Toward accelerating fluvial morphodynamic simulations through a speed accuracy trade-off assessment

Physics-based modeling approaches are crucial for advancing our predictive capabilities of fluvial morphodynamics. Investigating the decadal to centennial-scale responses of river systems is essential for comprehending long-term geomorphic adjustments to climatic variations. However, the significant computational demands and prolonged processing times of the available models often restrict their application to shorter temporal scales. This paper evaluates two powerful techniques: morphological acceleration factor (morfac), which expedites bed evolution by scaling sediment transport rates, and employing condensed hydrograph inputs, which shorten flow time series by emphasizing dominant runoff events that govern geomorphic change. While both methods have historical foundations, their combined application and calibration for fluvial environments, to reduce computational demand, remain underexplored. The results highlighted the capabilities of morfac technique, with values up to 20, to enhance model efficiency, while maintaining robust performance, whereas values exceeding 20 significantly reduce performance. Furthermore, employing condensed hydrograph inputs provides additional enhancements in the model's performance by incorporating only the most dominant runoff events in the shaping of riverbed evolution. Integrating these two techniques yields a theoretical computational efficiency that surpasses 98.8% reduction in total runtime. This study offers practical guidance for applying these methods in fluvial morphodynamic modeling, contributing to more feasible long-term simulations and advancing the operational utility of existing modeling frameworks.