Abstract：Tank model is a helpful tool for rainfall-groundwater-runoff analysis since it can represent a nonlinear transport behavior and get solutions very quickly. It is known that the successful application of one conceptual model mostly depends on how well its parameters can be calibrated. Recently，in many literatures，it is indicated that by use of existing calibration methods，the calibration process with many parameters(such as multi-tank model proposed in this paper has parameters over 20) is typically difficult，sometimes even impossible to obtain unique optimal parameters. A new random optimization approach called dynamically dimensioned search(DDS) algorithm is introduced and improved for parameters calibration of tank model. DDS is designed for calibration problems with many parameters，requires no complicated algorithm parameter to be adjusted，and automatically scales the search to find good solutions within the maximum model evaluations. Tank model with 27 parameters is applied to the actual case；and DDS algorithm is adopted to find optimal solutions. The calculated runoff roughly agrees with the measured values. Finally a comparison between finite element method(FEM) and tank model is conducted，which shows that during rainfall infiltration，the multi-tank model has advantages over FEM in the simulation process of predicting groundwater table. It is clarified that the multi-connected tank model is useful in groundwater table prediction of the basin especially when the slope stability analysis is necessary there.
