A study on flood hazard and GDP exposure for the Foshan-Zhongshan region in the Pearl River Delta, China

Flood has caused 20% of the worldwide economic loss arising from catastrophe events over 2008 to 2018. It ranks as the most frequent peril in China. These observations inspired the MEng project to study the flood risk of China’s Pearl River Delta region with its high asset concentration, and specifi...

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Bibliographic Details
Main Author: Zhang, Qi
Other Authors: Lo Yat-Man, Edmond
Format: Thesis-Master by Research
Language:English
Published: Nanyang Technological University 2020
Subjects:
Online Access:https://hdl.handle.net/10356/143277
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Institution: Nanyang Technological University
Language: English
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Summary:Flood has caused 20% of the worldwide economic loss arising from catastrophe events over 2008 to 2018. It ranks as the most frequent peril in China. These observations inspired the MEng project to study the flood risk of China’s Pearl River Delta region with its high asset concentration, and specifically for a basin within. A hydrological model was constructed using HEC-HMS for this basin using only publicly accessible data sources as data availability is often restricted. The HEC-HMS simulation model was built based on two recent historical flood events occurring in 2017, a high river inflow event and 2018, a high local precipitation event. Needed river rating curves for mid to downstream stations have further been developed to provide relationships between observed water level and the river discharge as data for the latter is often unavailable. A more severe flood event was synthesized by having the high 2017 upstream river inflows and the high 2018 local precipitation occurring simultaneously. Climate change impact has also been included by having the precipitation intensity increased. An empirical approach was developed to estimate the flood extent as resulting from river overflows. This enabled the area flooded to be assessed in extent and depth, particularly for the more severe synthetic events, along with the GDP at risk from the flooding.