Comparison of Sequential Uncertainty Fitting Algorithm (SUFI-2) and Parameter Solution (ParaSol) Method for Analyzing Uncertainties in Distributed Hydrological Modeling - A Case Study

摘要

As the distributed hydrological models play a very important role at water resource management, reliable quantification of uncertainty in hydrological modeling results is quite necessary. The purpose of this study is to better understand the hydrology of the study area and help decision making processes for watershed water resource management through scientific uncertainty analysis. In this study, the upstream of the Wenjing River watershed in Western China was selected as the study area. The soil and water assessment tool (SWAT) model was applied to simulate the surface runoff during 1998-2001 and validated by the observed data. After global sensitivity analysis and modeling calibration, the R~2 values of surface runoff for calibration and verification periods were up to 0.724 and 0.921, respectively. Due to less computation efforts and the feasibility to handle complex models, two uncertainty analysis methods were further conducted and compared: 1) the sequential uncertainty fitting algorithm (SUFI-2) and 2) the parameter solution (ParaSol) method. After comparison of evaluation criteria (r-factor and p-factor) and performance of best estimates of uncertainty analysis, SUFI-2 was able to provide more reasonable predictive results than ParaSol.