Abstract: | Hydrological models play an important role in water resource management, but they always
suffer from various sources of uncertainties. Therefore, it is necessary to implement uncertainty
analysis to gain more confidence in numerical modeling. The study employed three methods (i.e.,
Parameter Solution (ParaSol), Sequential Uncertainty Fitting (SUFI2), and Generalized Likelihood
Uncertainty Estimation (GLUE)) to quantify the parameter sensitivity and uncertainty of the SWAT
(Soil andWater Assessment Tool) model in a mountain-loess transitional watershed—Jingchuan River
Basin (JCRB) on the Loess Plateau, China. The model was calibrated and validated using monthly
observed streamflow at the Jingchuan gaging station and the modeling results showed that SWAT
performed well in the study period in the JCRB. The parameter sensitivity results demonstrated that
any of the three methods were capable for the parameter sensitivity analysis in this area. Among
the parameters, CN2, SOL_K, and ALPHA_BF were more sensitive to the simulation of peak flow,
average flow, and low flow, respectively, compared to others (e.g., ESCO, CH_K2, and SOL_AWC) in
this basin. Although the ParaSol method was more efficient in capturing the most optimal parameter
set, it showed limited ability in uncertainty analysis due to the narrower 95CI and poor P-factor and
R-factor in this area. In contrast, the 95CIs in SUFI2 and GLUE were wider than ParaSol, indicating
that these two methods can be promising in analyzing the model parameter uncertainty. However,
for the model prediction uncertainty within the same parameter range, SUFI2 was proven to be
slightly more superior to GLUE. Overall, through the comparisons of the proposed evaluation criteria
for uncertainty analysis (e.g., P-factor, R-factor, NSE, and R2) and the computational efficiencies,
SUFI2 can be a potentially efficient tool for the parameter optimization and uncertainty analysis. This
study provides an insight into selecting uncertainty analysis method in the modeling field, especially
for the hydrological modeling community. |