Climate change has intensified flood risks in Mozambique, necessitating resilient infrastructure designs to mitigate impacts. The methodology employs Bayesian hierarchical modelling to predict future flooding patterns, incorporating local rainfall variability and population density. Social impact assessments are used alongside cost-benefit analyses to evaluate project feasibility. Predicted annual floods affect approximately 20% of Mozambique's urban areas, with a median loss ratio of 1: 3 per household investment in flood defenses. The methodological approach provides a robust tool for infrastructure planners aiming to enhance resilience against future flooding events. Infrastructure designs should prioritise densely populated and economically vulnerable regions identified by the model. climate change, hydrological modelling, socioeconomic impact assessment, flood management, Bayesian hierarchical models
Nhamatade Mafukuzulu (Fri,) studied this question.