A comparative study of different objective functions to improve the flood forecasting accuracy
In the calibration of flood forecasting models, different objective functions and their combinations could lead to different simulation results and affect the flood forecast accuracy. In this paper, the Xinanjiang model was chosen as the flood forecasting model and shuffled complex evolution (SCE-UA) algorithm was used to calibrate the model. The performance of different objective functions and their combinations by using the aggregated distance measure in calibrating flood forecasting models was assessed and compared. And the impact of different thresholds of the peak flow in the objective functions was discussed and assessed. Finally, a projection pursuit method was proposed to composite the four evaluation indexes to assess the performance of the flood forecasting model. The results showed that no single objective function could represent all the characteristics of the shape of the hydrograph simultaneously and significant trade-offs existed among different objective functions. The results of different thresholds of peak flow indicated that larger thresholds of peak flow result in good performance of peak flow at the expense of bad simulation in other aspects of hydrograph. The evaluation results of the projection pursuit method verified that it can be a potential choice to synthesize the performance of the multiple evaluation indexes.