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Please use this identifier to cite or link to this item: http://repositorio.ufba.br/ri/handle/ri/26268

Title: Contaminant discharge and uncertainty estimates from passive flux meter measurements
Other Titles: Water Resources Research
Authors: Klammler, Harald
Hatfield, Kirk
Luz, Joana Angélica Guimarães da
Annable, Michael D.
Newman, Mark
Cho, Jaehyun
Peacock, Aaron
Stucker, Valerie
Keywords: TCE;Uranium;Conditional simulation;Contaminant plume;Effective number of data;Geostatistics
Issue Date: 2012
Abstract: 1] The passive flux meter (PFM) measures local cumulative water and contaminant fluxes at an observation well. Conditional stochastic simulation accounting for both spatial correlation and data skewness is introduced to interpret passive flux meter observations in terms of probability distributions of discharges across control planes (transects) of wells. An estimator of the effective number of independent data is defined and applied in the development of two significantly simpler approximate methods for estimating discharge distributions. One method uses a transformation of the t statistic to account for data skewness and the other method is closely related to the classic bootstrap. The approaches are demonstrated with passive flux meter data from two field sites (a trichloroethylene [TCE] plume at Ft. Lewis, WA, and a uranium plume at Rifle, CO). All methods require that the flux heterogeneity is sufficiently represented by the data and maximum differences in discharge quantile estimates between methods are ∼7%.
Description: Texto completo: acesso restrito. p. 1-19
URI: http://repositorio.ufba.br/ri/handle/ri/26268
ISSN: 0043-1397
Appears in Collections:Artigos Publicados em Periódicos (ICADS)

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