Variation of uncertainty of drainage density in flood hazard mapping assessment with coupled 1D–2D hydrodynamics model
Song-Yue Yang (),
Che-Hao Chang (),
Chih-Tsung Hsu () and
Shiang-Jen Wu ()
Additional contact information
Song-Yue Yang: Feng Chia University
Che-Hao Chang: National Taipei University of Technology
Chih-Tsung Hsu: National Center for High-performance Computing, National Applied Research Laboratories
Shiang-Jen Wu: National United University
Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2022, vol. 111, issue 3, No 7, 2297-2315
Abstract:
Abstract Coupled 1D–2D hydrodynamic models are widely utilized in flood hazard mapping. Previous studies adopted conceptual hydrological models or 1D hydrodynamic models to evaluate the impact of drainage density on river flow. However, the drainage density affects not only river flow, but also the flooded area and location. Therefore, this work adopts the 1D–2D model SOBEK to investigate the impact of drainage density on river flow. The uncertainty of drainage density in flood hazard mapping is assessed by a designed case and a real case, Yanshuixi Drainage in Tainan, Taiwan. Analytical results indicate that under the same return period rainfall, reduction in tributary drainages in a model (indicating a lower drainage density) results in an underestimate of the flooded area in tributary drainages. This underestimate causes higher peak discharges and total volume of discharges in the drainages, leading to flooding in certain downstream reaches, thereby overestimating the flooded area. The uncertainty of drainage density decreases with increased rainfall. We suggest that modeling flood hazard mapping with low return period rainfalls requires tributary drainages. For extreme rainfall events, a lower drainage density could be selected, but the drainage density of local key areas should be raised.
Keywords: Uncertainty; Drainage density; Flood hazard mapping; 1D–2D hydrodynamics model (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:spr:nathaz:v:111:y:2022:i:3:d:10.1007_s11069-021-05138-1
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DOI: 10.1007/s11069-021-05138-1
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