Rusmawan Suwarman
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Abstract
Floods are one of the hydrometeorological disasters that often occur in Indonesia, causing economic losses , social, and environmental significance. To overcome this challenge, a technology-based flood early warning system was developed through collaboration between the Bandung Institute of Technology (ITB) and the Geospatial Information Agency (BIG). This system is designed for the Kendal Regency, Batang Regency, Pekalongan Regency and Pekalongan City areas, with the aim of providing information on predicting flood inundation quickly and accurately to the community and stakeholders.
The methodology for developing this system involves a >lookup table, which consists of two main stages: database building and prediction system operation. The database development stage includes processing GSMaP satellite rainfall data using the Monte Carlo method to overcome data uncertainty. This data produces aprobabilistic rainfall data ensemblethat reflects various rainfall pattern scenarios. Next, the hydrology and flood models are developed using theRain-on-Gridapproach, which processes direct rainfall input at each cell in the study area. Historical data on river discharge and flood inundation are used to build empirical correlations between rain, discharge and inundation.
The operational prediction system stage is carried out by utilizing high-performance computing (HPC) to run probabilistic model on a daily basis. Weather predictions from the Global Forecast System (GFS) are used to update rainfall and flood inundation prediction data, which includes information on inundation depth (low, medium and high) along with its probability. This data is then presented in a visual format via the WebGIS platform, allowing easy and fast access via an interactive dashboard on the site seiswing.com/igt.
This project also involves validation and refinement through field supervision on 5 June and 4 September 2024, as well as focus group discussions (FGD) with BPBDs from target areas on 7 November 2024. This ensures that the system is not only technically relevant but also meets needs local.
The results achieved include a flood inundation prediction system that is integrated with spatial and temporal data, providing reliable prediction information up to three days in advance. This system is expected to increase community preparedness, support decision making by local governments, and reduce the risk and impact of flood disasters. With technology-based innovation and cross-sector collaboration, this early warning system is a step forward in managing the risk of hydrometeorological disasters in Indonesia.
Availability of flood hazard prediction modeling. Availability of quality spatial visualization of flood hazard modeling.
For Expertise Groups: Gaining exposure to KK SA can contribute to the field of hydrometeorological disasters. For the Meteorology Study Program: Gain good experience to broaden your knowledge in teaching or laboratory activities. For ITB: This project involves collaboration with KK between Faculties. For Indonesia: This project contributes to increasing the capacity of communities/government institutions in dealing with disasters.