Estimating snow water equivalent using observed snow depth data in China

Abstract

Study region: China. Study focus: The snow water equivalent (SWE) characterizes the hydrological significance of the snow and is essential for the study of water resources in snow-covered areas. However, SWE measurements are time-consuming and labour-intensive, and the amount of observed SWE data globally is small compared to snow depth (SD), particularly in China. This has limited the study of snow hydrology in China. To this end, we parameterize the SWE and briefly analyse the spatiotemporal distribution and variations of the SWE in China. New hydrological insights for the region: The mean absolute error, root mean square error and Nash-Sutcliffe efficiency coefficient of the estimation model are 0.49 g cm−2, 0.81 g cm−2, and 0.80, respectively, which indicate that the model performs well overall. The estimation model is able to accurately estimate SWE for different seasons and altitudes in China. However, due to the influence of SD, the estimation model is more applicable in snow-rich areas such as the Northern Xinjiang, Northeast China and middle and lower Yangtze River Plain, and less applicable in the Qinghai-Tibet Plateau. The trend of SWE in China increases at high latitudes and low altitudes and decreases at low latitudes and high altitudes. The seasonality trend of SWE varies widely in different regions. The results of the study provide a new approach to the study of snow hydrology in China.

Keywords

• Snow water equivalent
• Snow depth
• Estimation model
• Spatiotemporal distribution
• Variations
• China