A novel multisite cascading calibration (MSCC) approach using the shuffled complex evolution–University of Arizona (SCE-UA) optimization method, developed at the University of Arizona, was employed to calibrate the variable infiltration capacity (VIC) model in the Red River Basin. Model simulations were conducted at 35 nested gauging stations. Compared with simulated results using a priori parameters, single-site calibration can improve VIC model performance at specific calibration sites; however, improvement is still limited in upstream locations. The newly developed MSCC approach overcomes this limitation. Simulations using MSCC not only utilize all of the available streamflow observations but also better represent spatial heterogeneities in the model parameters. Results indicate that MSCC largely improves model performance by decreasing the number of stations with negative Nash-Sutcliffe coefficient of efficiency (NSCE) values from 69% (66%) for a priori parameters to 37% (34%) for single-site ...

The understanding of the temporal and spatial dynamics of soil moisture and hydraulic property of soil is crucial to the study of hydrological and ecological processes. The purpose of this study was to derive equations that describe spatial soil water storage deficit based on topography and soil properties. This storage deficit together with the topographical index can be used to conclude the spatial distribution curve of storage capacity in a (sub-) basin for developing hydrological model. The established model was able to match spatial and temporal variations of water balance components (i.e., soil moisture content (SMC), evapotranspiration, and runoff) over the Ziluoshan basin. Explicit expression of the soil moisture storage capacity (SMSC) in the model reduced parameters, which provides a method for hydrological simulation in ungauged basins.