Forecasting of Amount of Rainfall in Rainy Season by using Information Obtained from El Nino Data

Abstract

In electric power system operation and dam management, it is important that we forecast the rainfall depth in the rainy season. This paper studies the technique using neural network in order to forecast the amount of rainfall in rainy season on upper district of dam for hydro power plant. A case study was carried out on Central Japan. We were able to confirm the effectiveness of the information obtained from El Nino and La Nina data.