Exploring the Utility of Bayesian Belief Networks for Climate Adaptation Decision Making: Insights from Glasgow, UK

11:15 Tuesday 28 May

OC034

Room S16

 

Eleanor Murtagh (United Kingdom) 1

1 - University of Strathclyde

Ensuring climate adaptation decisions are informed by relevant evidence and supported by appropriate options appraisal methods is one the most significant challenges of the 21st century. The adaptation decision making landscape is characterised by complexity and uncertainty arising from a myriad of sources from the variability of future climate conditions to the effectiveness, benefits and potential consequences of differing adaptation options.

There is thus a clear need for methods and resources to enable decision-makers to effectively make appropriate adaptation decisions. This paper assesses what decision methods are currently used within a studied local authority, how this influences their ability to adapt and identifies practitioner requirements for decision support tools. It then proposes and explores Bayesian Belief Nets (BBN) as a method to address identified challenges, such as understanding the effects of different adaptation options on the exposure, adaptive capacity and sensitivity of a city’s citizens, services and assets.

The research was conducted using a case study approach in Glasgow, UK. The BBN was co-created with practitioners during multiple workshops to develop a qualitative conceptual model of perceived determinants of climate resilience and the dependencies between identified variables, which were later quantified through expert elicitation to identify conditional probability distributions of dependence relations. The model was then tested with a decision maker in the local authority to explore the perceived potential effect of different adaptation options on the modelled system.

Findings illustrate the advantages of Bayesian Belief Networks in the field of adaptation decision making. Results demonstrate that they can aid communicating the consequence of climate change, strengthen understanding of the system, illustrate relationships between climate risks and examine trade-offs and benefits of different adaptation options.

Climate impacts as a result of climate change may be exacerbated by inefficient or reckless adaptation decision making. This paper contributes to the literature on and empirical examples of decision-making under uncertainty by exploring the utility of Bayesian Belief Networks to the field of climate adaptation in Glasgow city. Continued study and reflection on decision support for climate adaptation is essential for the continued functioning and sustainability of local authorities across the world and further research needs will be presented.