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 |
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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 |
| _version_ | 1811263918614511616 |
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| author | S. Almeida E. A. Holcombe F. Pianosi T. Wagener |
| author_facet | S. Almeida E. A. Holcombe F. Pianosi T. Wagener |
| author_sort | S. Almeida |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-12T19:53:46Z |
| format | Article |
| id | doaj.art-dd8b0432a7e44c4ebe5fb02640e35e46 |
| institution | Directory Open Access Journal |
| issn | 1561-8633 1684-9981 |
| language | English |
| last_indexed | 2024-04-12T19:53:46Z |
| publishDate | 2017-02-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Natural Hazards and Earth System Sciences |
| spelling | doaj.art-dd8b0432a7e44c4ebe5fb02640e35e462022-12-22T03:18:43ZengCopernicus PublicationsNatural Hazards and Earth System Sciences1561-86331684-99812017-02-0117222524110.5194/nhess-17-225-2017Dealing with deep uncertainties in landslide modelling for disaster risk reduction under climate changeS. Almeida0E. A. Holcombe1F. Pianosi2T. Wagener3Department of Civil Engineering, University of Bristol, Bristol, BS8 1TR, UKDepartment of Civil Engineering, University of Bristol, Bristol, BS8 1TR, UKDepartment of Civil Engineering, University of Bristol, Bristol, BS8 1TR, UKDepartment of Civil Engineering, University of Bristol, Bristol, BS8 1TR, UKLandslides 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.http://www.nat-hazards-earth-syst-sci.net/17/225/2017/nhess-17-225-2017.pdf |
| spellingShingle | S. Almeida E. A. Holcombe F. Pianosi T. Wagener Dealing with deep uncertainties in landslide modelling for disaster risk reduction under climate change Natural Hazards and Earth System Sciences |
| title | Dealing with deep uncertainties in landslide modelling for disaster risk reduction under climate change |
| title_full | Dealing with deep uncertainties in landslide modelling for disaster risk reduction under climate change |
| title_fullStr | Dealing with deep uncertainties in landslide modelling for disaster risk reduction under climate change |
| title_full_unstemmed | Dealing with deep uncertainties in landslide modelling for disaster risk reduction under climate change |
| title_short | Dealing with deep uncertainties in landslide modelling for disaster risk reduction under climate change |
| title_sort | dealing with deep uncertainties in landslide modelling for disaster risk reduction under climate change |
| url | http://www.nat-hazards-earth-syst-sci.net/17/225/2017/nhess-17-225-2017.pdf |
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