EXTRAPOLATION OF PREDICTIONS OF DAM INFLOW BASED ON THE SPARSE MODELING METHOD

Abstract

This study aimed to propose a method for the extrapolation of dam inflow predictions applicable to water utilization dams. In recent years, in response to the frequent floods that have occurred nationwide, improing the flood control function of dams through leveraging pre-emptive discharge has attracted attention. How-ever, as there is little observed information regarding water utilization dams and because specific flood control operations have not been decided upon, there is concern regarding the adverse effects of such ac-tions on water use. Therefore, difficult judgments on the implementation of pre-emptive discharge are re-quired, which increases the burden on managers. In tandem with this, there is a desire to improve the accu-racy of inflow prediction in water utilization dams. In this study, we propose a regression model that can predict the inflow of dams based on analysis using Elastic Net, a sparse modeling method that is utilized to identify relationships between data from small amounts of information. In summary, we were able to pro-pose a method to make predictions, even in circumstances with scarce information gleaned from observa-tion.