Compound Flood Hazards in Chinese Coastal Cities

Abstract

Coastal regions are at risk of flooding because of their natural layout. Evidence of a changing climate, like sea levels rise and more extreme weather events, along with growing populations and cities, can make the impact of floods on society even greater. Additionally, estuary regions are threatened by compound floods, i.e., flood events generated when multiple physical drivers, e.g., the water level and river discharge, interact, even if each driver on its own might not seem threatening.

Along the Chinese coastline, particularly in the south, cities like Shanghai and Haikou are prone to flood, especially during the typhoon season. When typhoons hit the coast, high storm surges and heavy rainfall can interact leading to severe impacts. Characterizing compound flooding in coastal regions poses different challenges, including identifying the physical drivers that potentially generate a flood event, selecting an appropriate numerical model to describe the interaction between these drivers in terms of frequency and magnitude, and ensuring the quality and representativity of the available observations.

This thesis aims to tackle these challenges using cities along the Chinese coast as case studies. It seeks to (i) provide a probabilistic characterization of the physical drivers of compound floods, considering the effect of sea level rise, and (ii) integrate this quantification with a hydrodynamic model to assess the extent and depth of compound flood impacts in inundated areas. This approach can lay a solid foundation for developing flood-resilient strategies and mitigating potential impacts.

Chapter 2 introduces a design approach via conditional probability for quantifying compound flood hazards in coastal regions and its implication for infrastructure design considering the seasonal variation in surge peak occurrence. We found that along the southern coast of China, the severity of the expected rainfall events in case of a storm surge peak is larger compared to the expected severity inferred from the probability distribution of annual maxima of precipitation. Consequently, from a design perspective, implementing rainwater storage systems and facilities to mitigate hydrograph peaks is crucial for these regions.

Chapter 3 focuses on Shanghai and investigates how relative sea level rise (RSLR) affects design values for flood protection systems. We employed the D-Flow FM ocean storm surge model to reconstruct 210 historical typhoon storm surge events in Shanghai to overcome the constraint of unavailable water level records. We then applied a copula-based approach to calculate the joint probability and design value of peak water level and accumulated rainfall with the impact of RSLR. This research improves our understanding of how storm surges, rainfall, and RSLR interact, revealing how they collectively contribute to the risk of flood in coastal areas. Thus, it is crucial to monitor and predict the interplay of these factors for developing future design standards for better flood preparedness.

Chapter 4 reveals distinct patterns in the relationship between flooded areas and volume for both single-driven and multi-driven flood scenarios at the coastal city of Haikou by implementing an ocean storm surge generator and urban overland hydrodynamic model. The results highlighted storm tide (a combination of surge and astronomical tide) as the predominant factor contributing to compound flooding in Haikou. Only examining single-driven factors would underestimate flood hazard.

Chapter 5 investigates the sensitivity of inundated areas to the relative timing between the occurrence of the rainfall peak and the storm surge peak in Shanghai and provides a characterization of the consequent inundated areas based on the main flood driver(s). This is achieved by inferring from the probabilistic model the severity of the expected pairs of storm surges and rainfall events. They are then used as forcing of a hydrodynamic model to generate flood extent. We showed that the relative time between the peak of flood drivers affects the extent and depth of the flood and the flood zone classification. This can better suggest potential strategies for dealing with different types of compound flooding for coastal cities.