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冰川冻土 ›› 2022, Vol. 44 ›› Issue (3): 984-997.doi: 10.7522/j.issn.1000-0240.2022.0093

• 冰冻圈与全球变化 • 上一篇    下一篇

1979—2020年天山地区积雪量估算及其特征分析

朱淑珍1,2,3(), 黄法融1,2,4,5, 冯挺1,2,3, 赵鑫6, 李兰海1,2,3,4,5()   

  1. 1.中国科学院 新疆生态与地理研究所 荒漠与绿洲生态国家重点实验室,新疆 乌鲁木齐 830011
    2.中国科学院 伊犁河流域生态系统 研究站,新疆 新源 835800
    3.中国科学院大学,北京 100049
    4.新疆干旱区水循环与水利用重点实验室,新疆 乌鲁木齐 830011
    5.中国科学院 中亚生态与环境研究中心,新疆 乌鲁木齐 830011
    6.南宁师范大学 地理与海洋研究院,广西 南宁 530001
  • 收稿日期:2021-12-23 修回日期:2022-04-08 出版日期:2022-06-25 发布日期:2022-08-27
  • 通讯作者: 李兰海 E-mail:zhushuzhen19@mails.ucas.ac.cn;lilh@ms.xjb.ac.cn
  • 作者简介:朱淑珍,硕士研究生,主要从事积雪水文研究. E-mail: zhushuzhen19@mails.ucas.ac.cn
  • 基金资助:
    国家自然科学基金青年科学基金项目(41901048);国家自然科学基金联合基金项目(U1703241);科技部科技基础资源调查专项(2017FY100501);中国科学院青年创新促进会项目(2021438)

Estimation of snow mass and its distribution characteristics from 1979 to 2020 in Tianshan Mountains, China

Shuzhen ZHU1,2,3(), Farong HUANG1,2,4,5, Ting FENG1,2,3, Xin ZHAO6, Lanhai LI1,2,3,4,5()   

  1. 1.State Key Laboratory of Desert and Oasis Ecology,Xinjiang Institute of Ecology and Geography,Chinese Academy of Sciences,Urumqi 830011,China
    2.Ili Station for Watershed Ecosystem Research,Chinese Academy of Sciences,Xinyuan 835800,Xinjiang,China
    3.University of Chinese Academy of Sciences,Beijing 100049,China
    4.Xinjiang Key Laboratory of Water Cycle and Utilization in Arid Zone,Urumqi 830011,China
    5.Research Center for Ecology and Environment of Central Asia,Chinese Academy of Sciences,Urumqi 830011,China
    6.Institute of Geography and Oceanography,Nanning Normal University,Nanning 530001,China
  • Received:2021-12-23 Revised:2022-04-08 Online:2022-06-25 Published:2022-08-27
  • Contact: Lanhai LI E-mail:zhushuzhen19@mails.ucas.ac.cn;lilh@ms.xjb.ac.cn

摘要:

积雪作为干旱区的重要水源,深刻影响区域水资源及经济发展。决定积雪量的积雪深度、积雪面积和积雪密度在时空分布上存在不确定性,尤其是积雪密度难以获取。本文利用FY-3B/MWRI(Fengyun 3B Microwave Radiation Imager)数据反演积雪密度,结合1979—2020年长时间序列遥感雪深数据集,对天山地区40多年来积雪期(11月—次年3月)及其不同时期(积累期、稳定期、消融期)的积雪量进行估算,并分析其时空分布及与地形、气象等因子之间的关系。结果表明:1979—2020年,天山地区积雪期不同时期积雪量存在差异,稳定期积雪量最大,消融期次之,积累期最小。研究时段内,积雪期积雪量最大值出现在1979年,最小值出现在1998年,积雪期积雪量呈微弱的下降趋势,消融期积雪量下降趋势显著。多年平均积雪量空间格局与积雪深度和积雪密度基本一致,主要呈现为西北多东南少的特点。天山地区积雪量空间分布主要受海拔、坡度影响,积雪量与海拔正相关,海拔越高,积雪量越丰富;在15°以下时,坡度对积雪的影响较大,且坡度越大,积雪量越大。不同时期积雪量的多年变化与气温关系密切,在一定温度范围内,气温越低,积雪量越大;稳定期积雪量变化同时受积累期降水影响,积累期降水越多,稳定期积雪量越大。本文基于遥感积雪深度和密度的天山积雪量研究结果,可供气候变化条件下新疆水资源利用和经济发展参考。

关键词: 积雪密度, 积雪量, 遥感, FY-3B/MWRI, 天山

Abstract:

Snow mass in mountains areas is an important water source and can bring economic benefits to regional development. Therefore, the amount of snow mass has a profound impact on regional water resources and economic development. The uncertainties in the spatial and temporal distribution of snow depth, snow cover and snow density, which integrally determine the amount of snow, result in the difficulties to determine the snow mass. This paper estimated the snow mass amount during the snow season (November to March ) and its different periods (accumulation, stable and melt period) in Tianshan Mountains over the past 40 years, and analyze its spatial and temporal distributions as well as its relationship with topographic and meteorological factors, using the dataset of snow depth time series from 1979 to 2020 and the snow density retrieving from the Fengyun 3B Microwave Radiation Imager (FY-3B/MWRI). The results showed that: (1) snow mass in the Tianshan Mountains varied in different periods from 1979 to 2020, i.e. the snow mass in the stable period was the largest, followed by the ablation period and the smallest in the accumulation period. The maximum and minimum values of snow mass in snow season appeared in 1979 and 1998, respectively. The snow mass showed a slight downward trend during the study period, but a significant downward trend during the ablation period. (2) The spatial pattern of mean snow mass is consistent with snow depth and snow density during the study period, i.e. high in northwest and low in southeast. (3) The spatial distribution of snow mass is mainly affected by altitude and slope, and the snow mass is positively correlated with altitude. The higher the altitude, the higher snow mass. The slope below 15° has a great impact on snow mass, and the greater the slope within the 15° limit, the higher the snow mass. (4) The multi-year variation of snow mass in different periods is closely related to air temperature. The lower the air temperature in certain range, the greater the snow mass. The change of snow mass in the stable period is also affected by precipitation in the accumulation period, i.e. higher precipitation, and more snow mass. The results of estimated snow mass in Tianshan Mountains based on the snow depth and density retrieved from remote sensing data may provide a reference for water resources utilization and economic development in Xinjiang under the condition of climate change.

Key words: snow density, snow mass, remote sensing, FY-3B/MWRI, Tianshan Mountains

中图分类号: 

  • P426.63+5