Cheney Reservoir, constructed during 1962 to 1965, is the primary water supply for the city of Wichita, the largest city in Kansas. Sediment is an important concern for the reservoir as it degrades water quality and progressively decreases water storage capacity. Long-term data collection provided a unique opportunity to estimate the annual suspended sediment loads for the entire history of the reservoir. To quantify and characterize sediment loading to Cheney Reservoir, discrete suspended sediment samples and continuously measured streamflow data were collected from the North Fork Ninnescah River, the primary inflow to Cheney Reservoir, over a 48-year period. Continuous turbidity data also were collected over a 15-year period. These data were used together to develop simple linear regression models to compute continuous suspended sediment concentrations and loads from 1966 to 2013. The inclusion of turbidity as an additional explanatory variable with streamflow improved regression model diagnostics and increased the amount of variability in suspended sediment concentration explained by 14%. Using suspended sediment concentration from the streamflow-only model, the average annual suspended sediment load was 102,517 t (113,006 tn) and ranged from 4,826 t (5,320 tn) in 1966 to 967,569 t (1,066,562 tn) in 1979. The sediment load in 1979 accounted for about 20% of the total load over the 48-year history of the reservoir and 92% of the 1979 sediment load occurred in one 24-hour period during a 1% annual exceedance probability flow event (104-year flood). Nearly 60% of the reservoir sediment load during the 48-year study period occurred in 5 years with extreme flow events (9% to 1% annual exceedance probability, or 11- to 104-year flood events). A substantial portion (41%) of sediment was transported to the reservoir during five storm events spanning only eight 24-hour periods during 1966 to 2013. Annual suspended sediment load estimates based on streamflow were, on average, within ±20% of estimates based on streamflow and turbidity combined. Results demonstrate that large suspended sediment loads are delivered to Cheney Reservoir in very short time periods, indicating that sediment management plans eventually must address large, infrequent inflow events to be effective.
","language":"English","publisher":"Soil and Water Conservation Society","doi":"10.2489/jswc.70.2.91","usgsCitation":"Stone, M.L., Juracek, K.E., Graham, J., and Foster, G.M., 2015, Quantifying suspended sediment loads delivered to Cheney Reservoir, Kansas: Temporal patterns and management implications: Journal of Soil and Water Conservation, v. 70, no. 2, p. 91-100, https://doi.org/10.2489/jswc.70.2.91.","productDescription":"10 p.","startPage":"91","endPage":"100","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-058102","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":472250,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.2489/jswc.70.2.91","text":"Publisher Index Page"},{"id":325358,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Kansas","otherGeospatial":"Cheney Reservoir Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -99.0692138671875,\n 37.67077737288316\n ],\n [\n -99.0692138671875,\n 38.01564013749379\n ],\n [\n -97.77145385742188,\n 38.01564013749379\n ],\n [\n -97.77145385742188,\n 37.67077737288316\n ],\n [\n -99.0692138671875,\n 37.67077737288316\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"70","issue":"2","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2015-03-12","publicationStatus":"PW","scienceBaseUri":"578dfdb8e4b0f1bea0e0f8e1","contributors":{"authors":[{"text":"Stone, Mandy L. 0000-0002-6711-1536 mstone@usgs.gov","orcid":"https://orcid.org/0000-0002-6711-1536","contributorId":4409,"corporation":false,"usgs":true,"family":"Stone","given":"Mandy","email":"mstone@usgs.gov","middleInitial":"L.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":642667,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Juracek, Kyle E. 0000-0002-2102-8980 kjuracek@usgs.gov","orcid":"https://orcid.org/0000-0002-2102-8980","contributorId":2022,"corporation":false,"usgs":true,"family":"Juracek","given":"Kyle","email":"kjuracek@usgs.gov","middleInitial":"E.","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"preferred":true,"id":642668,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Graham, Jennifer L. 0000-0002-6420-9335 jlgraham@usgs.gov","orcid":"https://orcid.org/0000-0002-6420-9335","contributorId":150737,"corporation":false,"usgs":true,"family":"Graham","given":"Jennifer L.","email":"jlgraham@usgs.gov","affiliations":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true},{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":false,"id":642669,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Foster, Guy M. 0000-0002-9581-057X gfoster@usgs.gov","orcid":"https://orcid.org/0000-0002-9581-057X","contributorId":149145,"corporation":false,"usgs":true,"family":"Foster","given":"Guy","email":"gfoster@usgs.gov","middleInitial":"M.","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":642670,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70168391,"text":"70168391 - 2015 - The importance of scaling for detecting community patterns: success and failure in assemblages of introduced species","interactions":[],"lastModifiedDate":"2016-08-31T16:00:07","indexId":"70168391","displayToPublicDate":"2015-03-01T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1398,"text":"Diversity","active":true,"publicationSubtype":{"id":10}},"title":"The importance of scaling for detecting community patterns: success and failure in assemblages of introduced species","docAbstract":"Community saturation can help to explain why biological invasions fail. However, previous research has documented inconsistent relationships between failed invasions (i.e., an invasive species colonizes but goes extinct) and the number of species present in the invaded community. We use data from bird communities of the Hawaiian island of Oahu, which supports a community of 38 successfully established introduced birds and where 37 species were introduced but went extinct (failed invasions). We develop a modified approach to evaluate the effects of community saturation on invasion failure. Our method accounts (1) for the number of species present (NSP) when the species goes extinct rather than during its introduction; and (2) scaling patterns in bird body mass distributions that accounts for the hierarchical organization of ecosystems and the fact that interaction strength amongst species varies with scale. We found that when using NSP at the time of extinction, NSP was higher for failed introductions as compared to successful introductions, supporting the idea that increasing species richness and putative community saturation mediate invasion resistance. Accounting for scale-specific patterns in body size distributions further improved the relationship between NSP and introduction failure. Results show that a better understanding of invasion outcomes can be obtained when scale-specific community structure is accounted for in the analysis.
","language":"English","publisher":"MDPI","doi":"10.3390/d7030229","usgsCitation":"Allen, C.R., Angeler, D., Moulton, M.P., and Holling, C.S., 2015, The importance of scaling for detecting community patterns: success and failure in assemblages of introduced species: Diversity, v. 7, no. 3, p. 229-241, https://doi.org/10.3390/d7030229.","productDescription":"13 p.","startPage":"229","endPage":"241","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-066119","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":472251,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/d7030229","text":"Publisher Index Page"},{"id":317933,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Oahu","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", 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G.","affiliations":[],"preferred":false,"id":619881,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Moulton, Michael P.","contributorId":166723,"corporation":false,"usgs":false,"family":"Moulton","given":"Michael","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":619882,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Holling, Crawford S.","contributorId":20511,"corporation":false,"usgs":true,"family":"Holling","given":"Crawford","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":619883,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70196455,"text":"70196455 - 2015 - Real-time validation of the Dst Predictor model","interactions":[],"lastModifiedDate":"2019-07-10T14:00:14","indexId":"70196455","displayToPublicDate":"2015-02-28T00:00:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"seriesTitle":{"id":5677,"text":"Air Force Research Laboratory Technical Report ","active":true,"publicationSubtype":{"id":1}},"seriesNumber":"AFRL-RV-PS-TR-2015-0073","title":"Real-time validation of the Dst Predictor model","docAbstract":"The Dst Predictor model, which has been running real-time in the Space Weather Analysis and Forecast System (SWAFS), provides 1-hour and 4-hour forecasts of the Dst index. This is useful for awareness of impending geomagnetic activity, as well as driving other real-time models that use Dst as an input. In this report, we examine the performance of this forecast model in detail. When validating indices it should be noted that performance is only with respect to a reference index as they are derived quantities assumed to reflect a state of the magnetosphere that cannot be directly measured. In this case U.S. Geological Survey (USGS) Definitive Dst is the reference index (Section 3). Whether or not the model better reflects the actual activity level is nearly impossible to discern and is outside the scope of this report. We evaluate the performance of the model by computing continuous predictant skill scores against USGS Definitive Dst values as “observations” (Section 4.2). The two sets of data are not well-correlated for both 1-hour and 4-hour forecasts. The Dst Predictor Prediction Efficiency for both the 1- and 4-hour forecasts suggests poor performance versus the climatological mean. However, the skill score against a nowcast persistence model is positive, suggesting value added by the Dst Predictor model. We further examine statistics for storm times (Section 4.3) with similar results: nowcast persistence performs worse than Dst Predictor. Dst Predictor is superior to the nowcast persistence model for the metric used in this study. We recommend continued use of the DstPredictor model for 1-and4-hour Dst predictions along with active study of other Dst forecast models that do not rely on nowcast inputs (Section 6). The lack of certified requirements makes further recommendations difficult. A study of how the error in Dst translates to error in models and a better understanding of operational needs for magnetic storm warning are needed to determine such requirements. Nowcast persistence is often hard to beat for short term forecasts and specification and Dst Predictor clearly performs well against that standard (with 1-hour and 4-hour skill-scores of 0.233 and 0.485 respectively), although poor in absolute terms (with1-hourand4-hour prediction efficiencies of-64.6and-43.1, respectively).
","language":"English","publisher":"Air Force Research Laboratory","usgsCitation":"McCollough, J.P., Young, S.L., Rigler, E.J., and Simpson, H.A., 2015, Real-time validation of the Dst Predictor model: Air Force Research Laboratory Technical Report AFRL-RV-PS-TR-2015-0073, iii, 9 p.","productDescription":"iii, 9 p.","numberOfPages":"12","ipdsId":"IP-063134","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true},{"id":422,"text":"National Geomagnetism Program","active":false,"usgs":true}],"links":[{"id":353266,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5afeebcfe4b0da30c1bfc686","contributors":{"authors":[{"text":"McCollough, James P.","contributorId":204030,"corporation":false,"usgs":false,"family":"McCollough","given":"James","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":732972,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Young, Shawn L.","contributorId":204031,"corporation":false,"usgs":false,"family":"Young","given":"Shawn","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":732973,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Rigler, E. Joshua 0000-0003-4850-3953 erigler@usgs.gov","orcid":"https://orcid.org/0000-0003-4850-3953","contributorId":4367,"corporation":false,"usgs":true,"family":"Rigler","given":"E.","email":"erigler@usgs.gov","middleInitial":"Joshua","affiliations":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"preferred":true,"id":732974,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Simpson, Hal A.","contributorId":204032,"corporation":false,"usgs":false,"family":"Simpson","given":"Hal","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":732975,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70142063,"text":"ofr20151019 - 2015 - Obtaining valid geologic models from 3-D resistivity inversion of magnetotelluric data at Pahute Mesa, Nevada","interactions":[],"lastModifiedDate":"2015-02-27T13:07:46","indexId":"ofr20151019","displayToPublicDate":"2015-02-27T12:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-1019","title":"Obtaining valid geologic models from 3-D resistivity inversion of magnetotelluric data at Pahute Mesa, Nevada","docAbstract":"We summarize the results of a three-dimensional (3-D) resistivity inversion simulation that we conducted with the intent of characterizing the subsurface 3-D distribution of volcanic composite units of Pahute Mesa, Nevada, without any a priori information on the actual 3-D distribution of the known subsurface geology. The 3-D methodology involved using a 3-D geologic model based on drillhole data and average electrical resistivities of the key hydrostratigraphic units at Pahute Mesa to create a 3-D resistivity forward (“known”) model that depicted the subsurface resistivity structure expected for the input geologic configuration. The calculated magnetotelluric response of the modeled resistivity structure was then assumed to represent observed magnetotelluric data and was used as input into a 3-D resistivity inverse model that was allowed to iteratively estimate in 3-D without any a priori geologic information, in particular, the thickness and resistivity of the volcanic composite units. The resulting 3-D resistivity inversion simulation was compared to the “known” model and the results evaluated.
\nThe 3-D inversion was generally able to reproduce the gross resistivity structure of the “known” model, but the simulated conductive volcanic composite unit horizons were often too shallow when compared to the “known” model. Additionally, the chosen computation parameters such as station spacing appear to have resulted in computational artifacts that are difficult to interpret but could potentially be removed with further refinements of the 3-D resistivity inversion modeling technique.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20151019","usgsCitation":"Rodriguez, B.D., and Sweetkind, D., 2015, Obtaining valid geologic models from 3-D resistivity inversion of magnetotelluric data at Pahute Mesa, Nevada: U.S. Geological Survey Open-File Report 2015-1019, iv, 104 p., https://doi.org/10.3133/ofr20151019.","productDescription":"iv, 104 p.","numberOfPages":"108","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-051924","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":298187,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr20151019.jpg"},{"id":298185,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2015/1019/"},{"id":298186,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2015/1019/pdf/ofr2015-1019.pdf","text":"Report","size":"20.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"datum":"North American 1983 Continental United States (CONUS) datum","country":"United States","state":"Nevada","otherGeospatial":"Pahute Mesa","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.51687622070314,\n 37.22103367911787\n ],\n [\n -116.51687622070314,\n 37.33795407160059\n ],\n [\n -116.3733673095703,\n 37.33795407160059\n ],\n [\n -116.3733673095703,\n 37.22103367911787\n ],\n [\n -116.51687622070314,\n 37.22103367911787\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54f19545e4b02419550ceaee","contributors":{"authors":[{"text":"Rodriguez, Brian D. 0000-0002-2263-611X brod@usgs.gov","orcid":"https://orcid.org/0000-0002-2263-611X","contributorId":836,"corporation":false,"usgs":true,"family":"Rodriguez","given":"Brian","email":"brod@usgs.gov","middleInitial":"D.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":541601,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sweetkind, Donald S. dsweetkind@usgs.gov","contributorId":130958,"corporation":false,"usgs":true,"family":"Sweetkind","given":"Donald S.","email":"dsweetkind@usgs.gov","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":false,"id":541602,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70143049,"text":"70143049 - 2015 - Using a laboratory-based growth model to estimate mass- and temperature-dependent growth parameters across populations of juvenile Chinook Salmon","interactions":[],"lastModifiedDate":"2015-03-17T11:02:13","indexId":"70143049","displayToPublicDate":"2015-02-27T12:15:00","publicationYear":"2015","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":"Using a laboratory-based growth model to estimate mass- and temperature-dependent growth parameters across populations of juvenile Chinook Salmon","docAbstract":"To estimate the parameters that govern mass- and temperature-dependent growth, we conducted a meta-analysis of existing growth data from juvenile Chinook Salmon Oncorhynchus tshawytscha that were fed an ad libitum ration of a pelleted diet. Although the growth of juvenile Chinook Salmon has been well studied, research has focused on a single population, a narrow range of fish sizes, or a narrow range of temperatures. Therefore, we incorporated the Ratkowsky model for temperature-dependent growth into an allometric growth model; this model was then fitted to growth data from 11 data sources representing nine populations of juvenile Chinook Salmon. The model fit the growth data well, explaining 98% of the variation in final mass. The estimated allometric mass exponent (b) was 0.338 (SE = 0.025), similar to estimates reported for other salmonids. This estimate of b will be particularly useful for estimating mass-standardized growth rates of juvenile Chinook Salmon. In addition, the lower thermal limit, optimal temperature, and upper thermal limit for growth were estimated to be 1.8°C (SE = 0.63°C), 19.0°C (SE = 0.27°C), and 24.9°C (SE = 0.02°C), respectively. By taking a meta-analytical approach, we were able to provide a growth model that is applicable across populations of juvenile Chinook Salmon receiving an ad libitum ration of a pelleted diet.
","language":"English","publisher":"American Fisheries Society","publisherLocation":"Bethesda, MD","doi":"10.1080/00028487.2014.996667","usgsCitation":"Perry, R.W., Plumb, J.M., and Huntington, C., 2015, Using a laboratory-based growth model to estimate mass- and temperature-dependent growth parameters across populations of juvenile Chinook Salmon: Transactions of the American Fisheries Society, v. 144, no. 2, p. 331-336, https://doi.org/10.1080/00028487.2014.996667.","productDescription":"6 p.","startPage":"331","endPage":"336","numberOfPages":"6","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-053357","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":472258,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/00028487.2014.996667","text":"Publisher Index Page"},{"id":298618,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":298587,"type":{"id":15,"text":"Index Page"},"url":"https://afs.tandfonline.com/doi/full/10.1080/00028487.2014.996667#.VQdH9cIRC70"}],"volume":"144","issue":"2","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationDate":"2015-02-27","publicationStatus":"PW","scienceBaseUri":"55095034e4b02e76d757e637","contributors":{"authors":[{"text":"Perry, Russell W. 0000-0003-4110-8619 rperry@usgs.gov","orcid":"https://orcid.org/0000-0003-4110-8619","contributorId":2820,"corporation":false,"usgs":true,"family":"Perry","given":"Russell","email":"rperry@usgs.gov","middleInitial":"W.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":542446,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Plumb, John M. 0000-0003-4255-1612 jplumb@usgs.gov","orcid":"https://orcid.org/0000-0003-4255-1612","contributorId":3569,"corporation":false,"usgs":true,"family":"Plumb","given":"John","email":"jplumb@usgs.gov","middleInitial":"M.","affiliations":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"preferred":true,"id":542447,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Huntington, Charles","contributorId":139682,"corporation":false,"usgs":false,"family":"Huntington","given":"Charles","email":"","affiliations":[{"id":12878,"text":"Clearwater BioStudies, Inc., 1160 Old Ferry Rd., Shady Cove, OR 95616","active":true,"usgs":false}],"preferred":false,"id":542448,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70129565,"text":"fs20143102 - 2015 - Water resources of St. John the Baptist Parish, Louisiana","interactions":[],"lastModifiedDate":"2015-02-27T09:10:49","indexId":"fs20143102","displayToPublicDate":"2015-02-27T09:00:00","publicationYear":"2015","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":"2014-3102","title":"Water resources of St. John the Baptist Parish, Louisiana","docAbstract":"Information concerning the availability, use, and quality of water in St. John the Baptist Parish, Louisiana, is critical for proper water-supply management. The purpose of this fact sheet is to present information that can be used by water managers, parish residents, and others for stewardship of this vital resource. Information on the availability, past and current use, use trends, and water quality from groundwater and surface-water sources in the parish is presented. Previously published reports and data stored in the U.S. Geological Survey’s National Water Information System (http://waterdata.usgs.gov/nwis) are the primary sources of the information presented here.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20143102","collaboration":"Prepared in cooperation with the Louisiana Department of Transportation and Development","usgsCitation":"White, V.E., Prakken, L.B., and Fendick, R., 2015, Water resources of St. John the Baptist Parish, Louisiana: U.S. Geological Survey Fact Sheet 2014-3102, 6 p., https://doi.org/10.3133/fs20143102.","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057860","costCenters":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"links":[{"id":298176,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20143102.jpg"},{"id":298174,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2014/3102/"},{"id":298175,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2014/3102/pdf/fs2014-3102.pdf","text":"Report","size":"10.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"projection":"Albers Equal-Area Conic projection","datum":"North American Datum of 1983","country":"United States","state":"Louisiana","county":"St. John the Baptist Parish","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.68252563476561,\n 29.88411360077131\n ],\n [\n -90.68252563476561,\n 30.30294635121175\n ],\n [\n -90.20118713378906,\n 30.30294635121175\n ],\n [\n -90.20118713378906,\n 29.88411360077131\n ],\n [\n -90.68252563476561,\n 29.88411360077131\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54f1954de4b02419550ceb0a","contributors":{"authors":[{"text":"White, Vincent E. 0000-0002-1660-0102 vwhite@usgs.gov","orcid":"https://orcid.org/0000-0002-1660-0102","contributorId":5388,"corporation":false,"usgs":true,"family":"White","given":"Vincent","email":"vwhite@usgs.gov","middleInitial":"E.","affiliations":[{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true},{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":true,"id":519894,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Prakken, Lawrence B. lprakken@usgs.gov","contributorId":2319,"corporation":false,"usgs":true,"family":"Prakken","given":"Lawrence","email":"lprakken@usgs.gov","middleInitial":"B.","affiliations":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":false,"id":519893,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fendick, Robert B. Jr. rfendick@usgs.gov","contributorId":1313,"corporation":false,"usgs":true,"family":"Fendick","given":"Robert B.","suffix":"Jr.","email":"rfendick@usgs.gov","affiliations":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":false,"id":541590,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70142998,"text":"70142998 - 2015 - Wide-ranging phylogeographic structure of invasive red lionfish in the Western Atlantic and Greater Caribbean","interactions":[],"lastModifiedDate":"2016-11-22T18:37:58","indexId":"70142998","displayToPublicDate":"2015-02-26T13:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2660,"text":"Marine Biology","active":true,"publicationSubtype":{"id":10}},"title":"Wide-ranging phylogeographic structure of invasive red lionfish in the Western Atlantic and Greater Caribbean","docAbstract":"The red lionfish (Pterois volitans) is an invasive predatory marine fish that has rapidly expanded its presence in the Western Hemisphere. We collected 214 invasive red lionfish samples from nine countries and territories, including seven unpublished locations. To more comprehensively evaluate connectivity, we compiled our d-loop sequence data with 846 published sequences, resulting in 1,060 samples from 14 locations. We found low nucleotide diversity (π = 0.003) and moderate haplotype diversity (h = 0.59). Using haplotype population pairwise ΦST tests, we analyzed possible phylogeographic breaks that were previously proposed based on other reef organisms. We found support for the Bahamas/Turks/Caicos versus Caribbean break (ΦST = 0.12) but not for the Northwestern Caribbean, Eastern Caribbean, or US East Coast versus Bahamas breaks. The Northern Region had higher variation and more haplotypes, supporting introductions of at least five haplotypes to the region. Our wide-ranging samples showed that a lower-frequency haplotype in the Northern Region dominated the Southern Region and suggested multiple introductions, possibly to the south. We tested multiple scenarios of phylogeographic structure with analyses of molecular variance and found support for a Northern and Southern Region split at the Bahamas/Turks/Caicos versus Caribbean break (percentage of variation among regions = 8.49 %). We found that Puerto Rico clustered with the Southern Region more strongly than with the Northern Region, as opposed to previous reports. We also found the rare haplotype H03 for the first time in the southern Caribbean (Panama), indicating that either secondary releases occurred or that the low-frequency haplotypes have had time to disperse to extreme southern Caribbean locations.
Groundwater quality in the 633-square-mile (1,639-square-kilometer) Northern Coast Ranges (NOCO) study unit was investigated as part of the Priority Basin Project (PBP) of the Groundwater Ambient Monitoring and Assessment (GAMA) Program and the U.S. Geological Survey (USGS) National Water-Quality Assessment Program. The study unit is composed of two study areas (Interior Basins and Coastal Basins) and is located in northern California in Napa, Sonoma, Lake, Colusa, Mendocino, Glenn, Humboldt, and Del Norte Counties. The GAMA-PBP is being conducted by the California State Water Resources Control Board in collaboration with the USGS and the Lawrence Livermore National Laboratory.
\nThe GAMA NOCO study was designed to provide a spatially unbiased assessment of the quality of untreated (ambient) groundwater in the primary aquifer system within the study unit. The assessment is based on water-quality and ancillary data collected in 2009 by the USGS from 58 sites and on water-quality data from the California Department of Public Health (CDPH) database. The primary aquifer system is defined by the perforation intervals of sites listed in the CDPH water-quality database for the NOCO study unit. Groundwater quality in the primary aquifer system may differ from the quality in the shallow or deep water-bearing zones.
\nThe first component of this study, the status assessment of the current quality of the groundwater resource, was performed by using data from samples analyzed for inorganic constituents (such as trace elements and major and minor ions), organic constituents (volatile organic compounds and pesticides and pesticide degradates), the special-interest constituent perchlorate, and microbial indicators. This status assessment is intended to characterize the quality of groundwater resources in the primary aquifer system of the NOCO study unit, not the quality of treated drinking water delivered to consumers by water purveyors.
\nRelative-concentrations (sample concentration divided by the health- or aesthetic-based benchmark concentration) were used for evaluating groundwater quality for those constituents that have Federal or California regulatory or nonregulatory benchmarks for drinking-water quality. A relative-concentration greater than (>) 1.0 indicates a concentration greater than a benchmark, and a relative-concentration less than or equal to (≤) 1.0 indicates a concentration less than or equal to a benchmark. Relative-concentrations of organic constituents and perchlorate were classified as “high” (relative-concentration >1.0), “moderate” (0.1 < relative-concentration ≤1.0), or “low” (relative-concentration ≤0.1). Relative-concentrations of inorganic constituents were classified as “high” (relative-concentration >1.0), “moderate” (0.5 < relative-concentration ≤1.0), or “low” (relative-concentration ≤0.5).
\nAquifer-scale proportion was used as the primary metric in the status assessment for evaluating regional-scale groundwater quality. High aquifer-scale proportion was defined as the percentage of the area of the primary aquifer system with a relative-concentration >1.0 for a particular constituent or class of constituents; the percentage is based on an aerial rather than a volumetric basis. Moderate and low aquifer-scale proportions were defined as the percentage of the primary aquifer system with moderate and low relative-concentrations, respectively. Two statistical approaches—grid-based and spatially weighted—were used to evaluate aquifer-scale proportions for individual constituents and classes of constituents. Grid-based and spatially weighted estimates were comparable in the NOCO study unit (within 90 percent confidence intervals).
\nInorganic constituents (one or more) with health-based benchmarks were detected at high relative-concentrations in 10.3 percent and at moderate relative-concentrations in 13.8 percent of the primary aquifer system. The high aquifer-scale proportion of inorganic constituents primarily reflected high aquifer-scale proportions of boron (in 8.6 percent of the primary aquifer system), arsenic (in 3.4 percent), and barium (in 1.7 percent). Inorganic constituents with aesthetic-based benchmarks were detected at high relative-concentrations in 39.7 percent and at moderate relative-concentrations in 10.3 percent of the primary aquifer system. The constituents present at high relative-concentrations were iron (25.9 percent) and manganese (39.7 percent).
\nRelative-concentrations of organic constituents with health-based benchmarks (one or more) were high in 0.2 percent, moderate in 1.7 percent, and low in 39.7 percent of the primary aquifer system. Organic constituents were not detected in 58.4 percent of the primary aquifer system. Of the 168 organic constituents analyzed, 11 constituents were detected. Two organic constituents had detection frequencies >10 percent: the trihalomethane chloroform and the herbicide simazine. For the 10 detected organic constituents that had health-based benchmarks, nearly all detections had low relative-concentrations. The special-interest constituent perchlorate was detected at moderate relative-concentrations in 1.7 percent and at low relative-concentrations in 22.4 percent of the primary aquifer system. Perchlorate was not detected in 75.9 percent of the primary aquifer system.
\nThe second component of this study, the understanding assessment, evaluated relations between constituent concentrations and values of selected potential explanatory factors to identify the factors potentially affecting the concentrations and occurrences of constituents found at high relative-concentrations or, for organic constituents, with detection frequencies >10 percent. The potential explanatory factors evaluated were land use (including density of septic tanks and leaking or formerly leaking underground fuel tanks), well construction (well depth and depth to the top of the perforated interval in the well), hydrologic conditions (aridity index, field water temperature, and distance to nearest hot spring and geothermal well), pH, dissolved oxygen concentration, study area, groundwater age distribution, and geochemical conditions.
\nHigh and moderate relative-concentrations of boron primarily occurred in the Interior Basins study area and may be attributed to groundwater interacting with hydrothermal systems. High and moderate relative-concentrations of boron were associated with elevated groundwater temperatures, groundwater chemistry characteristics similar to those of geothermal waters, and distance to known geothermal areas. Boron concentrations generally were higher where low dissolved oxygen concentrations or anoxic conditions exist. High and moderate relative-concentrations of arsenic predominantly occur in the Interior Basins study area under reducing conditions. Arsenic concentrations also may be influenced by hydrothermal systems (when present).
\nChloroform, simazine, and perchlorate were observed in the Interior Basins and Coastal Basins study areas, predominantly at shallow sites with top-of-perforation depths ≤70 feet below land surface, with modern water (post-1950s), and with oxic groundwater conditions.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145215","collaboration":"Prepared in cooperation with the California State Water Resources Control Board and the U.S. Geological Survey National Water-Quality Assessment Program","usgsCitation":"Mathany, T.M., and Belitz, K., 2015, Status and understanding of groundwater quality in the Northern Coast Ranges study unit, 2009: California GAMA Priority Basin Project: U.S. Geological Survey Scientific Investigations Report 2014-5215, x, 86 p., https://doi.org/10.3133/sir20145215.","productDescription":"x, 86 p.","numberOfPages":"100","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2009-01-01","temporalEnd":"2009-12-31","ipdsId":"IP-030141","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":298170,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145215.jpg"},{"id":298169,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5215/pdf/sir2014-5215.pdf","text":"Report","size":"13.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":298148,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5215/"}],"country":"United States","state":"California","county":"Colusa County, Del Norte County, Glenn County, Humboldt County, Lake County, Mendocino County, Napa County, Sonoma County","otherGeospatial":"Northern Coast Ranges","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.541015625,\n 38.66835610151509\n ],\n [\n -124.541015625,\n 41.96765920367816\n ],\n [\n -121.79443359375,\n 41.96765920367816\n ],\n [\n -121.79443359375,\n 38.66835610151509\n ],\n [\n -124.541015625,\n 38.66835610151509\n ]\n ]\n ]\n }\n }\n ]\n}","publicComments":"A product of the California Groundwater Ambient Monitoring and Assessment (GAMA) Program","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54f043afe4b02419550ce86c","contributors":{"authors":[{"text":"Mathany, Timothy M. 0000-0002-4747-5113 tmathany@usgs.gov","orcid":"https://orcid.org/0000-0002-4747-5113","contributorId":1713,"corporation":false,"usgs":true,"family":"Mathany","given":"Timothy","email":"tmathany@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":false,"id":541550,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belitz, Kenneth 0000-0003-4481-2345 kbelitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":442,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","email":"kbelitz@usgs.gov","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":541551,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70133291,"text":"fs20143114 - 2015 - Groundwater quality in the Northern Coast Ranges Basins, California","interactions":[],"lastModifiedDate":"2018-05-24T12:52:45","indexId":"fs20143114","displayToPublicDate":"2015-02-26T11:00:00","publicationYear":"2015","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":"2014-3114","title":"Groundwater quality in the Northern Coast Ranges Basins, California","docAbstract":"The Northern Coast Ranges (NOCO) study unit is 633 square miles and consists of 35 groundwater basins and subbasins (California Department of Water Resources, 2003; Mathany and Belitz, 2015). These basins and subbasins were grouped into two study areas based primarily on locality. The groundwater basins and subbasins located inland, not adjacent to the Pacific Ocean, were aggregated into the Interior Basins (NOCO-IN) study area. The groundwater basins and subbasins adjacent to the Pacific Ocean were aggregated into the Coastal Basins (NOCO-CO) study area (Mathany and others, 2011).
\nThe primary aquifer system in the NOCO-IN study area occurs in alluvial basins made up of sand, silt, gravel, clay, and thin volcanic ash layers or lenses. Groundwater movement in the NOCO-IN study area follows the topography and direction of surface-water features. In the NOCO-CO study area, groundwater is present in alluvial fan, floodplain, and terrace deposits. Groundwater movement in the NOCO-CO study area is from east to west towards the Pacific Ocean.
\nThe primary aquifer system in the study unit generally is defined as those parts of the aquifer system corresponding to the perforated intervals of sites listed in the California Department of Public Health (CDPH) database of public drinking-water supply sources. Well depths in the NOCO-IN study area ranged from 36 to 400 feet below land surface (ft bls), and depths to top-of-perforations ranged from 15 to 148 ft bls. In the NOCO-CO study area, well depths ranged from 15 to 400 ft bls, and depths to top-of-perforations ranged from 10 to 356 ft bls. Water quality in the primary aquifer system may differ from that in the shallower and deeper parts of the aquifer system.
\nAverage annual rainfall in the NOCO study unit ranges from 22 to 79 inches. In the NOCO-IN study area, the climate is classified as Mediterranean, with warm to hot, dry summers and cold, wet winters. In the NOCO-CO study area, the climate is influenced by the Pacific Ocean and is characterized by cool to mild summers and cold, wet winters. The study unit is drained by several rivers and their principal tributaries: the Eel, Russian, Mad, Navarro, Smith, Klamath, Noyo, and Big Rivers.
\nLand use in the study unit is about 60 percent (%) natural (mostly grassland and forest), 29% agricultural, and 11% urban. The primary uses of agricultural lands are pasture, row crops, hay, vineyards, and timberlands. The largest urban areas are the cities of Crescent City, Arcata, Eureka, Fort Bragg, Willits, Ukiah, and Lakeport.
\nRecharge to the groundwater system is primarily from mixture of ambient sources, including direct percolation of precipitation and irrigation waters, infiltration of runoff from surrounding hills/areas, seepage from rivers and creeks, and subsurface inflow (from non-alluvial geologic units that bound the alluvial basins). The primary sources of discharge are evaporation, discharge to streams, and water pumped for municipal supply and irrigation.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20143114","collaboration":"U.S. Geological Survey and the California State Water Resources Control Board","usgsCitation":"Mathany, T.M., and Belitz, K., 2015, Groundwater quality in the Northern Coast Ranges Basins, California: U.S. Geological Survey Fact Sheet 2014-3114, 4 p., https://doi.org/10.3133/fs20143114.","productDescription":"4 p.","onlineOnly":"N","additionalOnlineFiles":"Y","ipdsId":"IP-044056","costCenters":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"links":[{"id":298165,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20143114.JPG"},{"id":298163,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2014/3114/pdf/fs2014-3114.pdf","text":"Report","size":"1.6 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":298164,"type":{"id":22,"text":"Related Work"},"url":"https://pubs.usgs.gov/sir/2014/5215/","text":"Scientific Investigations Report 2014-5215","size":"1.7 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Scientific Investigations Report 2014-5215"},{"id":298147,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2014/3114/"}],"country":"United States","state":"California","otherGeospatial":"Northern Coast Ranges","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -124.541015625,\n 38.66835610151509\n ],\n [\n -124.541015625,\n 41.96765920367816\n ],\n [\n -121.79443359375,\n 41.96765920367816\n ],\n [\n -121.79443359375,\n 38.66835610151509\n ],\n [\n -124.541015625,\n 38.66835610151509\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":1,"text":"Sacramento PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54f043ace4b02419550ce864","contributors":{"authors":[{"text":"Mathany, Timothy M. 0000-0002-4747-5113 tmathany@usgs.gov","orcid":"https://orcid.org/0000-0002-4747-5113","contributorId":1713,"corporation":false,"usgs":true,"family":"Mathany","given":"Timothy","email":"tmathany@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":false,"id":541548,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Belitz, Kenneth 0000-0003-4481-2345 kbelitz@usgs.gov","orcid":"https://orcid.org/0000-0003-4481-2345","contributorId":442,"corporation":false,"usgs":true,"family":"Belitz","given":"Kenneth","email":"kbelitz@usgs.gov","affiliations":[{"id":27111,"text":"National Water Quality Program","active":true,"usgs":true},{"id":376,"text":"Massachusetts Water Science Center","active":true,"usgs":true},{"id":451,"text":"National Water Quality Assessment Program","active":true,"usgs":true},{"id":503,"text":"Office of Water Quality","active":true,"usgs":true},{"id":466,"text":"New England Water Science Center","active":true,"usgs":true}],"preferred":true,"id":541549,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70141633,"text":"pp1650G - 2015 - Atlas of relations between climatic parameters and distributions of important trees and shrubs in North America: Revisions for all taxa from the United States and Canada and new taxa from the western United States","interactions":[],"lastModifiedDate":"2023-08-29T14:10:23.523993","indexId":"pp1650G","displayToPublicDate":"2015-02-26T10:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":331,"text":"Professional Paper","code":"PP","onlineIssn":"2330-7102","printIssn":"1044-9612","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"1650","chapter":"G","title":"Atlas of relations between climatic parameters and distributions of important trees and shrubs in North America: Revisions for all taxa from the United States and Canada and new taxa from the western United States","docAbstract":"This is the seventh volume in an atlas series that explores the relations between the geographic distributions of woody plant species and climatic variables in North America. A 25-kilometer (km) equal-area grid of modern climatic and bioclimatic variables was constructed from weather data. The geographic distributions of selected tree and shrub species were digitized, and the presence or absence of each species was determined for each point on the 25-km grid, thus providing a basis for comparing climatic data and species' distributions. The relations between climate and plant distributions are presented in graphical and tabular form. The results of this effort are intended primarily for use in biogeographic, ecologic, paleoclimatic, and global-change research.
\nThis volume of the atlas provides numerous changes, updates, and enhancements from previous volumes. Its geographic coverage is now restricted to Canada and the continental United States, and the source and time period of the climatic data have changed. New variables were added, including monthly values for temperature and precipitation, and measures of interannual variability. The distribution maps for all previously published species were redigitized, some distribution maps were revised, and 148 new species were added from the arid and semiarid western United States. The graphical displays were expanded to illustrate the new climatic variables, and the data tables were modified to provide more detail on the population distributions of plant taxa relative to climatic variables.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/pp1650G","usgsCitation":"Thompson, R.S., Anderson, K.H., Pelltier, R.T., Strickland, L.E., Shafer, S.L., Bartlein, P.J., and McFadden, A., 2015, Atlas of relations between climatic parameters and distributions of important trees and shrubs in North America: Revisions for all taxa from the United States and Canada and new taxa from the western United States: U.S. Geological Survey Professional Paper 1650, HTML Document; Downloads Directory, https://doi.org/10.3133/pp1650G.","productDescription":"HTML Document; Downloads Directory","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-048941","costCenters":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"links":[{"id":419975,"rank":4,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9FPD80E","text":"USGS data release","linkHelpText":"A gridded database of the modern distributions of climate, woody plant taxa, and ecoregions for the continental United States and Canada"},{"id":298161,"rank":1,"type":{"id":7,"text":"Companion Files"},"url":"https://pubs.usgs.gov/pp/p1650-g/downloads/pp1650-g.zip","text":"Downloads Directory","linkHelpText":"Contains: PP1650-G.zip"},{"id":298162,"rank":3,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/pp1650g.JPG"},{"id":298146,"rank":2,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/pp/p1650-g/"}],"country":"Canada, United States","otherGeospatial":"North America","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -141.328125,\n 24.846565348219734\n ],\n [\n -141.328125,\n 70.0205873017406\n ],\n [\n -55.1953125,\n 70.0205873017406\n ],\n [\n -55.1953125,\n 24.846565348219734\n ],\n [\n -141.328125,\n 24.846565348219734\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54f043a8e4b02419550ce860","contributors":{"authors":[{"text":"Thompson, Robert S. 0000-0001-9287-2954 rthompson@usgs.gov","orcid":"https://orcid.org/0000-0001-9287-2954","contributorId":891,"corporation":false,"usgs":true,"family":"Thompson","given":"Robert","email":"rthompson@usgs.gov","middleInitial":"S.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":541541,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Anderson, Katherine H. 0000-0003-2677-6109","orcid":"https://orcid.org/0000-0003-2677-6109","contributorId":52556,"corporation":false,"usgs":true,"family":"Anderson","given":"Katherine","email":"","middleInitial":"H.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":false,"id":541542,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Pelltier, Richard T. 0000-0001-8322-7961 rtpelltier@usgs.gov","orcid":"https://orcid.org/0000-0001-8322-7961","contributorId":4683,"corporation":false,"usgs":true,"family":"Pelltier","given":"Richard","email":"rtpelltier@usgs.gov","middleInitial":"T.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":541543,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Strickland, Laura E. 0000-0002-1958-7273 lstrickland@usgs.gov","orcid":"https://orcid.org/0000-0002-1958-7273","contributorId":4682,"corporation":false,"usgs":true,"family":"Strickland","given":"Laura","email":"lstrickland@usgs.gov","middleInitial":"E.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":541544,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Shafer, Sarah L. 0000-0003-3739-2637 sshafer@usgs.gov","orcid":"https://orcid.org/0000-0003-3739-2637","contributorId":1684,"corporation":false,"usgs":true,"family":"Shafer","given":"Sarah","email":"sshafer@usgs.gov","middleInitial":"L.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":false,"id":541545,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Bartlein, Patrick J.","contributorId":106879,"corporation":false,"usgs":true,"family":"Bartlein","given":"Patrick","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":541546,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"McFadden, Andrew K.","contributorId":139367,"corporation":false,"usgs":false,"family":"McFadden","given":"Andrew K.","affiliations":[{"id":6672,"text":"former: USGS Southwest Biological Science Center, Colorado Plateau Research Station, Flagstaff, AZ. Current address: TN-SCORE, Univ of Tennessee, Knoxville, TN, e-mail: jennen@gmail.com","active":true,"usgs":false}],"preferred":false,"id":541547,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70138825,"text":"fs20153005 - 2015 - In-place oil shale resources of the Mahogany zone sorted by grade, overburden thickness and stripping ratio, Green River Formation, Piceance Basin, Colorado and Uinta Basin, Utah","interactions":[],"lastModifiedDate":"2015-02-26T11:45:42","indexId":"fs20153005","displayToPublicDate":"2015-02-26T10:15:00","publicationYear":"2015","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":"2015-3005","title":"In-place oil shale resources of the Mahogany zone sorted by grade, overburden thickness and stripping ratio, Green River Formation, Piceance Basin, Colorado and Uinta Basin, Utah","docAbstract":"A range of geological parameters relevant to mining oil shale have been examined for the Mahogany zone of the Green River Formation in the Piceance Basin, Colorado, and Uinta Basin, Utah, using information available in the U.S. Geological Survey Oil Shale Assessment database. Basinwide discrete and cumulative distributions of resource in-place as a function of (1) oil shale grade, (2) Mahogany zone thickness, (3) overburden thickness, and (4) stripping ratio (overburden divided by zone thickness) were determined for both basins on a per-acre basis, and a resource map showing the areal distribution of these properties was generated. Estimates of how much of the Mahogany zone resource meets various combinations of these parameters were also determined. Of the 191.7 billion barrels of Mahogany zone oil in-place in the Piceance Basin, 32.3 percent (61.8 billion barrels) is associated with oil shale yielding at least 25 gallons of oil per ton (GPT) of rock processed, is covered by overburden 1,000 feet thick or less, and has a stripping ratio of less than 10. In the Uinta Basin, 14.0 percent (29.9 billion barrels) of the 214.5 billion barrels of Mahogany zone oil in-place meets the same overburden and stripping ratio criteria but only for the lower grade cutoff of 15 GPT.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20153005","usgsCitation":"Birdwell, J.E., Mercier, T.J., Johnson, R.C., and Brownfield, M.E., 2015, In-place oil shale resources of the Mahogany zone sorted by grade, overburden thickness and stripping ratio, Green River Formation, Piceance Basin, Colorado and Uinta Basin, Utah: U.S. Geological Survey Fact Sheet 2015-3005, 6 p., https://doi.org/10.3133/fs20153005.","productDescription":"6 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-060005","costCenters":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"links":[{"id":298159,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20153005.jpg"},{"id":298157,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2015/3005/"},{"id":298158,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2015/3005/pdf/fs2015-3005.pdf","text":"Report","size":"1.4 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"country":"United States","state":"Colorado, Utah","otherGeospatial":"Piceance Basin, Uinta Basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -114.08203125,\n 37.00255267215955\n ],\n [\n -114.08203125,\n 41.983994270935625\n ],\n [\n -102.041015625,\n 41.983994270935625\n ],\n [\n -102.041015625,\n 37.00255267215955\n ],\n [\n -114.08203125,\n 37.00255267215955\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54f043aee4b02419550ce866","contributors":{"authors":[{"text":"Birdwell, Justin E. 0000-0001-8263-1452 jbirdwell@usgs.gov","orcid":"https://orcid.org/0000-0001-8263-1452","contributorId":3302,"corporation":false,"usgs":true,"family":"Birdwell","given":"Justin","email":"jbirdwell@usgs.gov","middleInitial":"E.","affiliations":[{"id":569,"text":"Southwest Climate Science Center","active":true,"usgs":true},{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":255,"text":"Energy Resources Program","active":true,"usgs":true}],"preferred":true,"id":541537,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Mercier, Tracey J. 0000-0002-8232-525X tmercier@usgs.gov","orcid":"https://orcid.org/0000-0002-8232-525X","contributorId":2847,"corporation":false,"usgs":true,"family":"Mercier","given":"Tracey","email":"tmercier@usgs.gov","middleInitial":"J.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":541538,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Johnson, Ronald C. 0000-0002-6197-5165 rcjohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-6197-5165","contributorId":1550,"corporation":false,"usgs":true,"family":"Johnson","given":"Ronald","email":"rcjohnson@usgs.gov","middleInitial":"C.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":541539,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"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":541540,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70141913,"text":"fs20153014 - 2015 - Maine StreamStats: a water-resources web application","interactions":[],"lastModifiedDate":"2015-02-26T10:56:46","indexId":"fs20153014","displayToPublicDate":"2015-02-26T09:45:00","publicationYear":"2015","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":"2015-3014","title":"Maine StreamStats: a water-resources web application","docAbstract":"Maine StreamStats is a tool that any user with Internet access can use to delineate a basin on the fly and estimate a wide variety of streamflow statistics for ungaged sites on rivers and streams in Maine. Estimates are based on regression equations or are from data from similar gaged locations on the stream. Maine StreamStats is based on a national StreamStats application that can be used for streamflow estimates in many other states across the country.
\nReports referenced in this fact sheet present the regression equations used to estimate the flow statistics, describe the errors associated with the estimates, and describe the methods used to develop the equations and to measure the basin characteristics used in the equations. Limitations of the methods are also described in the reports; for example, all of the equations are appropriate only for ungaged, unregulated, rural streams in Maine.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20153014","collaboration":"Prepared in cooperation with Maine Department of Transportation","usgsCitation":"Lombard, P., 2015, Maine StreamStats: a water-resources web application: U.S. Geological Survey Fact Sheet 2015-3014, 2 p., https://doi.org/10.3133/fs20153014.","productDescription":"2 p.","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-063510","costCenters":[{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true}],"links":[{"id":298152,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20153014.jpg"},{"id":298150,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2015/3014/pdf/fs2015-3014.pdf","text":"Report","size":"739 kB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":298151,"rank":3,"type":{"id":7,"text":"Companion Files"},"url":"https://streamstats.usgs.gov/","text":"Maine StreamStats","linkHelpText":"a geographic information system-based Web application of the U.S. Geological Survey, is a tool for calculating basin characteristics and streamflow statistics for user-selected sites on streams in Maine."},{"id":298149,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2015/3014/"}],"country":"United States","state":"Maine","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -70.927734375,\n 43.068887774169625\n ],\n [\n -70.927734375,\n 47.517200697839414\n ],\n [\n -66.884765625,\n 47.517200697839414\n ],\n [\n -66.884765625,\n 43.068887774169625\n ],\n [\n -70.927734375,\n 43.068887774169625\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":11,"text":"Pembroke PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54f043aee4b02419550ce868","contributors":{"authors":[{"text":"Lombard, Pamela J. plombard@usgs.gov","contributorId":871,"corporation":false,"usgs":true,"family":"Lombard","given":"Pamela J.","email":"plombard@usgs.gov","affiliations":[{"id":371,"text":"Maine Water Science Center","active":true,"usgs":true}],"preferred":false,"id":541536,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70141967,"text":"70141967 - 2015 - The Landscape Evolution Observatory: a large-scale controllable infrastructure to study coupled Earth-surface processes","interactions":[],"lastModifiedDate":"2018-04-02T15:24:19","indexId":"70141967","displayToPublicDate":"2015-02-25T10:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1801,"text":"Geomorphology","active":true,"publicationSubtype":{"id":10}},"title":"The Landscape Evolution Observatory: a large-scale controllable infrastructure to study coupled Earth-surface processes","docAbstract":"Zero-order drainage basins, and their constituent hillslopes, are the fundamental geomorphic unit comprising much of Earth's uplands. The convergent topography of these landscapes generates spatially variable substrate and moisture content, facilitating biological diversity and influencing how the landscape filters precipitation and sequesters atmospheric carbon dioxide. In light of these significant ecosystem services, refining our understanding of how these functions are affected by landscape evolution, weather variability, and long-term climate change is imperative. In this paper we introduce the Landscape Evolution Observatory (LEO): a large-scale controllable infrastructure consisting of three replicated artificial landscapes (each 330 m2 surface area) within the climate-controlled Biosphere 2 facility in Arizona, USA. At LEO, experimental manipulation of rainfall, air temperature, relative humidity, and wind speed are possible at unprecedented scale. The Landscape Evolution Observatory was designed as a community resource to advance understanding of how topography, physical and chemical properties of soil, and biological communities coevolve, and how this coevolution affects water, carbon, and energy cycles at multiple spatial scales. With well-defined boundary conditions and an extensive network of sensors and samplers, LEO enables an iterative scientific approach that includes numerical model development and virtual experimentation, physical experimentation, data analysis, and model refinement. We plan to engage the broader scientific community through public dissemination of data from LEO, collaborative experimental design, and community-based model development.
","conferenceTitle":"46th Annual Binghamton Geomorphology Symposium","conferenceDate":"September 18-20, 2015","language":"English","publisher":"Elsevier","doi":"10.1016/j.geomorph.2015.01.020","usgsCitation":"Pangle, L.A., DeLong, S.B., Abramson, N., Adams, J., Barron-Gafford, G.A., Breshears, D.D., Brooks, P.D., Chorover, J., Dietrich, W., Dontsova, K., Durcik, M., Espeleta, J., Ferre, T., Ferriere, R., Henderson, W., Hunt, E.A., Huxman, T.E., Millar, D., Murphy, B., Niu, G., Pavao-Zuckerman, M., Pelletier, J.D., Rasmussen, C., Ruiz, J., Saleska, S., Schaap, M., Sibayan, M., Troch, P.A., Tuller, M., van Haren, J., and Zeng, X., 2015, The Landscape Evolution Observatory: a large-scale controllable infrastructure to study coupled Earth-surface processes: Geomorphology, v. 244, p. 190-203, https://doi.org/10.1016/j.geomorph.2015.01.020.","productDescription":"14 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The Natural Resources Conservation Service evaluated the effects on seasonal irrigation efficiency and deep percolation of irrigation water of various on-farm irrigation system improvements in the three salinity control units, and reported the results in a series of internal Natural Resources Conservation Service annual reports. Because of the large amount of effort and expense that went into the Natural Resources Conservation Service Monitoring and Evaluation and the importance of the data to help quantify the changes to deep percolation, the Natural Resources Conservation Service has determined that having the evaluation results made public through a characterization and analysis of the results by the U.S. Geological Survey could be of use to a wider audience of water managers and the general public.
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A comparison of the 4 models, as they were presented at the MMME Workshop in Brussels, Belgium (May 2012), is provided herein. Overall, the models were found to be similar in structure (free ion activities computed by WHAM; specific or non-specific binding of metals/cations in or on the organism; specification of metal potency factors and/or toxicity response functions to relate metal accumulation to biological response). Major differences in modeling approaches are attributed to various modeling assumptions (e.g., single versus multiple types of binding site on the organism) and specific calibration strategies that affected the selection of model parameters. The models provided a reasonable description of additive (or nearly additive) toxicity for a number of individual toxicity test results. Less-than-additive toxicity was more difficult to describe with the available models. 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2015 - Development of regression equations to revise estimates of historical streamflows for the St. Croix River at Stillwater, Minnesota (water years 1910-2011), and Prescott, Wisconsin (water years 1910-2007)","interactions":[],"lastModifiedDate":"2015-02-19T15:39:45","indexId":"sir20145239","displayToPublicDate":"2015-02-19T16:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2014-5239","title":"Development of regression equations to revise estimates of historical streamflows for the St. Croix River at Stillwater, Minnesota (water years 1910-2011), and Prescott, Wisconsin (water years 1910-2007)","docAbstract":"A natural dam of glacial-era sediments at the confluence of the St. Croix and Mississippi Rivers forms Lake St. Croix, a riverine lake that comprises the lowest 25 miles of the St. Croix River. Historically, backwater effects from the Mississippi River prevented the use of traditional streamgages for collecting continuous streamflow data needed to calculate nutrient loads at the inlet to and outlet from Lake St. Croix at Stillwater, Minnesota and Prescott, Wisconsin, respectively. The development of index-velocity streamgages has enabled the measurement of continuous streamflow in backwater conditions using continuously measured velocities at the streamgage. Index-velocity streamgages were installed at Prescott, Wisconsin, and Stillwater, Minnesota, in 2007 and 2011, respectively.
\nContinuous daily mean streamflow data from the new index-velocity streamgages, long-term upstream streamgages, and tributary streamgages were used to (1) develop regression equations that improve estimates of historical streamflow at Stillwater and Prescott, (2) evaluate the accuracies of new and previous equations used to estimate historical streamflows, and (3) compute and evaluate revised estimates of historical streamflows for Stillwater for water years 1910–2011 and for Prescott for water years 1910–2007. The abilities of previous and newly developed regression equations to accurately estimate streamflows were evaluated using Nash-Sutcliffe Efficiency (NSE) values. The NSE values at Stillwater improved from 0.90 to 0.98, and the NSE values at Prescott improved from 0.77 to 0.94.
\nThe new regression equations were used to calculate revised estimates of historical streamflows for Stillwater and Prescott starting in 1910 and ending when index-velocity streamgages were installed. Monthly, annual, 30-year, and period of record statistics were examined between previous and revised estimates of historical streamflows. The abilities of the new regression equations to estimate historical streamflows were evaluated by using percent differences to compare new estimates of historical daily streamflows to discrete streamflow measurements made at Stillwater and Prescott before the installation of index-velocity streamgages. Although less variability was observed between estimated and measured streamflows at Stillwater compared to Prescott, the percent difference data indicated that the new estimates closely approximated measured streamflows at both locations.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20145239","collaboration":"Prepared in cooperation with the St. Croix Watershed Research Station","usgsCitation":"Ziegeweid, J.R., and Magdalene, S., 2015, Development of regression equations to revise estimates of historical streamflows for the St. Croix River at Stillwater, Minnesota (water years 1910-2011), and Prescott, Wisconsin (water years 1910-2007): U.S. Geological Survey Scientific Investigations Report 2014-5239, Report: vi, 23 p.; 3 Appendices, https://doi.org/10.3133/sir20145239.","productDescription":"Report: vi, 23 p.; 3 Appendices","numberOfPages":"34","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"1909-10-01","temporalEnd":"2011-09-30","ipdsId":"IP-060060","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"links":[{"id":298059,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir20145239.jpg"},{"id":298056,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2014/5239/pdf/sir14-5239.pdf","text":"Report","size":"1.87 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":298055,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2014/5239/"},{"id":298057,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5239/downloads/Appendix2.xlsx","text":"Appendix 2","size":"1.33 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Appendix 2"},{"id":298058,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2014/5239/downloads/Appendix3.xlsx","text":"Appendix 3","size":"1.27 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Appendix 3"}],"country":"United States","state":"Minnesota, Wisconsin","city":"Prescott, Stillwater","otherGeospatial":"St. Croix River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -93.53759765625,\n 44.26093725039923\n ],\n [\n -93.53759765625,\n 45.07352060670971\n ],\n [\n -91.7138671875,\n 45.07352060670971\n ],\n [\n -91.7138671875,\n 44.26093725039923\n ],\n [\n -93.53759765625,\n 44.26093725039923\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54e70929e4b02d776a66a006","contributors":{"authors":[{"text":"Ziegeweid, Jeffrey R. 0000-0001-7797-3044 jrziege@usgs.gov","orcid":"https://orcid.org/0000-0001-7797-3044","contributorId":4166,"corporation":false,"usgs":true,"family":"Ziegeweid","given":"Jeffrey","email":"jrziege@usgs.gov","middleInitial":"R.","affiliations":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"preferred":true,"id":540948,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Magdalene, Suzanne","contributorId":138500,"corporation":false,"usgs":false,"family":"Magdalene","given":"Suzanne","email":"","affiliations":[{"id":12429,"text":"Science Museum of Minnesota","active":true,"usgs":false}],"preferred":false,"id":540949,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70139795,"text":"ds920 - 2015 - Groundwater geochemical and selected volatile organic compound data, Operable Unit 1, Naval Undersea Warfare Center, Division Keyport, Washington, June and September 2014","interactions":[],"lastModifiedDate":"2015-02-18T13:42:20","indexId":"ds920","displayToPublicDate":"2015-02-18T13:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"920","title":"Groundwater geochemical and selected volatile organic compound data, Operable Unit 1, Naval Undersea Warfare Center, Division Keyport, Washington, June and September 2014","docAbstract":"Previous investigations indicate that concentrations of chlorinated volatile organic compounds (CVOCs) are substantial in groundwater beneath the 9-acre former landfill at Operable Unit 1, Naval Undersea Warfare Center, Division Keyport, Washington. The U.S. Geological Survey has continued to monitor groundwater geochemistry to ensure that conditions remain favorable for contaminant biodegradation at the site. This report presents groundwater geochemical and selected CVOC data collected at Operable Unit 1 by the U.S. Geological Survey during June 23–25 and September 4, 2014, in support of long-term monitoring for natural attenuation. Groundwater samples were collected from 13 wells and 9 piezometers, as well as from 10 shallow groundwater passive-diffusion sampling sites in the nearby marsh. Samples from all wells and piezometers were analyzed for oxidation-reduction (redox) sensitive constituents and dissolved gases. Samples from all piezometers and four wells also were analyzed for CVOCs, as were all samples from the passive-diffusion sampling sites. In 2014, concentrations of redox-sensitive constituents measured at all wells and piezometers were consistent with those measured in previous years, with dissolved oxygen concentrations all less than 1 milligram per liter; little to no detectable nitrate; abundant dissolved manganese, iron, and methane; and commonly detected sulfide. In the upper aquifer of the northern plantation in 2014, CVOC concentrations at all piezometers were similar to those measured in previous years, and concentrations of the reductive dechlorination byproducts ethane and ethene were slightly lower or the same as concentrations measured in 2013. In the upper aquifer of the southern plantation, CVOC concentrations measured in piezometers during 2014 continued to be variable as in previous years, often high, and reductive dechlorination byproducts were detected in one of the three wells and in all but two piezometers. Beneath the marsh adjacent to the southern plantation, chloroethene concentrations measured in 2014 continued to vary spatially and temporally, and were high. Trends for total CVOC concentration continued to increase at the historically most contaminated passive‑diffusion sampler sites (S-4, S-4B, and S-5). For the intermediate aquifer in 2014, concentrations of reductive dechlorination byproducts ethane and ethene and CVOCs were consistent with those measured in previous years.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds920","collaboration":"Prepared in cooperation with Department of the Navy, Naval Facilities Engineering Command, Northwest","usgsCitation":"Huffman, R.L., 2015, Groundwater geochemical and selected volatile organic compound data, Operable Unit 1, Naval Undersea Warfare Center, Division Keyport, Washington, June and September 2014: U.S. Geological Survey Data Series 920, iv, 50 p., https://doi.org/10.3133/ds920.","productDescription":"iv, 50 p.","numberOfPages":"58","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-062663","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":298034,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ds920.jpg"},{"id":298033,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0920/pdf/ds920.pdf","text":"Report","size":"1.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"},{"id":298030,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/ds/0920/"}],"projection":"Washington State Plane, North Zone","datum":"North American Datum of 1927","country":"United States","state":"Washington","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -122.63437271118164,\n 47.689312506350575\n ],\n [\n -122.63437271118164,\n 47.706527200903395\n ],\n [\n -122.61308670043945,\n 47.706527200903395\n ],\n [\n -122.61308670043945,\n 47.689312506350575\n ],\n [\n -122.63437271118164,\n 47.689312506350575\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":12,"text":"Tacoma PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54e5b7b3e4b02d776a669ea1","contributors":{"authors":[{"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":540777,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70128289,"text":"sim3311 - 2015 - Potentiometric surface, 2013, and water-level differences, 1991-2013, of the Carrizo-Wilcox aquifer in northwest Louisiana","interactions":[],"lastModifiedDate":"2015-02-18T13:27:04","indexId":"sim3311","displayToPublicDate":"2015-02-18T13:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":333,"text":"Scientific Investigations Map","code":"SIM","onlineIssn":"2329-132X","printIssn":"2329-1311","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"3311","title":"Potentiometric surface, 2013, and water-level differences, 1991-2013, of the Carrizo-Wilcox aquifer in northwest Louisiana","docAbstract":"The Carrizo-Wilcox aquifer is the primary source of fresh groundwater for public supply as well as industrial, agricultural, and domestic uses in several parishes in northwestern Louisiana, including Bienville, Bossier, Caddo, De Soto, Natchitoches, Red River, Sabine, and Webster. In 2010, about 19 million gallons per day (Mgal/d) were withdrawn from the Carrizo-Wilcox aquifer in Louisiana. This is an increase of over 6 Mgal/d from 1990 withdrawal amounts. The largest increase in withdrawals occurred in Caddo (3.79 Mgal/d) and De Soto Parishes (2.32 Mgal/d), whereas the largest decrease in withdrawals occurred in Natchitoches Parish (1.17 Mgal/d). Groundwater withdrawals from the Carrizo-Wilcox aquifer have caused water-level declines throughout much of the aquifer in the study area. Additional knowledge about the effects of withdrawals on water levels and flow directions in the Carrizo-Wilcox aquifer are needed to assess current conditions in the aquifer. In 2012, the U.S. Geological Survey (USGS) in cooperation with the Louisiana Department of Natural Resources began a study to document current water levels and water-level changes in selected aquifers.
\nThis report presents data and maps that illustrate the potentiometric surface of the Carrizo-Wilcox aquifer during March–May 2013 and water-level differences from 1991 to 2013. The potentiometric surface map can be used for determining the direction of groundwater flow, hydraulic gradients, and effects of withdrawals on the groundwater resource. The rate of groundwater movement also can be estimated from the gradient when the hydraulic conductivity is applied. Water-level data collected for this study are stored in the USGS National Water Information System (NWIS) (http://waterdata.usgs.gov/nwis) and are on file at the USGS office in Baton Rouge, La.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sim3311","collaboration":"Prepared in cooperation with the Louisiana Department of Natural Resources","usgsCitation":"Fendick, R., and Carter, K., 2015, Potentiometric surface, 2013, and water-level differences, 1991-2013, of the Carrizo-Wilcox aquifer in northwest Louisiana: U.S. Geological Survey Scientific Investigations Map 3311, 44.0 x 34.0 inches, https://doi.org/10.3133/sim3311.","productDescription":"44.0 x 34.0 inches","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"1991-01-01","temporalEnd":"2013-12-31","ipdsId":"IP-057693","costCenters":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"links":[{"id":298032,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sim3311.jpg"},{"id":298025,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sim/3311/"},{"id":298031,"type":{"id":17,"text":"Plate"},"url":"https://pubs.usgs.gov/sim/3311/pdf/sim3311.pdf","text":"Map","size":"1.02 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Map"}],"country":"United States","state":"Louisiana","otherGeospatial":"Carrizo-Wilcox aquifer","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.04296874999999,\n 31.194007509998823\n ],\n [\n -94.04296874999999,\n 33.02248191961359\n ],\n [\n -92.7520751953125,\n 33.02248191961359\n ],\n [\n -92.7520751953125,\n 31.194007509998823\n ],\n [\n -94.04296874999999,\n 31.194007509998823\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54e5b7eee4b02d776a669ea7","contributors":{"authors":[{"text":"Fendick, Robert B. Jr. rfendick@usgs.gov","contributorId":1313,"corporation":false,"usgs":true,"family":"Fendick","given":"Robert B.","suffix":"Jr.","email":"rfendick@usgs.gov","affiliations":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":false,"id":540766,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Carter, Kayla kcarter@usgs.gov","contributorId":5681,"corporation":false,"usgs":true,"family":"Carter","given":"Kayla","email":"kcarter@usgs.gov","affiliations":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":false,"id":540767,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70135821,"text":"fs20143118 - 2015 - Water resources of St. Charles Parish, Louisiana","interactions":[],"lastModifiedDate":"2015-02-18T12:58:08","indexId":"fs20143118","displayToPublicDate":"2015-02-18T12:45:00","publicationYear":"2015","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":"2014-3118","title":"Water resources of St. Charles Parish, Louisiana","docAbstract":"Information concerning the availability, use, and quality of water in St. Charles Parish, Louisiana, is critical for proper water-supply management. The purpose of this fact sheet is to present information that can be used by water managers, parish residents, and others for stewardship of this vital resource. Information on the availability, past and current use, use trends, and water quality from groundwater and surface-water sources in the parish is presented. Previously published reports and data stored in the U.S. Geological Survey’s National Water Information System (http://waterdata.usgs.gov/nwis) are the primary sources of the information presented here.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20143118","collaboration":"Prepared in cooperation with the Louisiana Department of Transportation and Development","usgsCitation":"White, V.E., and Prakken, L., 2015, Water resources of St. Charles Parish, Louisiana: U.S. Geological Survey Fact Sheet 2014-3118, 6 p., https://doi.org/10.3133/fs20143118.","productDescription":"6 p.","numberOfPages":"6","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-059438","costCenters":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"links":[{"id":298028,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs20143118.jpg"},{"id":298026,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2014/3118/"},{"id":298027,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2014/3118/pdf/fs2014-3118.pdf","text":"Report","size":"8.22 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"country":"United States","state":"Louisiana","county":"St. Charles Parish","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -90.58914184570311,\n 29.679701222948996\n ],\n [\n -90.58914184570311,\n 30.191431221535417\n ],\n [\n -90.14762878417969,\n 30.191431221535417\n ],\n [\n -90.14762878417969,\n 29.679701222948996\n ],\n [\n -90.58914184570311,\n 29.679701222948996\n ]\n ]\n ]\n }\n }\n ]\n}","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"54e5b7f1e4b02d776a669eab","contributors":{"authors":[{"text":"White, Vincent E. 0000-0002-1660-0102 vwhite@usgs.gov","orcid":"https://orcid.org/0000-0002-1660-0102","contributorId":5388,"corporation":false,"usgs":true,"family":"White","given":"Vincent","email":"vwhite@usgs.gov","middleInitial":"E.","affiliations":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true},{"id":24708,"text":"Lower Mississippi-Gulf Water Science Center","active":true,"usgs":true}],"preferred":true,"id":540768,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Prakken, Lawrence B. lprakken@usgs.gov","contributorId":139067,"corporation":false,"usgs":true,"family":"Prakken","given":"Lawrence B.","email":"lprakken@usgs.gov","affiliations":[{"id":369,"text":"Louisiana Water Science Center","active":true,"usgs":true}],"preferred":false,"id":540769,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70137314,"text":"sir20155003 - 2015 - Water-quality characteristics and trends for selected wells possibly influenced by wastewater disposal at the Idaho National Laboratory, Idaho, 1981-2012","interactions":[],"lastModifiedDate":"2015-02-20T13:52:28","indexId":"sir20155003","displayToPublicDate":"2015-02-18T09:45:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2015-5003","title":"Water-quality characteristics and trends for selected wells possibly influenced by wastewater disposal at the Idaho National Laboratory, Idaho, 1981-2012","docAbstract":"The U.S. Geological Survey, in cooperation with the U.S. Department of Energy, analyzed water-quality data collected from 64 aquifer wells and 35 perched groundwater wells at the Idaho National Laboratory (INL) from 1981 through 2012. The wells selected for the study were wells that possibly were affected by wastewater disposal at the INL. The data analyzed included tritium, strontium-90, major cations, anions, nutrients, trace elements, total organic carbon, and volatile organic compounds. The analyses were performed to examine water-quality trends that might influence future management decisions about the number of wells to sample at the INL and the type of constituents to monitor.
\nThe data were processed using custom computer scripts developed in the R programming language. Summary statistics were calculated for the datasets. Water-quality trends were determined using a parametric survival regression model to fit the observed data, including left-censored, interval-censored, and uncensored data. The null hypothesis of the trend test was that no relation existed between time and concentration; the alternate hypothesis was that time and concentration were related through the regression equation. A significance level of 0.05 was selected to determine if the trend was statistically significant.
\nTrend test results for tritium and strontium-90 concentrations in aquifer wells indicated that nearly all wells had decreasing or no trends. Similarly, trends in perched groundwater wells were mostly decreasing or no trends; trends were increasing in two perched groundwater wells near the Advanced Test Reactor Complex. Decreasing trends generally are attributed to lack of recent wastewater disposal and radioactive decay.
\nTrend test results for chloride, sodium, sulfate, nitrite plus nitrate (as nitrogen), chromium, trace elements, and total organic carbon concentrations in aquifer wells indicated that most wells had either decreasing or no trends. The decreasing trends in these constituents are attributed to decrease in disposal of these constituents, as well as discontinued use of the old percolation ponds south of the Idaho Nuclear Technology and Engineering Center (INTEC) and redirection of wastewater to the new percolation ponds 2 miles southwest of the INTEC in 2002.
\nChloride (along with sodium, sulfate, and some nitrate) concentrations in wells south of the INTEC may be influenced by episodic recharge from the Big Lost River. These constituent concentrations decrease during wetter periods when there is probably more recharge from the Big Lost River and increase during dry periods, when there is less recharge.
\nSome wells downgradient of the Central Facilities Area and near the southern boundary of the INL showed increasing trends in sodium concentration, whereas there was no trend in chloride. The increasing trend for sodium could be due to the long term influence of wastewater disposal from upgradient facilities and the lack of trend for chloride could be because chloride is more mobile than sodium and more dispersed in the aquifer system.
\nVolatile organic compound concentration trends were analyzed for nine aquifer wells. Trend test results indicated an increasing trend for carbon tetrachloride for the Radioactive Waste Management Complex Production Well for the period 1987–2012; however, trend analyses of data collected since 2005 show no statistically significant trend indicating that engineering practices designed to reduce movement of volatile organic compounds to the aquifer may be having a positive effect on the aquifer.
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2015 - Basement domain map of the conterminous United States and Alaska","interactions":[],"lastModifiedDate":"2016-06-29T13:36:05","indexId":"ds898","displayToPublicDate":"2015-02-18T09:15:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"898","title":"Basement domain map of the conterminous United States and Alaska","docAbstract":"The basement-domain map is a compilation of basement domains in the conterminous United States and Alaska designed to be used at 1:5,000,000-scale, particularly as a base layer for national-scale mineral resource assessments. Seventy-seven basement domains are represented as eighty-three polygons on the map. The domains are based on interpretations of basement composition, origin, and architecture and developed from a variety of sources. Analysis of previously published basement, lithotectonic, and terrane maps as well as models of planetary development were used to formulate the concept of basement and the methodology of defining domains that spanned the ages of Archean to present but formed through different processes. The preliminary compilations for the study areas utilized these maps, national-scale gravity and aeromagnetic data, published and limited new age and isotopic data, limited new field investigations, and conventional geologic maps. Citation of the relevant source data for compilations and the source and types of original interpretation, as derived from different types of data, are provided in supporting descriptive text and tables.
\nThe tectonic settings for crustal types represented in the basement domains are subdivided into constituent geologic environments and the types of primary metals endowments and deposits in them are documented. The compositions, architecture, and original metals endowments are potentially important to assessments of primary mineral deposits and to the residence and recycling of metals in the crust of the United States portion of the North American continent. The databases can be configured to demonstrate the construction of the United States through time, to identify specific types of crust, or to identify domains potentially containing metal endowments of specific genetic types or endowed with specific metals. The databases can also be configured to illustrate other purposes chosen by users.
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The Susquehanna River is the largest tributary to Chesapeake Bay and transports about one-half of the total freshwater input and substantial amounts of sediment and nutrients to the bay. The transported loads are affected by deposition in reservoirs (Lake Clarke, Lake Aldred, and Conowingo Reservoir) behind three hydropower dams. The geometry and texture of the deposited sediments in each reservoir upstream from the three dams has been a subject of research in recent decades. Particle size deposition and sediment scouring processes are part of the reservoir dynamics. A Total Maximum Daily Load (TMDL) for nitrogen, phosphorus, and sediment was established for Chesapeake Bay to attain water-quality standards. Six states and the District of Columbia agreed to reduce loads to the bay and to meet load allocation goals for the TMDL. The USGS has been estimating annual sediment loads at the Susquehanna River at Marietta, Pennsylvania (above Lake Clarke), and Susquehanna River at Conowingo, Maryland (below Conowingo Reservoir), since the mid-1980s to predict the mass balance of sediment transport through the reservoir system. Using streamflow and sediment data from the Susquehanna River at Harrisburg, Pennsylvania (upstream from the reservoirs), from 1900 to 1981, sediment loads were greatest in the early to mid-1900s when land disturbance activities from coal production and agriculture were at their peak. Sediment loads declined in the 1950s with the introduction of agricultural soil conservation practices. Loads were dominated by climatic factors in the 1960s (drought) and 1970s (very wet) and have been declining since the 1980s through 2012. The USGS developed a regression equation to predict the sediment scour load for daily mean streamflows greater than 300,000 cubic feet per second for the Lower Susquehanna River reservoirs. A compilation of data from various sources produced a range in total sediment transported through the reservoir system and allowed for apportioning to source (watershed or scour) for various streamflows. In 2011, Conowingo Reservoir was estimated to be about 92 percent of sediment storage capacity. Since construction of Conowingo Dam in 1929 through 2012, approximately 470 million tons of sediment was transported down the Susquehanna River into the reservoir system, approximately 290 million tons were trapped, and approximately 180 million tons were transported to Chesapeake Bay. Spatial and estimated total sand deposition in Conowingo Reservoir based on historical sediment cores indicated continued migration of sand downgradient toward the dam and the winnowing of silts and clays near the dam due to scour.
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Data collection formed part of the NCBN Vital Signs Monitoring Program implemented to detect threats of estuarine nutrient enrichment. Data included here were collected from six parks at predetermined intervals: Cape Cod National Seashore, Massachusetts (2007, 2008, 2009, 2010, 2011); Fire Island National Seashore, New York (2009, 2011); Gateway National Recreation Area, New York and New Jersey (2010); Assateague Island National Seashore, Maryland and Virginia (2006, 2008, 2010); George Washington Birthplace National Monument, Virginia (2009, 2011); and Colonial National Historic Park, Virginia (2008, 2010). Monitoring variables consisted of dissolved-oxygen concentration, chlorophyll a concentration, attenuation of downwelling photosynthetically available radiation (PAR), turbidity, water temperature, and salinity. All monitoring was conducted during four-week summer index periods. The monitoring design incorporated data collection at multiple, complementary spatial and temporal scales. Within each park, a spatial survey was conducted once during the index period following a probability design using a grid of tessellated hexagons as the basis for sample site selection. The spatial survey was supplemented with weekly measurements at a subset of sites and continuous monitoring at a single reference site. Within parks, data were reported as area-weighted water-quality conditions during each index period, the location and extent of estuarine area within condition categories, and spatial and temporal trends. In addition, we used a repeated measures analysis of variance to determine the extent to which variability in three water quality metrics (chlorophyll a in surface water, dissolved oxygen in bottom water, and water clarity expressed by PAR attenuation) was explained by year to year changes in each park's respective estuary.
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hneckles@usgs.gov","orcid":"https://orcid.org/0000-0002-5662-2314","contributorId":3821,"corporation":false,"usgs":true,"family":"Neckles","given":"Hilary","email":"hneckles@usgs.gov","middleInitial":"A.","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":539496,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pooler, Penelope S.","contributorId":51018,"corporation":false,"usgs":true,"family":"Pooler","given":"Penelope","email":"","middleInitial":"S.","affiliations":[],"preferred":false,"id":539497,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70138661,"text":"ofr20131070 - 2015 - Environmental assessment of water, sediment, and biota collected from the Bear Creek watershed, Colusa County, California","interactions":[],"lastModifiedDate":"2015-02-18T09:08:52","indexId":"ofr20131070","displayToPublicDate":"2015-02-17T17:30:00","publicationYear":"2015","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2013-1070","title":"Environmental assessment of water, sediment, and biota collected from the Bear Creek watershed, Colusa County, California","docAbstract":"The Cache Creek watershed lies within California's North Coast Range, an area with abundant geologic sources of mercury (Hg) and a long history of Hg contamination (Rytuba, 2000). Bear Creek, Cache Creek, and the North Fork of Cache Creek are the major streams of the Cache Creek watershed, encompassing 2978 km2. The Cache Creek watershed contains soils naturally enriched in Hg as well as natural springs (both hot and cold) with varying levels of aqueous Hg (Domagalski and others, 2004, Suchanek and others, 2004, Holloway and others 2009). All three tributaries are known to be significant sources of anthropogenically derived Hg from historic mines, both Hg and gold (Au), and associated ore storage/processing sites and facilities (Slotton and others, 1995, 2004; CVRWQCB, 2003; Schwarzbach and others, 2001; Gassel and others, 2005; Suchanek and others., 2004, 2008a, 2009). Historically, two of the primary sources of mercury contamination in the upper part of Bear Creek have been the Rathburn and Petray Hg Mines.
The Rathburn Hg mine was discovered and initially mined in the early 1890s. The Rathburn and the more recently developed Petray open pit mines are localized along fault zones in serpentinite that has been altered and cut by quartz and chalcedony veins. Cold saline-carbonate springs are located perepheral to the Hg deposits and effluent from the springs locally has high concentrations of Hg (Slowey and Rytuba, 2008). Several ephemeral tributaries to Bear Creek drain the mine area which is located on federal land managed by the U.S. Bureau of Land Management (USBLM). The USBLM requested that the U.S. Geological Survey (USGS) measure and characterize Hg and other geochemical constituents in sediment, water, and biota to establish baseline information prior to remediation of the Rathburn and Petray mines. Samples sites were established in Bear Creek upstream and downstream from the mine area. This report is made in response to the USBLM request, the lead agency mandated to conduct a Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA) - Removal Site Investigation (RSI). The RSI applies to the possible removal of Hg-contaminated mine waste from Bear Creek.
This report summarizes data obtained from field sampling of water, sediment, and biota in Bear Creek, above input from the mine area and downstream from the Rathburn-Petray mine area to the confluence with Cache Creek. Our results permit a preliminary assessment of the chemical constituents that could elevate levels of monomethyl Hg (MMeHg) in Bear Creek and its uptake by biota and provide baseline information for comparison to conditions after mine remediation is completed.