日本地球惑星科学連合2021年大会

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[E] 口頭発表

セッション記号 M (領域外・複数領域) » M-GI 地球科学一般・情報地球科学

[M-GI30] Near Surface Investigation and Modeling for Groundwater Resources Assessment and Conservation

2021年6月4日(金) 15:30 〜 17:00 Ch.12 (Zoom会場12)

コンビーナ:Jui-Pin Tsai(National Taiwan University, Taiwan)、谷口 真人(総合地球環境学研究所)、Ping-Yu Chang(National Central University)、座長:Jui-Pin Tsai(National Taiwan University, Taiwan)、Shao-Yiu Hsu(National Taiwan University)

16:00 〜 16:15

[MGI30-03] Stochastic-based Approach to Quantify the Uncertainty of Groundwater Vulnerability

*Chuen-Fa Ni1、Tien-Duc Vu1、Kim-Tu Tran 1、Wei-Ci Li1 (1.National Central University)

キーワード:groundwater vulnerability, stochastic approach, MODFLOW, DRASTIC

The study proposes a stochastic approach to quantify the uncertainty of groundwater vulnerability (GV). In the study, the physical-based MODFLOW model has been integrated with the DRASTIC method modified by the analytical hierarchy process (AHP) technique. Specifically, the flow fields from the MODFLOW model provide the parameter of depth to water and the associated hydraulic conductivity (K) for the DRASTIC method. The integrated loops between MODFLOW and DRASTIC method enable the evaluations of GV maps by considering stress changes applied to an aquifer system. The study focused on the uncertainty produced by the natural logarithm of K (lnK) heterogeneity. Different degrees of lnK heterogeneity were assessed to quantify the impact of the lnK heterogeneity on the GV maps. Results show that the stochastic-based GV performs a better match of nitrate concentration pattern. There are large discrepancies of GV values in both the spatial distribution and intensity in all GV classes by considering the input uncertainty in the GV mapping. The results clarify the potential risk of groundwater contaminations in the Pingtung Plain groundwater basin.