Accounting for soil parameter uncertainty in a physically based and distributed approach for rainfall-triggered landslides

Arnone, Elisa; Dialynas, Y. G.; Noto, L. V.; Bras, Rafael L.

doi:10.1002/hyp.10609

Cited by 70 publications

(50 citation statements)

References 54 publications

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“…Designating landslide hazard as a probability, rather than an index, systematically accounts for uncertainty and variability in stability analysis (Hammond et al, 1992;Simoni et al, 2008;Arnone et al, 2014) and more appropriately represents complex systems (Berti et al, 2012). Recently, some promising advances have been made in process-based models accounting for data uncertainty in landslide hazard mapping (e.g., Raia et al, 2014;Arnone et al, 2016a).…”

Section: Geomorphology and Modeling Backgroundmentioning

confidence: 99%

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A hydroclimatological approach to predicting regional landslide probability using Landlab

et al. 2018

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Abstract. We develop a hydroclimatological approach to the modeling of regional shallow landslide initiation that integrates spatial and temporal dimensions of parameter uncertainty to estimate an annual probability of landslide initiation based on Monte Carlo simulations. The physically based model couples the infinite-slope stability model with a steady-state subsurface flow representation and operates in a digital elevation model. Spatially distributed gridded data for soil properties and vegetation classification are used for parameter estimation of probability distributions that characterize model input uncertainty. Hydrologic forcing to the model is through annual maximum daily recharge to subsurface flow obtained from a macroscale hydrologic model. We demonstrate the model in a steep mountainous region in northern Washington, USA, over 2700 km 2 . The influence of soil depth on the probability of landslide initiation is investigated through comparisons among model output produced using three different soil depth scenarios reflecting the uncertainty of soil depth and its potential long-term variability. We found elevation-dependent patterns in probability of landslide initiation that showed the stabilizing effects of forests at low elevations, an increased landslide probability with forest decline at midelevations (1400 to 2400 m), and soil limitation and steep topographic controls at high alpine elevations and in post-glacial landscapes. These dominant controls manifest themselves in a bimodal distribution of spatial annual landslide probability. Model testing with limited observations revealed similarly moderate model confidence for the three hazard maps, suggesting suitable use as relative hazard products. The model is available as a component in Landlab, an open-source, Python-based landscape earth systems modeling environment, and is designed to be easily reproduced utilizing HydroShare cyberinfrastructure.

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Section: Geomorphology and Modeling Backgroundmentioning

confidence: 99%

“…• in other studies (e.g., Abbaszadeh et al, 2011;Arnone et al, 2016a). Other spatial soil and vegetation datasets can be used in the preprocessing of the model.…”

Section: Model Drivermentioning

confidence: 99%

A hydroclimatological approach to predicting regional landslide probability using Landlab

et al. 2018

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“…The lack in accuracy of forcing boundary conditions, such as the temporal and areal variability of historical rainfall, introduces further uncertainty that needs to be considered (Minder et al, 2009;von Ruette et al, 2014). Studies have assessed the impact of uncertainties associated with such models Arnone et al, 2016) for both site-specific and spatially distributed landslide hazard predictions -though such information is rarely used to support risk reduction decisionmaking.…”

Section: Introductionmentioning

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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“…The slope stability model explicitly accounts for the spatial heterogeneity of factors that control shallow landslides, including mechanical and hydrological soil properties (Arnone et al, , ), local topographic characteristics, and the temporal variation of soil moisture in response to precipitation events, which controls the temporal FS dynamics at the watershed scale (Simoni et al, ; Arnone et al, ; Lepore et al, ; Formetta et al, ). Possible landslide deposition paths are estimated based on the concept of run‐out distance (Bathurst et al, ).…”

Section: Methodsmentioning

confidence: 99%

Hydro‐geomorphic behavior of contrasting tropical landscapes and critical zone response to changing climate

Dialynas

Bras

2018

Earth Surf Processes Landf

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The potentially important influence of climate change on landscape evolution and on critical zone processes is not sufficiently understood. The relative contribution of hydro‐climatic factors on hillslope erosion rates may significantly vary with topography at the watershed scale. The objective of this study is to quantify the hydro‐geomorphic behavior of two contrasting landscapes in response to different climate change scenarios in the Luquillo Critical Zone Observatory, a site of particular geomorphological interest, in terms of hillslope erosion and rainfall‐triggered landslides. We investigate the extent to which hillslope erosion and landslide occurrence remain relatively invariant with future hydro‐climatic perturbations. The adjacent Mameyes and Icacos watersheds are studied, which are underlain by contrasting lithologies. A high resolution coupled hydro‐geomorphic model based on tRIBS (Triangulated Irregular Network‐based Real‐time Integrated Basin Simulator) is used. Observations of landslide activity and hillslope erosion are used to evaluate the model performance. The process‐based model quantifies feedbacks among different hydrologic processes, landslide occurrence, and topsoil erosion and deposition. Simulations suggest that the propensity for landslide occurrence in the Luquillo Mountains is controlled by tropical storms, subsurface water flow, and by non‐climatic factors, and is expected to remain significant through 2099. The Icacos watershed, which is underlain by quartz diorite, is dominated by relatively large landslides. The relative frequency of smaller landslides is higher at the Mameyes watershed, which is underlain by volcaniclastic rock. While projections of precipitation decrease at the study site may lead to moderate decline in hillslope erosion rates, the simulated erosional potential of the two diverse landscapes likely remains significant. © 2018 John Wiley & Sons, Ltd.

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Accounting for soil parameter uncertainty in a physically based and distributed approach for rainfall-triggered landslides

Cited by 70 publications

References 54 publications

A hydroclimatological approach to predicting regional landslide probability using Landlab

A hydroclimatological approach to predicting regional landslide probability using Landlab

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

Hydro‐geomorphic behavior of contrasting tropical landscapes and critical zone response to changing climate

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