Stochastic modeling of suspended sediment load in alluvial rivers

Research Context

Suspended sediment is a major non-point pollution carrier and strongly affects nutrients, toxicants, and downstream ecological stability. Modeling nonlinear discharge-sediment dynamics remains a central challenge in river engineering.

Method

The paper introduces a parsimonious probabilistic framework built on copula theory and Bayesian structures to represent dependence between discharge ($Q$) and suspended sediment load ($SSL$).

$$ F_{QS}(q, s) = C(F_Q(q), F_S(s)) $$

Key Contributions

• Captures nonlinear dependence and tail behavior beyond linear correlation.
• Infers conditional SSL distributions for given discharge conditions.
• Improves reliability over conventional regression models.