RESEARCH OF YEAR-ROUND DAM INFLOW PREDICTION BY THE ELASTIC NET CONSIDERING ENSEMBLE RAINFALL PREDICTION AND SNOWMELT

Abstract

 Objective of this study is to propose year-round dam inflow forecasting method by introducing snowmelt into the Elastic Net, in addition to taking into account the uncertainty of the forecast by using ensemble rainfall forecasts. In recent years, climate change has caused more frequent and severe flooding not only during the summer due to heavy rainfall, but also during the snowmelt season.With this in mind, there is a need for inflow forecasting that can be used for effective dam operation. In this study, we used Elastic Net, a sparse modeling method, to predict inflow at a dam in Hokkaido, Japan. The ensemble rainfall forecast was introduced as an explanation variable to the model. In addition, the snowmelt calculated by the Degree Hour method using the Analytical Snow Depth and air temperature in MSM was used as an explanation variable, and it was shown that the inflow rate could be predicted with good accuracy throughout the year.