Abstract:
Based on streamflow data from station observations, CN05 gridded precipitation and temperature data over China, and remote sensing snow data, the interannual variations of spring streamflow and its relationships with precipitation, snowpack, and temperature in the Three-River Headwater region were investigated. Results show that spring streamflow exhibits high interannual variability from 1980 to 2020, with the largest interannual variability in May. Correlation analysis indicates that spring streamflow is significantly correlated with spring snowpack. The streamflow in April and May is significantly correlated with snow depth, snow cover fraction, and previous accumulated precipitation. Among these, snow depth shows the strongest correlation, with a correlation coefficient of up to 0.7. Further analysis shows that the influence of snowmelt on streamflow varies between different basins and spring months, depending on snow depth conditions and maximum temperature. In the Yellow River headwater area, the April and May streamflow is most influenced by snow depth in April. In the Yangtze River headwater area, May streamflow is mostly influenced by snow depth in April and May. Similarly, in the Lancang River headwater area, streamflow in April and May is influenced by the snow depth from February to May. The impact of snow depth on streamflow relies on altitude. At lower altitudes, the influence occurs in early spring. In mountainous regions, such as the Aemye Ma-chhen Range, BaYanKaLa Mountains, and Tanggula Mountains, the influence can last until May. Moreover, air temperature plays a crucial role in influencing spring snowmelt by influencing snow accumulation and melting processes. The results of this study will help understand how climate change affects spring streamflow in the Three-River Headwater region.