基于双变量方法的滑坡易感性评价——以尼勒姆河和耶赫勒姆河流域为例

Shehla Gul, Tehmina Bibi, Sabit Rahim, J. Qureshi, Arshad Ali Shadayi, A. Jalal, Humanyoun Tariq
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摘要

滑坡是巴基斯坦北部地区频繁发生的自然灾害。目前的研究旨在评估滑坡灾害的易感性,以突出Muzaffarabad地区Neelum和Jehlum河沿岸的脆弱地区,以减少风险。采用数据驱动的预测方法,采用证据权重(WOE)模型和11个条件因子进行研究。利用数字高程模型(DEM)的正射影像图、既往记录和导数(山影、地形开阔度、坡度、坡向、曲率)绘制滑坡空间分布图。结果表明,道路、岩性和河流是两个流域滑坡最重要的触发因素。Jhelum流域约30%的面积处于低易感区,而Neelum流域仅13%的面积处于低易感区。Jhelum河流域中易感带面积占总面积的35%,Neelam河流域中易感带面积占总面积的26%。Neelam河谷约61%的土地和Jhelum河谷约35%的土地处于高易感带。高危区位于该区东北部,岩性薄弱(泥岩、砂岩、页岩、粘土)、陡坡高海拔、降水过多(1800 mm/年)等因素均有利于引发山体滑坡。研究区高危险区不适宜建设,适宜人工造林。验证结果(89.41%)证明了该模型的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Landslide Susceptibility Assessment Using Bivariate Method: A Case Study from River Neelum and Jehlum Catchment Area
Landslide is a frequently occurring natural calamity in the northern areas of Pakistan. The current study is aimed to assess the susceptibility of landslide hazard to highlight the vulnerable areas for the purpose of risk reduction along Neelum and Jehlum rivers in district Muzaffarabad. A data-driven predictive approach was adopted to conduct this study by using Weight of Evidence (WOE) model along with eleven conditioning factors. A spatial distribution map of landslides was prepared using orthophoto, previous records, and derivatives (hill shad, topographic openness, slope, aspect, curvature) of Digital Elevation Model (DEM). The results show that the roads, lithology, and rivers are the most important triggering factors for landslides in both valleys. Approximately 30% of the area is under low susceptibility zone in Jhelum valley while only 13% of the area falls under low susceptibility zone in Neelum river valley. In Jhelum river valley the medium susceptibility zone covers 35% of the total area whereas, Neelam river valley has 26% of the total area under medium susceptibility zone. Around 61% of the land in the Neelam river valley and 35% of the land in the Jhelum river valley are under high susceptibility zone. The area under high hazard lies in the north-east of the district due to multiple conducive factors to trigger landslides including weak lithology (mudstone, sandstone, shales, and clays), high altitude along steep slopes and excessive precipitation (1800 mm/ year). Furthermore, the high hazard zone in study area is not suitable for construction purpose but was suitable for plantation. The validation result (89.41%) is justifying the performance of this model.
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