4.7 Article

Impact of Tides and Surges on Fluvial Floods in Coastal Regions

期刊

REMOTE SENSING
卷 14, 期 22, 页码 -

出版社

MDPI
DOI: 10.3390/rs14225779

关键词

compound flood; hydrodynamic model; sea water level; tide and surge

资金

  1. Zhejiang Provincial Natural Science Foundation of China [LY22E090011]
  2. Scientific Research Fund of the Second Institute of Oceanography, MNR [JG2015]
  3. National Natural Science Foundation of China [41906151]
  4. China Scholarship Council [202104180007]
  5. Japan Society for the Promotion of Science (JSPS) [20K22428]
  6. Belt and Road Special Foundation of the State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering [2021491111]

向作者/读者索取更多资源

This study established a model framework to investigate the flood processes affected by seawater level fluctuation in small river basins. The integration of dynamic seawater levels increases the flood risk along the coasts of Zhejiang Province, China.
Fluvial floods in coastal areas are affected by tides and storm surges, while the impact is seldom quantified because the dynamics of seawater levels are often not represented in river routing models. This study established a model framework by coupling a surge model with a global hydrodynamic model at a higher spatiotemporal resolution than previous studies so that flood processes affected by seawater level fluctuation in small river basins can be investigated. Model implementation in Zhejiang Province, China, shows that the integration of dynamic seawater levels increases the stress of flooding along the Zhejiang coasts. The ocean effect varies in space, as it is much stronger in northern Zhejiang because of the lower landform and strong tidal amplification, while the mountainous rivers in southern Zhejiang are dominated by river flow regimes. Typhoon Lekima resulted in compound flood events (i.e., rainfall-induced riverine flood, tides, and surges), during which the maximum water level at the outlet of Qiantang River was 0.80 m in the default model settings with a constant downstream seawater level (i.e., 0 m), while it increased to 2.34 m (or 2.48 m) when tides (or tides and surges) were considered. The maximum increase due to tides and surges was 2.09 m and 1.45 m, respectively, while the maximum increase did not match the time of the flood peak. This mismatching indicates the need to consider different processes in physical models rather than linearly summing up different extreme water levels (i.e., river flood, tide, and surge) found in previous studies. The model framework integrating various flow processes will help to prevent risks of compound events in coastal cities in practical and future projections under different scenarios.

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