Application of stochastic models for long-range sediment transport during extreme typhoon events
Study Region: The research focuses on the Shihmen Reservoir in northern Taiwan, a multifunctional rolled rockfill reservoir experiencing reduced capacity due to sediment accumulation, which is further exacerbated by significant flood events during typhoons. Study Focus: Our research employs a novel...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-08-01
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| Series: | Journal of Hydrology: Regional Studies |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2214581825002885 |
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| Summary: | Study Region: The research focuses on the Shihmen Reservoir in northern Taiwan, a multifunctional rolled rockfill reservoir experiencing reduced capacity due to sediment accumulation, which is further exacerbated by significant flood events during typhoons. Study Focus: Our research employs a novel fractional stochastic diffusion particle tracking model (FSD-PTM), incorporating fractional Brownian motion to account for the long-range dependencies observed in suspended sediment transport during extreme typhoon events. By capturing these dependencies, the model offers improved predictions of sediment dynamics, essential for understanding and managing sediment-related challenges in hydrological reservoir systems under severe weather conditions, thereby supporting operational safety and environmental compliance. New Hydrological Insights for the Region: The application of the FSD-PTM has provided new insights into sediment dynamics during typhoon events in the Shihmen Reservoir. Traditional models based on memoryless diffusion often fail to represent the persistence observed in suspended sediment transport under sustained turbulent flows. By incorporating long-range dependence into the particle motion framework, this study highlights the importance of memory effects in simulating sediment spread. These findings support more accurate predictions of sediment deposition patterns, providing a scientific basis for adaptive reservoir operation strategies in response to intensifying climatic extremes. |
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| ISSN: | 2214-5818 |