Impact-Based Forecasting Model for Flood Hazard Mitigation in Java, Indonesia

Flooding is the most frequent and damaging hydrometeorological disaster in Indonesia, with Java being especially vulnerable due to its dense population and rapid urbanization. This study aims to refine the Impact-Based Forecasting (IBF) model to improve flood hazard predictions and mitigation efforts. Using Global Precipitation Measurement (GPM-IMERG) rainfall data as the hazard component combined with vulnerability and capacity datasets from InaRISK, this research focuses on enhancing the precision and reliability of impact assessments.

Initial analyses highlight the potential of impact-based rainfall thresholds and assessment probabilistic impacts to refine the IBF model and reduce subjectivity in impact assessments. By linking calculated impact values and disaster magnitudes for the 2014 – 2023 period, this study shows a promising skill for significant and severe flood events, although improvements are needed for minor and minimal disaster classifications.

This research lays the groundwork for a more robust and scalable IBF model tailored to Java’s unique challenges. The findings aim to support BMKG’s operational needs, enabling the delivery of more actionable early warnings and targeted disaster preparedness measures. By addressing critical gaps in existing IBF systems, this study contributes to bridging the divide between hazard-impact forecasts and societal resilience, ultimately mitigating the impacts of floods in Indonesia.