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作 者:徐航 陈宁生[2] 杨志全 XU Hang;CHEN Ning-sheng;YANG Zhi-quan(Faculty of Public Safety and Emergency Management,Kunming Universality of Science and Technology,Kunming 650093,China;Institute of Mountain Hazards and Environment,Chinese Academy of Sciences,Ministry of Water Resources,Chengdu 610041,China)
机构地区:[1]昆明理工大学公共安全与应急管理学院,昆明650093 [2]中国科学院、水利部成都山地灾害与环境研究所,成都610041
出 处:《科学技术与工程》2023年第9期3641-3647,共7页Science Technology and Engineering
基 金:国家自然科学基金国际(地区)合作与交流项目(41861134008);国家自然科学基金联合基金(U20A20110)。
摘 要:冰湖溃决事件频繁发生,严重阻碍西藏自治区区域社会经济发展,影响社会稳定。随着气候变暖,冰川减薄后退,冰川径流量增大,冰湖溃决风险上升。基于西藏自治区东南地区的嘎隆拉冰川径流观测资料,分析了2017—2019年消融期间5—9月冰川径流变化特征,探讨了西藏1931—2020年冰湖溃决事件发生的频次与径流峰值流量的关系。结果表明:在1931—2020年,西藏地区共发生冰湖溃决事件32次,集中在5—9月发生;在旬变化上,极大值频次呈单峰结构,在7月上旬频次最高;冰湖溃决频次与径流峰值流量显著相关,相关系数为0.673,随着径流增大,冰湖溃决发生的频次逐渐增大。在气候变暖的背景下,冰川融化引发的冰湖溃决灾害应引起重视,要加强冰川消融径流观测及冰湖水位的监测,进行冰湖溃决洪水预报。The frequent occurrence of the glacial lake outburst floods(GLOFs)has seriously hindered the social and economic development of Tibet and affected social stability.As the climate warms,the glacier thins and retreats,the glacier runoff increases,and the risk of GLOFs increases.Based on the observation data of Galongla Glacier runoff in Southeast Tibet,the characteristics of glacier runoff changes from May to September during the ablation period from 2017 to 2019 were analyzes,and the relationship between the frequency of GLOFs events in Tibet from 1931 to 2020 and the peak runoff were discussed.The results show that from 1931 to 2020,32 GLOFs occurs in Tibet,mainly from May to September.In ten-day change,the maximum frequency shows a single peak structure,and the frequency is the highest in the first ten days of July.The frequency of GLOFs is significantly correlated with the peak runoff,and the correlation coefficient is 0.673.With the increase of runoff,the frequency of GLOFs gradually increases.In the context of climate warming,GLOFs caused by glacier melting should be paid attention to,and the observation of glacier melting runoff and the monitoring of glacial lake water level should be strengthened to predict GLOFs.
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