PREDICTION OF DAM STORAGE LEVELS AND THE VOLUME OF DISCHARGE ASSOCIATED WITH DISASTER PREVENTION MANAGEMENT DURING EXTREME FLOODING USING ELASTIC NET

Abstract

 The current study aimed to propose a method for the prediction of inflow, storage levels, and discharge flow rates from dams for extreme flood disaster prevention management. In recent years, owing to the damage from frequent large floods nationwide, the prediction of water storage levels and discharge flow rate to be utilized for effective dam management has become critical. In this study, using Elastic Net, a sparse modeling method capable of identifying relationships between data even from small amounts of information, we predicted the inflow volume for dams that have experienced cases in the past wherein engaging disaster prevention management was required during extreme flooding. Subsequently, the water storage level was estimated based on predicted inflow and discharge based on operational regulations. Furthermore, the predicted discharge flow rate was shown to be effective for predicting the water level of downstream rivers. In summary, it is considered that the proposed method can be utilized in judging pre-emptive discharge and recognizing the effect of the discharge on the downstream area.