Uncertainty analysis of sediment rating curve and suspended sediment dynamics in the Hieu river basin

The sediment rating curve (SRC), which describes the empirical relationship between suspended sediment concentration (SSC) and streamflow (Q), is widely used for sediment transport estimation. Uncertainties in SRC coefficients can substantially affect the reliability of estimation. This study investigates the uncertainty associated with SRC parameters in the Hieu river basin. Monte Carlo (MC) simulation and Bootstrap (BM) resampling techniques were applied to quantify uncertainties in the rating coefficient (a) and exponent (b) of the SRC for Quy Chau and Nghia Khanh stations under both pre- and post-reservoir construction conditions. Daily streamflow data (1969–2024) and SSC observations (2009–2024) were collected. The results indicate that 5,000 iterations are sufficient for convergence of probabilistic metrics, including the continuous ranked probability score (CRPS) and Sharpness. The estimated 95% confidence intervals of rating coefficient range from 0.0004 to 0.0021 for Quy Chau and 0.0015 to 0.0036 for Nghia Khanh, while the exponent varies between 1.786–2.046 and 1.604–1.799, respectively. Reservoir construction significantly modified the SSC–Q relationship, reducing the rating coefficient at the upstream station while increasing the nonlinearity of sediment transport processes. SSC estimates from SRC showed good agreement with observations, with dimensional errors (including root mean square error, mean absolute error, and mean error) less than 3% of the observed SSC magnitude at stations, while dimensionless errors (including Nash–Sutcliffe efficiency and Pearson's correlation coefficient) range from 0.68 to 0.86. Using the appropriate values of SRC coefficients, historical SSC series for the period 1969–2008 were reconstructed, revealing substantial long-term variability in sediment transport. Wavelet analysis further identified dominant periodicities and multiscale dynamics in SSC, thus highlighting strong seasonal and multiyear variability and a persistent coupling between streamflow and sediment transport. The integration of probabilistic uncertainty analysis and wavelet techniques provides a reliable framework for improving sediment estimation and enhancing the understanding of sediment dynamics in the river basin.