Flood Risk Visualization and Prediction Information System: Case of City Manila, Philippines

Abstract

Nowadays, the need for flood management using non-structural measures is becoming vital to experts and decision-makers. While technological intervention using information systems for flood risk visualization is widely recognized, the assimilation of flood risk prediction is nascent in the literature. This research presented the Flood Information System as an assistive tool for managing floods in the urban capital integrating analytics and machine learning algorithms for a more dynamic flood risk visualization and prediction. This paper shows that flood management information systems added value in monitoring and predicting flood risk areas in Manila City, Philippines.