Physical flood vulnerability assessment using geospatial indicator-based approach and participatory analytical hierarchy process: A case study in Kota Bharu, Malaysia

• المؤلفون الرئيسيون: Kaoje, Ismaila Usman, Abdul Rahman, Muhammad Zulkarnain, Idris, Nurul Hazrina, Razak, Khamarrul Azahari, Wan Mohd. Rani, Wan Nurul Mardiah, Tam, Tze Huey, Mohd. Salleh, Mohd Radhie
• التنسيق: مقال
• اللغة: English
• منشور في: MDPI AG 2020
• الموضوعات: GE Environmental Sciences
• الوصول للمادة أونلاين: http://eprints.utm.my/id/eprint/93367/1/MuhammadZulkarnain2020_PhysicalFloodVulnerabilityAssessmentusingGeospatial.pdf; http://eprints.utm.my/id/eprint/93367/; http://dx.doi.org/10.3390/w13131786

The most devastating flood event in Kota Bharu was recorded in December 2014, which affected several properties worth millions of dollars and thousands of homes. Damage to physical properties, especially buildings, is identified as a significant contributor to flood disasters in Malaysia. Therefore, it is essential to address physical flood vulnerability by developing an integrated approach for modeling buildings’ flood vulnerability to decrease the flood consequences. This study aims at developing a flood vulnerability assessment approach using an indicator‐based model (IBM) for individual buildings in Kota Bahru, Kelantan, Malaysia. An intensive literature review and expert opinions were used to determine suitable indicators that contribute to the physical flood vulnerability of buildings. The indicators were grouped into three components, i.e., flood hazard intensity (I), building characteristics (C), and effect of the surrounding environment (E). The indicators were further refined based on expert opinions and Relative Importance Index (RII) analysis. Based on their contribution to the Malaysia local building flood vulnerability, priority weight is assigned by the experts to each of the selected indicators using the participatory Analytical Hierarchy Process (AHP). A spatial database of buildings in Kota Bharu is developed through field surveys and manually digitizing building footprints from satellite imageries. The identified indicators and their weight are added to each building footprint. The Weighted Linear Combination (WLC) aggregation method combined the weight of indicators into a vulnerability index and maps. The results of a physical flood vulnerability were validated using building damage information obtained through interviews with the community that experienced previous flood in the study area. The result showed that about 98% of the study area’s buildings have either moderate or low vulnerability to flooding. The flood vulnerability map has an overall accuracy of 75.12% and 0.63 kappa statistics. In conclusion, the IBM approach has been used successfully to develop a physical flood vulnerability for buildings in Kota Bharu. The model contributes to support different structural and non‐structural approaches in the flood mitigations process.