An integrated framework of coastal flood modelling under the failures of sea dikes: a case study in Shanghai

Abstract

Climate change leads to sea level rise worldwide, as well as increases in the intensity and frequency of tropical cyclones (TCs). Storm surge induced by TC’s, together with spring tides, threatens to cause failure of flood defenses, resulting in massive flooding in low-lying coastal areas. However, limited research has been done on the combined effects of the increasing intensity of TCs and sea level rise on the characteristics of coastal flooding due to the failure of sea dikes. This paper investigates the spatial variation of coastal flooding due to the failure of sea dikes subject to past and future TC climatology and sea level rise, via a case study of a low-lying deltaic city- Shanghai, China. Using a hydrodynamic model and a spectral wave model, storm tide and wave parameters were calculated as input for an empirical model of overtopping discharge rate. The results show that the change of storm climatology together with relative sea level rise (RSLR) largely exacerbates the coastal hazard for Shanghai in the future, in which RSLR is likely to have a larger effect than the TC climatology change on future coastal flooding in Shanghai. In addition, the coastal flood hazard will increase to a large extent in terms of the flood water volume for each corresponding given return period. The approach developed in this paper can also be utilized to investigate future flood risk for other low-lying coastal regions.

Tropical Cyclone Changes in Convection‐Permitting Regional Climate Projections: A Study Over the Shanghai Region

“…However, given the lack of high-resolution studies of tropical cyclone risk for this region, this study still offers valuable insights into the hazards facing the Shanghai region in the present and future from tropical cyclones. Results from these simulations have already been used in a flood modeling study by Ke et al (2021) over Shanghai, in which changes in coastal flooding due to the combined effects of tropical cyclones, sea level rise and spring tide have been investigated.…”

Compound flood impact of water level and rainfall during tropical cyclone periods in a coastal city: the case of Shanghai

“…The domain of the model covers the East China Sea, Hangzhou Bay, the Yangtze Estuary, and the downstream reach of the Yangtze River, ranging from 24 to 34 • N and 118 to 128 • E, and consists of 69 000 mesh cells. The model has been validated with observed storm tide and astronomical tide data obtained from 10 stations around Shanghai during TC Winnie in 1997 (Ke et al, 2021). The storm tides and astronomical tides of 210 TCs are calculated in this D-Flow FM model.…”

“…June to September are the rainy months. From late August until early September, Shanghai is frequently affected by typhoons and rainstorms (Yin et al, 2021). Storm flooding caused by typhoons is the main natural disaster in Shanghai.…”

“…A numerical simulation is carried out to better understand the distribution and timing of the peak water level and the areas of the country affected. The physics-based ocean model was calibrated using the recorded atmospheric pressure, and focused on TCs with the most severe damage; the results compared well with the results from field survey data (Ke et al, 2021). Following this, the copula function is used to connect peak water level with accumulated rainfall and construct a joint distribution.…”

“…In 1962, storm flooding inundated half of the downtown region for nearly 10 d due to 46 failures along the floodwalls of the Huangpu River and its branches and led to huge losses (one-sixth) of the local gross domestic product (GDP) in Shanghai (Ke, 2014). In 1997, Typhoon Winnie killed seven people and flooded more than 5000 households due to the extreme storm surge and rainfall (Ke et al, 2021). Although the construction of flood control measures in the past 50 years (especially after Typhoon Winnie in 1997) has effectively reduced the risk of storm surges and rainstorm floods, Typhoon Matsa in 2005 (which caused USD 2.23 billion of damage), Typhoon Fitow in 2013 (USD 10.4 billion of damage), and Typhoon Lekima in 2019 (USD 2.55 billion of damage) also caused significant damage to Shanghai (Du et al, 2020).…”