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. A good performance of hydrological model for flood simulation isof critical importance for flood forecasting. Taking Yandu River catchment,as the study area, three hydrological models (i.e. Xin'anjiang model,TOPMODEL, artificial neural network model) and a multi-model ensemblesimulation method (i.e. entropy-based method) were applied to simulate thehydrological processes of 30 flood events occurring in 1981–1987. Theperformance of the ensemble members and multi-model ensemble simulationmethod was evaluated by comparing indicators of Nash-Efficiency coefficient,errors in root mean square, peak occurrence time, and relative errors offlood peak discharge, event runoff depth. Results show that thethree hydrological models perform well for hydrological simulation of all 30storm floods with Nash and Sutcliffe Efficiency coefficient of above 0.75and relative error of less than 10 %. However, different model exhibits adifference in simulation errors of peak discharge and peak occurrence time.For example, BP model has the smallest error of 3.78 % for peak dischargesimulation while that of Xin'anjiang model and TOPMODEL are 20.9 % and24.7 % respectively. The entropy-based ensemble simulation method improvedflood simulation accuracy to some extent for all evaluation criteriacomparing to the three hydrological models. It is feasible to applyentropy-based ensemble approach for improving accuracy of flood forecastingin humid regions of China.

Ensemble flood simulation for the typical catchment in humid climatic zone by using multiple hydrological models