Estimating future (next-month’s) spatial groundwater response from current regional pumping and precipitation rates

Abstract

The equilibrium of natural groundwater systems can be disrupted by excessive withdrawal. Accurate estimation of groundwater levels is needed to assess water-level fluctuations caused by groundwater withdrawal and seasonal distributions of precipitation. This study aims to estimate the next-month’s groundwater levels using monthly real-world data that includes rainfall, electricity-estimated pumping volumes, and current groundwater levels invoking time-dependent spatial regression. The new approach involves state-estimation and change-estimation methods, which will be evaluated to determine the optimal model based on its root mean square error values. The response of estimated future (next-month’s) groundwater levels within the alluvial fan in Changhua and Yunlin, Taiwan is based on monthly precipitation and pumping. This study yields a data-driven explanation of how water levels temporally and spatially respond to groundwater pumping and rainfall infiltration in different regions within the alluvial fan. Results indicate that the proximal fan yields the smallest response to decreased groundwater levels and subsequent increases in pumping. The effect of reducing groundwater levels is greater in the southern areas of the study site than in the northern areas. Water levels in the mid-fan and distal-fan in the southern area show a greater drawdown due to larger pumping volumes compared to the northern area.