IMHE OpenIR  > 山地灾害与地表过程重点实验室
气候变暖对藏东南山地灾害的影响机制
Alternative TitleThe inpact mechanism of climate warming on mountain hazards in the southeast of Tibet
贾洋
Subtype博士
Thesis Advisor崔鹏
2018
Degree Grantor中国科学院大学
Place of Conferral北京
Degree Discipline自然地理学
Keyword气候变暖 冰川泥石流 冰湖溃决 灾变条件 藏东南
Abstract以藏东南冰湖溃决和冰川泥石流为研究对象,利用气象观测数据(1960年至今)和灾史资料,通过分析藏东南极端气候的变化规律,对藏东南过去几十年发生的冰湖溃决和大型冰川泥石流灾害进行气候重建。并针对灾害成灾环境特点,提取关键致灾因子,开展气候变暖对藏东南山地灾害影响机制的研究。基于研究结论,结合RCP气候变化情景模式,对藏东南地区未来山地灾害活动趋势进行预测。论文取得以下主要成果:1、针对藏东南气象资料缺乏的问题,应用气象插值、遥感降水栅挌数据多边型区域纠偏等方法,计算获得一套具有较高精度的时间序列气象数据资料,填补了藏东南地区无气象站点监测区域的灾害分析数据空白。2、系统分析了藏东南地区50多年气象资料和多时相遥感数据,阐明了藏东南极端气候与孕灾环境变化规律及其突变特征。3、根据典型灾害形成机理,遴选出冰湖溃决和冰川泥石流形成的关键气候因子,构建了冰崩型冰湖溃决灾害和冰川泥石流灾害判定模型,确定了灾害发生的阈值条件。4、综合利用气候变化特征和地表地形特征,构建了同时考虑气候和地表因素的冰崩型冰湖溃决灾害危险判识综合模型。此外,基于积雪气候和流域物质能量条件对藏东南冰川泥石流危险性进行阈值分区。基于气候变化情景,分析了藏东南未来极端气候演变特征,预估了未来大规模山地灾害的活动趋势。根据冰湖面积和地形危险程度及各泥石流流域未来地表变化情况,提出未来具有较大概率暴发大型灾害事件的12条泥石流沟和25个冰湖,需要重点关注。 
Other AbstractBy analyzing meteorological data and mountain hazards events since 1960, we summed up the characteristics of the extreme climate change in Tibet and found the relationship between the mountain hazards formation and climate extremes. And we determined the key factors based on the change of environment that benefits the occurrence of hazards. Through the analysis of the characteristic space of each factor, we created the climate model of the disaster and identified the thresholds of model. Finally, we predict the future trend of mountain hazards activities in the southeast of Tibet by using the RCP scenario model of climate change.The thesis mainly achieved the following results1. In view of the lack of meteorological data in southeastern Tibet, a set of regional meteorological data with high accuracy have been developed by using the method of Anusplin, and ThiessenPolygons-based TRMM precipitation correction. The error evaluation results show that the mean error of the temperature interpolated data is less than 0.9 ℃and the average error of cumulative precipitation for 30 days is 15.24 mm, which can be used to the weather conditions analysis of mountain hazards in Tibet. These regional data fill the gap the acquisition of temperature and precipitation in the non-monitoring area in southeastern Tibet.2. Through remote sensing interpretation and meteorological data analysis since 1960s from the time scale of decadal, annual, seasonal and monthly respectively. The reasons for the abrupt change of extreme climate, seasonal and regional extreme climate change in Tibet are revealed from the aspects of atmospheric circulation, water vapor flux and topography. Moreover, the changes of glacier, glacial lake and snow accumulation in southeastern Tibet were analized during the past 50 years. 3. According to the formation mechanism of glacial debris flows and glacier lake outburst flood (GLOF) triggered by glacier collapse, some key climatic factors were selected to build the hazards (glacial debris flows and GLOF) identification models in the annual climate change and the short-term weather condition, and the climate threshold of models were determined.4. The comprehensive model, considering terrain ground surface environment and climate background, were built to assess the risk of glacial debris flows and GLOF triggered by glacier collapse, respectively. What’s more, the activity trends of mountain hazards in the southeast of Tibet were predicted by the future change of temperature, precipitation and glacier under the RCP2.6 scenario model. The results show that the future climate environment is beneficial to the outbreak of large mountain disasters. Finally, 12 debris flow gullies and 25 glacial lakes have high harzard probability in the future according to comprehensive changes of the area of glacial lakes, the hazard degree of terrain and the land surface of debris flows gullies.
Pages202
Language中文
Document Type学位论文
Identifierhttp://ir.imde.ac.cn/handle/131551/24791
Collection山地灾害与地表过程重点实验室
Affiliation中国科学院成都山地灾害与环境研究所
First Author Affilication中国科学院水利部成都山地灾害与环境研究所
Recommended Citation
GB/T 7714
贾洋. 气候变暖对藏东南山地灾害的影响机制[D]. 北京. 中国科学院大学,2018.
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