Governance of PPPs under climate-induced flood risk: a bayesian and bargaining-based approach

Introduction Public–private partnerships (PPPs) are increasingly adopted as mechanisms for financing and delivering critical infrastructure. However, their resilience under climate-induced hazards, particularly floods, remains underexplored. Methods This study develops a hybrid framework that integrates Bayesian network (BN) modeling, Monte Carlo (MC) simulation, and Nash bargaining (NB) to evaluate flood losses and negotiate risk-sharing arrangements in PPP contracts. Using Gonbad-e Kavus, Iran, as a case study, four flood scenarios were analyzed: the 2019 historical flood, and 100-, 1,000-, and 10,000-year return periods. Results The BN–MC module quantified probabilistic losses across sectors (buildings, agriculture, and infrastructure), capturing both expected damages and associated uncertainties. These results were then embedded in a NB framework, where public and private stakeholders negotiated risk allocations under varying utility preferences. Validation against the 2019 flood demonstrated close alignment between simulated and observed damages, with error margins below 5%. Discussion The findings reveal that catastrophic flood scenarios shift a greater share of risks toward the private sector, while sensitivity analysis confirms the robustness of negotiated outcomes against changes in stakeholder utility weights. By linking probabilistic hazard modeling with governance-oriented bargaining, this research provides a novel contribution to PPP resilience studies and offers actionable insights for designing adaptive contracts in flood-prone regions.