Combination of Multiple Data-Driven Models for Long-Term Monthly Runoff Predictions Based on Bayesian Model Averaging

Accurate and reliable long-term runoff forecasting is very important for water resource system planning and management. This study utilized three data-driven models to simulate and forecast the monthly runoff series of the Huangzhuang hydrological station from 1981 to 2017. To improve the accuracy and reduce the uncertainty, two model averaging techniques were applied to merge forecast results of the different models, and 90% confidence...