期刊
JOURNAL OF GEOPHYSICAL RESEARCH-EARTH SURFACE
卷 126, 期 7, 页码 -出版社
AMER GEOPHYSICAL UNION
DOI: 10.1029/2021JF006067
关键词
extreme event; geohazard; geomorphology; landslide susceptibility modeling; Nepal
资金
- Natural Environment Research Council through University of East Anglia [NE/L002582/1]
- Natural Environment Research Council through University of Plymouth [NE/L002582/1]
- AECOM
This study quantified the spatial distribution variations of monsoon-triggered landslides in Nepal over different years, finding significant changes in landslide distribution in years affected by extreme events such as storms, earthquakes, and floods. Developing susceptibility models using more than 6-8 years of landslide data showed consistently good accuracy in hindcasting landslide occurrence.
Landslide susceptibility models are fundamental components of landslide risk management strategies. These models typically assume that landslide occurrence is time-independent, even though processes including earthquake preconditioning and landslide path dependency transiently impact landslide occurrence. Understanding the temporal characteristics of landslide occurrence remains limited by a lack of systematic investigation into how landslide distributions vary through time, and how this impacts landslide susceptibility. Here, we apply Kolmogorov-Smirnoff and chi-square statistics to a 30-yr inventory of monsoon-triggered landslides from Nepal to systematically quantify how landslide spatial distributions vary through time in normal years and years impacted by extreme events. We then develop binary logistic regression (BLR) susceptibility models for 12 yrs in our inventory with >400 landslides and use area under receiver operator curve validation to assess how well these models can hindcast landslide occurrence in other years. Landslide distributions are found to vary through time, particularly in years impacted by storms (1993 and 2002), earthquakes (2015), and floods (2017). Notably, Gorkha earthquake landscape preconditioning shifted 2015 monsoon-triggered landslides to higher slopes, reliefs, and excess topographies. These variations significantly impact BLR susceptibility modeling, with models trained on extreme years unable to consistently hindcast landslide occurrence in other years. However, developing BLR models using increasingly long historical inventories shows that susceptibility models developed using >6-8 yrs of landslide data provide consistently good hindcasting accuracy. Overall, our results challenge time-independent assumptions of landslide susceptibility approaches, highlighting the need for time-dependent modeling techniques or historical inventories for landslide susceptibility modeling.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据