Water Level Prediction at TICH-BUI river in Vietnam Using Support Vector Regression

Abstract

In this paper, the support vector regression model is used to predict water levels at a downstream station of the Tich-Bui river basin. The study investigated the effects of rainfall data collected from eight gauging stations and water levels at the downstream station for the performance forecast. The model was set up to forecast water levels at the downstream station before 6-lead-hour, 12-lead-hour, 18-lead-hour and 24-lead-hour. Although the model does not require data on the climate, terrain but the forecast results are accurate. In the case of a water level forecast before 6 hours and 12 hours, the Nash coefficient gives a value of over 98.81% and the RMSE value is less than 0.20 m. This results suggest that the support vector regression model, which the authors use to accurately predict water levels in real time, can be used to warn of floods in Vietnam's rivers.