Three-dimensional uncertainty analysis of sediment dynamics: Exploring suspended sediment concentration, flood discharge, and sediment yield

The simultaneous occurrence of extreme flood discharge and sediment discharge events has profound impacts, including infrastructure damage, water pollution, increased treatment costs, and threats to aquatic ecosystems. Understanding spatial and temporal dynamics of water and sediment transport during extreme flood events is critical. Copulas are powerful tools for analyzing multivariate flood frequencies and establishing relationships between design variables and return periods, aiding hydrology and water resource management. This study analyzes conditional uncertainty of flood discharge (Qf), sediment discharge (Qs), and suspended sediment concentration (Sc) in the Minab watershed using symmetric and Khoudraji copula functions. Conditional probabilities (CP) for these variables were assessed under different scenarios with a focus on Qf. Results identified the Khoudraji copula as the most effective function for modeling dependencies among the variables. Findings revealed that as Qf increases from 20.99 to 310.184 m³/s with Sc held constant, the CP of Qs rises. When Qf remains steady, increased Sc leads to higher Qs, but with reduced probability of occurrence (longer return periods). Both sources of uncertainty (i.e., copula parameters and input data) significantly affect CP contours, with uncertainty amplifying as CP decreases. The uncertainty bandwidth of conditional curves grows with rising flood discharge, indicating that higher return periods or lower probabilities increase uncertainty. Overall, our study shows strong relationships between hydrological variables, emphasizing that accurate data input is essential to decrease prediction uncertainty. Advanced probabilistic methods, especially the Khoudraji copula, improve sediment transport model precision, aiding better flood risk assessment and watershed management efforts.