The U.S. Geological Survey—in cooperation with the U.S. Army Corps of Engineers, Fort Worth District; City of Corpus Christi; Guadalupe–Blanco River Authority; San Antonio River Authority; and San Antonio Water System— configured, calibrated, and tested a watershed model for a study area consisting of about 7,726 square miles of the middle Nueces River watershed in south Texas. The purpose of the model is to contribute to the understanding of watershed processes and hydrologic conditions in the middle Nueces River watershed. The model simulates streamflow, evapotranspiration, and groundwater recharge by using a numerical representation of physical characteristics of the landscape and meteorological and streamflow data.
\nModel simulations of streamflow, evapotranspiration, and groundwater recharge were performed for various periods of record depending upon available gaged data for input and comparison, starting as early as 1961. Because of the large size of the study area, the middle Nueces River watershed was divided into eight subwatersheds, and separate Hydrological Simulation Program—FORTRAN models were developed for each subwatershed. Simulation of the overall study area involved running simulations in downstream order. Output from the model was summarized by subwatershed, point locations, stream and reservoir reaches, and the Carrizo– Wilcox aquifer outcrop area. Four long-term U.S. Geological Survey streamflow-gaging stations were used for streamflow model calibration and testing with data from 1990 to 2008. Monthly evaporation estimates from 2001 to 2008 and waterlevel data from 1961 to 2008 at Lake Corpus Christi also were used for model calibration. Additionally, evapotranspiration data for 2006–8 from a U.S. Geological Survey meteorological station in Medina County were used for calibration.
\nStreamflow calibrations were considered poor to very good. The 2000–8 calibration results were characterized as good to very good for total flow volumes and for the volume of the highest 10 percent of daily flows. Calibration results for streamflow volumes of the lowest 50 percent of daily flows were considered poor. The daily streamflow calibration at U.S. Geological Survey streamflow-gaging station 08210000 Nueces River near Three Rivers, Tex., had the lowest (best) root mean square error, and U.S. Geological Survey streamflow-gaging station 08194500 Nueces River near Tilden, Tex., had the highest root mean square error expressed as a percentage of the mean flow rate. The mean daily reservoir volume during 1961–2008 was 182,000 acre-feet. Simulated mean daily reservoir volume was within 9 percent of this computed volume.
\nSelected results of the model include streamflow yields for the subwatersheds and water-balance information for the Carrizo–Wilcox aquifer outcrop area. For the entire model domain, the area-weighted mean streamflow yield from 1961 to 2008 was 1.12 inches/year. The mean annual rainfall on the outcrop area during the 1961–2008 simulation period was 21.7 inches. Of this rainfall, an annual mean of 20.1 inches (about 93 percent) was simulated as evapotranspiration, 1.2 inches (about 6 percent) was simulated as groundwater recharge, and 0.5 inches (about 2 percent) was simulated as surface runoff.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125136","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers, Fort Worth District; City of Corpus Christi; Guadalupe-Blanco River Authority; San Antonio River Authority; and San Antonio Water System","usgsCitation":"Dietsch, B.J., and Wehmeyer, L.L., 2012, Simulation of streamflow, evapotranspiration, and groundwater recharge in the middle Nueces River watershed, south Texas, 1961-2008: U.S. Geological Survey Scientific Investigations Report 2012-5136, vi, 37 p., https://doi.org/10.3133/sir20125136.","productDescription":"vi, 37 p.","numberOfPages":"37","onlineOnly":"N","additionalOnlineFiles":"N","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":258887,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5136.JPG"},{"id":258871,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5136/pdf/sir2012-5136.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":258870,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5136/","linkFileType":{"id":5,"text":"html"}}],"scale":"24000","projection":"Universal Transverse Mercator","datum":"North American Datum","country":"United States","state":"Texas","otherGeospatial":"Nueces River","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -100.5,27.5 ], [ -100.5,30.000833333333333 ], [ -97.5,30.000833333333333 ], [ -97.5,27.5 ], [ -100.5,27.5 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505b9096e4b08c986b3195b4","contributors":{"authors":[{"text":"Dietsch, Benjamin J. 0000-0003-1090-409X bdietsch@usgs.gov","orcid":"https://orcid.org/0000-0003-1090-409X","contributorId":1346,"corporation":false,"usgs":true,"family":"Dietsch","given":"Benjamin","email":"bdietsch@usgs.gov","middleInitial":"J.","affiliations":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true},{"id":84311,"text":"Central Plains Water Science Center","active":true,"usgs":true}],"preferred":true,"id":465396,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wehmeyer, Loren L.","contributorId":90412,"corporation":false,"usgs":true,"family":"Wehmeyer","given":"Loren","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":465397,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70039008,"text":"70039008 - 2012 - Likelihood analysis of species occurrence probability from presence-only data for modelling species distributions","interactions":[],"lastModifiedDate":"2012-07-13T01:01:54","indexId":"70039008","displayToPublicDate":"2012-07-12T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2717,"text":"Methods in Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Likelihood analysis of species occurrence probability from presence-only data for modelling species distributions","docAbstract":"1. Understanding the factors affecting species occurrence is a pre-eminent focus of applied ecological research. However, direct information about species occurrence is lacking for many species. Instead, researchers sometimes have to rely on so-called presence-only data (i.e. when no direct information about absences is available), which often results from opportunistic, unstructured sampling. MAXENT is a widely used software program designed to model and map species distribution using presence-only data. 2. We provide a critical review of MAXENT as applied to species distribution modelling and discuss how it can lead to inferential errors. A chief concern is that MAXENT produces a number of poorly defined indices that are not directly related to the actual parameter of interest – the probability of occurrence (ψ). This focus on an index was motivated by the belief that it is not possible to estimate ψ from presence-only data; however, we demonstrate that ψ is identifiable using conventional likelihood methods under the assumptions of random sampling and constant probability of species detection. 3. The model is implemented in a convenient r package which we use to apply the model to simulated data and data from the North American Breeding Bird Survey. We demonstrate that MAXENT produces extreme under-predictions when compared to estimates produced by logistic regression which uses the full (presence/absence) data set. We note that MAXENT predictions are extremely sensitive to specification of the background prevalence, which is not objectively estimated using the MAXENT method. 4. As with MAXENT, formal model-based inference requires a random sample of presence locations. Many presence-only data sets, such as those based on museum records and herbarium collections, may not satisfy this assumption. However, when sampling is random, we believe that inference should be based on formal methods that facilitate inference about interpretable ecological quantities instead of vaguely defined indices.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Methods in Ecology and Evolution","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","publisherLocation":"Hoboken, NJ","doi":"10.1111/j.2041-210X.2011.00182.x","usgsCitation":"Royle, J., Chandler, R.B., Yackulic, C., and Nichols, J., 2012, Likelihood analysis of species occurrence probability from presence-only data for modelling species distributions: Methods in Ecology and Evolution, v. 3, no. 3, p. 545-554, https://doi.org/10.1111/j.2041-210X.2011.00182.x.","productDescription":"10 p.","startPage":"545","endPage":"554","numberOfPages":"10","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":474417,"rank":10000,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/j.2041-210x.2011.00182.x","text":"Publisher Index Page"},{"id":258435,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":258431,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1111/j.2041-210X.2011.00182.x","linkFileType":{"id":5,"text":"html"}}],"volume":"3","issue":"3","noUsgsAuthors":false,"publicationDate":"2012-01-31","publicationStatus":"PW","scienceBaseUri":"505a477fe4b0c8380cd67895","contributors":{"authors":[{"text":"Royle, J. Andrew 0000-0003-3135-2167","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":80808,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":465405,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Chandler, Richard B. rchandler@usgs.gov","contributorId":63524,"corporation":false,"usgs":true,"family":"Chandler","given":"Richard","email":"rchandler@usgs.gov","middleInitial":"B.","affiliations":[],"preferred":false,"id":465404,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Yackulic, Charles","contributorId":21831,"corporation":false,"usgs":true,"family":"Yackulic","given":"Charles","affiliations":[],"preferred":false,"id":465403,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Nichols, James D. 0000-0002-7631-2890 jnichols@usgs.gov","orcid":"https://orcid.org/0000-0002-7631-2890","contributorId":405,"corporation":false,"usgs":true,"family":"Nichols","given":"James D.","email":"jnichols@usgs.gov","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":false,"id":465402,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70045452,"text":"70045452 - 2012 - Concentrations and annual fluxes of sediment-associated chemical constituents from conterminous US coastal rivers using bed sediment data","interactions":[],"lastModifiedDate":"2013-05-09T15:44:32","indexId":"70045452","displayToPublicDate":"2012-07-12T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1924,"text":"Hydrological Processes","active":true,"publicationSubtype":{"id":10}},"title":"Concentrations and annual fluxes of sediment-associated chemical constituents from conterminous US coastal rivers using bed sediment data","docAbstract":"Coastal rivers represent a significant pathway for the delivery of natural and anthropogenic sediment-associated chemical constituents to the Atlantic, Pacific and Gulf of Mexico coasts of the conterminous USA. This study entails an accounting segment using published average annual suspended sediment fluxes with published sediment-associated chemical constituent concentrations for (1) baseline, (2) land-use distributions, (3) population density, and (4) worldwide means to estimate concentrations/annual fluxes for trace/major elements and total phosphorus, total organic and inorganic carbon, total nitrogen, and sulphur, for 131 coastal river basins. In addition, it entails a sampling and subsequent chemical analysis segment that provides a level of ‘ground truth’ for the calculated values, as well as generating baselines for sediment-associated concentrations/fluxes against which future changes can be evaluated. Currently, between 260 and 270 Mt of suspended sediment are discharged annually from the conterminous USA; about 69% is discharged from Gulf rivers (n = 36), about 24% from Pacific rivers (n = 42), and about 7% from Atlantic rivers (n = 54). Elevated sediment-associated chemical concentrations relative to baseline levels occur in the reverse order of sediment discharges:Atlantic rivers (49%)>Pacific rivers (40%)>Gulf rivers (23%). Elevated trace element concentrations (e.g. Cu, Hg, Pb, Zn) frequently occur in association with present/former industrial areas and/or urban centres, particularly along the northeast Atlantic coast. Elevated carbon and nutrient concentrations occur along both the Atlantic and Gulf coasts but are dominated by rivers in the urban northeast and by southeastern and Gulf coast (Florida) ‘blackwater’ streams. Elevated Ca, Mg, K, and Na distributions tend to reflect local petrology, whereas elevated Ti, S, Fe, and Al concentrations are ubiquitous, possibly because they have substantial natural as well as anthropogenic sources. Almost all the elevated sediment-associated chemical concentrations found in conterminous US coastal rivers are lower than worldwide averages.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Hydrological Processes","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1002/hyp.8437","usgsCitation":"Horowitz, A.J., Stephens, V.C., Elrick, K.A., and Smith, J.J., 2012, Concentrations and annual fluxes of sediment-associated chemical constituents from conterminous US coastal rivers using bed sediment data: Hydrological Processes, v. 26, p. 1090-1114, https://doi.org/10.1002/hyp.8437.","startPage":"1090","endPage":"1114","numberOfPages":"25","ipdsId":"IP-033553","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true}],"links":[{"id":272162,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":272161,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1002/hyp.8437"}],"country":"United States","volume":"26","noUsgsAuthors":false,"publicationDate":"2012-02-08","publicationStatus":"PW","scienceBaseUri":"518cc560e4b05ebc8f7cc100","contributors":{"authors":[{"text":"Horowitz, Arthur J. 0000-0002-3296-730X horowitz@usgs.gov","orcid":"https://orcid.org/0000-0002-3296-730X","contributorId":1400,"corporation":false,"usgs":true,"family":"Horowitz","given":"Arthur","email":"horowitz@usgs.gov","middleInitial":"J.","affiliations":[{"id":13634,"text":"South Atlantic Water Science Center","active":true,"usgs":true},{"id":316,"text":"Georgia Water Science Center","active":true,"usgs":true}],"preferred":true,"id":477515,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stephens, Verlin C.","contributorId":34479,"corporation":false,"usgs":true,"family":"Stephens","given":"Verlin","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":477516,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Elrick, Kent A.","contributorId":78415,"corporation":false,"usgs":true,"family":"Elrick","given":"Kent","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":477518,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Smith, James J.","contributorId":74086,"corporation":false,"usgs":true,"family":"Smith","given":"James","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":477517,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70039005,"text":"70039005 - 2012 - Assessment of bias in US waterfowl harvest estimates","interactions":[],"lastModifiedDate":"2012-07-13T01:01:54","indexId":"70039005","displayToPublicDate":"2012-07-12T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3777,"text":"Wildlife Research","active":true,"publicationSubtype":{"id":10}},"title":"Assessment of bias in US waterfowl harvest estimates","docAbstract":"Context. North American waterfowl managers have long suspected that waterfowl harvest estimates derived from national harvest surveys in the USA are biased high. Survey bias can be evaluated by comparing survey results with like estimates from independent sources. Aims. We used band-recovery data to assess the magnitude of apparent bias in duck and goose harvest estimates, using mallards (Anas platyrhynchos) and Canada geese (Branta canadensis) as representatives of ducks and geese, respectively. Methods. We compared the number of reported mallard and Canada goose band recoveries, adjusted for band reporting rates, with the estimated harvests of banded mallards and Canada geese from the national harvest surveys. Weused the results of those comparisons to develop correction factors that can be applied to annual duck and goose harvest estimates of the national harvest survey. Key results. National harvest survey estimates of banded mallards harvested annually averaged 1.37 times greater than those calculated from band-recovery data, whereas Canada goose harvest estimates averaged 1.50 or 1.63 times greater than comparable band-recovery estimates, depending on the harvest survey methodology used. Conclusions. Duck harvest estimates produced by the national harvest survey from 1971 to 2010 should be reduced by a factor of 0.73 (95% CI = 0.71–0.75) to correct for apparent bias. Survey-specific correction factors of 0.67 (95% CI = 0.65–0.69) and 0.61 (95% CI = 0.59–0.64) should be applied to the goose harvest estimates for 1971–2001 (duck stamp-based survey) and 1999–2010 (HIP-based survey), respectively. Implications. Although this apparent bias likely has not influenced waterfowl harvest management policy in the USA, it does have negative impacts on some applications of harvest estimates, such as indirect estimation of population size. For those types of analyses, we recommend applying the appropriate correction factor to harvest estimates.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Wildlife Research","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"CSIRO Publishing","publisherLocation":"Collingwood, Australia","doi":"10.1071/WR11105","usgsCitation":"Padding, P.I., and Royle, J., 2012, Assessment of bias in US waterfowl harvest estimates: Wildlife Research, v. 39, no. 4, p. 336-342, https://doi.org/10.1071/WR11105.","productDescription":"7 p.","startPage":"336","endPage":"342","numberOfPages":"7","costCenters":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":258432,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":258428,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1071/WR11105","linkFileType":{"id":5,"text":"html"}}],"country":"United States","volume":"39","issue":"4","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059ee21e4b0c8380cd49bae","contributors":{"authors":[{"text":"Padding, Paul I.","contributorId":38411,"corporation":false,"usgs":true,"family":"Padding","given":"Paul","email":"","middleInitial":"I.","affiliations":[],"preferred":false,"id":465398,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Royle, J. Andrew 0000-0003-3135-2167","orcid":"https://orcid.org/0000-0003-3135-2167","contributorId":80808,"corporation":false,"usgs":true,"family":"Royle","given":"J. Andrew","affiliations":[{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"preferred":true,"id":465399,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70189053,"text":"70189053 - 2012 - Imaging with cross-hole seismoelectric tomography","interactions":[],"lastModifiedDate":"2017-06-30T09:40:56","indexId":"70189053","displayToPublicDate":"2012-07-12T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1803,"text":"Geophysical Journal International","active":true,"publicationSubtype":{"id":10}},"title":"Imaging with cross-hole seismoelectric tomography","docAbstract":"We propose a cross-hole imaging approach based on seismoelectric conversions (SC) associated with the transmission of seismic waves from seismic sources located in a borehole to receivers (electrodes) located in a second borehole. The seismoelectric (seismic-to-electric) problem is solved using Biot theory coupled with a generalized Ohm's law with an electrokinetic streaming current contribution. The components of the displacement of the solid phase, the fluid pressure, and the electrical potential are solved using a finite element approach with Perfect Match Layer (PML) boundary conditions for the seismic waves and boundary conditions mimicking an infinite material for the electrostatic problem. We develop an inversion algorithm using the electrical disturbances recorded in the second borehole to localize the position of the heterogeneities responsible for the SC. Because of the ill-posed nature of the inverse problem (inherent to all potential-field problems), regularization is used to constrain the solution at each time in the SC-time window comprised between the time of the seismic shot and the time of the first arrival of the seismic waves in the second borehole. All the inverted volumetric current source densities are aggregated together to produce an image of the position of the heterogeneities between the two boreholes. Two simple synthetic case studies are presented to test this concept. The first case study corresponds to a vertical discontinuity between two homogeneous sub-domains. The second case study corresponds to a poroelastic inclusion (partially saturated by oil) embedded into an homogenous poroelastic formation. In both cases, the position of the heterogeneity is recovered using only the electrical disturbances associated with the SC. That said, a joint inversion of the seismic and seismoelectric data could improve these results.
","language":"English","publisher":"Royal Astronomical Society","doi":"10.1111/j.1365-246X.2011.05325.x","usgsCitation":"Araji, A., Revil, A., Jardani, A., Minsley, B.J., and Karaoulis, M., 2012, Imaging with cross-hole seismoelectric tomography: Geophysical Journal International, v. 188, no. 3, p. 1285-1302, https://doi.org/10.1111/j.1365-246X.2011.05325.x.","productDescription":"18 p.","startPage":"1285","endPage":"1302","ipdsId":"IP-026821","costCenters":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":474418,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1111/j.1365-246x.2011.05325.x","text":"Publisher Index Page"},{"id":343211,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"188","issue":"3","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationDate":"2012-01-25","publicationStatus":"PW","scienceBaseUri":"59576339e4b0d1f9f051b553","contributors":{"authors":[{"text":"Araji, A.H.","contributorId":37988,"corporation":false,"usgs":true,"family":"Araji","given":"A.H.","email":"","affiliations":[],"preferred":false,"id":702658,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Revil, A.","contributorId":49627,"corporation":false,"usgs":true,"family":"Revil","given":"A.","affiliations":[],"preferred":false,"id":702657,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Jardani, A.","contributorId":74599,"corporation":false,"usgs":true,"family":"Jardani","given":"A.","email":"","affiliations":[],"preferred":false,"id":703000,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Minsley, Burke J. 0000-0003-1689-1306 bminsley@usgs.gov","orcid":"https://orcid.org/0000-0003-1689-1306","contributorId":697,"corporation":false,"usgs":true,"family":"Minsley","given":"Burke","email":"bminsley@usgs.gov","middleInitial":"J.","affiliations":[{"id":211,"text":"Crustal Geophysics and Geochemistry Science Center","active":true,"usgs":true}],"preferred":true,"id":702656,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Karaoulis, M.","contributorId":77762,"corporation":false,"usgs":true,"family":"Karaoulis","given":"M.","email":"","affiliations":[],"preferred":false,"id":702659,"contributorType":{"id":1,"text":"Authors"},"rank":13}]}} ,{"id":70190225,"text":"70190225 - 2012 - An algal model for predicting attainment of tiered biological criteria of Maine's streams and rivers","interactions":[],"lastModifiedDate":"2017-08-20T09:49:53","indexId":"70190225","displayToPublicDate":"2012-07-11T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1699,"text":"Freshwater Science","active":true,"publicationSubtype":{"id":10}},"title":"An algal model for predicting attainment of tiered biological criteria of Maine's streams and rivers","docAbstract":"State water-quality professionals developing new biological assessment methods often have difficulty relating assessment results to narrative criteria in water-quality standards. An alternative to selecting index thresholds arbitrarily is to include the Biological Condition Gradient (BCG) in the development of the assessment method. The BCG describes tiers of biological community condition to help identify and communicate the position of a water body along a gradient of water quality ranging from natural to degraded. Although originally developed for fish and macroinvertebrate communities of streams and rivers, the BCG is easily adapted to other habitats and taxonomic groups. We developed a discriminant analysis model with stream algal data to predict attainment of tiered aquatic-life uses in Maine's water-quality standards. We modified the BCG framework for Maine stream algae, related the BCG tiers to Maine's tiered aquatic-life uses, and identified appropriate algal metrics for describing BCG tiers. Using a modified Delphi method, 5 aquatic biologists independently evaluated algal community metrics for 230 samples from streams and rivers across the state and assigned a BCG tier (1–6) and Maine water quality class (AA/A, B, C, nonattainment of any class) to each sample. We used minimally disturbed reference sites to approximate natural conditions (Tier 1). Biologist class assignments were unanimous for 53% of samples, and 42% of samples differed by 1 class. The biologists debated and developed consensus class assignments. A linear discriminant model built to replicate a priori class assignments correctly classified 95% of 150 samples in the model training set and 91% of 80 samples in the model validation set. Locally derived metrics based on BCG taxon tolerance groupings (e.g., sensitive, intermediate, tolerant) were more effective than were metrics developed in other regions. Adding the algal discriminant model to Maine's existing macroinvertebrate discriminant model will broaden detection of biological impairment and further diagnose sources of impairment. The algal discriminant model is specific to Maine, but our approach of explicitly tying an assessment tool to tiered aquatic-life goals is widely transferrable to other regions, taxonomic groups, and waterbody types.
","language":"English","publisher":"Society for Freshwater Science","doi":"10.1899/11-061.1","usgsCitation":"Danielson, T.J., Loftin, C., Tsomides, L., DiFranco, J.L., Connors, B., Courtemanch, D.L., Drummond, F., and Davies, S., 2012, An algal model for predicting attainment of tiered biological criteria of Maine's streams and rivers: Freshwater Science, v. 31, no. 2, p. 318-340, https://doi.org/10.1899/11-061.1.","productDescription":"23 p.","startPage":"318","endPage":"340","ipdsId":"IP-029126","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"links":[{"id":344973,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"31","issue":"2","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"599a9fb7e4b0b589267d58bd","contributors":{"authors":[{"text":"Danielson, Thomas J.","contributorId":195761,"corporation":false,"usgs":false,"family":"Danielson","given":"Thomas","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":708075,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Loftin, Cyndy 0000-0001-9104-3724 cyndy_loftin@usgs.gov","orcid":"https://orcid.org/0000-0001-9104-3724","contributorId":146427,"corporation":false,"usgs":true,"family":"Loftin","given":"Cyndy","email":"cyndy_loftin@usgs.gov","affiliations":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true}],"preferred":true,"id":708027,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Tsomides, Leonidas","contributorId":195762,"corporation":false,"usgs":false,"family":"Tsomides","given":"Leonidas","email":"","affiliations":[],"preferred":false,"id":708076,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"DiFranco, Jeanne L.","contributorId":195763,"corporation":false,"usgs":false,"family":"DiFranco","given":"Jeanne","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":708077,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Connors, Beth","contributorId":195764,"corporation":false,"usgs":false,"family":"Connors","given":"Beth","email":"","affiliations":[],"preferred":false,"id":708078,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Courtemanch, David L.","contributorId":70639,"corporation":false,"usgs":true,"family":"Courtemanch","given":"David","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":708079,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Drummond, Francis","contributorId":195765,"corporation":false,"usgs":false,"family":"Drummond","given":"Francis","affiliations":[],"preferred":false,"id":708080,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Davies, Susan","contributorId":63249,"corporation":false,"usgs":true,"family":"Davies","given":"Susan","email":"","affiliations":[],"preferred":false,"id":708081,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70038965,"text":"ofr20121133 - 2012 - An environmental streamflow assessment for the Santiam River basin, Oregon","interactions":[],"lastModifiedDate":"2012-07-10T01:01:44","indexId":"ofr20121133","displayToPublicDate":"2012-07-09T00:00:00","publicationYear":"2012","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":"2012-1133","title":"An environmental streamflow assessment for the Santiam River basin, Oregon","docAbstract":"The Santiam River is a tributary of the Willamette River in northwestern Oregon and drains an area of 1,810 square miles. The U.S. Army Corps of Engineers (USACE) operates four dams in the basin, which are used primarily for flood control, hydropower production, recreation, and water-quality improvement. The Detroit and Big Cliff Dams were constructed in 1953 on the North Santiam River. The Green Peter and Foster Dams were completed in 1967 on the South Santiam River. The impacts of the structures have included a decrease in the frequency and magnitude of floods and an increase in low flows. For three North Santiam River reaches, the median of annual 1-day maximum streamflows decreased 42–50 percent because of regulated streamflow conditions. Likewise, for three reaches in the South Santiam River basin, the median of annual 1-day maximum streamflows decreased 39–52 percent because of regulation. In contrast to their effect on high flows, the dams increased low flows. The median of annual 7-day minimum flows in six of the seven study reaches increased under regulated streamflow conditions between 60 and 334 percent. On a seasonal basis, median monthly streamflows decreased from February to May and increased from September to January in all the reaches. However, the magnitude of these impacts usually decreased farther downstream from dams because of cumulative inflow from unregulated tributaries and groundwater entering the North, South, and main-stem Santiam Rivers below the dams. A Wilcox rank-sum test of monthly precipitation data from Salem, Oregon, and Waterloo, Oregon, found no significant difference between the pre-and post-dam periods, which suggests that the construction and operation of the dams since the 1950s and 1960s are a primary cause of alterations to the Santiam River basin streamflow regime. In addition to the streamflow analysis, this report provides a geomorphic characterization of the Santiam River basin and the associated conceptual framework for assessing possible geomorphic and ecological changes in response to river-flow modifications. Suggestions for future biomonitoring and investigations are also provided. This study was one in a series of similar tributary streamflow and geomorphic studies conducted for the Willamette Sustainable Rivers Project. The Sustainable Rivers Project is a national effort by the USACE and The Nature Conservancy to develop environmental flow requirements in regulated river systems.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121133","collaboration":"Prepared in cooperation with the U.S. Army Corps of Engineers","usgsCitation":"Risley, J.C., Wallick, J., Mangano, J.F., and Jones, K.L., 2012, An environmental streamflow assessment for the Santiam River basin, Oregon: U.S. Geological Survey Open-File Report 2012-1133, vi, 66 p.; Appendices; ZIP Downloads of Appendices A and C; XLSX Download of Appendix D, https://doi.org/10.3133/ofr20121133.","productDescription":"vi, 66 p.; Appendices; ZIP Downloads of Appendices A and C; XLSX Download of Appendix D","startPage":"i","endPage":"66","numberOfPages":"72","onlineOnly":"Y","additionalOnlineFiles":"Y","costCenters":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"links":[{"id":258277,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1133.jpg"},{"id":258272,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1133/","linkFileType":{"id":5,"text":"html"}},{"id":258273,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1133/pdf/ofr20121133.pdf","linkFileType":{"id":1,"text":"pdf"}}],"country":"United States","state":"Oregon","otherGeospatial":"Santiam River Basin","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5059ea3ee4b0c8380cd4871d","contributors":{"authors":[{"text":"Risley, John C. 0000-0002-8206-5443 jrisley@usgs.gov","orcid":"https://orcid.org/0000-0002-8206-5443","contributorId":2698,"corporation":false,"usgs":true,"family":"Risley","given":"John","email":"jrisley@usgs.gov","middleInitial":"C.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":465320,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Wallick, J. Rose 0000-0002-9392-272X rosewall@usgs.gov","orcid":"https://orcid.org/0000-0002-9392-272X","contributorId":3583,"corporation":false,"usgs":true,"family":"Wallick","given":"J. Rose","email":"rosewall@usgs.gov","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":465321,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Mangano, Joseph F. 0000-0003-4213-8406 jmangano@usgs.gov","orcid":"https://orcid.org/0000-0003-4213-8406","contributorId":4722,"corporation":false,"usgs":true,"family":"Mangano","given":"Joseph","email":"jmangano@usgs.gov","middleInitial":"F.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":465323,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jones, Krista L. 0000-0002-0301-4497 kljones@usgs.gov","orcid":"https://orcid.org/0000-0002-0301-4497","contributorId":4550,"corporation":false,"usgs":true,"family":"Jones","given":"Krista","email":"kljones@usgs.gov","middleInitial":"L.","affiliations":[{"id":518,"text":"Oregon Water Science Center","active":true,"usgs":true}],"preferred":true,"id":465322,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70038969,"text":"ofr20121141 - 2012 - Relative abundance and distribution of fishes and crayfish at Ash Meadows National Wildlife Refuge, Nye County, Nevada, 2010-11","interactions":[],"lastModifiedDate":"2016-05-04T11:43:09","indexId":"ofr20121141","displayToPublicDate":"2012-07-09T00:00:00","publicationYear":"2012","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":"2012-1141","title":"Relative abundance and distribution of fishes and crayfish at Ash Meadows National Wildlife Refuge, Nye County, Nevada, 2010-11","docAbstract":"Ash Meadows National Wildlife Refuge (AMNWR) was established by the U.S. Fish and Wildlife Service (with the assistance of The Nature Conservancy) in 1984 to protect one of the highest concentrations of endemic flora and fauna in North America (Pister, 1985; Sada, 1990). Prior to federal acquisition, Ash Meadows had been anthropogenically altered, and non-native species had been introduced to the detriment of native species; reports and published literature document the negative effects to the Ash Meadows flora and fauna (Deacon and others, 1964; U.S. Department of the Interior, 1971; Landye, 1973; Pister, 1974; Soltz and Naiman, 1978; Taylor, 1980; Williams and others, 1985; Williams and Sada, 1985; Baugh and others, 1986; Hershler and Sada, 1987; Knight and Clemmer, 1987; Sada, 1990; Deacon and Williams, 1991; Scoppettone and others, 2005; Kennedy and others, 2006). Such activities led to the extinction of the endemic Ash Meadows poolfish (Empetrichthyes merriami) (Miller, 1961; Soltz and Naiman, 1978), and subsequently the federal government listed three local endemic fish as endangered pursuant to the Endangered Species Act (U.S. Fish and Wildlife Service, 1989)—Warm springs pupfish (Cyprinodon nevadensis pectoralis), Ash Meadows Amargosa pupfish (Cyprinodon nevadensis mionectes), and Ash Meadows speckled dace (Rhinichthys osculus nevadensis).
\nPublic ownership of a large portion of Ash Meadows provided the opportunity to restore the landscape to some semblance of its historical condition. Elimination of invasive aquatic species may be more difficult than landscape restoration, and their persistence can cause additional native fish decline or extirpation (Taylor and others, 1984; Moyle and others, 1986; Miller and others, 1989; Minckley and Deacon, 1991; Olden and Poff, 2005). Chemical treatment to remove invasive fishes is often unsuccessful (Meffe, 1983; Rinne and Turner, 1991; Meronek and others, 1996). In Ash Meadows, there has been some success in chemical eradication of localized populations of largemouth bass (Micropterus salmoides) and black bullhead (Ameiurus melas) (St. George, 1998, 1999; Weissenfluh, 2008b), as well as convict cichlid (Archocentrus nigrofasciatus) and sailfin molly (Poecilia latipinna) (Weissenfluh,2008a). However, there has been less success in removing western mosquitofish (Gambusia affinis) from Ash Meadows’s larger spring systems, and sailfin molly maintains strongholds in several spring systems (Scoppettone and others, 2011b). Perhaps the more destructive invasive species are two invertebrates: red swamp crayfish (Procambarus clarkii) and red-rim melania (Melanoides tuberculata). Following the appearance of red swamp crayfish within the Warm Springs Complex, Warm Springs pupfish was believed to be extirpated from one spring system (St. George, 2000) and near extirpation in two others (Darrick Weissenfluh, Ash Meadows National Wildlife Refuge, oral commun., 2008, 2011). Crayfish also were demonstrated to greatly suppress the Bradford Springs population of Ash Meadows speckled dace population (McShane and others, 2004). Red-rim melania is known to displace native snail populations (Mitchell and others, 2007), and has been implicated as an agent of extinction of native Ash Meadows spring-snails (Donald Sada, Desert Research Institute, oral commun., 2011). Both invasive invertebrates are difficult to control or eradicate (Mitchell and others, 2007; Freeman and others, 2010).
\nHabitat restoration that favors native species can help control non-native species (McShane and others, 2004; Scoppettone and others, 2005; Kennedy and others, 2006). Restoration of Carson Slough and its tributaries present an opportunity to promote habitat types that favor native species over non-natives. Historically, the majority of Ash Meadows spring systems were tributaries to Carson Slough. In 2007 and 2008, a survey of Ash Meadows spring systems was conducted to generate baseline information on the distribution of fishes throughout AMNWR (Scoppettone and others, 2011b). In this study, we conducted a follow-up survey with emphasis on upper Carson Slough. This permitted us to gauge the early effects of spring system restoration on fish populations and to generate further baseline data relevant to future restoration efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20121141","usgsCitation":"Scoppettone, G., Johnson, D., Hereford, M., Rissler, P., Fabes, M., Salgado, A., and Shea, S., 2012, Relative abundance and distribution of fishes and crayfish at Ash Meadows National Wildlife Refuge, Nye County, Nevada, 2010-11: U.S. Geological Survey Open-File Report 2012-1141, iv, 44 p., https://doi.org/10.3133/ofr20121141.","productDescription":"iv, 44 p.","startPage":"i","endPage":"44","numberOfPages":"52","onlineOnly":"Y","additionalOnlineFiles":"N","temporalStart":"2010-01-01","temporalEnd":"2011-12-31","costCenters":[{"id":654,"text":"Western Fisheries Research Center","active":true,"usgs":true}],"links":[{"id":258310,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/ofr_2012_1141.jpg"},{"id":258305,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/of/2012/1141/","linkFileType":{"id":5,"text":"html"}},{"id":258306,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2012/1141/pdf/ofr20121141.pdf","text":"Report","size":"8.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"Report"}],"country":"United States","state":"Nevada","county":"Nye County","otherGeospatial":"Ash Meadows National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -116.4111328125,\n 36.54384614538856\n ],\n [\n -116.37954711914062,\n 36.54329449143642\n ],\n [\n -116.25938415527344,\n 36.50301312197295\n ],\n [\n -116.22230529785156,\n 36.47375460532763\n ],\n [\n -116.20239257812499,\n 36.448903794892864\n ],\n [\n -116.17835998535156,\n 36.4052575563742\n ],\n [\n -116.17973327636719,\n 36.36490441440569\n ],\n [\n -116.18591308593749,\n 36.32397712011264\n ],\n [\n -116.23329162597655,\n 36.296864779193506\n ],\n [\n -116.27037048339844,\n 36.29741818650811\n ],\n [\n -116.31912231445312,\n 36.330062268112485\n ],\n [\n -116.42074584960936,\n 36.4113363510602\n ],\n [\n -116.44958496093749,\n 36.49086941889727\n ],\n [\n -116.4502716064453,\n 36.52288052805137\n ],\n [\n -116.4111328125,\n 36.54384614538856\n ]\n ]\n ]\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505aa669e4b0c8380cd84e2d","contributors":{"authors":[{"text":"Scoppettone, G.G.","contributorId":22793,"corporation":false,"usgs":true,"family":"Scoppettone","given":"G.G.","email":"","affiliations":[],"preferred":false,"id":465328,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, D.M.","contributorId":58266,"corporation":false,"usgs":true,"family":"Johnson","given":"D.M.","email":"","affiliations":[],"preferred":false,"id":465330,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hereford, M.E.","contributorId":88203,"corporation":false,"usgs":true,"family":"Hereford","given":"M.E.","email":"","affiliations":[],"preferred":false,"id":465333,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rissler, Peter","contributorId":83647,"corporation":false,"usgs":true,"family":"Rissler","given":"Peter","affiliations":[],"preferred":false,"id":465332,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Fabes, Mark","contributorId":39639,"corporation":false,"usgs":true,"family":"Fabes","given":"Mark","affiliations":[],"preferred":false,"id":465329,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Salgado, Antonio","contributorId":20595,"corporation":false,"usgs":true,"family":"Salgado","given":"Antonio","email":"","affiliations":[],"preferred":false,"id":465327,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Shea, Sean","contributorId":60491,"corporation":false,"usgs":true,"family":"Shea","given":"Sean","affiliations":[],"preferred":false,"id":465331,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70038964,"text":"fs20123068 - 2012 - National hydrography dataset--linear referencing","interactions":[],"lastModifiedDate":"2012-07-10T01:01:44","indexId":"fs20123068","displayToPublicDate":"2012-07-09T00:00:00","publicationYear":"2012","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":"2012-3068","title":"National hydrography dataset--linear referencing","docAbstract":"Geospatial data normally have a certain set of standard attributes, such as an identification number, the type of feature, and name of the feature. These standard attributes are typically embedded into the default attribute table, which is directly linked to the geospatial features. However, it is impractical to embed too much information because it can create a complex, inflexible, and hard to maintain geospatial dataset. Many scientists prefer to create a modular, or relational, data design where the information about the features is stored and maintained separately, then linked to the geospatial data. For example, information about the water chemistry of a lake can be maintained in a separate file and linked to the lake. A Geographic Information System (GIS) can then relate the water chemistry to the lake and analyze it as one piece of information. For example, the GIS can select all lakes more than 50 acres, with turbidity greater than 1.5 milligrams per liter.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20123068","collaboration":"National Geospatial Program","usgsCitation":"Simley, J., and Doumbouya, A., 2012, National hydrography dataset--linear referencing: U.S. Geological Survey Fact Sheet 2012-3068, 2 p., https://doi.org/10.3133/fs20123068.","productDescription":"2 p.","numberOfPages":"2","additionalOnlineFiles":"N","costCenters":[],"links":[{"id":258276,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2012_3068.gif"},{"id":258270,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2012/3068/","linkFileType":{"id":5,"text":"html"}},{"id":258271,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2012/3068/FS12-3068.pdf","linkFileType":{"id":1,"text":"pdf"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a6271e4b0c8380cd71ef6","contributors":{"authors":[{"text":"Simley, Jeffrey","contributorId":31246,"corporation":false,"usgs":true,"family":"Simley","given":"Jeffrey","affiliations":[],"preferred":false,"id":465318,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Doumbouya, Ariel","contributorId":44025,"corporation":false,"usgs":true,"family":"Doumbouya","given":"Ariel","affiliations":[],"preferred":false,"id":465319,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70101102,"text":"70101102 - 2012 - Initial assessment of the intensity distribution of the 2011 Mw5.8 Mineral, Virginia, earthquake","interactions":[],"lastModifiedDate":"2014-04-10T13:26:52","indexId":"70101102","displayToPublicDate":"2012-07-07T13:19:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3372,"text":"Seismological Research Letters","onlineIssn":"1938-2057","printIssn":"0895-0695","active":true,"publicationSubtype":{"id":10}},"title":"Initial assessment of the intensity distribution of the 2011 Mw5.8 Mineral, Virginia, earthquake","docAbstract":"The intensity data collected by the U.S. Geological Survey (USGS) \"Did You Feel It?\" (DYFI) Website (USGS, DYFI; http://earthquake.usgs.gov/earthquakes/dyfi/events/se/082311a/us/index.html, last accessed Sept 2011) for the Mw5.8 Mineral, Virginia, earthquake, are unprecedented in their spatial richness and geographical extent. More than 133,000 responses were received during the first week following the earthquake. Although intensity data have traditionally been regarded as imprecise and generally suspect (e.g., Hough 2000), there is a growing appreciation for the potential utility of spatially rich, systematically determined DYFI data to address key questions in earthquake ground-motions science (Atkinson and Wald, 2007; Hauksson et al., 2008).","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Seismological Research Letters","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"SRL","doi":"10.1785/0220110140","usgsCitation":"Hough, S.E., 2012, Initial assessment of the intensity distribution of the 2011 Mw5.8 Mineral, Virginia, earthquake: Seismological Research Letters, v. 83, no. 4, 9 p., https://doi.org/10.1785/0220110140.","productDescription":"9 p.","ipdsId":"IP-034418","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":286198,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":286197,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1785/0220110140"}],"country":"United States","state":"Virginia","city":"Mineral","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -88.0,32.0 ], [ -88.0,46.0 ], [ -70.0,46.0 ], [ -70.0,32.0 ], [ -88.0,32.0 ] ] ] } } ] }","volume":"83","issue":"4","noUsgsAuthors":false,"publicationDate":"2012-07-26","publicationStatus":"PW","scienceBaseUri":"5355947ce4b0120853e8c028","contributors":{"authors":[{"text":"Hough, Susan E. 0000-0002-5980-2986 hough@usgs.gov","orcid":"https://orcid.org/0000-0002-5980-2986","contributorId":587,"corporation":false,"usgs":true,"family":"Hough","given":"Susan","email":"hough@usgs.gov","middleInitial":"E.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"preferred":true,"id":492602,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70038943,"text":"70038943 - 2012 - Ecosystem performance monitoring of rangelands by integrating modeling and remote sensing","interactions":[],"lastModifiedDate":"2013-02-19T23:45:06","indexId":"70038943","displayToPublicDate":"2012-07-06T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3228,"text":"Rangeland Ecology and Management","onlineIssn":"1551-5028","printIssn":"1550-7424","active":true,"publicationSubtype":{"id":10}},"title":"Ecosystem performance monitoring of rangelands by integrating modeling and remote sensing","docAbstract":"Monitoring rangeland ecosystem dynamics, production, and performance is valuable for researchers and land managers. However, ecosystem monitoring studies can be difficult to interpret and apply appropriately if management decisions and disturbances are inseparable from the ecosystem's climate signal. This study separates seasonal weather influences from influences caused by disturbances and management decisions, making interannual time-series analysis more consistent and interpretable. We compared the actual ecosystem performance (AEP) of five rangeland vegetation types in the Owyhee Uplands for 9 yr to their expected ecosystem performance (EEP). Integrated growing season Normalized Difference Vegetation Index data for each of the nine growing seasons served as a proxy for annual AEP. Regression-tree models used long-term site potential, seasonal weather, and land cover data sets to generate annual EEP, an estimate of ecosystem performance incorporating annual weather variations. The difference between AEP and EEP provided a performance measure for each pixel in the study area. Ecosystem performance anomalies occurred when the ecosystem performed significantly better or worse than the model predicted. About 14% of the Owyhee Uplands showed a trend of significant underperformance or overperformance (P<0.10). Land managers can use results from weather-based rangeland ecosystem performance models to help support adaptive management strategies.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Rangeland Ecology and Management","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Society for Range Management","publisherLocation":"Wheat Ridge, CO","doi":"10.2111/REM-D-11-00058.1","usgsCitation":"Wylie, B.K., Boyte, S., and Major, D.J., 2012, Ecosystem performance monitoring of rangelands by integrating modeling and remote sensing: Rangeland Ecology and Management, v. 65, no. 3, p. 241-252, https://doi.org/10.2111/REM-D-11-00058.1.","productDescription":"12 p.","startPage":"241","endPage":"252","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":474423,"rank":10000,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"http://hdl.handle.net/10150/642631","text":"External Repository"},{"id":258235,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":258225,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.2111/REM-D-11-00058.1","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Oregon;Idaho","otherGeospatial":"Owyhee Uplands","volume":"65","issue":"3","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a059fe4b0c8380cd50e99","contributors":{"authors":[{"text":"Wylie, Bruce K. 0000-0002-7374-1083 wylie@usgs.gov","orcid":"https://orcid.org/0000-0002-7374-1083","contributorId":750,"corporation":false,"usgs":true,"family":"Wylie","given":"Bruce","email":"wylie@usgs.gov","middleInitial":"K.","affiliations":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true},{"id":223,"text":"Earth Resources Observation and Science (EROS) Center (Geography)","active":false,"usgs":true}],"preferred":true,"id":465278,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Boyte, Stephen P. 0000-0002-5462-3225","orcid":"https://orcid.org/0000-0002-5462-3225","contributorId":103539,"corporation":false,"usgs":true,"family":"Boyte","given":"Stephen P.","affiliations":[],"preferred":false,"id":465280,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Major, Donald J.","contributorId":83405,"corporation":false,"usgs":false,"family":"Major","given":"Donald","email":"","middleInitial":"J.","affiliations":[{"id":7217,"text":"Bureau of Land Management","active":true,"usgs":false}],"preferred":false,"id":465279,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70038871,"text":"sir20125125 - 2012 - Streamflow gains and losses and selected water-quality observations in five subreaches of the Rio Grande/Rio Bravo del Norte from near Presidio to Langtry, Texas, Big Bend area, United States and Mexico, 2006","interactions":[],"lastModifiedDate":"2016-08-08T08:55:35","indexId":"sir20125125","displayToPublicDate":"2012-07-05T00:00:00","publicationYear":"2012","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":"2012-5125","title":"Streamflow gains and losses and selected water-quality observations in five subreaches of the Rio Grande/Rio Bravo del Norte from near Presidio to Langtry, Texas, Big Bend area, United States and Mexico, 2006","docAbstract":"Few historical streamflow and water-quality data are available to characterize the segment of the Rio Grande/Rio Bravo del Norte (hereinafter Rio Grande) extending from near Presidio to near Langtry, Texas. The U.S. Geological Survey, in cooperation with the National Park Service and the Texas Commission on Environmental Quality, collected water-quality and streamflow data from the Rio Grande from near Presidio to near Langtry, Texas, to characterize the streamflow gain and loss and selected constituent concentrations in a 336.3-mile reach of the Rio Grande from near Presidio to near Langtry, Texas. Streamflow was measured at 38 sites and water-quality samples were collected at 20 sites along the Rio Grande in February, March, and June 2006. Streamflow gains and losses over the course of the stream were measured indirectly by computing the differences in measured streamflow between sites along the stream. Water-quality data were collected and analyzed for salinity, dissolved solids, major ions, nutrients, trace elements, and stable isotopes. Selected properties and constituents were compared to available Texas Commission on Environmental Quality general use protection criteria or screening levels. Summary statistics of selected water-quality data were computed for each of the five designated subreaches. Streamflow gain and loss and water-quality constituent concentration were compared for each subreach, rather than the entire segment because of the temporal variation in sample collection caused by controlled releases upstream. Subreach A was determined to be a losing reach, and subreaches B, C, D, and E were determined to be gaining reaches. Compared to concentrations measured in upstream subreaches, downstream subreaches exhibited evidence of dilution of selected constituent concentrations. Subreaches A and B had measured total dissolved solids, chloride, and sulfate exceeding the Texas Commission on Environmental Quality general use protection criteria. Subreaches C, D, and E did not exceed the general use protection criteria for any constituent concentration criteria, but dissolved oxygen concentrations did not meet the general use criteria in these subreaches.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20125125","collaboration":"Prepared in cooperation with the National Park Service and the Texas Commission on Environmental Quality","usgsCitation":"Raines, T.H., Turco, M.J., Connor, P.J., and Bennett, J.B., 2012, Streamflow gains and losses and selected water-quality observations in five subreaches of the Rio Grande/Rio Bravo del Norte from near Presidio to Langtry, Texas, Big Bend area, United States and Mexico, 2006: U.S. Geological Survey Scientific Investigations Report 2012-5125, vi, 30 p., https://doi.org/10.3133/sir20125125.","productDescription":"vi, 30 p.","numberOfPages":"30","onlineOnly":"N","additionalOnlineFiles":"N","temporalStart":"2006-02-01","temporalEnd":"2006-06-30","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":258213,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/sir_2012_5125.JPG"},{"id":258207,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/sir/2012/5125/","linkFileType":{"id":5,"text":"html"}},{"id":258206,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2012/5125/pdf/sir2012-5125.pdf","linkFileType":{"id":1,"text":"pdf"}}],"scale":"100000","projection":"Universal Transverse Mercator Projection Zone 13","datum":"North American Datum of 1983","country":"Mexico, United States","state":"Chihuahua, Coahuila, Texas","county":"Brewster County, Presido County, Terrell County, Val Verde County","city":"Langtry, Presidio","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -104.75,28.25 ], [ -104.75,30 ], [ -101.25,30 ], [ -101.25,28.25 ], [ -104.75,28.25 ] ] ] } } ] }","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505b9b01e4b08c986b31cc18","contributors":{"authors":[{"text":"Raines, Timothy H. thraines@usgs.gov","contributorId":3862,"corporation":false,"usgs":true,"family":"Raines","given":"Timothy","email":"thraines@usgs.gov","middleInitial":"H.","affiliations":[],"preferred":true,"id":465123,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Turco, Michael J. mjturco@usgs.gov","contributorId":1011,"corporation":false,"usgs":true,"family":"Turco","given":"Michael","email":"mjturco@usgs.gov","middleInitial":"J.","affiliations":[],"preferred":true,"id":465122,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Connor, Patrick J.","contributorId":11081,"corporation":false,"usgs":true,"family":"Connor","given":"Patrick","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":465124,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bennett, Jeffery B.","contributorId":82993,"corporation":false,"usgs":true,"family":"Bennett","given":"Jeffery","email":"","middleInitial":"B.","affiliations":[],"preferred":false,"id":465125,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70038915,"text":"70038915 - 2012 - Interannual variability of snowmelt in the Sierra Nevada and Rocky Mountains, United States: examples from two alpine watersheds","interactions":[],"lastModifiedDate":"2012-07-06T01:01:41","indexId":"70038915","displayToPublicDate":"2012-07-05T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Interannual variability of snowmelt in the Sierra Nevada and Rocky Mountains, United States: examples from two alpine watersheds","docAbstract":"The distribution of snow and the energy flux components of snowmelt are intrinsic characteristics of the alpine water cycle controlling the location of source waters and the effect of climate on streamflow. Interannual variability of these characteristics is relevant to the effect of climate change on alpine hydrology. Our objective is to characterize the interannual variability in the spatial distribution of snow and energy fluxes of snowmelt in watersheds of a maritime setting, Tokopah Basin (TOK) in California's southern Sierra Nevada, and a continental setting, Green Lake 4 Valley (GLV4) in Colorado's Front Range, using a 12 year database (1996–2007) of hydrometeorological observations and satellite-derived snow cover. Snowpacks observed in GLV4 exhibit substantially greater spatial variability than in TOK (0.75 versus 0.28 spatial coefficient of variation). In addition, modeling results indicate that the net turbulent energy flux contribution to snowmelt in GLV4 is, on average, 3 times greater in magnitude (mean 29% versus 10%) and interannual variability (standard deviation 17% versus 6%) than in TOK. These energy flux values exhibit strong seasonality, increasing as the melt season progresses to times later in the year (R2 = 0.54–0.77). This seasonality of energy flux appears to be associated with snowmelt rates that generally increase with onset date of melt (0.02 cm d-2). This seasonality in snowmelt rate, coupled to differences in hydrogeology, may account for the observed differences in correspondence between the timing of snowmelt and timing of streamflow in these watersheds.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Water Resources Research","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Geophysical Union","publisherLocation":"Washington, D.C.","doi":"10.1029/2011WR011006","usgsCitation":"Jepsen, S.M., Molotch, N., Williams, M.W., Rittger, K.E., and Sickman, J.O., 2012, Interannual variability of snowmelt in the Sierra Nevada and Rocky Mountains, United States: examples from two alpine watersheds: Water Resources Research, v. 48, 15 p.; W02529, https://doi.org/10.1029/2011WR011006.","productDescription":"15 p.; W02529","numberOfPages":"15","costCenters":[{"id":145,"text":"Branch of Regional Research-Central Region","active":false,"usgs":true}],"links":[{"id":474424,"rank":10000,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2011wr011006","text":"Publisher Index Page"},{"id":258177,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":258169,"rank":9999,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1029/2011WR011006","linkFileType":{"id":5,"text":"html"}}],"country":"United States","otherGeospatial":"Sierra Nevada;Rocky Mountains","volume":"48","noUsgsAuthors":false,"publicationDate":"2012-02-23","publicationStatus":"PW","scienceBaseUri":"505a3ce9e4b0c8380cd63143","contributors":{"authors":[{"text":"Jepsen, Steven M. sjepsen@usgs.gov","contributorId":3892,"corporation":false,"usgs":true,"family":"Jepsen","given":"Steven","email":"sjepsen@usgs.gov","middleInitial":"M.","affiliations":[],"preferred":true,"id":465223,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Molotch, Noah P.","contributorId":79741,"corporation":false,"usgs":true,"family":"Molotch","given":"Noah P.","affiliations":[],"preferred":false,"id":465227,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Williams, Mark W.","contributorId":43046,"corporation":false,"usgs":true,"family":"Williams","given":"Mark","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":465226,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Rittger, Karl E.","contributorId":13850,"corporation":false,"usgs":true,"family":"Rittger","given":"Karl","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":465224,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Sickman, James O.","contributorId":30741,"corporation":false,"usgs":true,"family":"Sickman","given":"James","email":"","middleInitial":"O.","affiliations":[],"preferred":false,"id":465225,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70005999,"text":"70005999 - 2012 - New aquaculture drugs under FDA review","interactions":[],"lastModifiedDate":"2012-07-06T01:01:41","indexId":"70005999","displayToPublicDate":"2012-07-05T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1834,"text":"Global Aquaculture Advocate","active":true,"publicationSubtype":{"id":10}},"title":"New aquaculture drugs under FDA review","docAbstract":"Only eight active pharmaceutical ingredients available in 18 drug products have been approved by the U.S. Food and Drug Administration for use in aquaculture. The approval process can be lengthy and expensive, but several new drugs and label claims are under review. Progress has been made on approvals for Halamid (chloramine-T), Aquaflor (florfenicol) and 35% PeroxAid (hydrogen peroxide) as therapeutic drugs. Data are also being generated for AQUI-S 20E, a fish sedative.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Global Aquaculture Advocate","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Global Aquaculture Alliance","publisherLocation":"St. Louis, MO","usgsCitation":"Bowker, J.D., and Gaikowski, M.P., 2012, New aquaculture drugs under FDA review: Global Aquaculture Advocate, v. January/February 2012, p. 36-39.","productDescription":"3 p.","startPage":"36","endPage":"39","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":258178,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":258173,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pdf.gaalliance.org/pdf/GAA-Bowker-Jan12.pdf","linkFileType":{"id":1,"text":"pdf"}}],"volume":"January/February 2012","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505a655be4b0c8380cd72b88","contributors":{"authors":[{"text":"Bowker, James D.","contributorId":51240,"corporation":false,"usgs":true,"family":"Bowker","given":"James","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":353627,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gaikowski, Mark P. 0000-0002-6507-9341 mgaikowski@usgs.gov","orcid":"https://orcid.org/0000-0002-6507-9341","contributorId":796,"corporation":false,"usgs":true,"family":"Gaikowski","given":"Mark","email":"mgaikowski@usgs.gov","middleInitial":"P.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":false,"id":353626,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70156900,"text":"70156900 - 2012 - Modelling ecosystem service flows under uncertainty with stochiastic SPAN","interactions":[],"lastModifiedDate":"2021-10-22T14:20:07.094242","indexId":"70156900","displayToPublicDate":"2012-07-05T00:00:00","publicationYear":"2012","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Modelling ecosystem service flows under uncertainty with stochiastic SPAN","docAbstract":"Ecosystem service models are increasingly in demand for decision making. However, the data required to run these models are often patchy, missing, outdated, or untrustworthy. Further, communication of data and model uncertainty to decision makers is often either absent or unintuitive. In this work, we introduce a systematic approach to addressing both the data gap and the difficulty in communicating uncertainty through a stochastic adaptation of the Service Path Attribution Networks (SPAN) framework. The SPAN formalism assesses ecosystem services through a set of up to 16 maps, which characterize the services in a study area in terms of flow pathways between ecosystems and human beneficiaries. Although the SPAN algorithms were originally defined deterministically, we present them here in a stochastic framework which combines probabilistic input data with a stochastic transport model in order to generate probabilistic spatial outputs. This enables a novel feature among ecosystem service models: the ability to spatially visualize uncertainty in the model results. The stochastic SPAN model can analyze areas where data limitations are prohibitive for deterministic models. Greater uncertainty in the model inputs (including missing data) should lead to greater uncertainty expressed in the model’s output distributions. By using Bayesian belief networks to fill data gaps and expert-provided trust assignments to augment untrustworthy or outdated information, we can account for uncertainty in input data, producing a model that is still able to run and provide information where strictly deterministic models could not. Taken together, these attributes enable more robust and intuitive modelling of ecosystem services under uncertainty.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"2012 International Congress on Environmental Modelling and Software: Managing resources of a limited planet","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"2012 International Congress on Environmental Modelling and Software: Managing Resources of a Limited Planet","conferenceDate":"July 1-5, 2012","conferenceLocation":"Leipzig, Germany","language":"English","publisher":"International Environmental Modelling and Software Society (iEMSs)","usgsCitation":"Johnson, G.W., Snapp, R.R., Villa, F., and Bagstad, K.J., 2012, Modelling ecosystem service flows under uncertainty with stochiastic SPAN, in 2012 International Congress on Environmental Modelling and Software: Managing resources of a limited planet, Leipzig, Germany, July 1-5, 2012, p. 1021-1028.","productDescription":"8 p.","startPage":"1021","endPage":"1028","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-037621","costCenters":[{"id":547,"text":"Rocky Mountain Geographic Science Center","active":true,"usgs":true}],"links":[{"id":307789,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"560bb6d6e4b058f706e53d8e","contributors":{"authors":[{"text":"Johnson, Gary W.","contributorId":90618,"corporation":false,"usgs":true,"family":"Johnson","given":"Gary","email":"","middleInitial":"W.","affiliations":[],"preferred":false,"id":571051,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Snapp, Robert R.","contributorId":147293,"corporation":false,"usgs":false,"family":"Snapp","given":"Robert","email":"","middleInitial":"R.","affiliations":[],"preferred":false,"id":571052,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Villa, Ferdinando","contributorId":84249,"corporation":false,"usgs":true,"family":"Villa","given":"Ferdinando","affiliations":[],"preferred":false,"id":571053,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Bagstad, Kenneth J. 0000-0001-8857-5615 kjbagstad@usgs.gov","orcid":"https://orcid.org/0000-0001-8857-5615","contributorId":3680,"corporation":false,"usgs":true,"family":"Bagstad","given":"Kenneth","email":"kjbagstad@usgs.gov","middleInitial":"J.","affiliations":[{"id":318,"text":"Geosciences and Environmental Change Science Center","active":true,"usgs":true}],"preferred":true,"id":571054,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70040395,"text":"70040395 - 2012 - Use of Dry Tortugas National Park by threatened and endangered marine turtles","interactions":[],"lastModifiedDate":"2022-11-14T16:19:25.926867","indexId":"70040395","displayToPublicDate":"2012-07-04T02:30:00","publicationYear":"2012","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"chapter":"5","title":"Use of Dry Tortugas National Park by threatened and endangered marine turtles","docAbstract":"Satellite and acoustic tracking results for green turtles, hawksbills, and loggerheads have revealed patterns in the proportion of time that tagged turtles spend within various zones of the park, including the RNA. Green turtles primarily utilize the shallow areas in the northern portion of the park. Hawksbills were mostly observed near Garden Key and loggerheads were observed throughout DRTO. Our record of turtle captures, recaptures, and sightings over the last 4 years serves as a baseline database for understanding the size classes of each species present in the park, as well as species-specific habitats in DRTO waters.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Implementing the Dry Tortugas National Park Research Natural Area science plan: The 5-year report","largerWorkSubtype":{"id":1,"text":"Federal Government Series"},"language":"English","publisher":"National Park Service","collaboration":"National Park Service and the Florida Fish and Wildlife Conservation Commission","usgsCitation":"Hart, K.M., Fujisaki, I., and Sartain-Iverson, A.R., 2012, Use of Dry Tortugas National Park by threatened and endangered marine turtles, 6 p.","productDescription":"6 p.","startPage":"28","endPage":"33","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-033891","costCenters":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"links":[{"id":319611,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":319610,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://irma.nps.gov/DataStore/Reference/Profile/2188640","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Florida","otherGeospatial":"Dry Tortugas National Park","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -82.76726111255684,\n 24.668880028267623\n ],\n [\n -82.76808893731325,\n 24.70347980045176\n ],\n [\n -82.80244366469317,\n 24.726039692971767\n ],\n [\n -82.8670139956724,\n 24.725287762430412\n ],\n [\n -82.90012698591825,\n 24.717768207105777\n ],\n [\n -82.96635296640954,\n 24.647814596972225\n ],\n [\n -82.96511122927551,\n 24.5657760529391\n ],\n [\n -82.89722959927172,\n 24.566528944544928\n ],\n [\n -82.79996019042464,\n 24.616209786360997\n ],\n [\n -82.76767502493483,\n 24.668880028267623\n ],\n [\n -82.76726111255684,\n 24.668880028267623\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56fd0613e4b0a6037df2d04c","contributors":{"authors":[{"text":"Hart, Kristin M.","contributorId":147610,"corporation":false,"usgs":false,"family":"Hart","given":"Kristin","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":625606,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Fujisaki, Ikuko","contributorId":42152,"corporation":false,"usgs":false,"family":"Fujisaki","given":"Ikuko","affiliations":[],"preferred":false,"id":514619,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Sartain-Iverson, Autumn R. 0000-0002-8353-6745 asartain@usgs.gov","orcid":"https://orcid.org/0000-0002-8353-6745","contributorId":5477,"corporation":false,"usgs":true,"family":"Sartain-Iverson","given":"Autumn","email":"asartain@usgs.gov","middleInitial":"R.","affiliations":[{"id":566,"text":"Southeast Ecological Science Center","active":true,"usgs":true}],"preferred":false,"id":514620,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70046934,"text":"70046934 - 2012 - Process-based coastal erosion modeling for Drew Point (North Slope, Alaska)","interactions":[],"lastModifiedDate":"2013-07-23T10:19:29","indexId":"70046934","displayToPublicDate":"2012-07-03T09:56:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2504,"text":"Journal of Waterway, Port, Coastal and Ocean Engineering","active":true,"publicationSubtype":{"id":10}},"title":"Process-based coastal erosion modeling for Drew Point (North Slope, Alaska)","docAbstract":"A predictive, coastal erosion/shoreline change model has been developed for a small coastal segment near Drew Point, Beaufort Sea, Alaska. This coastal setting has experienced a dramatic increase in erosion since the early 2000’s. The bluffs at this site are 3-4 m tall and consist of ice-wedge bounded blocks of fine-grained sediments cemented by ice-rich permafrost and capped with a thin organic layer. The bluffs are typically fronted by a narrow (∼ 5 m wide) beach or none at all. During a storm surge, the sea contacts the base of the bluff and a niche is formed through thermal and mechanical erosion. The niche grows both vertically and laterally and eventually undermines the bluff, leading to block failure or collapse. The fallen block is then eroded both thermally and mechanically by waves and currents, which must occur before a new niche forming episode may begin. The erosion model explicitly accounts for and integrates a number of these processes including: (1) storm surge generation resulting from wind and atmospheric forcing, (2) erosional niche growth resulting from wave-induced turbulent heat transfer and sediment transport (using the Kobayashi niche erosion model), and (3) thermal and mechanical erosion of the fallen block. The model was calibrated with historic shoreline change data for one time period (1979-2002), and validated with a later time period (2002-2007).","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Journal of Waterway, Port, Coastal and Ocean Engineering","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"American Society of Civil Engineers","doi":"10.1061/(ASCE)WW.1943-5460.0000106","usgsCitation":"Ravens, T.M., Jones, B.M., Zhang, J., Arp, C.D., and Schmutz, J.A., 2012, Process-based coastal erosion modeling for Drew Point (North Slope, Alaska): Journal of Waterway, Port, Coastal and Ocean Engineering, v. 138, no. 2, p. 122-130, https://doi.org/10.1061/(ASCE)WW.1943-5460.0000106.","productDescription":"9 p.","startPage":"122","endPage":"130","numberOfPages":"9","ipdsId":"IP-026511","costCenters":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"links":[{"id":275273,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":275272,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1061/(ASCE)WW.1943-5460.0000106"}],"country":"United States","state":"Alaska","otherGeospatial":"Teshekpuk Lake","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -153.9444,70.5395 ], [ -153.9444,70.9763 ], [ -152.1354,70.9763 ], [ -152.1354,70.5395 ], [ -153.9444,70.5395 ] ] ] } } ] }","volume":"138","issue":"2","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"51efa5f6e4b0b09fbe58f1d8","contributors":{"authors":[{"text":"Ravens, Thomas M.","contributorId":24668,"corporation":false,"usgs":true,"family":"Ravens","given":"Thomas","email":"","middleInitial":"M.","affiliations":[],"preferred":false,"id":480645,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jones, Benjamin M. 0000-0002-1517-4711 bjones@usgs.gov","orcid":"https://orcid.org/0000-0002-1517-4711","contributorId":2286,"corporation":false,"usgs":true,"family":"Jones","given":"Benjamin","email":"bjones@usgs.gov","middleInitial":"M.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"preferred":true,"id":480643,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Zhang, Jinlin","contributorId":25841,"corporation":false,"usgs":true,"family":"Zhang","given":"Jinlin","email":"","affiliations":[],"preferred":false,"id":480646,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Arp, Christopher D.","contributorId":17330,"corporation":false,"usgs":false,"family":"Arp","given":"Christopher","email":"","middleInitial":"D.","affiliations":[{"id":6752,"text":"University of Alaska Fairbanks","active":true,"usgs":false}],"preferred":false,"id":480644,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Schmutz, Joel A. 0000-0002-6516-0836 jschmutz@usgs.gov","orcid":"https://orcid.org/0000-0002-6516-0836","contributorId":1805,"corporation":false,"usgs":true,"family":"Schmutz","given":"Joel","email":"jschmutz@usgs.gov","middleInitial":"A.","affiliations":[{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":480642,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70038896,"text":"fs20123074 - 2012 - U.S. Geological Survey community for data integration: data upload, registry, and access tool","interactions":[],"lastModifiedDate":"2012-07-03T17:03:09","indexId":"fs20123074","displayToPublicDate":"2012-07-02T00:00:00","publicationYear":"2012","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":"2012-3074","title":"U.S. Geological Survey community for data integration: data upload, registry, and access tool","docAbstract":"As a leading science and information agency and in fulfillment of its mission to provide reliable scientific information to describe and understand the Earth, the U.S. Geological Survey (USGS) ensures that all scientific data are effectively hosted, adequately described, and appropriately accessible to scientists, collaborators, and the general public. To succeed in this task, the USGS established the Community for Data Integration (CDI) to address data and information management issues affecting the proficiency of earth science research. Through the CDI, the USGS is providing data and metadata management tools, cyber infrastructure, collaboration tools, and training in support of scientists and technology specialists throughout the project life cycle. One of the significant tools recently created to contribute to this mission is the Uploader tool. This tool allows scientists with limited data management resources to address many of the key aspects of the data life cycle: the ability to protect, preserve, publish and share data. By implementing this application inside ScienceBase, scientists also can take advantage of other collaboration capabilities provided by the ScienceBase platform.","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20123074","usgsCitation":"Fort Collins Science Center Web Applications Team, 2012, U.S. Geological Survey community for data integration: data upload, registry, and access tool: U.S. Geological Survey Fact Sheet 2012-3074, 2 p., https://doi.org/10.3133/fs20123074.","productDescription":"2 p.","numberOfPages":"2","onlineOnly":"Y","additionalOnlineFiles":"N","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":258133,"rank":0,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/fs_2012_3074.gif"},{"id":258127,"rank":300,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2012/3074/FS12-3074.pdf","linkFileType":{"id":1,"text":"pdf"}},{"id":258128,"rank":100,"type":{"id":15,"text":"Index Page"},"url":"https://pubs.usgs.gov/fs/2012/3074/","linkFileType":{"id":5,"text":"html"}}],"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"505bbaa5e4b08c986b32829c","contributors":{"authors":[{"text":"Fort Collins Science Center Web Applications Team","contributorId":128106,"corporation":true,"usgs":false,"organization":"Fort Collins Science Center Web Applications Team","id":535197,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ,{"id":70169880,"text":"70169880 - 2012 - Examining spring wet slab and glide avalanche occurrence along the Going-to-the-Sun Road corridor, Glacier National Park, Montana, USA","interactions":[],"lastModifiedDate":"2016-03-29T10:43:41","indexId":"70169880","displayToPublicDate":"2012-07-01T11:45:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1264,"text":"Cold Regions Science and Technology","active":true,"publicationSubtype":{"id":10}},"title":"Examining spring wet slab and glide avalanche occurrence along the Going-to-the-Sun Road corridor, Glacier National Park, Montana, USA","docAbstract":"Wet slab and glide snow avalanches are dangerous and yet can be particularly difficult to predict. Wet slab and glide avalanches are presumably triggered by free water moving through the snowpack and the subsequent interaction with layer or ground interfaces, and typically occur in the spring during warming and subsequent melt periods. In Glacier National Park (GNP), Montana, both types of avalanches can occur in the same year and affect the spring opening operations of the Going-to-the-Sun Road (GTSR).
\nWe investigated the timing of wet slab and glide avalanche occurrence along the GTSR from 2003 to 2011 using meteorological and snowpack data from two high-elevation weather stations, one SNOTEL site, and an avalanche database to characterize 55 wet slab and 182 glide avalanches. Daily wet slab and glide avalanche occurrence were combined to represent an avalanche day and were compared to non-avalanche days (no avalanche occurrence) for 60 variables (both direct and derived measurements) using a univariate analysis. A classification tree (CART) was then trained to capture the most important variables for examining specific meteorological and snowpack variables that contribute to these types of wet snow avalanches. The CART was 10-fold cross validated using the data for 2003–2010 seasons and resulted in overall predictive accuracy of 73%. We then used the statistically optimal CART as a predictive model for the spring avalanche season of 2011, which resulted in an overall predictive accuracy of 82% for both avalanche and non-avalanche days, and a predictive accuracy of 91% for avalanche days.
\nThe results suggest that the role of air temperature and snowpack settlement appear to be the most important variables in wet slab and glide avalanche occurrence. When applied to the 2011 season, the results of the CART model are encouraging and they enhance our understanding of some of the required meteorological and snowpack conditions for wet slab and glide avalanche occurrence.
","language":"English","publisher":"Elsevier Science Pub. Co.","publisherLocation":"New York, NY","doi":"10.1016/j.coldregions.2012.01.012","usgsCitation":"Peitzsch, E.H., Hendrikx, J., Fagre, D.B., and Reardon, B., 2012, Examining spring wet slab and glide avalanche occurrence along the Going-to-the-Sun Road corridor, Glacier National Park, Montana, USA: Cold Regions Science and Technology, v. 78, p. 73-81, https://doi.org/10.1016/j.coldregions.2012.01.012.","productDescription":"9 p.","startPage":"73","endPage":"81","numberOfPages":"9","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-032503","costCenters":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"links":[{"id":319575,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"78","publishingServiceCenter":{"id":2,"text":"Denver PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56fba7a5e4b0a6037df1a140","contributors":{"authors":[{"text":"Peitzsch, Erich H. 0000-0001-7624-0455 epeitzsch@usgs.gov","orcid":"https://orcid.org/0000-0001-7624-0455","contributorId":3786,"corporation":false,"usgs":true,"family":"Peitzsch","given":"Erich","email":"epeitzsch@usgs.gov","middleInitial":"H.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":625438,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hendrikx, Jordy","contributorId":166967,"corporation":false,"usgs":false,"family":"Hendrikx","given":"Jordy","affiliations":[{"id":13628,"text":"Department of Earth Sciences, P.O. Box 173480, Montana State University, Bozeman, MT, USA. 59717.","active":true,"usgs":false}],"preferred":false,"id":625440,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Fagre, Daniel B. 0000-0001-8552-9461 dan_fagre@usgs.gov","orcid":"https://orcid.org/0000-0001-8552-9461","contributorId":2036,"corporation":false,"usgs":true,"family":"Fagre","given":"Daniel","email":"dan_fagre@usgs.gov","middleInitial":"B.","affiliations":[{"id":481,"text":"Northern Rocky Mountain Science Center","active":true,"usgs":true}],"preferred":true,"id":625437,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Reardon, Blase","contributorId":168313,"corporation":false,"usgs":false,"family":"Reardon","given":"Blase","affiliations":[{"id":25251,"text":"University of Montana, Department of Geosciences","active":true,"usgs":false}],"preferred":false,"id":625439,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70074333,"text":"70074333 - 2012 - Monitoring groundwater-surface water interaction using time-series and time-frequency analysis of transient three-dimensional electrical resistivity changes","interactions":[],"lastModifiedDate":"2014-01-29T11:47:14","indexId":"70074333","displayToPublicDate":"2012-07-01T11:21:00","publicationYear":"2012","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3722,"text":"Water Resources Research","onlineIssn":"1944-7973","printIssn":"0043-1397","active":true,"publicationSubtype":{"id":10}},"title":"Monitoring groundwater-surface water interaction using time-series and time-frequency analysis of transient three-dimensional electrical resistivity changes","docAbstract":"Time-lapse resistivity imaging is increasingly used to monitor hydrologic processes. Compared to conventional hydrologic measurements, surface time-lapse resistivity provides superior spatial coverage in two or three dimensions, potentially high-resolution information in time, and information in the absence of wells. However, interpretation of time-lapse electrical tomograms is complicated by the ever-increasing size and complexity of long-term, three-dimensional (3-D) time series conductivity data sets. Here we use 3-D surface time-lapse electrical imaging to monitor subsurface electrical conductivity variations associated with stage-driven groundwater-surface water interactions along a stretch of the Columbia River adjacent to the Hanford 300 near Richland, Washington, USA. We reduce the resulting 3-D conductivity time series using both time-series and time-frequency analyses to isolate a paleochannel causing enhanced groundwater-surface water interactions. Correlation analysis on the time-lapse imaging results concisely represents enhanced groundwater-surface water interactions within the paleochannel, and provides information concerning groundwater flow velocities. Time-frequency analysis using the Stockwell (S) transform provides additional information by identifying the stage periodicities driving groundwater-surface water interactions due to upstream dam operations, and identifying segments in time-frequency space when these interactions are most active. These results provide new insight into the distribution and timing of river water intrusion into the Hanford 300 Area, which has a governing influence on the behavior of a uranium plume left over from historical nuclear fuel processing operations.","largerWorkType":{"id":2,"text":"Article"},"largerWorkTitle":"Water Resources Research","largerWorkSubtype":{"id":10,"text":"Journal Article"},"language":"English","publisher":"Wiley","doi":"10.1029/2012WR011893","usgsCitation":"Johnson, T., Slater, L.D., Ntarlagiannis, D., Day-Lewis, F.D., and Elwaseif, M., 2012, Monitoring groundwater-surface water interaction using time-series and time-frequency analysis of transient three-dimensional electrical resistivity changes: Water Resources Research, v. 48, no. 7, 13 p., https://doi.org/10.1029/2012WR011893.","productDescription":"13 p.","numberOfPages":"13","onlineOnly":"Y","ipdsId":"IP-037950","costCenters":[{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true}],"links":[{"id":474426,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2012wr011893","text":"Publisher Index Page"},{"id":281648,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":281637,"type":{"id":10,"text":"Digital Object Identifier"},"url":"https://dx.doi.org/10.1029/2012WR011893"}],"country":"United States","state":"Washington","city":"Richland","otherGeospatial":"Doe Hanford 300 Area","geographicExtents":"{ \"type\": \"FeatureCollection\", \"features\": [ { \"type\": \"Feature\", \"properties\": {}, \"geometry\": { \"type\": \"Polygon\", \"coordinates\": [ [ [ -119.400291,46.259468 ], [ -119.400291,46.370457 ], [ -119.211394,46.370457 ], [ -119.211394,46.259468 ], [ -119.400291,46.259468 ] ] ] } } ] }","volume":"48","issue":"7","noUsgsAuthors":false,"publicationDate":"2012-07-10","publicationStatus":"PW","scienceBaseUri":"53cd681fe4b0b29085101d37","contributors":{"authors":[{"text":"Johnson, Timothy C.","contributorId":99884,"corporation":false,"usgs":true,"family":"Johnson","given":"Timothy C.","affiliations":[],"preferred":false,"id":489506,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Slater, Lee D.","contributorId":95792,"corporation":false,"usgs":true,"family":"Slater","given":"Lee","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":489505,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ntarlagiannis, Dimitris","contributorId":14295,"corporation":false,"usgs":true,"family":"Ntarlagiannis","given":"Dimitris","affiliations":[],"preferred":false,"id":489503,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Day-Lewis, Frederick D. 0000-0003-3526-886X daylewis@usgs.gov","orcid":"https://orcid.org/0000-0003-3526-886X","contributorId":1672,"corporation":false,"usgs":true,"family":"Day-Lewis","given":"Frederick","email":"daylewis@usgs.gov","middleInitial":"D.","affiliations":[{"id":493,"text":"Office of Ground Water","active":true,"usgs":true},{"id":486,"text":"OGW Branch of Geophysics","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":489502,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Elwaseif, Mehrez","contributorId":86681,"corporation":false,"usgs":true,"family":"Elwaseif","given":"Mehrez","email":"","affiliations":[],"preferred":false,"id":489504,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ]}