Regional test of a model for shallow landsliding

Montgomery, David R.; Sullivan, Kathleen M.; Greenberg, Harvey

doi:10.1002/(sici)1099-1085(199805)12:6<943::aid-hyp664>3.0.co;2-z

Cited by 171 publications

(115 citation statements)

References 29 publications

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“…Slope failure probability was calculated using SHALSTAB (Montgomery and Dietrich, 1994), a distributed, process based slope stability model that has been widely used to predict relative failure probabilities (Montgomery et al, 1998;Dietrich et al, 2001;Borga et al, 2002;Fernandes et al, 2004). Relative failure probability is expressed as the ratio of rainfall (Q) to transmissivity (T) required for a cell to fail, it can be calculated using the equation: (2) where: ρ s is the soil density, ρ w is the density of water and ϕ is the angle of internal friction of the soil.…”

Section: Assessment Of Filter Impactsmentioning

confidence: 99%

The potential of digital filtering of generic topographic data for geomorphological research

Milledge

Lane

Warburton

2008

Earth Surf Processes Landf

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High resolution terrain models generated from widely available Interferometric Synthetic Aperture Radar (IfSAR) and digital photogrammetry are an exciting resource for geomorphological research. However, these data contain error, necessitating pre-processing to improve their quality. We evaluate the ability of digital filters to improve topographic representation, using: (1) a Gaussian noise removal filter; (2) the proprietary filters commonly applied to these datasets; and (3) a terrain sensitive filter, similar to those applied to laser altimetry data. Topographic representation is assessed in terms of both absolute accuracy measured with reference to independent check data and derived geomorphological variables (slope, upslope contributing area, topographic index and landslide failure probability) from a steepland catchment in northern England. Results suggest that proprietary filters often degrade or fail to improve precision. A combination of terrain sensitive and Gaussian filters performs best for both IfSAR and digital photogrammetry datasets, improving the precision of photogrammetry digital elevation models (DEMs) by more than 50 per cent relative to the unfiltered data. High-frequency noise and high-magnitude gross errors corrupt geomorphological variables derived from unfiltered photogrammetry DEMs. However, a terrain sensitive filter effectively removes gross errors and noise is minimized using a Gaussian filter. These improvements propagate through derived variables in a landslide prediction model, to reduce the area of predicted instability by up to 29 per cent of the study area. Interferometric Synthetic Aperture Radar is susceptible to removal of topographic detail by oversmoothing and its errors are less sensitive to filtering (maximum improvement in precision of 5 per cent relative to the raw data).

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Section: Assessment Of Filter Impactsmentioning

confidence: 99%

The potential of digital filtering of generic topographic data for geomorphological research

Milledge

Lane

Warburton

2008

Earth Surf Processes Landf

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“…To study storm event-induced landslides on a regional scale, a deterministic physical-based method is commonly used which requires the employment of an infinite-slope model and a hydrological model (Okimura and Ichikawa, 1985;Dietrich et al, 1986Dietrich et al, , 1995Keefer et al, 1987; Correspondence to: C.-T. Lee (ct@ncu.edu.tw) and Dietrich, 1994;Wu and Sidle, 1995;Montgomery et al, 1998;Terlien, 1998;Crozer, 1999;Polemic and Sdao, 1999;Iverson, 2000;Borga et al, 2002;Wilkinson et al, 2002;Crosta and Frattini, 2003;Malet et al, 2005;Baum et al, 2005;Salciarini et al, 2006;Claessens et al, 2007aClaessens et al, , 2007bSchmidt et al, 2008). This approach requires the strength parameters, failure depth and soil conductibility for every point in the limit-equilibrium slope stability calculation, a requirement which can cause serious problems in terms of acquisition and control of spatial variability of the variables (Hutchinson, 1995;Guzzetti et al, 1999).…”

Section: Introductionmentioning

confidence: 99%

Statistical approach to storm event-induced landslides susceptibility

Lee

Huang

Lee

et al. 2008

Nat. Hazards Earth Syst. Sci.

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Abstract. For the interpretation of the storm event-induced landslide distribution for an area, deterministic methods are frequently used, while a region's landslide susceptibility is commonly predicted via a statistical approach based upon multi-temporal landslide inventories and environmental factors. In this study we try to use an event-based landslide inventory, a set of environmental variables and a triggering factor to build a susceptibility model for a region which is solved using a multivariate statistical method. Data for shallow landslides triggered by the 2002 typhoon, Toraji, in central western Taiwan, are selected for training the susceptibility model. The maximum rainfall intensity of the storm event is found to be an effective triggering factor affecting the landslide distribution and this is used in the model. The model is built for the Kuohsing region and validated using data from the neighboring Tungshih area and a subsequent storm event -the 2004 typhoon, Mindulle, which affected both the Kuohsing and the Tungshih areas. The results show that we can accurately interpret the landslide distribution in the study area and predict the occurrence of landslides in the neighboring region in a subsequent typhoon event. The advantage of this statistical method is that neither hydrological data, strength data, failure depth, nor a long-period landslide inventory is needed as input.

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“…The increase of the hydrologic ratio (Q/T ) indicates that soil saturation will be faster and more extensive. The topographic ratio (a/(b · sin β)) describes the topographical effect on runoff (Dietrich and Montegomery, 1998;Montgomery et al, 1998). The transmissivity of the soil was estimated using Eq.…”

Section: Hydraulic Modelmentioning

confidence: 99%

Combination of statistical and physically based methods to assess shallow slide susceptibility at the basin scale

Oliveira

Zêzere²,

Lajas

et al. 2017

Nat. Hazards Earth Syst. Sci.

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Abstract. Approaches used to assess shallow slide susceptibility at the basin scale are conceptually different depending on the use of statistical or physically based methods. The former are based on the assumption that the same causes are more likely to produce the same effects, whereas the latter are based on the comparison between forces which tend to promote movement along the slope and the counteracting forces that are resistant to motion. Within this general framework, this work tests two hypotheses: (i) although conceptually and methodologically distinct, the statistical and deterministic methods generate similar shallow slide susceptibility results regarding the model's predictive capacity and spatial agreement; and (ii) the combination of shallow slide susceptibility maps obtained with statistical and physically based methods, for the same study area, generate a more reliable susceptibility model for shallow slide occurrence. These hypotheses were tested at a small test site (13.9 km 2 ) located north of Lisbon (Portugal), using a statistical method (the information value method, IV) and a physically based method (the infinite slope method, IS). The landslide susceptibility maps produced with the statistical and deterministic methods were combined into a new landslide susceptibility map. The latter was based on a set of integration rules defined by the cross tabulation of the susceptibility classes of both maps and analysis of the corresponding contingency tables. The results demonstrate a higher predictive capacity of the new shallow slide susceptibility map, which combines the independent results obtained with statistical and physically based models. Moreover, the combination of the two models allowed the identification of areas where the results of the information value and the infinite slope methods are contradictory. Thus, these areas were classified as uncertain and deserve additional investigation at a more detailed scale.

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Regional test of a model for shallow landsliding

Cited by 171 publications

References 29 publications

The potential of digital filtering of generic topographic data for geomorphological research

The potential of digital filtering of generic topographic data for geomorphological research

Statistical approach to storm event-induced landslides susceptibility

Combination of statistical and physically based methods to assess shallow slide susceptibility at the basin scale

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