- 1School of Civil and Environmental Engineering, University of Technology Sydney, Sydney, Australia (patricia.saco@uts.edu.au)
- 2School of Engineering, The University of Newcastle, Callaghan, Australia.
- 3Water Modelling Systems, WaterNSW, Sydney, Australia.
- 4School of Engineering, Deakin University, Deakin, Australia.
Coastal wetlands provide a wide range of ecosystem services, including shoreline protection, attenuation of storm surges and floods, water quality improvement, wildlife habitat and biodiversity conservation. These ecosystems have been observed to sequester atmospheric carbon dioxide at rates significantly higher than many other ecosystems, positioning them as promising nature-based solutions for climate change mitigation. However, projections of coastal wetland conditions under sea-level rise (SLR) remain highly variable, owing to uncertainties in environmental factors as well as the necessary simplifications embedded within the wetland evolution modelling frameworks. Assessing wetland resilience to rising sea levels and the effect of anthropogenic activities is inherently complex, given the uncertain nature of key processes and external influences. To enable long-term simulations that span extensive temporal and spatial scales, models must rely on a range of assumptions and simplifications—some of which may significantly affect the interpretation of wetland resilience.
Here we present a novel eco-hydro-geomorphological modelling framework to predict wetland evolution under SLR. We explore how accretion and lateral migration processes influence the response of coastal wetlands to SLR, using a computational framework that integrates detailed hydrodynamic and sediment transport processes. This framework captures the interactions between physical processes, vegetation, and landscape dynamics, while remaining computationally efficient enough to support simulations over extended timeframes. We examine several common simplifications employed in models of coastal wetland evolution and attempt to quantify their influence on model outputs. We focus on simplifications related to hydrodynamics, sediment transport, and vegetation dynamics, particularly in terms of process representation, interactions between processes, and spatial and temporal discretisation. Special attention is given to identifying modelling approaches that strike a balance between computational efficiency and acceptable levels of accuracy. We will present recent model results to assess the resilience of coastal wetland to SLR on several sites around the world and will discuss new results to assess the effect of human interventions and infrastructure on wetland resilience.
How to cite: Saco, P., Jose, R., Angelo, B., Sandi, E., and Sandi, S.: Modelling wetland resilience to climate change and anthropogenic impacts., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8292, https://doi.org/10.5194/egusphere-egu26-8292, 2026.