Defining a framework for integrating stakeholder-feedback, taking into account uncertainty, in multi-hazard model evaluation and development.

There is underlying uncertainty in every model, and understanding how this affects decision-making is crucial. Individual hazard models involve numerous assumptions, and quantifying uncertainties becomes even more challenging when these models are integrated to assess multi-hazard events. While these uncertainties are inescapable, it is vital that stakeholders have a good understanding of hazard-model limitations, whether they are involved in long-term policymaking (planning including early-warning systems, infrastructure, and risk management) or short-term decision-making (such as anticipatory action and disaster response).

With this in mind, the project explores the practical applications of environmental multi-hazard models currently in use, looking firstly at models of flooding and related hazards. Taking a multi-level approach, we use qualitative interview evidence and quantitative model evaluation metrics to assess whether these models provide the insights policy-makers need and explore potential improvements to enhance their effectiveness. The feedback from stakeholders is used to make recommendations for model selection, evaluation, and development to prioritise actionable outputs.

As it is important for all sectors to be involved in disaster risk management, it is equally important to examine all hazards to which population and infrastructure assets can be exposed to in a given location, who is vulnerable to such exposure, as well as how this exposure varies with the use of different underlying assumptions. We compare the exposure of assets based on two flood models and consider the effectiveness of this information for long-term decision support, such as prioritising infrastructure investments.

In an era where accessing data globally has simplified, the quality of this data can still vary significantly across different countries and regions. By understanding how scenario-based multi-hazard models are utilised - or could be utilised - to mitigate risks to human lives and livelihoods, we can help nations better prepare for both long- and short-term effects of extreme weather and climate change, while taking into account the underlying uncertainty.