1. Jang Cheng-Shing and Cheng-Wuing Liu, Hydrol. Process. 18, 1333-1350(2004) Adviser : Jui-Sheng Chen and Cheng-Shing Jang Presenter : Wei-Jie Wang 1

2.  INTRODUCTION  STUDY AREA  METHODS  RESULTS  SUMMARY AND CONCLUSIONS 2

3.  Why?  For establishing a sound water management plan to prevent further drawdown of groundwater levels, land subsidence and aquifer contamination in the Choushui River alluvial fan, Taiwan.  How?  Ordinary Kriging (OK)  Sequential Gaussion simulation (SGS)  MODFLOW 3

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6. Establishing baseline flow model Inverse calibration(pumping and recharge rate) Flow simulation Calculating global simulation errors(SAMSE) Calculating local simulation errors(SAMSE) along flow paths Assessing the different spatial variability of various estimated K fields Heterogeneous K fields by geostatistical methods (OK, mean SGS, individual SGS) 6

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8.  In a baseline flow model, a K field within each zone was constructed by determining a geometrical average of local measured data (Wen and Gómez- Hernández, 1996).  The pumping and recharge rates were inversely adjusted to reduce the difference between simulated and measured heads, and the calibrated errors were expected to fall within a tolerance of 1.5 m for each monitoring well (Gau et al., 1998). 8

9. 9 SAMSE=17.6M

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16. SAMSE=15.1M 16

17. SAMSE=15.5m 17

18. SAMSE=18.4 to 38.4m Mean=27.1M 18

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21.  The OK realization had the smallest sum of SAMSE and the SGS realizations preserved the spatial variability of the measured K fields.  The OK realization yields small local SAMSE in the measured K field of moderate magnitude,whereas the SGS realizations have small local SAMSE in the measured K fields, with high and low values. 21

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