STUDY ON GENERALIZATION OF DAM INFLOW PREDICTION METHOD USING ELASTIC NET BASED ON CLUSTERING OF GEOGRAFICAL CONDITIONS

Abstract

 This study proposes a generalized method for predicting Japanese dam inflow with various basin characteristics. Climate change has several consequences, including frequent major flooding. Accordingly, the Japanese government has announced a policy against floods, such as pre-flood discharges, even at wateruse dams without flood control measures. Proper dam functioning requires establishing an inflow prediction method. However, creating prediction models individually for the numerous dams that exist throughout Japan is complicated and requires intensive labor and time; thus, establishing a generalized prediction method that can be applied to multiple dams would be advantageous. In this study, we attempted to generalize the inflow prediction method using Elastic Net, a sparse modeling method. We clustered dams based on the geographical information of the basin and selected a model representative for each cluster to generalize the prediction method.