Typhoon Mangkhut: A focus
on the storm surge
flooding in Hong Kong

Typhoon Mangkhut swept past the Philippines on the morning of Saturday 15 September at 01:40 (PST), bringing sustained wind speeds of up to 270km/h (CNN). It is the strongest event since Typhoon Megi hit the region in 2010.

Pictured above: Overview of the track of Typhoon Mangkhut and destruction it caused in various locations.

The typhoon then continued westwards across the South China Sea before eventually making landfall close to the Pearl River Delta, a densely populated and industrious area in the south-east of China. Mangkhut made landfall in Jiang Men City at 17:00 16 September (CST) with wind speeds of approximately 175km/h. The event brought strong winds and storm surge flooding to Guangdong province (China), Macau, and Hong Kong.

The storm surges in Hong Kong were reported to be 2.35m at Quarry Bay and 3.38m at Tai Po Kau (South China Morning Post). Based on historical tide gauge data collected between 1954 and 2017 (Hong Kong Observatory (HKO)), the surge level experienced at Quarry Bay /North Point (Kowloon Bay) represents an estimated return period of 200 years. 

Pictured right: Estimated typhoon return period in Hong Kong, based on past storm surge data between 1954 and 2017 obtained from the Hong Kong Observatory (HKO) North Point (Quarry Bay) station. A General Pareto Distribution curve has been fitted to the historic data to give the return period estimation.

Fortunately, the storm surge level was somewhat mitigated as it did not coincide with the high astronomical tide that day. Similarly, historical records suggests that there have been previous typhoons causing larger surge heights in the past, including a surge height of 3.8m in 1937 (HKO). Considering this, it suggests that Mangkhut may have a lower return period for the surge than 200 years. Storm surge data at Quarry Bay was available from 1954 and was used to generate an estimated typhoon return period for Hong Kong. As events before 1954 were not recorded at the same location, these events were not taken into consideration for the analysis.

Many compared the scale of the event to Typhoon Hato which hit Hong Kong in August 2017 and was the strongest to hit Macau in the past 53 years (Willis Towers Watson). In comparison to Typhoon Hato, however, the damage to infrastructure caused by Mangkhut is likely to be more significant. Damage from fallen trees and broken windows is approximately three times higher than Hato, with the number of injuries around four times higher. The storm surge resulting from Mangkhut flooded several locations around Macau (North Island) and Hong Kong (Shek-O beach, Tai-O, Heng Fa Chuen, Lobster Bay).

Pictured above: Wind footprint generated using Delft 3D. Areas highlighted with the lightest shade of orange have a lower wind speed while areas highlighted in dark red-orange colour have the highest wind USD speed based on the model generated.

It is likely to take weeks, or even months, to clean up the damage from Mangkhut. There has been considerable damage to yachts, with trees and plant debris scattered across the scenic beaches in Hong Kong due to the strong waves and winds. Businesses along the beaches and on the offshore islands may need several months to fully recover.

To put the potential losses from Mangkhut into perspective, the economic losses for Typhoon Hato were estimated at around USD $2 billion and insured losses were approximately greater than USD $300 million (Willis Watson Tower). Typhoon Hato resulted in greater damage in Macau as compared to Hong Kong. In Macau, Hato claimed 10 lives and injured 240 people. The economic losses incurred in Macau directly by Hato are greater than USD $400 million.

Before Mangkhut, Super Typhoon Wanda was the strongest typhoon to affect Hong Kong since the start of instrumental records in 1946, causing extensive damage when it hit Hong Kong in 1962 with a wind gust of 250km/h at its height. The maximum surge recorded was 3.20m at Tai Po Kau and 1.77m at North Point station. Sea water inundated 869 acres of farmland, 3000 huts and 5 village houses in Sha Tin (northeast of Kowloon). It claimed 130 lives and displaced 72,000 people (HKO). 

In the Asia-Pacific (APAC) region, the total economic losses caused by catastrophes were estimated to be USD $34.5 billion in 2017. Of that, only USD $7.1 billion (20.5%) of the losses were insured (Swiss Re). For Typhoon Mangkhut, Hong Kong is likely to suffer a significant economic loss from this event and it is likely that only 30% of the losses were insured. The total insured losses are predicted to reach a record amount of over USD $1 billion (South China Morning Post).

Pictured above: Various locations affected by Typhoon Mangkhut in the south of Hong Kong. 

JBA Risk Management has nationwide return period flood maps for China at 30m resolution. Please get in touch for more information.

References

Cheung, T. and Xinqi, S., 2018, 'Typhoon Mangkhut Officially Hong Kong's Most Intense Storm Since Records Began', South China Morning Post, viewed 18 September 2018

Griffiths, J., George, S. and Shelley, J., 2018, 'Philippines Lashed By Typhoon Mangkhut, Strongest Storm This Year', CNN, viewed 17 September 2018

Hong Kong Observatory Historical Data, The Government of the Hong Kong Special Administrative Region, viewed 17 September 2018

Hong Kong Observatory, 2003, 'Typhoon Wanda, August 27 to September 3, 1962', extract from the Observatory's publication 'Supplement to Meteorological Results 1962', The Government of the Hong Kong Special Administrative Region, viewed 18 September 2018

Swiss Re, 2018, 'Sigma 1/2018: Natural Catastrophes and Man-Made Disasters in 2017', viewed 17 September 2018

Tsang, D., Yiu, E. and Cheung, T., 2018, 'Typhoon Mangkhut Bill Could Set Hong Kong Record of US$1 billion in Insurance Claims', South China Morning Post, viewed 18 September 2018

Willis Towers Watson, 2018, 'Asia Insurance Market Report 2018', viewed 18 September 2018

News &
Insights

News Celebrating our 10th anniversary

We're celebrating 10 years of The Flood People and creating world-leading flood risk insights.

Learn more
Blog COP26: A window on change

Dr Emma Raven reflects on what COP26 means for climate modellers, the opportunity it presented to move forward together in addressing the challenges, and the importance of open data in doing so.

Continue reading
Blog Investing in Disaster Prevention in the EU

JBA specialists modelled flood risk in Europe as part of a World Bank and EU Commission project on disaster preparedness in the region. Our blog explores key results.

Continue reading
Blog Representing uncertainty in flood maps

As with any scientific modelling, there is inherent uncertainty within flood mapping. We explore JBA tools to help mitigate this uncertainty and help users understand the full risk.

Continue reading