A technique for quantifying groundwater pumping and land subsidence using a nonlinear stochastic poroelastic model

Abstract

Subsidence in Yunlin County, Taiwan, is serious and continuous. The Taiwan High Speed Rail (THSR) route crosses the subsidence area and might be affected by differential settlements. It is important to evaluate the pumping quantity for water resource management and to predict the subsidence for land resource management to mitigate the subsidence problem in Taiwan. This study combines first-order second-moment (FOSM) stochastic poroelastic theory with nonlinear parameters to develop a FOSM nonlinear stochastic poroelastic model and applies it to quantify groundwater pumping and future subsidence with uncertainty. The additional loading and discharge are evaluated by fitting the subsidence historical data to the numerical model. The results show that the proposed model well describes the subsidence behavior and quantifies groundwater pumping. However, the numerical results are larger than the monitoring data at various depths, which might be due to the different compaction situations in individual formations of the aquifer system. The predicted subsidence at the Yuanchang monitoring well is the largest (0.32 ± 0.52 m in 2020) with consideration of the climate change effects, achieved by adding an additional discharge of 31.7 %. The large uncertainty is caused by the large variation of hydraulic conductivity caused by the heterogeneity of the aquifer system, which could be improved by doing more experiments or using a conditioned model. The information provided in this study is useful for the safety of THSR and for land and groundwater resource management in Yunlin County, Taiwan.