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Field evidences showing rapid frontal degeneration of the Kangriz glacier,western Himalayas,Jammu&Kashmir

Journal of Mountain Science 2018年第6期15卷 1199-1208页

作者： garg siddhi shukla aparna mehta manish kumar vinit samuel shruti anna bartarya s.k. shukla uma kant wadia institute of himalayan geology 33GMS RoadDehradun 248001India department of geology banaras hindu universityVaranasi 221005India

Life cycle of glaciers in the Himalayan region has notably changed due to the climatic variability since last few decades. Glaciers across the world and specially the Himalayan glaciers have shown large scale degeneration in the last few decades. Himalayan glaciers serve as an important fresh water resource for the downstream communities, who are dependent on this water for domestic and other purposes. Therefore, glacier shrinkage and the associated hydrological changes pose a significant problem for regional-scale water budgets and resource management. These issues necessitate the regular and rigorous monitoring of the wastage pattern of the Himalayan glaciers in field and using satellite remote sensing data. In this work, we report rapid and enhanced degeneration of the frontal part of the Kangriz glacier, Jammu and Kashmir(J & K), in terms of surface melting, debris cover, snout characteristics and meltwater discharge. Ablation data acquired during 2016-2017 shows the average lowering of the frontal part of the glacier to be ~148 ± 34 cm, one-third of which was found to have occurred within a 13 day time period in September, 2017. Also, the quantum of ice melt was found to be inversely influenced(r =-0.84) by the debris thickness. 15 day meltwater discharge measurement revealed its strong relationship with snout disintegration pattern, evidenced twice during the said time period. Volume of water discharged from the glacier was estimated to be 7.91×10~6 m^3 for the measurement duration. Also, mean daily discharge estimated for the 15 days interval showed good positive correction(r = 0.78) with temperature indicating the direct dependency of the former on land surface temperature conditions of the region. Besides the lowering and discharge observations, the frequent ice-block break-offs at the glacier snout further enhance its overall drastic degeneration. The study suggests that, being the largest glacier in the Suru basin, the Kangriz glacier needs to be continuo

关键词：数据显示克什米尔喜马拉雅山脉冰河退化西方证据卫星遥感数据

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Early warning system for shallow landslides using rainfall threshold and slope stability analysis

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Geoscience Frontiers 2018年第6期9卷 1871-1882页

作者： shruti Naidu K.S.Sajinkumar Thomas Oommen V.J.Anuja Rinu A.samuel C.Muraleedharan Department of Earth Sciences Pondicherry UniversityPondicherry 605 014India Department of Geology University of KeralaThiruvananthapuram 695 581KeralaIndia Department of Geological&Mining Engineering&Sciences Michigan Technological University1400 Townsend DriveHoughtonMI 49931USA Department of Civil Engineering University of TexasArlingtonTX 76019USA Geological Survey of India Thiruvananthapuram 695 013KeralaIndia

A combined cluster and regression analysis were performed for the first time to identify rainfall threshold that triggers landslide events in Amboori, Kerala, India. Amboori is a tropical area that is highly vulnerable to landslides. The 2, 3, and 5-day antecedent rainfall data versus daily rainfall was clustered to identify a cluster of critical events that could potentially trigger landslides. Further, the cluster of critical events was utilized for regression analysis to develop the threshold equations. The 5-day antecedent(xvariable) vs. daily rainfall(y-variable) provided the best fit to the data with a threshold equation of y = 80.7-0.1981 x. The intercept of the equation indicates that if the 5-day antecedent rainfall is zero, the minimum daily rainfall needed to trigger the landslide in the Amboori region would be 80.7 mm. The negative coefficient of the antecedent rainfall indicates that when the cumulative antecedent rainfall increases, the amount of daily rainfall required to trigger monsoon landslide decreases. The coefficient value indicates that the contribution of the 5-day antecedent rainfall is～20% to the landslide trigger threshold. The slope stability analysis carried out for the area, using Probabilistic Infinite Slope Analysis Model(PISA-m), was utilized to identify the areas vulnerable to landslide in the region. The locations in the area where past landslides have occurred demonstrate lower Factors of Safety(FS) in the slope stability analysis. Thus, rainfall threshold analysis together with the FS values from slope stability can be suitable for developing a simple, cost-effective, and comprehensive early-warning system for shallow landslides in Amboori and similar regions.

关键词： Landslide Cluster analysis Rainfall threshold analysis Factor of safety Slope stability analysis PISA-m

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