Robust and reliable models are needed to understand how coastlines will evolve over the coming decades, driven by both natural variability and climate change. This study evaluated how accurately five popular ‘reduced-complexity’ models replicate multi-decadal shoreline change at Narrabeen-Collaroy Beach, a sandy embayment in Sydney, Australia. Measured shoreline positions derived from approximately monthly field surveys were used for 20-year calibration and 20-year validation periods. The models performed similarly on average but with large variability between transects. The set-up of several models was modified to compensate for their sensitivity to imperfect input wave data, and further site-specific improvements were identified. Capturing interannual to decadal-scale variability in cross-shore and longshore dynamics at this site was challenging for all five models. Models appeared to aggregate key processes at this timescale into parameter values rather than representing them directly. This suggests time-varying parameters or changes to model structure may be necessary for decadal-scale simulations.

Understanding and predicting shoreline variability at various temporal and spatial scales is vital for effective, data-driven coastal management. Shoreline position, a reliable indicator of beach morphological changes, has been assessed using complex numerical models. Recently, equilibrium-based shoreline evolution models (EBSEMs) have gained traction for their efficiency in simulating shoreline orientation, including cross-shore and rotational (longshore) changes. However, existing EBSEMs for shoreline rotation have been applied predominantly to microtidal beaches, with limited validation across diverse coastal environments. This study evaluates the performance and scalability of the EBSEM proposed by Jaramillo et al. (2021) in modelling shoreline rotational variability at seven embayed beaches: Narrabeen Beach (Australia), Tairua Beach (New Zealand), Blackpool Beach (United Kingdom), Poniente Beach, Llevant Beach, Cala Millor Beach, and Moncofa Beach (Spain). These sites represent diverse environmental conditions in terms of sediment size, tidal regimes, monitoring frequency, and data types. The model was tested across full monitoring periods, elevation contours, and temporal resolutions. Results show that EBSEM performs well across contrasting beach types, effectively capturing short-term and seasonal shoreline rotation patterns. However, reduced accuracy was observed in environments with high-energy events or human interventions, such as Poniente, Llevant, and Cala Millor beaches. Sensitivity analyses highlight the importance of temporal resolution and intertidal elevation in model performance. While the EBSEM shows significant potential for broader application, further refinement is needed to better capture storm-driven and anthropogenic variability. These improvements would enhance its utility for coastal adaptation planning, hazard mitigation, and long-term shoreline management in the face of climate change.