Abstract
Abstract. Model calibration is essential for hydrologic modeling of large watersheds in a heterogeneous mountain environment. Little guidance is available for model calibration protocols for distributed models that aim at capturing the spatial variability of hydrologic processes. This study used the physically-based distributed hydrologic model, MIKE SHE, to contrast a lumped calibration protocol that used streamflow measured at one single watershed outlet to a multi-site calibration method which employed streamflow measurements at three stations within the large Chaohe River basin in northern China. Simulation results showed that the single-site calibrated model was able to sufficiently simulate the hydrographs for two of the three stations (Nash-Sutcliffe coefficient of 0.65–0.75, and correlation coefficient 0.81–0.87 during the testing period), but the model performed poorly for the third station (Nash-Sutcliffe coefficient only 0.44). Sensitivity analysis suggested that streamflow of upstream area of the watershed was dominated by slow groundwater, whilst streamflow of middle- and down- stream areas by relatively quick interflow. Therefore, a multi-site calibration protocol was deemed necessary. Due to the potential errors and uncertainties with respect to the representation of spatial variability, performance measures from the multi-site calibration protocol slightly decreased for two of the three stations, whereas it was improved greatly for the third station. We concluded that multi-site calibration protocol reached a compromise in term of model performance for the three stations, reasonably representing the hydrographs of all three stations with Nash-Sutcliffe coefficient ranging from 0.59–072. The multi-site calibration protocol applied in the analysis generally has advantages to the single site calibration protocol.
Highlights
The importance of spatial variability of land surface characteristics is widely recognized in understanding the physical/hydrological, biological, and other related process in watersheds (Becker and Braun, 1999)
It is important to take into account the spatial variability when modeling watershed hydrology and understanding watershed hydrological processes (Beven, 2001; Bloschl et al, 1995; Merz and Bardossy, 1998; Anquetin et al, 2010)
According to the performance criteria (Table 2), both EF and R indicated that the model generally performed well in simulating hydrograph of Xiahui station
Summary
The importance of spatial variability of land surface characteristics is widely recognized in understanding the physical/hydrological, biological, and other related process in watersheds (Becker and Braun, 1999). It is important to take into account the spatial variability when modeling watershed hydrology and understanding watershed hydrological processes (Beven, 2001; Bloschl et al, 1995; Merz and Bardossy, 1998; Anquetin et al, 2010). This is true for modeling large-scale watersheds that have more diverse hydrological conditions than small watersheds (Sivapalan, 2003). Lumped hydrologic models are usually precluded in the case of applications to un-gauged watersheds as a result of the significant changes between
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