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ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa
CURRENT PROBLEMS IN REMOTE SENSING OF THE EARTH FROM SPACE

  

Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2020, Vol. 17, No. 2, pp. 101-113

Snow cover changes of the Kazakhstan dry steppes and semi-deserts: the case of River Emba basin studies

A.G. Terekhov 1, 2 , N.I. Ivkina 2 , N.R. Unicheva 1 , I.S. Vitkovskaya 1 , A.G. Yeltay 3 
1 Institute of Information and Computing Technology MES RK, Almaty, Kazakhstan
2 RSE Kazhydromet, Almaty, Kazakhstan
3 Al-Farabi Kazakh National University, Almaty, Kazakhstan
Accepted: 10.02.2020
DOI: 10.21046/2070-7401-2020-17-2-101-113
The Snow Depth FEWS NET product with daily update was used to analyze the snow regime of the upper part of the Emba River basin. The observation interval covered the period from January 01 to April 30 for 2001–2019. The Emba River basin is situated in Kazakhstan at the Eastern coast of the Caspian Sea. The area is characterized by a semi-arid to arid and extreme continental climate with dry-steppe and semi-desert landscapes. The population is small and the anthropogenic impact on the snow cover is minimal there. These conditions give an opportunity to identify the natural tendency in long-term changes of snow cover. In this paper, the trends over the last 19 years of the three snow cover characteristics, including the seasonal maximum, seasonal average and snow cover duration are presented. It was shown that the snow conditions for the seasonal maximum are triggered. There are two modes, the first is a low-snow regime (approximately 20 % of the entire sample) and the second mode covers the other years. The trends of the last 19 years show increasing snow depth. Also, there is a tendency of snow cover duration decrease. There is no trend in the seasonal average of the snow depth. The results obtained for snow cover of the dry-steppe and semi-desert zones of Kazakhstan are consistent with data from the 7th National report on climate change in Kazakhstan, which is based on meteorological observation of the air temperature and precipitation. Comparison of the Snow Depth FEWS NET product with snow depth ground data of weather station (Kazakhstan, Aktobe; WMO ID 35299) showed a good agreement of the long-term daily average values with the Pearson correlation coefficient of 0.963.
Keywords: Central Asia, Eastern coast of the Caspian Sea, Emba River, remote sensing, snow depth, multi-year trends, Snow Depth FEWS NET
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