Ice flood disasters represent the most severe natural hazards affecting the Yellow River during winter-spring periods, posing significant threats to residents’ safety and impeding regional socioeconomic development in the basin. Despite their critical implications, systematic risk assessment methodologies tailored for Yellow River ice floods remain underdeveloped. Current approaches inadequately address the inherent uncertainty and fuzziness characteristics of ice flood disaster systems, thereby compromising assessment accuracy. To bridge this gap, this study develops an integrated risk assessment model combining Unascertained Measure Theory (UMT) and Variable Fuzzy Set Theory (VFST). The hybrid model was implemented in three typical reaches of the Yellow River’s Inner Mongolia section: Tokto County, Jungar Banner, and Qingshuihe County. Risk evaluation results classified Tokto County and Qingshuihe County as “medium-risk” areas, while Jungar Banner was identified as a “high-risk” zone. Validation analyses confirmed strong consistency between model outputs and historical disaster patterns, demonstrating the framework’s reliability. This research establishes a novel methodological foundation for ice flood risk quantification and provides actionable insights for disaster mitigation strategies in cold-region river systems. The proposed approach offers technical support for enhancing flood management decision-making processes in the Yellow River Basin.
Deng et al. (Fri,) studied this question.