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Arid Land Geography ›› 2024, Vol. 47 ›› Issue (11): 1828-1840.doi: 10.12118/j.issn.1000-6060.2023.609

• The Third Xinjiang Scientific Expedition • Previous Articles     Next Articles

Spatiotemporal distribution characteristics and impact assessment of snow disasters in the Ili region of Xinjiang from 1990 to 2020

HUO Hong1,2,3(), LIU Yan1,3,4(), Maiwulaxia MUBAREKE1,2,3   

  1. 1. Institute of Urumqi Desert Meteorology of China Meteorological Administration, Urumqi 830002, Xinjiang, China
    2. Wulanwusu Ecology and Agrometeorology Observation and Research Station of Xinjiang, Urumqi 830002, Xinjiang, China
    3. Field Scientific Experiment Base of Akdala Atmospheric Background, China Meteorological Administration, Urumqi 830002, Xinjiang, China
    4. Xinjiang Desert Meteorology and Sandstorm Key Laboratory, Urumqi 830002, Xinjiang, China
  • Received:2023-10-26 Revised:2024-03-04 Online:2024-11-25 Published:2024-12-03
  • Contact: LIU Yan E-mail:huohong@idm.cn;liuyan@idm.cn

Abstract:

The snow disasters in the Ili region of Xinjiang, China, have led to significant economic and social impacts, mainly through reduced agricultural production and ecosystem damage. To quantify and evaluate the impact of snow disasters in this region, this study analyzed 95 snow disaster events that occurred between 1990 and 2020. A disaster loss index was calculated using selected indicators, dimensionless processing, and weight assignment. The severity of snow disasters was categorized into four levels (mild, moderate, severe, and extreme) using the percentile method. The key findings are as follows: (1) Snow disasters in the Ili region exhibited a bimodal distribution, with peak occurrences in November and January-February, aligning with the region’s seasonal climatic characteristics. Since 2014, the frequency of snow disasters has notably decreased. (2) Mild snow disasters were the most frequent, accounting for 49.4% of events, while moderate, severe, and extreme snow disasters represented 23.2%, 24.2%, and 5.0%, respectively. (3) The most severe disaster losses were observed in Nilka County, followed by Xinyuan County and Yining County, whereas Zhaosu County was the least affected. (4) Key meteorological factors influencing snow disasters, including cumulative snowfall, maximum snow depth, minimum temperature, and snowfall duration, displayed regional variations. Areas with high snow disaster incidence had higher mean values of maximum snow depth compared to other regions. This study provides a scientific foundation for risk assessment and management of snow disasters in the Ili region.

Key words: snow disasters, disaster loss index, intensity and frequency, spatial patterns, Ili region