1990—2020年新疆伊犁地区雪灾时空分布特征及其影响评估

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

雪灾给伊犁地区带来了重大的经济和社会影响,主要表现在农业生产的减少和生态系统的破坏等方面。为量化和评估雪灾对伊犁地区的影响,基于1990—2020年伊犁地区的95次雪灾事件,通过指标选择、无量纲化处理以及权重分配,计算了灾损指数,并依据百分位数法,将雪灾严重性划分为一般、较重、严重和特重4个等级。结果表明:(1)1990—2020年伊犁地区雪灾次数呈双峰型分布,11月和1—2月为高发期,与季节性气候特征相关。自2014年以来,雪灾的发生次数显著下降。(2)1990—2020年伊犁地区一般等级雪灾最为常见,占比49.4%,较重、严重和特重等级占比分别为23.2%、24.2%和5.0%。(3)尼勒克县的灾损最严重,其次是新源县和伊宁县,昭苏县受影响最小。(4)雪灾发生及其严重性受累积降雪量、最大积雪深度、最低气温和降雪持续天数等气象要素影响。这些要素在县域间差异显著但整体趋势集中。研究结果可以为伊犁地区雪灾风险评估和管理提供科学依据。

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.