Evaluating the performance of depth-damage curves in flood damage and risk analysis: a case study from Malaysia

Depth–damage curves (DDC) are widely used in flood risk analysis to represent the range of losses when exposed to a range of flood depth. However, variations in DDCs, whether from international, national, or combined sources, pose challenges for selecting the most accurate curve for local applications, particularly in developing regions. The availability of these varied functions enables scientists and practitioners to perform monetary flood risk evaluations, aiding better investment decisions. However, ensuring that these models are locally validated is crucial, as unverified models can lead to significant inaccuracies. This study aims to compare the performance of international damage curve (IDC), national dam age curve (NDC), and unified damage curve (UDC) in local flood-prone areas of Malaysia where the monetary damages for each models were analysed. Comparisons were made at a community scale, with verification against site-specific damage curves (SDC), which include uncertainty bounds that established using boxplot based on empirical data. Results show that the internationally derived DDC overestimates community-scale aggregated building-level damage by 30 times compared to the SDC, revealing a significant overestimation. Conversely, the aggregated damages using NDC and UDC fall within the SDC’s uncertainty bounds. This demonstrates that integrating national data with international models significantly improves accuracy and reduces overestimation. Ignoring pre-treatment of IDC in flood risk studies could result in an alarming overestimation of damages. This study highlights the indispensable role of local data in ensuring accurate DDC representation and emphasizes the need for coordinated efforts in flood damage data collection and inventory management.

Text 121586.pdf - Published Version Download (2MB) Official URL or Download Paper: https://www.ukm.my/jkukm/wp-content/uploads/2025/3...

Actions (login required)

View Item