Identification of net groundwater recharge rate using an expert system model: a case study of Pintung plane

Abstract

Groundwater parameter techniques can be classified into two categories: tried and error methods and auto-calibration methods. Tried and error methods usually are time consuming. Most auto-calibration techniques are optimization techniques which rely on sensitivity analysis or a gradient search, which have increased computational demands with increasing parameter dimension. In addition to run time constraints, the applicability of optimization techniques is restricted by its difficult mathematical set up required in its implementation. This paper develops a rapid parameter calibration model, named RGEIS, using the combination of the expert system model and the groundwater simulation model to reduce the computational time and increase the model applicability. The developed model is applied to identify the net recharge rate, the summation of total recharge and total extraction of the study area, of Pintung plane in southern Taiwan. Pintung plane has an area of 78 km x 30 km with 3 aquifers and complex geological conditions. The study area is divided into 104 parameter zones. Since the planning horizon is 12 months, the total number of the net recharge rate to be calibrated is 1248 (104x12= 1,248). However, only 2,252 seconds are needed for the net recharge identification. The result shows accuracy and efficiency of the proposed model.