Author(s): Jorge E. San Juan; Rafael Tinoco
Linked Author(s): Rafael Tinoco
Keywords: Sediment transport; Turbulence; Aquatic vegetation; Coastal erosion
Abstract: Predictors for sediment transport often rely on measurements or estimates of bulk velocities to estimate bed shear stress. However, aquatic vegetation in watercourses and coastal areas generates turbulent flow structures at multiple scales that can drive sediment transport dynamics within and around vegetation patches. To account for the effect of vegetation-generated turbulence in predictive models, we can either conduct accurate high-resolution measurements under realistic scenarios, or find process-driven parameterizations to use bulk values to predict turbulence metrics, indirectly introducing turbulence effects in cases with limited data. We present results from laboratory experiments on an oscillatory tunnel using rigid cylinders as surrogates for submerged vegetation. We discuss how models for unidirectional flows can be adapted to account for the unsteadiness of oscillatory flows, coupled with the interactions between coherent flow structures generated within the vegetation patch and at the top of the submerged canopy. Given the challenges to measure accurate turbulent metrics within and around vegetation patches in the field, we present models to estimate turbulent kinetic energy based on representative values at critical locations, namely near the bed and at the top of the plants, which allows us to use bulk velocity values to estimate peak levels of turbulent kinetic energy, and use such maximum values to assess sediment dynamics. We show that while vegetation-generated turbulence can be used to estimate suspended sediment concentration within vegetation arrays, special attention must be paid to competing effects when ripples begin to develop within the patch, which can cause large variations in the predicted turbulence and sediment values. The presented models provide useful alternatives to incorporate turbulent effects on sediment transport models, and provide a bridge to evaluate the efficacy of these modified models in the field.