Stochastic discrete event simulation for government assisted owner driven participatory housing recovery modeling: Application to 2015 Gorkha earthquake sequence, Nepal

We develop and implement a Stochastic Discrete Event Simulation (SDES) algorithm to model the housing recovery trajectory after an extreme event. The algorithm models discrete events and their underlying uncertainties in each construction phase. Specifically, the algorithm is developed for the Government Assisted Owner Driven (GAOD) reconstruction system to simulate long-term recovery trajectory. SDES, as a flexible modeling approach, can simulate any housing recovery scenario that follows phased reconstruction. The 2015 M 7.8 Gorkha earthquake sequence in Nepal is considered the extreme event, with 796,245 buildings requiring reconstruction. We present some recovery trajectories from severely hit, crisis hit, and earthquake hit parishes, comparing them with the actual reconstruction progress. We also assess quality and improvement of reconstructed buildings using seismic fragility functions, compared to pre-earthquake constructions. Housing recovery uncertainties are dissected in relation to reconstruction pace. We conclude that the vast majority of the reconstructed buildings followed the Build Back Better (BBB) approach and missed the opportunity to pursue the Build Back Resilient (BBR) approach due to multifaceted challenges ranging from unclear policies to economic constraints. We critically assess the GAOD vs Owner Driven (OD) recovery framework and conclude that insurance-supported and technically assisted OD approach could be the most suitable model for post extreme event housing recovery.