The interconnected risks of flooding: Transforming flood assessment at multiple scales through better statistical understanding of risk
This research was applied to give the government, flood risk management authorities and the insurance industry a better understanding of risk.
1, 2, 3, 2, 3
1 JBA Trust and Lancaster Environment Centre, Lancaster University, United Kingdom
2 Lancaster University, United Kingdom
3 JBA Consulting, United Kingdom
Research led by Lancaster University, JBA and the JBA Trust - conducted over a decade - has supported the government, flood management authorities and the insurance industry to have a better understanding of flood risk from local to national scales.
Historically, flood risk was often assessed in isolated terms. This meant the focus was on single locations or individual flood events, rather than accounting for how extreme weather patterns can co-occur across large areas. As a result, assessments could underestimate the broader, interconnected risks of flooding.
The research team addressed this gap by developing methods that model flood events as multivariate extremes. This allowed for a more realistic estimation of the likelihood of concurrent flooding across multiple locations. The approach enabled flood risk to be assessed at a national scale, informing decisions in the UK's National Security Risk Assessment (NSRA) and aiding global reinsurance companies in risk evaluations.
Multivariate Extreme Value theory
The research breakthroughs were founded on multivariate extreme value theory. The theory addressed the probability of multiple extreme events occurring simultaneously. Prior to this research, methods were limited in scope, handling only a few variables or locations. While they were mathematically convenient, they didn't align with real-world flood data, often leading to inaccurate risk estimates.
To overcome this, Lancaster University researchers developed a conditional probability model that could handle a large number of variables with varied dependencies. This model demonstrated that, contrary to traditional beliefs, the probability of seeing a 1 in 100-year flood somewhere in England and Wales annually is as high as 88%.This finding underscored the need to shift from isolated risk descriptions to a more holistic framework, and recognised that a seemingly rare event locally could be much more probable when considered across a broader scale.
Impact
The new approach proved influential during the UK's 2016 National Flood Resilience Review (NFRR), which was prompted by severe flooding in 2013 to 2014 and 2015 to 2016.
UK Chief Scientific Adviser (2016) said:
There was pressure on Government to better understand the risks involved. … Your contribution to the review was very important. Ministers were determined to base the review's conclusions and recommendations on sound evidence and analysis… Our advice had significant influence on both the evidence and the way in which it was communicated.
The government's conclusions were heavily based on the research insights, which reshaped the understanding of flood risk. It also highlighted the urgency of comprehensive preparedness.
A direct outcome of the NFRR was the government's £12.5 million investment in new mobile flood defences, quadrupling the number of units from 2015 levels. Furthermore, a commitment to an ongoing £2.3 billion capital investment plan was secured, aiming to protect 300,000 homes. This strategic shift-grounded in more realistic risk assessments-increased the resilience of both urban and rural communities against future floods.
Beyond the UK, these advancements have been influential globally, especially for the insurance and reinsurance sectors.
Working with Lancaster University and the Environment Agency, JBA further refined the methods to improve their scalability and efficiency, leading to the development of the Multivariate Event Modeller tool. This open-source tool allows for joint probability analysis, making it accessible for environmental scientists and risk managers who need to analyse complex, interconnected flood events.
The research has extended into ocean wave analysis, contributing to a better understanding of coastal extremes that compound flood risks, especially in coastal regions.
These tools and insights have led to more accurate, data-driven assessments that can guide infrastructure planning, inform policy, and support sustainable urban development.