A scenario-based analysis of wetlands as nature-based solutions for flood risk mitigation using the TELEMAC-2D model

Urban flooding is an escalating threat in rapidly urbanising regions, particularly in sub-Saharan Africa (SSA), where unregulated expansion and climate change intensify risks. Nature-based Solutions (NbS) are increasingly recognised as sustainable and cost-effective, yet empirical evidence to support their strategic planning, especially through high-resolution modelling in data-scarce settings, remains limited. This study presents one of the first integrated applications of spectral indices and TELEMAC-2D hydrodynamic modelling to assess NbS effectiveness in a rapidly urbanising SSA city, the Greater Kumasi Metropolitan Area (GKMA) in Ghana. Focusing on the Aboabo catchment, we analysed wetland ecosystem loss (1986–2023) and evaluated the impact of NbS interventions (floodplain restoration and wetland creation) on flood dynamics. Specifically, we assessed the flood reduction potential of different implementation scenarios and how these scenarios affect the timing and intensity of peak flows under varying storm conditions. Results show that wetland cover declined (59 %) while built-up areas expanded (134 %), leading to reduced cumulative discharge and more intense, shorter-duration floods. The combined scenario (floodplain restoration and wetland creation) achieved consistent peak flow reductions (16–19 %) in prolonged storms, while the ambitious_restoration scenario (restoring the full floodplain network) performed best (24 %) in short-duration events. In contrast, the landscape scenario (wetland creation in available spaces) achieved only modest reductions (1–3 %), underscoring the limited capacity of space-dependent approaches and the importance of spatial targeting. These findings support the case for hybrid approaches that combine NbS with engineering solutions to enhance both immediate and long-term flood resilience. Our approach demonstrates the adaptability of TELEMAC-2D for NbS modelling in data-limited contexts and offers a replicable, decision-relevant framework for integrating NbS into urban flood resilience planning across SSA and similar regions.