Resumen
The scarcity and uneven distribution of precipitation stations in the inland river basins of the Northeastern Tibetan Plateau restrict the application of the distributed hydrological model and spatial analysis of water balance component characteristics. This study used the upper Heihe River Basin as a case study, and daily gridded precipitation data with 3 km resolution based on the spatial interpolation of gauged stations and a regional climate model were used to construct a soil and water assessment tool (SWAT) model. The aim was to validate the precision of high-resolution gridded precipitation for hydrological simulation in data-scarce regions; a scale transformation method was proposed by building virtual stations and calculating the lapse rate to overcome the defects of the SWAT model using traditional precipitation station data. The gridded precipitation was upscaled from the grid to the sub-basin scale to accurately represent sub-basin precipitation input data. A satisfactory runoff simulation was achieved, and the spatial variability of water balance components was analysed. Results show that the precipitation lapse rate ranges from 40 mm/km to 235 mm/km and decreases from the southeastern to the northwestern areas. The SWAT model achieves monthly runoff simulation compared with gauged runoff from 2000 to 2014; the determination coefficients are higher than 0.71, the Nash?Sutcliffe efficiencies are higher than 0.76, and the percentage bias is controlled within ±15%. Meadow and sparse vegetation are the major water yield landscapes, and the elevation band from 3500 m to 4500 m is the major water yield area. Precipitation and evapotranspiration present a slightly increasing trend, whereas water yield and soil water content present a slightly decreasing trend. This finding indicates that the high-resolution gridded precipitation data fully depict its spatial heterogeneity, and scale transformation significantly promotes the application of the distributed hydrological model in inland river basins. The spatial variability of water balance components can be quantified to provide references for the integrated assessment and management of basin water resources in data-scarce regions.