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冰川冻土 ›› 2016, Vol. 38 ›› Issue (2): 388-394.doi: 10.7522/j.issn.1000-0240.2016.0042

• 冰冻圈与全球变化 • 上一篇    下一篇

西藏喜马拉雅山地区冰湖溃决的预测模型及其应用研究

汪宙峰1 2, 张廷山1 2, 王成武1   

  1. 1. 西南石油大学 地球科学与技术学院, 四川 成都 610500;
    2. 西南石油大学 油气藏地质与开发工程国家重点实验室, 四川 成都 610500
  • 收稿日期:2015-10-27 修回日期:2016-02-03 出版日期:2016-04-25 发布日期:2016-07-13
  • 作者简介:汪宙峰(1983-),男,讲师,2011年在成都理工大学获博士学位,现主要从事3S与地质灾害防治研究.E-mail:1517580075@qq.com
  • 基金资助:
    国土资源部地学空间信息技术重点实验室开放基金项目(KLGSIT2015-01);西南石油大学青年教师“过学术关”资助计划项目(201131010020)资助

Prediction model and its application for glacial lake outburst in the Himalayas area, Tibet

WANG Zhoufeng1 2, ZHANG Tingshan1 2, WANG Chengwu1   

  1. 1. School of Geosciences and Technology, Southwest Petroleum University, Chengdu 610500, China;
    2. State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Southwest Petroleum University, Chengdu 610500, China
  • Received:2015-10-27 Revised:2016-02-03 Online:2016-04-25 Published:2016-07-13

摘要: 以西藏喜马拉雅山地区的冰湖为研究对象,基于现有的冰湖溃决预测方法,提出了建立冰湖溃决预测方法的关键点,即选取的指标必须能够体现冰湖的动态变化特征.在定量分析的建模过程中应该采用不确定性的数学理论,对于冰湖溃决可能性的等级划分需要进行合理性及实用性验证.选取坝顶宽度、湖水面距坝顶高度与坝高之比、冰湖面积和补给冰川面积为预测指标,通过对西藏喜马拉雅山地区29个冰湖样本进行逻辑回归分析,建立了冰湖溃决的预测模型,并用所有样本进行了交叉验证.结果表明:该模型能够在分类应用中取得较好效果,根据溃决冰湖累积百分数随冰湖溃决可能性大小的变化曲线,将冰湖溃决的可能性划分为四个等级.以黄湖为例,把湖水面距坝顶高度与坝高之比作为冰湖溃决的诱变指标,分析了冰湖溃决可能性大小的变化规律.结合现有的冰湖溃决预测的定性方法,讨论了所建立的冰湖溃决预测模型的优点和缺点.

关键词: 喜马拉雅山, 冰湖溃决, 预测模型, 逻辑回归

Abstract: Taking the glacial lakes as research object in the Himalayas area, Tibet, this paper firstly extracts three critical points in the process of making a glacial lake outburst prediction model, that is, the prediction index must be able to reflect the dynamic characteristics of the glacial lakes, the uncertainty mathematics theory should be employed to model in the quantitative analysis, and the grade classification of the probability of the glacial lake outburst need to be validated. After that, we choose the prediction variables as following, lake crest width, ratio of the lake freeboard to moraine crest height, lake area, and glacier area, and propose a prediction model based on the logistic regression analysis of 29 glacial lake samples. we found the model is effective with the cross-validation. According to the curve of the cumulative percentage of drained lakes versus outburst probability, the glacial lake outburst probability is divided into four grades. In the case of the Yellow Lake, we analyzed the variation of the glacial lake outburst probability when the ratio of the lake freeboard to moraine crest height is considered as the precipitating factor. Finally, in view of the existing qualitative methods, we have discussed the advantages and disadvantages of our model.

Key words: Himalayas, glacial lake outburst, prediction model, logistic regression

中图分类号: 

  • P343.6