Understanding the effects of dynamic sediment inputs on the prediction of coastal wetland evolution

Over the last two decades, there have been important advances in eco-geomorphological modelling of coastal wetlands to predict their evolution. Different features have been incorporated into models, bust most applications still assume a constant or static sediment concentration as input representing average conditions. Such imposition is related to many constraints in obtaining a time series of total suspended matter (TSM). However, with the increasing availability of multispectral satellite products and the development of artificial intelligence algorithms, TSM data can be estimated through remote sensing. This work aims to assess the effect of using a dynamic time varying condition for the TSM input when simulating eco-geomorphological processes. We implemented a modelling framework adapted to conditions found in SE Australian estuaries, which includes hydrodynamic and sediment transport processes. Many scenarios where simulated encompassing different levels of average TSM and water levels. Our findings suggest that under low water levels and low sediment concentration, a static TSM input results in more accretion than a dynamic input. However, at higher levels and concentration, the dynamic input led to higher accretion. Predictions of vegetation distribution were not particularly sensitive to changes in TSM over time.