Application of swat model with cmads data for hydrological simulation in western China

Abstract

Precise simulations of hydrological processes under the influence of climate change and human activities have special significance in arid basins. During the past 60 years, the annual average temperature and precipitation at the northern foothills of the Tianshan Mountains have increased at the rates of 0.035ºC/year and 0.881 mm/year, respectively. Rising temperatures will change the temporal and spatial distributions and forms of precipitation, accelerate glacier retreat, melt snow on high mountains, cause the degeneration of frozen soil, and change the runoff composition in the Tianshan area. In this work, the CMADS (China Meteorological Assimilation Driving Dataset for the SWAT model) was combined with the SWAT (Soil and Water Assessment Tool) model to simulate runoff in the upper reaches of the Jing River and Bo River Basins in the Tianshan area. The results were as follows. (1) On the monthly scale, the average Nash–Sutcliffe efficiency (NSE) coefficients of the calibration period in the Wenquan and Jinghe–Shankou hydrological stations were 0.79 and 0.87, respectively, and the NSE coefficients of validation period were 0.71 and 0.82, respectively. On the daily scale, the NSE coefficients of the two hydrological stations were between 0.69 and 0.77. The simulation results were considered to be ideal on the monthly and daily scales. (2) Under different climate scenarios and land-use patterns, the cultivated land in the basin leads to the reduction of runoff, and the grassland and woodland stabilise the river flood season. Lakes and wetlands, which can reduce the flow in the flood season and provide water for rivers in the dry season, are very important for runoff regulation. Compared with the traditional meteorological stations, CMADS demonstrates good representativeness and reliability in the Jinghe River and Bohe River Basins under different climate and land-use scenarios, greatly improving the runoff simulation ability.