Spatial and Temporal Characteristics of Snow Cover in the Tizinafu Watershed of the Western Kunlun Mountains

Remote Sensing

Jiangfeng She²  Yufang Zhang²  Xingong Li¹  Xuezhi Feng²  Yuei-An Liou³ 

[1] Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Wulumuqi 830011, China;Department of Geographical Information Science, Nanjing University, Nanjing 210023, China; E-Mails:Department of Geographical Information Science, Nanjing University, Nanjing 210023, China;

关键词: MODIS;    snow cover percentage;    snow cover duration;    topography;   

DOI  :  10.3390/rs70403426

来源: mdpi

【 摘 要 】

The Tizinafu watershed has a complex mountainous terrain in the western Kunlun Mountains; little study has been done on the spatial and temporal characteristics of snow cover in the region. Daily snow cover data of 10 hydrological years (October 2002 to September 2012) in the watershed were generated by combining MODIS Terra (MOD10A1) and Aqua (MYD10A1) snow cover products and employing a nine-day temporal filter for cloud reduction. The accuracy and window size of the temporal filter were assessed using a simulation approach. Spatial and temporal characteristics of snow cover in the watershed were then analyzed. Our results showed that snow generally starts melting in March and reaches the minimum in early August in the watershed. Snow cover percentages (SCPs) in all five elevation zones increase consistently with the rise of elevation. Slope doesn’t play a major role in snow cover distribution when it exceeds 10°. The largest SCP difference is between the south and the other aspects and occurs between mid-October and mid-November with decreasing SCP, indicating direct solar radiation may cause the reduction of snow cover. While both the mean snow cover durations (SCDs) of the hydrological years and of the snowmelt seasons share a similar spatial pattern to the topography of the watershed, the coefficient of variation of the SCDs exhibits an opposite spatial distribution. There is a significant correlation between annual mean SCP and annual total stream flow, indicating that snowmelt is a major source of stream runoff that might be predictable with SCP.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.