Comparative analyses of flood damage models in three Asian countries: towards a regional flood risk modelling

The use of different approaches in the development of flood damage models in various countries is expected to affect flood damage modelling at a regional or global scale. Since these models are often used as tools for disaster management and decision making, it is very needful to understand the comparative similarity and differences in countries’ loss models; this can help in the overall integration for developing regional risk models and cross-country risk assessment. In this study, empirically generated generalised loss models in three Asian countries (Sri Lanka, Thailand and Japan) were compared and applied to estimate potential flood damages in two different urban river basins. For each case study, each model was normalised using cost prices and floor areas (as applied to each country) and were integrated within the Geographic Information Systems (GIS) to estimate damages for the flood events. Using the mean vulnerability index of corresponding building types for the selected countries, a single model for regional flood risk assessment was created. However, the study showed that there are variations in the vulnerability and the potential flood damage estimates of similar global building types from the three countries, despite being developed by the same approach. These are attributed to the country’s specific conditions such as building regulations and codes, GDP per capita, cost price of building materials. Our results suggest that the average vulnerability index from the countries however reduced potential errors in the estimates. Moreover, it is proposed that the average regional vulnerability model derived with empirical data inputs from all the countries for regional risk assessment and cross-country comparison. Therefore, it can predict near accurate potential flood damages, which can serve as measures for regional flood disaster risk management plans. © 2018, Springer Science+Business Media, LLC, part of Springer Nature.