An integrated approach for modelling and quantifying housing infrastructure resilience against flood hazard

Abstract

Housing infrastructure is a basic human need and thus should be resilient against natural disasters. Therefore, an effective resilience-based framework for housing infrastructure is required to enhance the endurance capacity of housing and for effective recovery. Involving an expert opinion is also required for the representation of the nonlinear, complex relationship between the flood resilience parameters for housing infrastructure. In this work, initially, a hierarchical flood resilience model for housing infrastructure is developed using the decision-making trial and evaluation laboratory (DEMATEL) and the interpretive structure modeling (ISM) methods. The relationships among various resilience parameters related to flood hazards are obtained using integrated DEMATEL and ISM following the data received from expert opinions. Next, a flood resilience-based decision-making framework is developed integrating DEMATEL, ISM, and Bayesian Network (BN) methods. A field survey collects all the postdisaster data to feed in the BN model, capturing the interrelationship among the resilience parameters. Finally, the developed framework is implemented for a community in northeast India for flood resilience assessment and risk-informed decision making. It has been observed from the result that the resilience of the housing infrastructure for most of the surveyed places are extremely low, which means houses of those areas should be immediately strengthened. The evaluated resilience values provide the vulnerable scenarios of housing infrastructure of that community against flood hazards, which help the public authority of that community. Additionally, the identification of the most sensitive parameter/s among all considered parameters helps in decision making for future hazards.