Comprehensive analysis of data aggregation techniques for flood vulnerability and bivariate flood risk mapping of a coastal urban floodplain

Aggregation techniques that are frequently used to quantify indicator-based flood risk or vulnerability are often prone to rank-reversal problems. This necessitates the need to identify a robust aggregation technique in this context. This study aims to develop a framework for mapping flood risk by quantifying indicator-based flood vulnerability using a reliable data-aggregation technique. Further, this approach is integrated with hydrodynamic modelling to assess flood hazard, while considering potential near-future Land-Use-Land-Cover (LULC) changes. Total 12 indicators were identified and categorized into physical, socio-economic, and environmental vulnerability components. Among the widely employed techniques that include Analytical- Hierarchy-Process (AHP), entropy, Principal-Component-Analysis, integrated AHP-TOPSIS, and AHP-Entropy, AHP-TOPSIS approach is found to be more stable to rank-reversal problem. Therefore, using AHP-TOPSIS approach, flood vulnerability is quantified. A quasi-2D hydrodynamic model has been used to predict flood depth, velocity, and momentum for flood magnitudes of 1 in 50-, 100- and 250-year return periods, while accounting for projected LULC changes of year 2035. Flood risk is then mapped using bivariate choropleth scheme which inherently distinguishes dominant element among hazard and vulnerability. Additionally, adaptive capacity of the region is mapped by considering temporary-shelters, building-heights, literacy, and road- network. The results showed that the regions falling under high to very-high flood risk categories are constantly increasing under the influence of LULC changes as well as increasing flood magnitudes. Although urban areas exhibit high vulnerability, high adaptive capacity helps mitigate the risk of loss of life. However, damage to infrastructure and the economy exist. These findings provide insights for effective non-structural flood mitigation strategies.