability, and antecedent water temperature.\r\n\r\nChlorophyll concentrations in seston were positively correlated with phosphorus concentrations for all sites combined. Benthic chlorophyll was correlated strongly with nutrient concentrations in only the Delmarva study area and only in fine-grained habitats. Current velocity or hydraulic scour could explain correlation patterns for benthic chlorophyll among Georgia sites, whereas chlorophyll in seston was correlated with antecedent water temperature among Washington and Delmarva sites. The lack of any consistent correlation pattern between habitat characteristics and organic material density (ash-free dry mass)","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/sir20095224","usgsCitation":"Zelt, R.B., and Munn, M.D., 2009, Riparian and Associated Habitat Characteristics Related to Nutrient Concentrations and Biological Responses of Small Streams in Selected Agricultural Areas, United States, 2003-04: U.S. Geological Survey Scientific Investigations Report 2009-5224, xiv, 79 p., https://doi.org/10.3133/sir20095224.","productDescription":"xiv, 79 p.","temporalStart":"2003-01-01","temporalEnd":"2004-12-31","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":125779,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2009_5224.jpg"},{"id":13323,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2009/5224/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -130,20 ], [ -130,50 ], [ -65,50 ], [ -65,20 ], [ -130,20 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4a13e4b07f02db6020ef","contributors":{"authors":[{"text":"Zelt, Ronald B. 0000-0001-9024-855X rbzelt@usgs.gov","orcid":"https://orcid.org/0000-0001-9024-855X","contributorId":300,"corporation":false,"usgs":true,"family":"Zelt","given":"Ronald","email":"rbzelt@usgs.gov","middleInitial":"B.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true},{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":304114,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Munn, Mark D. 0000-0002-7154-7252 mdmunn@usgs.gov","orcid":"https://orcid.org/0000-0002-7154-7252","contributorId":976,"corporation":false,"usgs":true,"family":"Munn","given":"Mark","email":"mdmunn@usgs.gov","middleInitial":"D.","affiliations":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"preferred":true,"id":304115,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":98094,"text":"ofr20091188 - 2009 - Land-Surface Subsidence and Open Bedrock Fractures in the Tully Valley, Onondaga County, New York","interactions":[],"lastModifiedDate":"2012-03-08T17:16:29","indexId":"ofr20091188","displayToPublicDate":"2010-01-06T00:00:00","publicationYear":"2009","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":"2009-1188","title":"Land-Surface Subsidence and Open Bedrock Fractures in the Tully Valley, Onondaga County, New York","docAbstract":"Open bedrock fractures were mapped in and near two brine field areas in Tully Valley, New York. More than 400 open fractures and closed joints were mapped for dimension, orientation, and distribution along the east and west valley walls adjacent to two former brine fields. The bedrock fractures are as much as 2 feet wide and over 50 feet deep, while linear depressions in the soil, which are 3 to 10 feet wide and 3 to 6 feet deep, indicate the presence of open bedrock fractures below the soil. The fractures are probably the result of solution mining of halite deposits about 1,200 feet below the land surface.","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/ofr20091188","usgsCitation":"Hackett, W.R., Gleason, G.C., and Kappel, W.M., 2009, Land-Surface Subsidence and Open Bedrock Fractures in the Tully Valley, Onondaga County, New York: U.S. Geological Survey Open-File Report 2009-1188, 16 p., https://doi.org/10.3133/ofr20091188.","productDescription":"16 p.","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":125941,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2009_1188.jpg"},{"id":13330,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2009/1188/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -76.18333333333334,42.8 ], [ -76.18333333333334,42.916666666666664 ], [ -76.11666666666666,42.916666666666664 ], [ -76.11666666666666,42.8 ], [ -76.18333333333334,42.8 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4b23e4b07f02db6adf4e","contributors":{"authors":[{"text":"Hackett, William R.","contributorId":79198,"corporation":false,"usgs":true,"family":"Hackett","given":"William","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":304131,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gleason, Gayle C.","contributorId":34227,"corporation":false,"usgs":true,"family":"Gleason","given":"Gayle","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":304130,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kappel, William M. 0000-0002-2382-9757 wkappel@usgs.gov","orcid":"https://orcid.org/0000-0002-2382-9757","contributorId":1074,"corporation":false,"usgs":true,"family":"Kappel","given":"William","email":"wkappel@usgs.gov","middleInitial":"M.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":304129,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":98092,"text":"sir20095216 - 2009 - Analysis of Water-Quality Trends for Selected Streams in the Water Chemistry Monitoring Program, Michigan, 1998-2005 ","interactions":[],"lastModifiedDate":"2012-03-08T17:16:29","indexId":"sir20095216","displayToPublicDate":"2010-01-06T00:00:00","publicationYear":"2009","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":"2009-5216","title":"Analysis of Water-Quality Trends for Selected Streams in the Water Chemistry Monitoring Program, Michigan, 1998-2005 ","docAbstract":"In 1998, the Michigan Department of Environmental Quality and the U.S. Geological Survey began a long-term monitoring program to evaluate the water quality of most watersheds in Michigan. Major goals of this Water-Chemistry Monitoring Program were to identify streams exceeding or not meeting State or Federal water-quality standards and to assess if constituent concentrations reflecting water quality in these streams were increasing or decreasing over time. As part of this program, water-quality data collected from 1998 to 2005 were analyzed to identify potential trends. Sixteen water-quality constituents were analyzed at 31 sites across Michigan, 28 of which had sufficient data to analyze for trends. Trend analysis on the various water-quality data was done using the uncensored Seasonal Kendall test within the computer program ESTREND. The most prevalent trend detected throughout the state was for chloride. Chloride trends were detected at 8 of the 28 sites; trends at 7 sites were increasing and the trend at 1 site was decreasing. Although no trends were detected for various nitrogen species or phosphorus, these constituents were detected at levels greater than the U.S. Environmental Protection Agency recommendations for nutrients in water. The results of the trend analysis will help to establish a baseline to evaluate future changes in water quality in Michigan streams.","language":"ENGLISH","publisher":"U.S. Geological Survey","doi":"10.3133/sir20095216","collaboration":"Prepared in cooperation with the Michigan Department of Environmental Quality","usgsCitation":"Hoard, C.J., Fuller, L.M., and Fogarty, L., 2009, Analysis of Water-Quality Trends for Selected Streams in the Water Chemistry Monitoring Program, Michigan, 1998-2005 : U.S. Geological Survey Scientific Investigations Report 2009-5216, viii, 48 p., https://doi.org/10.3133/sir20095216.","productDescription":"viii, 48 p.","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"1998-01-01","temporalEnd":"2005-12-31","costCenters":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"links":[{"id":125875,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2009_5216.jpg"},{"id":13328,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2009/5216/","linkFileType":{"id":5,"text":"html"}}],"geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -91,41 ], [ -91,48 ], [ -82,48 ], [ -82,41 ], [ -91,41 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"4f4e4ad0e4b07f02db680ae5","contributors":{"authors":[{"text":"Hoard, C. J.","contributorId":37436,"corporation":false,"usgs":true,"family":"Hoard","given":"C.","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":304125,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fuller, Lori M. lmfuller@usgs.gov","contributorId":2100,"corporation":false,"usgs":true,"family":"Fuller","given":"Lori","email":"lmfuller@usgs.gov","middleInitial":"M.","affiliations":[{"id":382,"text":"Michigan Water Science Center","active":true,"usgs":true}],"preferred":false,"id":304124,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fogarty, Lisa R.","contributorId":74074,"corporation":false,"usgs":true,"family":"Fogarty","given":"Lisa R.","affiliations":[],"preferred":false,"id":304126,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70111598,"text":"70111598 - 2009 - Effect of water hardness and dissolved-solid concentration on hatching success and egg size in bighead carp","interactions":[],"lastModifiedDate":"2014-06-05T14:13:26","indexId":"70111598","displayToPublicDate":"2010-01-05T14:01:14","publicationYear":"2009","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3624,"text":"Transactions of the American Fisheries Society","active":true,"publicationSubtype":{"id":10}},"title":"Effect of water hardness and dissolved-solid concentration on hatching success and egg size in bighead carp","docAbstract":"Bighead carp Hypophthalmichthys nobilis is an Asian species that has been introduced to the United States and is regarded as a highly undesirable invader. Soft water has been said to cause the bursting of Asian carp eggs and thus has been suggested as a factor that would limit the spread of this species. To evaluate this, we subjected fertilized eggs of bighead carp to waters with a wide range of hardness and dissolved-solid concentrations. Hatching rate and egg size were not significantly affected by the different water qualities. These results, combined with the low hardness (28–84 mg/L) of the Yangtze River (the primary natal habitat of Hypophthalmichthys spp.), suggest that managers and those performing risk assessments for the establishment of Hypophthalmichthys spp. should be cautious about treating low hardness and dissolved-solid concentrations as limiting factors.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Transactions of the American Fisheries Society","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Taylor & Francis","doi":"10.1577/T09-004.1","usgsCitation":"Chapman, D., and Deters, J.E., 2009, Effect of water hardness and dissolved-solid concentration on hatching success and egg size in bighead carp: Transactions of the American Fisheries Society, v. 138, no. 6, p. 1226-1231, https://doi.org/10.1577/T09-004.1.","productDescription":"6 p.","startPage":"1226","endPage":"1231","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":476011,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1577/t09-004.1","text":"Publisher Index Page"},{"id":288114,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":288113,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1577/T09-004.1"}],"volume":"138","issue":"6","noUsgsAuthors":false,"publicationDate":"2011-01-09","publicationStatus":"PW","scienceBaseUri":"53919162e4b06f80638265c1","contributors":{"authors":[{"text":"Chapman, Duane 0000-0002-1086-8853 dchapman@usgs.gov","orcid":"https://orcid.org/0000-0002-1086-8853","contributorId":1291,"corporation":false,"usgs":true,"family":"Chapman","given":"Duane","email":"dchapman@usgs.gov","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true},{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":494372,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Deters, Joseph E. jdeters@usgs.gov","contributorId":3240,"corporation":false,"usgs":true,"family":"Deters","given":"Joseph","email":"jdeters@usgs.gov","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":494373,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":98087,"text":"sir20095248 - 2009 - The Water Availability Tool for Environmental Resources (WATER): A water-budget modeling approach for managing water-supply resources in non-karst areas of Kentucky (phase I) — Data processing and model structure documentstion","interactions":[],"lastModifiedDate":"2021-12-15T21:02:47.973093","indexId":"sir20095248","displayToPublicDate":"2010-01-05T00:00:00","publicationYear":"2009","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":"2009-5248","title":"The Water Availability Tool for Environmental Resources (WATER): A water-budget modeling approach for managing water-supply resources in non-karst areas of Kentucky (phase I) — Data processing and model structure documentstion","docAbstract":"The Water Availability Tool for Environmental Resources (WATER) was developed in cooperation with the Kentucky Division of Water to provide a consistent and defensible method of estimating streamflow and water availability in ungaged basins. WATER is process oriented; it is based on the TOPMODEL code and incorporates historical water-use data together with physiographic data that quantitatively describe topography and soil-water storage. The result is a user-friendly decision tool that can estimate water availability in non-karst areas of Kentucky without additional data or processing. The model runs on a daily time step, and critical source data include a historical record of daily temperature and precipitation, digital elevation models (DEMs), the Soil Survey Geographic Database (SSURGO), and historical records of water discharges and withdrawals. The model was calibrated and statistically evaluated for 12 basins by comparing the estimated discharge to that observed at U.S. Geological Survey streamflow-gaging stations. When statistically evaluated over a 2,119-day time period, the discharge estimates showed a bias of -0.29 to 0.42, a root mean square error of 1.66 to 5.06, a correlation of 0.54 to 0.85, and a Nash-Sutcliffe Efficiency of 0.26 to 0.72. The parameter and input modifications that most significantly improved the accuracy and precision of streamflow-discharge estimates were the addition of Next Generation radar (NEXRAD) precipitation data, a rooting depth of 30 centimeters, and a TOPMODEL scaling parameter (m) derived directly from SSURGO data that was multiplied by an adjustment factor of 0.10. No site-specific optimization was used.","language":"English","publisher":"U.S. Geological Survey","doi":"10.3133/sir20095248","collaboration":"Prepared in cooperation with the Kentucky Division of Water","usgsCitation":"Williamson, T., Odom, K.R., Newson, J.K., Downs, A.C., Nelson, H.L., Cinotto, P.J., and Ayers, M.A., 2009, The Water Availability Tool for Environmental Resources (WATER): A water-budget modeling approach for managing water-supply resources in non-karst areas of Kentucky (phase I) — Data processing and model structure documentstion: U.S. Geological Survey Scientific Investigations Report 2009-5248, vi, 34 p., https://doi.org/10.3133/sir20095248.","productDescription":"vi, 34 p.","costCenters":[{"id":354,"text":"Kentucky Water Science Center","active":true,"usgs":true}],"links":[{"id":125858,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2009_5248.jpg"},{"id":392968,"rank":3,"type":{"id":36,"text":"NGMDB Index 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Center","active":true,"usgs":true}],"preferred":true,"id":304104,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ayers, Mark A.","contributorId":84730,"corporation":false,"usgs":true,"family":"Ayers","given":"Mark","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":304110,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":98088,"text":"sir20095231 - 2009 - Regression models to estimate real-time concentrations of selected constituents in two tributaries to Lake Houston near Houston, Texas, 2005-07","interactions":[],"lastModifiedDate":"2016-08-15T11:00:28","indexId":"sir20095231","displayToPublicDate":"2010-01-05T00:00:00","publicationYear":"2009","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":"2009-5231","title":"Regression models to estimate real-time concentrations of selected constituents in two tributaries to Lake Houston near Houston, Texas, 2005-07","docAbstract":"In December 2005, the U.S. Geological Survey in cooperation with the City of Houston, Texas, began collecting discrete water-quality samples for nutrients, total organic carbon, bacteria (total coliform and Escherichia coli), atrazine, and suspended sediment at two U.S. Geological Survey streamflow-gaging stations upstream from Lake Houston near Houston (08068500 Spring Creek near Spring, Texas, and 08070200 East Fork San Jacinto River near New Caney, Texas). The data from the discrete water-quality samples collected during 2005-07, in conjunction with monitored real-time data already being collected - physical properties (specific conductance, pH, water temperature, turbidity, and dissolved oxygen), streamflow, and rainfall - were used to develop regression models for predicting water-quality constituent concentrations for inflows to Lake Houston. Rainfall data were obtained from a rain gage monitored by Harris County Homeland Security and Emergency Management and colocated with the Spring Creek station. The leaps and bounds algorithm was used to find the best subsets of possible regression models (minimum residual sum of squares for a given number of variables). The potential explanatory or predictive variables included discharge (streamflow), specific conductance, pH, water temperature, turbidity, dissolved oxygen, rainfall, and time (to account for seasonal variations inherent in some water-quality data). The response variables at each site were nitrite plus nitrate nitrogen, total phosphorus, organic carbon, Escherichia coli, atrazine, and suspended sediment. The explanatory variables provide easily measured quantities as a means to estimate concentrations of the various constituents under investigation, with accompanying estimates of measurement uncertainty. Each regression equation can be used to estimate concentrations of a given constituent in real time. In conjunction with estimated concentrations, constituent loads were estimated by multiplying the estimated concentration by the corresponding streamflow and applying the appropriate conversion factor. By computing loads from estimated constituent concentrations, a continuous record of estimated loads can be available for comparison to total maximum daily loads. The regression equations presented in this report are site specific to the Spring Creek and East Fork San Jacinto River streamflow-gaging stations; however, the methods that were developed and documented could be applied to other tributaries to Lake Houston for estimating real-time water-quality data for streams entering Lake Houston.
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