Improvement of Rainfall-Runoff Simulations Using the Runoff-Scale Weighting Method

Abstract

Objective selection and tradeoffs have always been key central issues in rainfall-runoff models. In general, precision for high and low flows cannot be achieved or considered concurrently. Combination forecasts are potentially capable of producing more suitable or superior results through appropriate methods. In this study, we propose an automatic method, a runoff-scale weighting method (RSWM), to solve issues regarding flow precision trade-offs. Objective functions that emphasize precision at various flows were used to conduct combination forecasts and validate the effectiveness of this method. The results indicated that combination forecasting is capable of improving precision during all flow stages to further enhance model effectiveness. In addition, we used the fuzzy multiobjective function simple-average (FMOF-SA) and fuzzy multiobjective function-low (FMOF-low) as reference flows to test the robustness of parameters to determine whether the RSWM is affected by reference flows. The results indicated that the FMOF-low is relatively more robust than the FMOF-SA, although both had only a slight influence on the final results. According to the final results, the mean absolute relative residual of most flow stages is approximately 0.2, which shows that the RSWM can be applied to various runoff conditions.