Measures for improving dam operation and research trends in AI-based inflow prediction

Abstract

The implementation of measures to advance dam operation focuses on the promotion of Hybrid Dams, which aim to achieve both adaptations to increasingly severe torrential rain disasters due to climate change and promotion of hydroelectric power generation. A key to realizing this is inflow prediction technology, with expectations for the use of AI. This paper introduces research trends in Japan and overseas. AI-based inflow prediction research is actively progressing both domestically and internationally, with various models centered on deep learning being proposed and giving good results. Multi-faceted approaches are being explored, including handling low-frequency and unprecedented cases, application of reinforcement deep learning, consideration of prediction uncertainty, model generalization, and snowmelt period predictions. On the other hand, challenges include strengthening responses to unprecedented floods, evaluating prediction uncertainties, and interpreting the causal relationships of black-box models like the deep neural network.