An approach for data-driven time-varying flood resilience quantification of housing infrastructure system

Abstract

ABSTRACT Resilience is the ability of infrastructure systems possessing a sufficient acclimatizing property to absorb hazards and return to normalcy post-damage in the least possible amount of time. Quantification of infrastructure resilience requires data collection, which must be accomplished cautiously using the available resources and securing key collaborations with local agencies to fasten and ease the mammoth process. Herein, the collected data were fed into the developed evidence-based Dempster-Shafer (D-S) model to quantify resilience over the desired frame of targeted output possibilities. The data collection procedure was performed with proper predetermined objectives and tools. The subject matter of this research, viz. flood resilience is a time-dependent phenomenon, with a typically higher recovery, as flooding is a long seasonal occurrence. To this end, data has been collected during seven different periods spanning 7 months of the rainy season, the resilience indices were calculated, and profiling was conducted to understand the resilience behavior. In this work, Barak Valley test bed in the North-East India is considered. The resilience indices are utilized as a performance indicator of housing infrastructure resilience, which help to support the decisions of the critical infrastructure owners/operators in risk and resilience management.