Multivariate Frequency Analysis of Annual Maxima Suspended Sediment Concentrations and Floods in the Jinsha River, China

Abstract

Streamflow plays a critical role in sediment transport. Traditional frequency analysis of annual maximal (AM) suspended sediment concentrations (SSCs) is usually based on univariate distribution of SSCs and may provide a limited assessment of SSC state, leading to an underestimate or overestimate of the corresponding probability. To address this issue, a multivariate frequency analysis framework is proposed for extreme sediment events using copula functions that account for the joint behavior of SSC and flood flow (i.e., peak discharge and volume). The uncertainties associated with copula modeling are also discussed. The Jinsha River in China is used as a case study. The results show that the copula-based multivariate method provides a more comprehensive assessment of extreme SSCs and their recurrence intervals than univariate frequency analysis. The uncertainty of copula modeling decreases with longer observation time and increases with larger return periods. The uncertainty ranges of the most likely design quantiles vary with different copulas, and the uncertainty range for the best-fit copula is not the smallest. This study is useful for the risk assessment of extreme SSC events under flood conditions.