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.
CEPAT has chosen to apply the Creative Commons Attribution NonCommercial 4.0 License (CC BY-NC 4.0) to all manuscripts to be published. Authors who publish with this journal agree to the following terms.
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work’s authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal’s published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.
