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http://dx.doi.org/10.9719/EEG.2020.53.6.703

Introduction of Inverse Analysis Model Using Geostatistical Evolution Strategy and Estimation of Hydraulic Conductivity Distribution in Synthetic Aquifer  

Park, Eungyu (Department of Geology, Kyungpook National University)
Publication Information
Economic and Environmental Geology / v.53, no.6, 2020 , pp. 703-713 More about this Journal
Abstract
In many geological fields, including hydrogeology, it is of great importance to determine the heterogeneity of the subsurface media. This study briefly introduces the concept and theory of the method that can estimate the hydraulic properties of the media constituting the aquifer, which was recently introduced by Park (2020). After the introduction, the method was applied to the synthetic aquifer to demonstrate the practicality, from which various implications were drawn. The introduced technique uses a global optimization technique called the covariance matrix adaptation evolution strategy (CMA-ES). Conceptually, it is a methodology to characterize the aquifer heterogeneity by assimilating the groundwater level time-series data due to the imposed hydraulic stress. As a result of applying the developed technique to estimate the hydraulic conductivity of a hypothetical aquifer, it was confirmed that a total of 40000 unknown values were estimated in an affordable computational time. In addition, the results of the estimates showed a close numerical and structural similarity to the reference hydraulic conductivity field, confirming that the quality of the estimation by the proposed method is high. In this study, the developed method was applied to a limited case, but it is expected that it can be applied to a wider variety of cases through additional development of the method. The development technique has the potential to be applied not only to the field of hydrogeology, but also to various fields of geology and geophysics. Further development of the method is currently underway.
Keywords
aquifer characterization; inverse analysis; covariance matrix adaptation; evolution strategy; model calibration;
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