Bayesian-Based Modelling of Coastal Risk: The Case of the Volta Delta in Ghana

Abstract

The study leverages Bayesian ontology to model consequences, uncertainty and expert judgment in quantifying risk with shoreline change at the Volta Delta. The study explores the integration of Bayesian networks and expert opinions to comprehensively assess and address erosion threats, thereby contributing to sustainable development and environmental resilience. Modelling risk involves analysing variables, including potential occurrences, consequences, estimated likelihoods, and expert judgments. The study creates a thorough risk appraisal structure for different erosion-related scenarios, presenting the baseline risk, best-case, worst-case, current case and intervention scenario with an erosion protection system. The findings suggest that implementing erosion protection measures and reducing human activities could profoundly benefit decision-makers resource allocation. The study presented a systematic approach to tackling coastal erosion-related hazards, which can guide prioritizing and implementing effective interventions. Collation, monitoring, research and risk communication strategies are also emphasized for effective erosion risk management and sustainable development.

Keywords: Bayesian network, Coastal Risk Assessment, Expert Elicitation, Volta Delta, Risk Modeling, Shoreline Change, Sensitivity Analysis