National-Scale Rainfall-Triggered Landslide Susceptibility and Exposure in Nepal

被引:4
|
作者
Kincey, M. E. [1 ]
Rosser, N. J. [2 ,3 ]
Swirad, Z. M. [4 ]
Robinson, T. R. [5 ]
Shrestha, R. [6 ]
Pujara, D. S. [6 ]
Basyal, G. K. [6 ]
Densmore, A. L. [2 ,3 ]
Arrell, K. [7 ]
Oven, K. J. [7 ]
Dunant, A. [2 ,3 ]
机构
[1] Newcastle Univ, Sch Geog Polit & Sociol, Newcastle Upon Tyne, England
[2] Univ Durham, Dept Geog, Durham, England
[3] Univ Durham, Inst Hazard Risk & Resilience, Durham, England
[4] Polish Acad Sci, Inst Geophys, Warsaw, Poland
[5] Univ Canterbury, Sch Earth & Environm, Canterbury, New Zealand
[6] Natl Soc Earthquake Technol, Kathmandu, Nepal
[7] Northumbria Univ, Dept Geog & Environm Sci, Newcastle Upon Tyne, England
基金
英国工程与自然科学研究理事会;
关键词
DISASTER RISK REDUCTION; LOGISTIC-REGRESSION; NATURAL HAZARDS; FUZZY-LOGIC; QUANTITATIVE-ANALYSIS; GLOBAL LANDSLIDE; FREQUENCY RATIO; CLIMATE-CHANGE; GIS; MODELS;
D O I
10.1029/2023EF004102
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Nepal is one of the most landslide-prone countries in the world, with year-on-year impacts resulting in loss of life and imposing a chronic impediment to sustainable livelihoods. Living with landslides is a daily reality for an increasing number of people, so establishing the nature of landslide hazard and risk is essential. Here we develop a model of landslide susceptibility for Nepal and use this to generate a nationwide geographical profile of exposure to rainfall-triggered landslides. We model landslide susceptibility using a fuzzy overlay approach based on freely-available topographic data, trained on an inventory of mapped landslides, and combine this with high resolution population and building data to describe the spatial distribution of exposure to landslides. We find that whilst landslide susceptibility is highest in the High Himalaya, exposure is highest within the Middle Hills, but this is highly spatially variable and skewed to on average relatively low values. Around 4 x 106 Nepalis (similar to 15% of the population) live in areas considered to be at moderate or higher degree of exposure to landsliding (>0.25 of the maximum), and critically this number is highly sensitive to even small variations in landslide susceptibility. Our results show a complex relationship between landslides and buildings, that implies wider complexity in the association between physical exposure to landslides and poverty. This analysis for the first time brings into focus the geography of the landslide exposure and risk case load in Nepal, and demonstrates limitations of assessing future risk based on limited records of previous events.
引用
收藏
页数:23
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