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An efficient deterministic‐probabilistic approach to modeling regional groundwater flow: 2. Application to Owens Valley, California
Author(s) -
Guymon Gary L.,
Yen ChungCheng
Publication year - 1990
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/wr026i007p01569
Subject(s) - probabilistic logic , hydraulic conductivity , groundwater flow , spatial variability , hydrology (agriculture) , mathematics , mathematical optimization , groundwater , statistics , environmental science , soil science , geology , geotechnical engineering , aquifer , soil water
The applicability of a deterministic‐probabilistic model for predicting water tables in southern Owens Valley, California, is evaluated. The model is based on a two‐layer deterministic model that is cascaded with a two‐point probability model. To reduce the potentially large number of uncertain variables in the deterministic model, lumping of uncertain variables was evaluated by sensitivity analysis to reduce the total number of uncertain variables to three variables: hydraulic conductivity, storage coefficient or specific yield, and source‐sink function. Results demonstrate that lumping of uncertain parameters reduces computational effort while providing sufficient precision for the case studied. Simulated spatial coefficients of variation for water table temporal position in most of the basin is small, which suggests that deterministic models can predict water tables in these areas with good precision. However, in several important areas where pumping occurs or the geology is complex, the simulated spatial coefficients of variation are over estimated by the two‐point probability method.