Bayesian network modeling of flood cascade and climate risks in the Pearl River Delta

Abstract Climate change and rapid urbanization are intensifying flood vulnerability in highly urbanized delta regions. This study develops a Bayesian network model to assess flood control infrastructure vulnerability (including flood susceptibility and critical failure nodes) and cascading failures in the Pearl River Delta (PRD) under future climatic scenarios. To evaluate future flood hazards, downscaled climate projections from global climate models and a stochastic weather generator were employed to simulate extreme precipitation patterns. Results indicate that in certain PRD areas, 100-year return period design rainstorm values may double by the 2050 s under high-emission scenarios and the central/southeastern PRD face highest cascading flood failures due to dense hydrological interconnectivity and topographic constraints. These findings underscore the urgent need for climate-adaptive infrastructure planning, enhanced early-warning systems, and integrated watershed management. This study offers a systematic, data-driven framework to support resilient urban flood governance in deltaic megacities facing compounding environmental risks.