A Prediction of Total Amount of River Flow Rate Following a Spell of Rainfall by Using Radar Echo Data

摘要

This paper describes an application of neural network for prediction of total amount of river flow rate from the meteorological radar echo data. A neural network system is developed through a case study on a dam for hydropower plant located the upper district of the Yahagi River in Central Japan. The prediction system has 6 input nodes corresponding to the rainfall amounts from radar echo data, four ground rainfall gauges and the base flow rate. The output from the system is the predicted total amount of river flow. In addition, the same concept applies to estimating of runoff ratio. It is found from our investigations that predictions of total amount of river flow rate and estimation of runoff ratio are improved by utilization the radar echo data.