Prioritizing climate-resilient housing recovery in conflict-affected Yemen: a district-level MCDA and uncertainty framework

Yemen’s housing recovery requires choices among districts where flood exposure, conflict, displacement and humanitarian need overlap. This study develops a district-level multi-criteria decision analysis (MCDA) framework to identify districts that remain high priorities for early climate-resilient housing recovery under alternative assumptions. The model combines seven dimensions: flood hazard, human exposure, built exposure, climate stress, conflict fragility, displacement pressure and humanitarian severity. Four weighting scenarios are tested, and Monte Carlo perturbation examines rank stability when normalized inputs and scenario weights vary. The model does not estimate direct housing damage; it screens districts under combined physical and social pressures and compares the national ranking with heterogeneous city-level evidence. The highest-ranked districts are Ma’rib, Ma’rib City, Sirwah, Al Marawi’ah, Khur Maksar, Ad Durayhimi, Tuban and Bani Sa’d. Flood-gate, missing-data, internal-weight and sparse-RDT ablation tests preserve the leading pattern, although uncertainty increases near selection thresholds. The framework provides a transparent national screening tool for recovery sequencing, subject to local engineering assessment and stakeholder validation before implementation.