Preventing landslides on roads and railways: a new risk-based approach

Lloyd, D.; Anderson, M. G.; Hussein, A. N.; Jamaludin, Amril Hadri; Wilkinson, Paul

doi:10.1680/cien.2001.144.3.129

Cited by 13 publications

(9 citation statements)

References 6 publications

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“…This level of accuracy might typically enable disaster risk managers and practitioners (such as engineers and planners) to identify slopes exhibiting potentially high hazard and prioritize further investigation and/or risk reduction accordingly. CHASM has been extensively used by slope stability researchers and practitioners to assess landslide hazards along roads and in urban and rural areas, and to propose appropriate mitigation in Malaysia, Indonesia, the eastern Caribbean, United Kingdom and New Zealand (Anderson et al, 1997;Lloyd et al, 2001;Wilkinson et al, 2002a, b). A brief overview of CHASM is given here -full descriptions of the numerical scheme and principal equations can be found in Anderson and Lloyd (1991) and Wilkinson et al (2002b).…”

Section: A Physically Based Model For Rainfall-triggered Landslidesmentioning

confidence: 99%

Dealing with deep uncertainties in landslide modelling for disaster risk reduction under climate change

Almeida

Holcombe

Pianosi

et al. 2017

Nat. Hazards Earth Syst. Sci.

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Abstract. Landslides have large negative economic and societal impacts, including loss of life and damage to infrastructure. Slope stability assessment is a vital tool for landslide risk management, but high levels of uncertainty often challenge its usefulness. Uncertainties are associated with the numerical model used to assess slope stability and its parameters, with the data characterizing the geometric, geotechnic and hydrologic properties of the slope, and with hazard triggers (e.g. rainfall). Uncertainties associated with many of these factors are also likely to be exacerbated further by future climatic and socio-economic changes, such as increased urbanization and resultant land use change. In this study, we illustrate how numerical models can be used to explore the uncertain factors that influence potential future landslide hazard using a bottom-up strategy. Specifically, we link the Combined Hydrology And Stability Model (CHASM) with sensitivity analysis and Classification And Regression Trees (CART) to identify critical thresholds in slope properties and climatic (rainfall) drivers that lead to slope failure. We apply our approach to a slope in the Caribbean, an area that is naturally susceptible to landslides due to a combination of high rainfall rates, steep slopes, and highly weathered residual soils. For this particular slope, we find that uncertainties regarding some slope properties (namely thickness and effective cohesion of topsoil) are as important as the uncertainties related to future rainfall conditions. Furthermore, we show that 89 % of the expected behaviour of the studied slope can be characterized based on only two variables -the ratio of topsoil thickness to cohesion and the ratio of rainfall intensity to duration.

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Section: A Physically Based Model For Rainfall-triggered Landslidesmentioning

confidence: 99%

Dealing with deep uncertainties in landslide modelling for disaster risk reduction under climate change

Almeida

Holcombe

Pianosi

et al. 2017

Nat. Hazards Earth Syst. Sci.

View full text Add to dashboard Cite

show abstract

“…CHASM has been extensively used by slope stability researchers and practitioners in Malaysia, Indonesia, the Eastern Caribbean, United Kingdom and New Zealand (Anderson et al, 1997;Lloyd et al, 2001;Wilkinson et al, 2002a;Wilkinson et al, 2002b) A brief overview of CHASM is given herefull descriptions of the numerical scheme and principle equations can be found in Anderson and Lloyd (1991) and Wilkinson et al (2002b). CHASM represents the slope cross-section as a regular twodimensional mesh of columns and cells with geotechnical and hydrological parameters specified for each soil type (Fig.…”

Section: A Physically Based Model For Rainfall-triggered Landslidesmentioning

confidence: 99%

Dealing with deep uncertainties in landslide modelling for disaster risk reduction under climate change

Almeida¹,

Holcombe²,

Pianosi³

et al. 2016

Preprint

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Abstract. Landslides have large negative economic and societal impacts, including loss of life and damage to infrastructure. Slope stability assessment is a vital tool for landslide risk management, but high levels of uncertainty often challenge its usefulness. Uncertainties are associated with the numerical model used to assess slope stability and its parameters, with the data characterising the geometric, geotechnic and hydrologic properties of the slope, and with hazard triggers (e.g., rainfall). Uncertainties associated with many of these factors are also likely to be exacerbated further by future climatic and socio-economic changes, such as increased urbanisation and resultant land use change. In this study, we illustrate how numerical models can be used to explore the uncertain factors that influence potential future landslide hazard using a bottom-up strategy. Specifically, we link the Combined Hydrology And Stability Model (CHASM) with sensitivity analysis and Classification And Regression Trees (CART) to identify critical thresholds in slope properties and climatic (rainfall) drivers that lead to slope failure. We apply our approach to a slope in the Caribbean, an area that is naturally susceptible to landslides due to a combination of high rainfall rates, steep slopes, and highly weathered residual soils. For this particular slope, we find that uncertainties regarding some slope properties (namely thickness and effective cohesion of top soil) are as important as the uncertainties related to future rainfall conditions. Furthermore, we show that 89 % of the expected behaviour of the studied slope can be characterised based on only two variables – the ratio of top soil thickness to cohesion and the ratio of rainfall intensity to duration.

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“…In a validation exercise in Hong Kong CHASM was shown to be numerically robust and capable of correctly classifying 77% of failed slopes and 68% of stable slopes for a specified rainfall event (Anderson, 1990). 5 CHASM has been extensively used by slope stability researchers and practitioners in Malaysia, Indonesia, the Eastern Caribbean, United Kingdom and New Zealand (Anderson et al, 1997;Lloyd et al, 2001;Wilkinson et al, 2002a;Wilkinson et al, 2002b) A brief overview of CHASM is given herefull descriptions of the numerical scheme and principle equations can be found in Anderson and Lloyd (1991) and Wilkinson et al (2002b). CHASM represents the slope cross-section as a regular two-10 dimensional mesh of columns and cells with geotechnical and hydrological parameters specified for each soil type (Fig.…”

Section: A Physically Based Model For Rainfall-triggered Landslidesmentioning

confidence: 99%

Response to Reviewer 1

Almeida¹

2017

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deep uncertainties in landslide modelling for disaster risk reduction under climate change. Natural Hazards and Earth System Sciences Discussions. Abstract. Landslides have large negative economic and societal impacts, including loss of life and damage to infrastructure.Slope stability assessment is a vital tool for landslide risk management, but high levels of uncertainty often challenge its usefulness. Uncertainties are associated with the numerical model used to assess slope stability and its parameters, with the data characterising the geometric, geotechnic and hydrologic properties of the slope, and with hazard triggers (e.g., rainfall). 10Uncertainties associated with many of these factors are also likely to be exacerbated further by future climatic and socioeconomic changes, such as increased urbanisation and resultant land use change. In this study, we illustrate how numerical models can be used to explore the uncertain factors that influence potential future landslide hazard using a bottom-up strategy. Specifically, we link the Combined Hydrology And Stability Model (CHASM) with sensitivity analysis and ClassificationAnd Regression Trees (CART) to identify critical thresholds in slope properties and climatic (rainfall) drivers that lead to slope 15 failure. We apply our approach to a slope in the Caribbean, an area that is naturally susceptible to landslides due to a combination of high rainfall rates, steep slopes, and highly weathered residual soils. For this particular slope, we find that uncertainties regarding some slope properties (namely thickness and effective cohesion of top soil) are as important as the uncertainties related to future rainfall conditions. Furthermore, we show that 89% of the expected behaviour of the studied slope can be characterised based on only two variablesthe ratio of top soil thickness to cohesion and the ratio of rainfall 20 intensity to duration.

show abstract

Preventing landslides on roads and railways: a new risk-based approach

Cited by 13 publications

References 6 publications

Dealing with deep uncertainties in landslide modelling for disaster risk reduction under climate change

Dealing with deep uncertainties in landslide modelling for disaster risk reduction under climate change

Dealing with deep uncertainties in landslide modelling for disaster risk reduction under climate change

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