A decision support framework for catchment-scale nature-based flood solutions using multi-objective particle swarm optimization

This article presents a decision-support framework (DSF) for evaluating nature-based flood mitigation strategies at the catchment scale, focusing on afforestation. It integrates hydrological modelling (SWAT), flood frequency analysis, and multi-objective optimization (MOPSO) to assess trade-offs between flood damage reduction, costs, and carbon benefits, using the Bremer catchment in Australia as a case study.

The findings show that increasing forest cover reduces peak flood discharge by over 10% and total annual flood damage by around 12%, even during extreme events. While high implementation costs are required, afforestation generates long-term economic returns and carbon credits, making it a viable and sustainable flood mitigation strategy. The framework also highlights the importance of balancing economic, environmental, and risk-reduction objectives in decision-making.