Mangroves and Coastal Resilience: A Model-Based Evaluation

Coastal hazards such as erosion and flooding are intensifying and becoming more frequent due to climate change, posing significant threats to many low-lying coastal areas. Historically, interventions have focused on grey infrastructure, including seawalls, breakwaters, and revetments, which present challenges such as high construction costs and negative environmental impacts. Consequently, there is a growing drive towards adopting Nature-based Solutions (NBS), such as the use of mangroves. Utilizing the Digital Twin of the Ocean (DTO), the effectiveness of such NBS can be simulated through advanced models. This study explores What-if Scenarios (WiS) using mangroves as NBS to mitigate coastal erosion in the Volta Delta region, an area particularly lacking comprehensive observational data. The integration of the DTO framework bridges this data gap by providing high-resolution simulations and predictive capabilities. The approach adopted is based on a robust model chain integrated within the DTO to simulate different configurations and densities of mangroves. 1D and 2D -Xbeach model is used to explore three categories of WiS: the beach without mangroves, mangroves positioned at the back of the shoreline, and mangroves placed within the intertidal zone. Model validation against measured coastal profiles shows good agreement with observed erosion trends, providing accurate predictions of sediment volume changes. From the results, a significant reduction in erosion is observed, with mangroves at varying densities offering varied protection levels between 18% and 100%. High densities of mangroves introduced in the intertidal zone resulted in the complete stabilization of the shoreline. These simulations highlight the potential of mangroves as a dynamic coastal defense strategy, with DTO applications providing a valuable tool for testing and optimizing NBS interventions. This study contributes to the ongoing development of mangroves as a NBS for coastal defense, demonstrating how DTO applications can effectively test and optimize interventions. By addressing the scarcity of observational data, the DTO framework enhances our understanding and predictive capacity for coastal dynamics.