Parameter Uncertainty Analysis of Surface Flow and Sediment Yield in the Huolin Basin, China

Abstract

Growing concerns have been given to parameter uncertainty in hydrological modeling because of the associated effects on water resource management. In this study two uncertainty analysis methods, the sequential uncertainty fitting algorithm (SUFI-2) and the generalized likelihood uncertainty estimation (GLUE), were employed to analyze the uncertainty of surface flow and sediment yield modeling results by the soil and water assessment tool (SWAT) model. The two methods were also compared in terms of the capability in quantifying parameter and prediction uncertainties and the computational efficiency. The results showed that the SUFI-2 method was capable of examining the uncertainty by using the Latin hypercube sampling scheme. It also demonstrated the advantages in analyzing the effects of uncertainties for distributed hydrological models with complex structure and high computational demands. The GLUE method is specialized in reflecting parameter correlations and uncertainties associated with parameters and predictants.