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Probability Prediction Model for Landslide Occurrences in Xi'an, Shaanxi Province, China

Probability Prediction Model for Landslide Occurrences in Xi'an, Shaanxi Province, China

作     者:ZHUANG Jian-qi IQBAL Javed PENG Jian-bing LIU Tie-ming 

作者机构:College of Geological Engineering and Surveying of Changan University/Key Laboratory of Western China Mineral Resources and Geological Engineering Department of Earth Sciences COMSATS Institute of Information Technology Institute of Geology and GeophysicsChinese Academy of Sciences Geo-hazards Mitigation and Research of Chang'an University 

出 版 物:《Journal of Mountain Science》 (山地科学学报(英文))

年 卷 期:2014年第11卷第2期

页      面:345-359页

核心收录:

学科分类:081803[工学-地质工程] 08[工学] 0818[工学-地质资源与地质工程] 

基  金:financially supported by the National Natural Science Foundation of China (Grant Nos. 41130753 and 41202244) the National Key Fundamental Research Program of China (973) (Grant No. 2014CB744703) China Postdoctoral Science Foundation (Grant No. 2012M521728) 

主  题:Landslide Probability prediction model Real-time monitoring Xi'an 

摘      要:Landslides are increasing since the 1980s in Xi an, Shaanxi Province, China. This is due to the increase of the frequency and intensity of precipitation caused by complex geological structures, the presence of steep landforms, seasonal heavy rainfall, and the intensifcation of human activities. In this study, we propose a landslide prediction model based on the analysis of intraday rainfall(IR) and antecedent effective rainfall(AER). Primarily, the number of days and degressive index of the antecedent effective rainfall which affected landslide occurrences in the areas around Qin Mountains, Li Mountains and Loess Tableland was established. Secondly, the antecedent effective rainfall and intraday rainfall were calculated from weather data which were used to construct critical thresholds for the 10%, 50% and 90% probabilities for future landslide occurrences in Qin Mountain, Li Mountain and Loess Tableland. Finally, the regions corresponding to different warning levels were identified based on the relationship between precipitation and the threshold, that is; A region is safe, B region is on watch alert, C region is on warning alert and D region is on severe warning alert. Using this model, a warning program is proposed which can predict rainfall-induced landslides by means of real-time rain gauge data and real-time geo-hazard alert and disaster response programs. Sixteen rain gauges were installed in the Xi an region by keeping in accordance with the regional geology and landslide risks. Based on the data from gauges, this model accurately achieves the objectives of conducting real-time monitoring as well as providing early warnings of landslides in the Xi an region.

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