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Assessment of rainfall-generated shallow landslide/debris-flow susceptibility and runout using a GIS-based approach: application to western Southern Alps of New Zealand

机译:使用基于GIS的方法评估降雨产生的浅层滑坡/泥石流敏感性和径流:在新西兰南阿尔卑斯山西部的应用

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Rainfall-triggered shallow slope failures are very common in the western Southern Alps of New Zealand, causing widespread damage to property and infrastructure, injury and loss of life. This study develops a geographic information system (GIS)-based approach for shallow landslide/debris-flow susceptibility assessment. Since landslides are complex and their prediction involves many uncertainties, fuzzy logic is used to deal with uncertainties inherent in spatial analysis and limited knowledge on the relationship between conditioning factors and slope instability. A landslide inventory was compiled using data from existing catalogues, satellite imagery and field observations. Ten parameters were initially identified as the most important conditioning factors for rainfall-generated slope failures in the study area, and fuzzy memberships were established between each parameter and landslide occurrence based on both the landslide inventory and user-defined functions. Three output landslide susceptibility maps were developed and evaluated in a test area using an independent population of landslides. The models demonstrated satisfactory performance with area under the curve (AUC) varying from 0.708 to 0.727. Sensitivity analyses showed that a six-parameter model using slope angle, lithology, slope aspect, proximity to faults, soil induration, and proximity to drainage network had the highest predictive performance (AUC = 0.734). The runout path and distance of potential future landslides from the susceptible areas were also modelled based on a multiple flow direction algorithm and the topographic slope of existing debris-flow deposits. The final susceptibility map has the potential to inform regional-scale land-use planning and to prioritize areas where hazard mitigation measures are required.
机译:降雨引发的浅层边坡破坏在新西兰南部阿尔卑斯山西部非常普遍,对财产和基础设施造成广泛破坏,造成伤害和生命损失。本研究开发了一种基于地理信息系统(GIS)的浅层滑坡/泥石流敏感性评估方法。由于滑坡是复杂的并且其预测涉及许多不确定性,因此使用模糊逻辑来处理空间分析中固有的不确定性以及对条件因素与边坡不稳定性之间关系的有限知识。使用来自现有目录,卫星图像和现场观测的数据来编制滑坡清单。最初将十个参数确定为研究区域降雨引起的边坡破坏的最重要条件,然后根据滑坡清单和用户定义的函数在每个参数与滑坡发生之间建立了模糊隶属关系。使用独立的滑坡种群,在测试区域中开发并评估了三个输出滑坡敏感性图。这些模型表现出令人满意的性能,曲线下面积(AUC)从0.708到0.727。敏感性分析表明,使用坡度角,岩性,坡度,断层附近,土壤硬结和排水网络附近的六参数模型具有最高的预测性能(AUC = 0.734)。基于多流向算法和现有泥石流沉积物的地形坡度,还对从易受影响地区到未来潜在滑坡的跳动路径和距离进行了建模。最终的敏感性图有可能为区域规模的土地利用规划提供信息,并为需要采取减灾措施的地区确定优先次序。

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