Deforestation Effects on Rainfall-Induced Shallow Landslides: Remote Sensing and Physically-Based Modelling

被引:22
|
作者
Lehmann, Peter [1 ]
von Ruette, Jonas [1 ]
Or, Dani [1 ]
机构
[1] ETH, Soil & Terr Environm Phys, Zurich, Switzerland
基金
瑞士国家科学基金会;
关键词
Landslide; Remote Sensing; Modeling; Rainfall; ROOT REINFORCEMENT; FOREST MANAGEMENT; DEBRIS FLOWS; FREQUENCY; STRENGTH; COHESION; ISLAND;
D O I
10.1029/2019WR025233
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Deforestation of steep slopes may temporarily reduce evapotranspiration and lessen root reinforcement thus potentially enhancing landslide susceptibility. Quantifying the effects of deforestation and associated perturbations on landslide characteristics remains a challenge, especially for predictions in remote areas with limited information. We applied the STEP-TRAMM model that uses publicly available climatic and landscape information to assess effects of forest alteration on hydro-mechanical processes. The model considers two types of forest alterations: (i) removal of root reinforcement following permanent forest conversion, and (ii) time dependent root decay and regrowth following clear-cut timber harvesting. The model was applied to four study areas in different climatic regions (New Zealand, Oregon, Sumatra and Cambodia). We compared model predictions of landslide metrics with satellite-imaging of landslides following deforestation. Although we observe a higher propensity and larger landslides in deforested areas, effects were sensitive to deforestation practices and patterns. The largest increase in landslide area was associated with large and interconnected deforested tracts within a few years after deforestation as determined by competition between root decay and forest regrowth. For patchy small-scale forest conversion, the landslide areas were smaller but could occur many years after deforestation (> 10 years). The modeling framework offers ability to evaluate forest alteration scenarios through their potential impact on landslide hazard in specific regions of the landscape.
引用
收藏
页码:9962 / 9976
页数:15
相关论文
共 50 条
  • [31] Discussion of "A Simple Method for Predicting Rainfall-Induced Shallow Landslides"
    Huang, Wengui
    Zhang, Fanyu
    JOURNAL OF GEOTECHNICAL AND GEOENVIRONMENTAL ENGINEERING, 2023, 149 (07)
  • [32] Accelerating Effect of Vegetation on the Instability of Rainfall-Induced Shallow Landslides
    Zhang, Juanjuan
    Qiu, Haijun
    Tang, Bingzhe
    Yang, Dongdong
    Liu, Ya
    Liu, Zijing
    Ye, Bingfeng
    Zhou, Wenqi
    Zhu, Yaru
    REMOTE SENSING, 2022, 14 (22)
  • [33] Effect of tree roots on heavy rainfall-induced shallow landslides
    Lin, Yunzhao
    Jian, Wenbin
    Wu, Yilong
    Zhu, Zuteng
    Wang, Hao
    Dou, Hongqiang
    Lai, Zengrong
    GEOMATICS NATURAL HAZARDS & RISK, 2024, 15 (01)
  • [34] Closure to"A Simple Method for Predicting Rainfall-Induced Shallow Landslides"
    Conte, Enrico
    Pugliese, Luigi
    Troncone, Antonello
    JOURNAL OF GEOTECHNICAL AND GEOENVIRONMENTAL ENGINEERING, 2023, 149 (07)
  • [35] Development and Application of Numerical Model for Rainfall-induced Shallow Landslides
    Tsai, Tl
    INFORMATION TECHNOLOGY IN GEO-ENGINEERING, 2010, : 713 - 721
  • [36] Fragility curves for rainfall-induced shallow landslides on transport networks
    Martinovic, Karlo
    Reale, Cormac
    Gavin, Kenneth
    CANADIAN GEOTECHNICAL JOURNAL, 2018, 55 (06) : 852 - 861
  • [37] Visualization analysis of rainfall-induced landslides hazards based on remote sensing and geographic information system-an overview
    Yang, Zhengli
    Lu, Heng
    Zhang, Zhijie
    Liu, Chao
    Nie, Ruihua
    Zhang, Wanchang
    Fan, Gang
    Chen, Chen
    Ma, Lei
    Dai, Xiaoai
    Zhang, Min
    Zhang, Donghui
    INTERNATIONAL JOURNAL OF DIGITAL EARTH, 2023, 16 (01) : 2374 - 2402
  • [38] Modelling rainfall-induced landslides at a regional scale, a machine learning based approach
    Stefania Magrì
    Monica Solimano
    Fabio Delogu
    Tania Del Giudice
    Mauro Quagliati
    Michele Cicoria
    Francesco Silvestro
    Landslides, 2024, 21 : 573 - 582
  • [39] Spatiotemporal modelling of rainfall-induced landslides using machine learning
    Ng, C. W. W.
    Yang, B.
    Liu, Z. Q.
    Kwan, J. S. H.
    Chen, L.
    LANDSLIDES, 2021, 18 (07) : 2499 - 2514
  • [40] Modelling rainfall-induced landslides at a regional scale, a machine learning based approach
    Magri, Stefania
    Solimano, Monica
    Delogu, Fabio
    Del Giudice, Tania
    Quagliati, Mauro
    Cicoria, Michele
    Silvestro, Francesco
    LANDSLIDES, 2024, 21 (03) : 573 - 582