Disaster planning often overlooks how people truly respond during emergencies. New research, highlighted by CIWEM, using insights from schoolchildren shows how social data can make flood evacuation strategies more effective and inclusive.
In July 2021, devastating floods struck Germany and Belgium due to extreme rainfall, submerging many towns. In Germany, over 190 lives were lost, particularly in the small town of Schuld, where the River Ahr overflowed. Homes were destroyed, escape routes were blocked, and many residents were trapped with no means to communicate. Survivors described waking to the sound of water rushing through the streets, having received little to no warning about the impending disaster.
This tragedy raised serious questions about how a wealthy nation can fail so dramatically in flood response. Warnings were issued, but they did not lead to effective evacuations. Factors such as poor communication, lack of public preparedness and outdated evacuation strategies turned a potentially manageable situation into a deadly disaster.
Unfortunately, this story is not unique. From Pakistan to the United States, from Sri Lanka to the United Kingdom, people are dying in floods not only because of extreme weather, but also due to failures in disaster risk reduction. More recent floods in Spain and Scotland have also resulted in avoidable deaths, highlighting the fallacy of believing that developed countries are safe from extreme environmental phenomena.
Photo: The research team explores evacuation routes. CIWEM
How do we learn from mistakes?
The aftermath of the 2021 European floods revealed a crucial truth: current approaches are inadequate. Evacuation models exist, but they often fail to account for real human behaviour. People do not always evacuate when ordered. Some wait for neighbours to confirm information, while others overestimate their ability to survive at home. Vulnerable populations, such as children, the elderly and disabled people have specific evacuation needs. Yet many models take a one-size-fits-all approach based on limited data.
New research seeks to address this gap, with a focus on enhancing evacuation models by integrating real-world social data – especially insights from schoolchildren. By understanding how different demographics respond during disasters, we can develop models that lead to more effective preparedness and evacuation strategies.
The interdisciplinary approach, in collaboration with colleagues at UCL, Kansai and Kindai universities, saw a diverse team co-create a novel approach, bringing together expertise from the fields of coastal and civil engineering, disaster safety sciences, computer modelling, environmental psychology and education.
The Japan context
Researchers visited Inami Junior High School and conducted interactive workshops on climate change, flooding, evacuation and computer simulation modelling, collaborating with Japanese schoolchildren between the ages of 11 and 12 to explore their understanding and reactions to flood risks. As part of their homework, students surveyed their local community about evacuation behaviour.
Feedback from the workshops was overwhelmingly positive, with children demonstrating improved understanding of their safety during emergencies. The experience was enriching: instead of fear, the students exhibited a practical mindset. Many participated in regular evacuation drills and recognised the importance of evacuating quickly following a flood warning. Discussions about family evacuation plans revealed diverse perspectives.
The UK context
While the UK does not face tsunamis, flooding presents an increasing threat. In 2020, Storm Dennis caused record-breaking floods in England and Wales, costing the government an additional £500 million in preventing floods in Wales in the future. Much of the damage could have been avoided with better planning.
In the UK, researchers conducted similar workshops to those in Japan, but with younger children, who, even at age seven, have a basic understanding of flood risks and personal safety. This suggests that by adjusting resources and tailoring understanding, modelling techniques can be well received and effectively applied within the UK context where flood risks are rising quickly.
Unlike in the Japanese context, however, the UK school curriculum often lacks direct engagement with disaster preparedness, leaving gaps in understanding. Therefore, as risks rise due to climate impacts, there is a pressing need for curriculum changes to integrate disaster risk reduction information, especially pertaining to evacuation.
Why current approaches are insufficient
One major shortcoming in flood evacuation planning is the reliance on idealised human behaviour. Many models assume people will immediately follow evacuation orders. However, research shows that during real disasters, people often hesitate to evacuate for various reasons, including confusion, underestimating the risks, and social pressures.
The financial costs of inadequate planning are staggering. Every year of flood events can cost the UK economy at least £6.1 billion, yet investment in proactive flood defences and preparedness remains low, less than the £1.5 billion recommended by the National Infrastructure Commission. Research indicates that every £1 spent on flood prevention saves roughly £8 in recovery costs. Despite this, governments globally continue to prioritise post-disaster response over prevention.
The impact of climate change on flood preparedness
As climate change accelerates, flooding will become more severe. Rising sea levels and more intense storms mean that events once thought to occur ‘once-in-a-century’ are now becoming more frequent. Without urgent action, more lives will be lost, and recovery costs will escalate.
By improving flood evacuation models and incorporating real social data, we can create systems that reflect actual human behaviour during disasters. This leads to more targeted warnings, better evacuation planning and ultimately, fewer deaths. The time to act is now, before the next flood disaster strikes.
The full article can be found on the CIWEM pages.