Optimizing nature-based solutions for urban flood risk mitigation: A multi-objective genetic algorithm approach in Gdańsk, Poland
Anahita Azadgar, Artur Gańcza, Sina Razzaghi Asl, Stefano Salata, Lucyna Nyka
Abstract
Nature-based Solutions (NbS) have emerged as a sustainable approach to managing flood risks by enhancing natural water retention and reducing surface runoff in urban areas. As climate change and rapid urbanization exacerbate flood hazards, optimizing the spatial deployment of NbS is crucial for improving urban resilience and mitigating flood impacts. This study presents a comprehensive optimization framework for the spatial allocation of fourteen different NbS types aimed at mitigating urban flood risks in Gdańsk, Poland. Leveraging a genetic algorithm alongside the Urban Flood Risk Mitigation (UFRM) model of the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) software suite, we identified areas of the city most vulnerable to pluvial flooding and optimized NbS placement to maximize water retention and reduce runoff. The optimization process balanced multiple objectives, including minimizing implementation costs and maximizing water retention capacity, ensuring that the solutions are both economically feasible and environmentally effective. Three distinct scenarios were proposed: a cost-effective solution, a high-retention solution, and a balanced solution, offering urban planners a range of strategies to address flood risks based on their specific priorities and constraints. Results demonstrated considerable variations in water retention effectiveness across different NbS configurations, with denser urban regions showing the most significant improvements from targeted interventions. The optimized placement of NbS resulted in estimated total water retention improvement of approximately 15.5 % for the best solution considered. These findings provide valuable insights for integrating NbS into urban flood management strategies, enhancing citywide resilience, sustainability, and long-term flood mitigation. • The Urban Flood Risk Mitigation model assessed flooding susceptibility in Gdansk. • A genetic algorithm optimized the placement of 14 types of nature-based solutions, reducing runoff. • Three scenarios are given: cost-effective, high-retention, and balanced, offering flexibility in tackling urban flooding. • The framework shows the vital role of optimized nature-based solutions in flood mitigation and sustainable planning.