Ice flood disaster risk assessment of the Inner Mongolia reach in the Yellow River based on unascertained measure theory-variable fuzzy sets

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.

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Publication Details

Journal
PLoS ONE
Published
2026-05-29
DOI
https://doi.org/10.1371/journal.pone.0350284
Primary Topic
Flood Risk Assessment and Management
Type
article
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article

Ice flood disaster risk assessment of the Inner Mongolia reach in the Yellow River based on unascertained measure theory-variable fuzzy sets

Yu Deng, Lu Jiang, Juan Wang
PLoS ONE
Flood Risk Assessment and Management
article

Ice flood disaster risk assessment of the Inner Mongolia reach in the Yellow River based on unascertained measure theory-variable fuzzy sets

Yu Deng, Lu Jiang, Juan Wang
article en

Abstract

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.

PLoS ONEVol. 21(5)
Zhengzhou University (CN), Henan Province Water Conservancy Survey and Design Research (CN), Yellow River Institute of Hydraulic Research (CN), Henan Provincial Center for Disease Control and Prevention (CN)
Climate action
Openalex Percentile: Top 6%
Flood Risk Assessment and Management
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Ice flood disaster risk assessment of the Inner Mongolia reach in the Yellow River based on unascertained measure theory-variable fuzzy sets — Yu Deng, Lu Jiang, et al. · PLoS ONE (2026) | TGRS Research Map | TGRS