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Model Identification Criteria for Inverse Estimation of Hydraulic Parameters
Author(s) -
Hyun Yunjung,
Lee KangKun
Publication year - 1998
Publication title -
groundwater
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.84
H-Index - 94
eISSN - 1745-6584
pISSN - 0017-467X
DOI - 10.1111/j.1745-6584.1998.tb01088.x
Subject(s) - identification (biology) , aquifer , set (abstract data type) , anisotropy , field (mathematics) , data mining , data set , inverse , estimation theory , computer science , geology , mathematics , statistics , algorithm , geotechnical engineering , groundwater , geometry , physics , botany , pure mathematics , biology , programming language , quantum mechanics
This study deals with the problem of model structure identification when the zonation method is adopted for parameterization. Our method applies four identification criteria, recommended by Carrera and Neuman (1986a), to a synthetic model and to a set of field data from the Taegu area, Korea. Study of the synthetic model demonstrates that the quality of head data, the depth of data acquisition, and the anisotropy ratio of parameters are important factors for the parameter structure when it is identified using the four criteria. It also shows that a specific criterion is not preferable for every case, but that all four criteria should be considered in order to choose the best among a set of alternative aquifer zonation models. The field example shows that the anisotropy of aquifer parameters should be considered for the parameterization of crystalline rock aquifers, which are the most common systems in Korea.