Dealing with deep uncertainties in landslide modelling for disaster risk reduction under climate change
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...
Main Authors: | , , , |
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Format: | Article |
Language: | English |
Published: |
Copernicus Publications
2017-02-01
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Series: | Natural Hazards and Earth System Sciences |
Online Access: | http://www.nat-hazards-earth-syst-sci.net/17/225/2017/nhess-17-225-2017.pdf |
Summary: | 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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ISSN: | 1561-8633 1684-9981 |