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• W4240711151 abstract "Abstract. Multiple-point geostatistic simulation (MPS) has recently become popular in stochastic hydrogeology, primarily because of its capability to derive multivariate distributions from the training image (TI). However, its application in three dimensional simulations has been constrained by the difficulty of constructing 3-D TI. The object-based TiGenerator may be a useful tool in this regard; yet the sensitivity of model predictions to the training image has not been documented. Another issue in MPS is the integration of multiple geophysical data. The best way to retrieve and incorporate information from high resolution geophysical data is still under discussion. This work shows that TI from TiGenerator delivers acceptable results when used for groundwater modeling, although the TI directly converted from high resolution geophysical data leads to better simulation. The model results also indicate that soft conditioning in MPS is a convenient and efficient way of integrating secondary data such as 3-D airborne electromagnetic data, but over conditioning has to be avoided." @default.
• W4240711151 created "2022-05-12" @default.
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• W4240711151 date "2013-09-26" @default.
• W4240711151 modified "2023-10-10" @default.
• W4240711151 title "The effect of training image and secondary data integration with multiple-point geostatistics in groundwater modeling" @default.
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• W4240711151 doi "https://doi.org/10.5194/hessd-10-11829-2013" @default.
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