Information system for extreme rain index prediction and potential flood warning based on rain radar in Jakarta area
Abstract
In Indonesia, significant variations in rainfall are a severe challenge, especially in the Special Capital Region (DKI) Jakarta, which is very vulnerable to flooding and the effects of climate change compared to other coastal areas in Southeast Asia. This flood caused considerable losses to society, industry, and government. Inaccurate predictions of rainfall lead to difficulties in anticipating floods and landslides, causing an expansion of the impact of these disasters. Therefore, a solution such as "Extreme Rain Index Prediction Information System and Rain Radar-Based Flood Potential Warning System for Jakarta” is needed. This system uses SANTANU rain radar and GSMaP satellite data to visualize real-time rainfall with Server-Sent Event (SSE) techniques. It also employs a Random Forest model to predict extreme rainfall and potential flooding by combining the output from PyStep-based radar nowcasting and Numerical Weather Prediction (NWP). Even though the predicted flood potential is accurate (93.75% accuracy, AUC 0.93), the prediction of flood movement using PyStep is not precise (RMSE 2.8, IoA 0.57), affecting the accuracy of the flood potential prediction. This system visualizes rain from SANTANU and GSMaP radars in real time and estimates the potential for flooding. Further efforts are needed to improve predictions of flood movements for better accuracy of flood potential information.
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