10 years on from 2011
10 years ago, Thailand was hit by some of the worst flooding in the region for over 30 years.
The event caused considerable insured losses and its wider impacts were felt around the globe for many months, if not years, afterwards.
Since then, there have been considerable advances by the risk management community to improve model coverage. But is the industry ready for another event of this scale? Are there other flood risk hotspots still being overlooked?
We look back on the 2011 event on its tenth anniversary and explore the ongoing flood risk across South East Asia.
2011 flooding overview
Several large flood events have affected Thailand over the last 100 years. Two events that stand out are the events of 1995 and 2011.
Whilst the 1995 event holds the record for the size of area affected, the 2011 event caused much more damage, mainly due to flood waters persisting for many months.
But why did these flood waters persist for so long?
The root cause of the 2011 event is complex. It involves the combination of an extremely wet year alongside several geophysical factors which combined to create the perfect conditions for prolonged flooding and large economic costs.
The summer monsoon was significantly wetter than normal, and this has been linked with the La Nina phase of the El Nino-Southern Oscillation (Promchote et al, 2015, Gale and Saunders, 2013).
However, tropical cyclone activity and monsoon rainfall post July were not exceptional and it is worth remembering that elevated rainfall levels are not solely responsible for flooding. For example, rainfall totals were higher in 2006 and did not lead to any serious flooding.
But when this rainfall was combined with unusually high soil moisture levels and elevated sea levels in the gulf of Thailand, which affected the drainage capacity of the Chao Phraya river basin (Promchote et al, 2016), it provided the perfect storm for severe flooding.
Shortly after the event, JBA’s Event Response team produced a flood footprint capturing the extent and depth of the flooding. This is shown in the figure below with the blue area illustrating the extent of the flooding throughout central Thailand.
Figure 1: The 2011 Thailand flood event showing the vast area of the flood extent ranging from the northern city of Phitsanulok down to Bangkok.
Impacts around the globe
Losses due to direct property damage were extremely high for this event. However, the prolonged flooding also caused significant issues worldwide by impacting global supply chains.
Many Japanese car manufacturers and technology companies had shifted production to Thailand following the 2011 Tōhoku earthquake and tsunami, with sites located in industrial parks around Bangkok.
However, many of these industrial parks sat on low-lying floodplains, which resulted in manufacturing sites being significantly flooded in 2011. This included suppliers of hard disk drives to the international market, whose supply chain interruptions had global ramifications (Haraguchi and Lall, 2015).
Several large international manufacturing companies based in Thailand made large business interruption claims, which went on to impact the global reinsurance market.
And, whilst the flooding in Thailand was particularly severe, other countries were simultaneously affected. Vietnam, Laos and Myanmar each experienced substantial losses as well as a number of fatalities.
2011 and Thailand’s wider flood risk
JBA’s probabilistic flood modelling in Thailand allows us to understand the severity of the 2011 event in the wider context of Thailand’s long-term flood risk.
Our Thailand Flood Model estimates that the 2011 event equates to a 1-in-43-year loss event, or USD $12.1 billion. This relates to financial losses directly attributed to flood damage based on a GDP portfolio.
When flood damage is considered alongside other impacts, such as business interruption, industry estimates place the event between a return period of 1-in-60-year and 1-in-200-year.
Figure 2: Losses for the 2011 event compared against JBA’s Occurrence Exceedance Probability curve for Thailand using a GDP based portfolio. JBA’s event loss estimate is USD $12.1 billion for direct flood damage.
Modelling the unmodelled: the need for global coverage
The 2011 floods caught the global re/insurance (and wider finance) market off-guard. To avoid this happening again, re/insurers made significant steps towards proactive risk management following the event, seeking to identify unmodelled territories that might be flood risk hotspots.
Immediately following the floods, we released JBA’s probabilistic Thailand Flood Model, followed shortly by models for several other countries in South East Asia that were affected by the event. In 2019, we produced the first probabilistic flood modelling on a global scale, which provides consistent flood risk analysis for every location worldwide.
This global flood modelling capability is vital for understanding the impacts that flooding can have across country and continental borders. As can be seen by the 2011 event, flooding doesn’t stop at geopolitical borders – weather systems can be extremely large and travel for long distances, impacting multiple countries at once. Having a flood model offering that enables simultaneous, consistent analysis across these borders helps re/insurers to understand the compound impact of a single event.
Where could the next major flood event occur?
Measures have been introduced to help reduce flood risk and losses since 2011, for example building dikes, elevating roads and constructing walls around industrial complexes, as well as government schemes to revive the automobile industry.
However, research suggests that the success of these measures is limited and may have even increased flood risk in other areas, either due to the redirection of flood waters or due to the increased demand for more non-permeable roads (Marks and Thomalla, 2017).
Furthermore, flood insurance penetration has remained low in South East Asia. As a result, this area remains at significant risk to flooding and financial loss.
Indonesia flood risk
Figure 3 shows JBA estimates of annual average losses for individual countries in South East Asia. Thailand stands out as having high losses relative to its neighbours Cambodia, Laos, and Myanmar, but Indonesia is identified as the country most at risk of flood losses, and therefore a potentially risky proposition for re/insurers writing business in the region.
Figure 3: Average annual losses for the South East Asia region using JBA’s probabilistic modelling. These losses were produced from a disaggregated portfolio consisting of residential buildings. Buildings were assigned a total insured value that was equally proportioned by the GDP of each country.
Using JBA’s probabilistic flood modelling, Figure 4 compares relative losses for South East Asia at the 1-in-200-year return period. All the losses have been normalised relative to Thailand i.e. a country with twice the 1-in-200-year losses of Thailand is shown as having a loss of 200%.
Figure 4: Losses for the 1 in 200-year flood event, relative to Thailand. Losses have been normalised against the Thailand 1-in-200-year loss to aid comparison. These results have been created using JBA’s probabilistic global flood modelling.
Figure 4 demonstrates that Thailand is second only to Indonesia in terms of likely losses should a large event occur.
Cambodia flood risk
However, in terms of risk per dollar of exposure, this picture doesn’t tell the full story. If we divide the losses produced in the figure above by the amount of insured in dollars, then the picture relative to Thailand looks very different.
Figure 5: As for Figure 4 except the initial losses were first divided by the total insured value of each individual country. This gives us the relative risk per unit of exposure that an underwriter might want to insure.
Figure 5 shows that on a per dollar basis of exposure, losses in Vietnam, Myanmar, Laos, the Philippines, and Cambodia are all expected to be higher than those incurred in Thailand.
Notably, Indonesia now appears to have the same amount of risk as Thailand compared to Figure 4, whereas Cambodia’s risk is much higher relative to Thailand.
In fact, JBA’s estimates suggest that, for a similar return period event and identical total sum insured values, we could expect losses in Cambodia of over three times those incurred in Thailand.
Given the enormous impact of the 2011 Thailand floods, the possibility of a similar event in Cambodia could be of significant concern to re/insurers writing business in the area.
JBA’s probabilistic flood modelling can be used to explore different risk scenarios and help insurers to proactively control their accumulation risk.
We include a wide range of historic and scenario events for analysis within the modelling. This allows clients to understand the impact to their portfolio should a similar event occur, and to understand these events in context of the exceedance probability curves, using a consistent methodology. These provide invaluable tools which can help with accumulation management.
If you would like to understand the impact of these events on your portfolio, or if you would like bespoke scenarios to be developed, get in touch today with the global flood modelling experts.
References
Gale, E L., and Saunders, M. A. 2013. The 2011 Thailand flood: climate causes and return periods. Weather (68.9): 233-237.
Haraguchi, M and Lall, U. 2015. Flood risks and impacts: A case study of Thailand’s floods in 2011 and research questions for supply chain decision making. International Journal of Disaster Risk Reduction (14) 256-272.
Marks, D., and Thomalla. F., 2017. Responses to the 2011 floods in Central Thailand: perpetuating the vulnerability of small and medium enterprises?. Natural Hazards (87.2) 1147-1165.
Promchote, P., Wang. S., Johnson, P.G. 2016. The 2011 great flood in Thailand: Climate diagnostics and Implications from climate change. Journal of Climate (29.1) 367-379.