Planning hydrological restoration of coastal wetlands: Key model considerations and solutions

• Published in: The Science of the total environment 2024-03, Vol.915, p.169881-169881, Article 169881
• Main Authors: Twomey, Alice J., Nunez, Karinna, Carr, Joel A., Crooks, Steve, Friess, Daniel A., Glamore, William, Orr, Michelle, Reef, Ruth, Rogers, Kerrylee, Waltham, Nathan J., Lovelock, Catherine E.
• Format: Article
• Language: English
• Subjects: Coastal restoration; Hydrological restoration; Hydrology; Tidal regime
• ISSN: 0048-9697; 1879-1026
• DOI: 10.1016/j.scitotenv.2024.169881

The hydrological restoration of coastal wetlands is an emerging approach for mitigating and adapting to climate change and enhancing ecosystem services such as improved water quality and biodiversity. This paper synthesises current knowledge on selecting appropriate modelling approaches for hydrological restoration projects. The selection of a modelling approach is based on project-specific factors, such as costs, risks, and uncertainties, and aligns with the overall project objectives. We provide guidance on model selection, emphasising the use of simpler and less expensive modelling approaches when appropriate, and identifying situations when models may not be required for project managers to make informed decisions. This paper recognises and supports the widespread use of hydrological restoration in coastal wetlands by bridging the gap between hydrological science and restoration practices. It underscores the significance of project objectives, budget, and available data and offers decision-making frameworks, such as decision trees, to aid in matching modelling methods with specific project outcomes. [Display omitted] •Hydrological restoration of coastal wetlands is emerging as a key tool for climate change mitigation and adaptation.•Hydrological restoration has risks and uncertainties that can limit uptake and profitability while increasing planning costs.•Data and models can help describe risks and reduce uncertainty.•Developing low-cost data sources and easy-to-implement models may enhance the potential for hydrological restoration.