Sensitivity analysis of the geomorphology flood index to extreme rainfall variability in Indonesia
DOI:
https://doi.org/10.61511/calamity.v2i1.2024.1834Keywords:
extreme rainfall, flood, flood hazard mapping, geomorphology flood indexAbstract
Background: Flooding is one of the most frequent and costly natural disasters worldwide. According to DIBI-BNPB data, Indonesia has experienced 11,806 flood events. Flood risk management is crucial to identify flood-prone areas, which can be done through Flood Hazard Mapping (FHM) using the Geomorphology Flood Index (GFI). While GFI relies on topographical factors, Indonesia's rainfall varies significantly, necessitating a sensitivity comparison across different extreme rainfall characteristics. Methods: This study compares conventional GFI (without rainfall) and modified GFI (incorporating extreme rainfall). It determines extreme rainfall return periods of 5, 10, 25, 50, and 100 years using the Generalized Extreme Value (GEV) method. These values are normalized into Ip-A and Ip-B indices, which are then integrated into the GFI model to estimate flood-prone areas. Findings: The Ip-A and Ip-B methods yield different results. At a 100-year return period, Ip-A produces the same flood extent as conventional GFI, whereas Ip-B varies. Maluku, with the highest extreme rainfall (323.91 mm/day), shows a larger flood extent than conventional GFI, while Java, with the lowest (188.11 mm/day), shows a smaller extent. Extreme rainfall variability significantly affects flood potential, making the Ip-B method highly sensitive to such variations. Conclusion: The study concludes that the Ip-A method produces flood potential areas similar to the conventional GFI at a 100-year return period, while the Ip-B method yields different flood extents depending on extreme rainfall intensity. The Ip-B method is highly sensitive to extreme rainfall variations, making it more responsive to regional differences in flood potential. Novelty/Originality of this article: This study introduces a novel approach by integrating extreme rainfall variability into the Geomorphology Flood Index (GFI) using two modified indices, Ip-A and Ip-B, to enhance flood hazard mapping accuracy.
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