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

Abstract

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.

Debris flow run-out simulation and analysis using a dynamic model

“…In addition, this type of model is not dependent on local conditions and do not require landslide inventories for modeling procedures, which is an advantage when the modeling is performed for locations where no inventories are available. Nonetheless, such inventories may remain essential to calibrate the rheological parameters by back-analysis and for validation purposes (Oliveira et al, 2017).…”

“…The consumption of vegetation, ash deposition, changes in physical properties of soils and rocks and the presence of water repellent soils are typical consequences of fire (Cannon and Gartner, 2005;Cannon et al, 2010;Parise and Cannon, 2012). In addition, the hydrological response of a burned basin includes the decrease in the infiltration rate and therefore the increase of surface runoff Cannon and Gartner, 2005;Cannon et al, 2010).…”

Review NHES-2019-311

“…To do so, I suggest them to consult several papers about comparisons between physical and statistical models (e.g. Cervi et al, 2010;Zizioli et al, 2013;Davis and Blesius, 2015;Ciurleo et al, 2017;Bartelleti et al, 2017;Galve et al, 2017;Oliveira et al, 2017). 4.…”

GIS-Based Random Forest Weight for Rainfall-Induced Landslide Susceptibility Assessment at a Humid Region in Southern China

“…The second general approach is statistical and thus does not posit mechanisms that control slope failure, but assumes rather that occurrences of past landslides can be related arbitrarily to measurable characteristics of the landscape [30][31][32]. In turn, these characteristics can be used to predict future landslide occurrence and then many common algorithms were applied including weighted linear combination (WLC), multiple regression model [33][34][35], artificial neural network model [36,37], and support vector machine [38,39]. All these statistical methods could properly present the probability distribution at spatial scale and show a prefect effect in practice.…”