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Landsliding is a complex phenomenon and its modelling aimed at predicting where the processes are most likely to occur is a tricky issue to be performed. Apart the chosen modelling approach, for both data-driven and physically-based models, paying adequate attention to the predisposing and triggering factors, as well as the input parameters is no less important. Generally, shallow landslides mobilize relatively small volumes of material sliding along a nearly planar rupture surface which is assumed to be roughly parallel to the ground surface. In the literature it is also widely accepted that shallow landslides involve only unconsolidated slope deposits (i.e., the colluvium), then the rupture surface corresponds to the discontinuity between the bedrock and the overlying loose soil. In this work, based on systematic field observations, we highlight that shallow landslides often involve also portions of the sub-surface bedrock showing different levels of weathering and fracturing. Then, we show that the engineering geological properties of slope deposits, as well as those related to the underlying bedrock, must be considered to obtain more reliable shallow landslides susceptibility assessment. As a first task, a multi-temporal shallow landslide inventory was built by photointerpretation of aerial orthoimages. Then, a new fieldwork-based method is proposed and implemented to acquire, process and spatialize the engineering geological properties of both slope deposits and bedrock. To support the regional scale approach, field observations were collected within, in the neighbour and far from the shallow landslide areas. Finally, both physically-based and data-driven methods were implemented to assess and compare shallow landslide susceptibility at regional scale, as well as to analyse the role of spatial distribution of rock mass quality for shallow slope failure development. The results highlight that, according to geology, structural setting and morphometric conditions, bedrock properties spatially change, defining clusters influencing both the distribution and characters of shallow landslides. As a consequence, the physically-based modelling provides better prediction accuracy when two possible rupture surfaces are analysed, the shallower one located at the slope deposit / bedrock discontinuity, and the deeper one located at the bottom of the fractured and weathered bedrock horizon. Even though the physically-based and data-driven models provide similar results in terms of ROC curves, the resulting susceptibility maps highlight quite substantial differences.

The diversity of geological and geomorphological landscapes in mainland Portugal is responsible for the occurrence of different landslide types. The present chapter illustrates three examples of destructive landslide hazardscapes responsible for recent hillslope evolution: in a granitic context, the Frades landslide, a lethal debris flow; and in sedimentary contexts, the Calhandriz landslide, the biggest rainfall-triggered landslide that occurred in Portugal in the last 50 years, and the Grande da Pipa River basin, the major landslide-prone area within the north of Lisbon region.

Landslides have a direct impact in the ecosystems dynamics being considered one of the main vegetation perturbation processes. Our objective is to determine the relation between vegetation cover evolution and time period after landslide disturbance, and therefore to assess the potential use of vegetation evolution within landslide areas as temporal bioindicators of landslide activity, in order to determine landslide relative age. Four rotational slides of known relative age, located in the Grande da Pipa River basin (Arruda dos Vinhos, Portugal) were selected. The methodology includes four main steps: (1) to identify the flora and vegetation differences between the main landslide sectors (scarp, body, foot); (2) to find out if the differences in floristic composition and vegetation structure are reflected in the succession process; (3) to find out if the succession process has produced different seral stages along the longitudinal gradients; (4) to compare the succession process in landslide affected areas with the undisturbed adjacent areas. The data points towards a slow evolution of the vegetation in the period following the disturbance, being necessary long periods for the perturbed area reach vegetation characteristics similar to the ones of the unperturbed areas. The progressive succession is rapid in the foot, slow in the body and extremely slow in the scarp. The presence of orchids in the body may be considered as an age bioindicator of more than 15 years since landslide disturbance. In the case of the older landslide (> 50 years), it corresponds to the evolved stage close to the potential natural vegetation.

Shallow landslide susceptibility modelling at regional scale may be performed using both a physically based and statistical approach. For the same area, these two approaches can have inconsistent results, mainly because the two methods are conceptually different. Physically based models are based on the infinite slope model and consists on the computation cell by cell of a safety factor comparing between driving and resisting forces. The assumption that landslides occur in slopes that are characterized by predisposing factors similar to those in which landslides have occurred in the past, is the concept behind the statistical models. The aim of this work is to compare the two approach and investigate the differences between the two models. The study area is located in northern Tuscany, central Italy, in which an extensive field survey highlighted that about 60% of landslides involve bedrock. For this reason, we developed a physically based susceptibility analysis taking into account both the surficial layer (slope deposit, SD) and the underlying layer (BR), characterized by weathered and fractured bedrock. This model is compared to the statistically based one, which take into account topographic and geologic predisposing factor as well as bedrock geo-mechanical properties, such Geological Strength Index (GSI), Schmidt hammer rebound values (Rv) and Joint density (Jv). The accuracy of the models is evaluated using a multi-temporal landslide inventory, in which involving bedrock landslides are distinct from slope deposits landslides. Within this general framework results are discussed regarding the model’s predictive capacity and spatial agreement.

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 km2) 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.

The two main events occurred during the 2012 seismic sequence on the Po Plain in Northern Italy (May 20 Mw 5.9 and May 29 Mw 5.8) induced widespread coseismic surface effects (CSEs), mostly liquefaction phenomena, which caused severe damages. To prevent risks related to CSE, an important non-structural measure is to assess locations susceptible to liquefaction, which is usually done at site scale by means of deterministic approaches in micro-zonation studies. This paper brings a novel methodological contribution in the field of CSE susceptibility mapping at regional scale, by testing and comparing bivariate (Weights of Evidence) and multivariate (Logistic Regression) methods that, so far, have not yet been used for such purpose. In a study area of 1480 km2 , the computation used an inventory of CSE as supporting evidence and a set of maps with geologic, geomorphic, hydrogeological and topographic factors as causal variables. Both methods provided susceptibility maps with a significant predictive capability and a fairly good spatial agreement between each other. In conclusion, this application of data-driven spatial modelling approaches indicates that such methods can be effectively used for liquefaction susceptibility zonation at regional scale, which can be of significant support for spatial planning over large areas.

In the Grande da Pipa river basin, north of Lisbon, 64 % of the total number of landslides inventoried is totally or partially included in a lithological unit composed by marl, clay, and sandstone intercalation complex that is present in 58 % of the study area. The Persistent Scatterer synthetic aperture radar interferometry technique is applied to a data set of TerraSAR-X SAR images, from April of 2010 to March of 2011, firstly to the Laje-Salema test site and further exported to the Grande da Pipa river basin. This work's specific objectives are the following: (i) to assess the potential of the Persistent Scatterer displacement maps to the identification of new landslides/unstable areas and in the redefinition of landslide limits, (ii) to update the landslide state of activity, and (iii) to evaluate the capacity of the Persistent Scatterer deformation maps in assessing landslide susceptibility at the regional scale. Based on this approach, it was possible to increment the number of landslides and to redefine the landslide limits in the test site in 3.8 %. For 39 landslides, it was possible to update the landslide state of activity, in particular from dormant to reactivated or dormant-reactivated (23 landslides) or from stabilized to reactivated (5 landslides). Landslide susceptibility map based in Persistent Scatterer deformation rates, independently validated with a deep rotational slide map, obtained the best value of area under the curve (0.668).

The Grande da Pipa River (GPR) basin (Portugal) has natural conditions that favor the occurrence of landslides. The hydrological year 2009/10 was characterized by high amounts of rainfall, which led to the occurrence of an also high number of landslides in this basin. The hydrodynamic character of the GPR basin was analyzed through a lumped parameter model of daily sequential water balances, in order to understand its influence in the stability of natural slopes. Results from the model were confronted to the inventory of landslides that occurred in the basin during the hydrological year 2009/10. Morphological, geotechnical, and hydrological local conditions affecting slope stability were also analyzed through back-analyses of two selected deep-seated landslides. Data here presented shows that the rise of water table is an importante triggering factor for landslides. The most important constraint for landslides in the area is the degree of weathering and thickness of the upper layer of degraded marls. In most of the basin, the degraded layer is less than 5 m deep, causing the occurrence of shallow and intermediate landslides. However, deep-seated landslides were also found in areas, even with degraded marls that were less than 5 m-thick, where landslides have also occurred in the past.

Rainfall is the most important physical process responsible for the landslide triggering in Portugal. Results obtained worldwide have shown that control of rainfall on landslides differs substantially depending upon landslide depth and kinematics and the affected material. Therefore, the critical rainfall conditions for failure are not the same for different types of landslides, and may be strongly influenced by regional geologic and geomorphologic conditions. Rapid debris flows are typically triggered by very intense showers concentrated in just a few hours, and shallow translational soil slips are usually triggered by intense precipitation falling within the 1–15 days long range. On the contrary, activity of deep-seated landslides of rotational, translational and complex types is related to periods of nearly constant rainfall, lasting from several weeks to several months. The different rainfall intensity–duration conditions are associated with different hydrologic mechanisms for slope failure. The generation of surface run-off and high peak discharges in first-order mountain catchments is a critical triggering mechanism for debris flows. The intense rainfall allows the rapid growth of pore water pressure and the drop of capillarity forces that sustain the apparent cohesion of thin soils. As a consequence, shallow soil slips occur within the soil material or at the contact with the underlying less permeable bedrock. Long lasting rainfall episodes enable the steady rise of the groundwater table and the development of positive pore water pressures into the soil. Consequently, deep-seated failures occur in relation to the reduction of shear strength of affected materials. In this work, we present the state of the art concerning the proposition of empirical rainfall thresholds in Portugal for different types of landslides observed in different zones of the country: the Lisbon region, the Douro Valley and the NW Mountains, and the Povoação Municipality in São Miguel Island (Azores). The empirical thresholds applied in Portugal are based on the identification of past landslide events and include (i) the computation of antecedent rainfall threshold defined by linear regression, (ii) the normalization of rainfall by the mean annual precipitation, (iii) the definition of lower limit and upper limit rainfall thresholds and (iv) the definition of combined rainfall thresholds, which integrates the rainfall event and the antecedent rainfall for different time periods.

Approaches used to assess shallow slides susceptibility at the basin scale are conceptually different depending on the use of empirically-based or physically-based methods. The former are sustained by 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 opposing forces that promote resistance to movement. Within this general framework, this work tests two hypotheses: (i) although conceptually and methodological distinct, the statistic and deterministic methods generate similar shallow slides susceptibility results regarding the model’s predictive capacity and spatial agreement; and (ii) the combination of shallow slides susceptibility maps obtained with empirically-based and physically-based methods, for the same study area, generate a more reliable susceptibility model for shallow slides occurrence. These hypotheses were tested in a small test site (13.9 km2) located north of Lisbon (Portugal), using a empirically-based method (the Information Value method) and a physically-based method (the Infinite Slope method). The landslide susceptibility maps produced with the statistic 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 slides susceptibility map, which combines the independent results obtained with empirically-based 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.

The purpose of the present study is the analysis of landslide risk for roads and buildings in a small test site (20 km 2 ) in the area north of Lisbon (Portugal). For this purpose, an evaluation is performed integrating into a GIS information obtained from multiple sources: (i) landslide hazard; (ii) elements at risk; and (iii) vulnerability. Landslide hazard is assessed on a probabilistic basis for three different types of slope movement (shallow translational slides, translational slides and rotational slides), based on some assumptions such as: (i) the likelihood of future landslide occurrence can be measured through statistical relationships between past landslide distribution and specified spatial data sets considered as landslide predisposing factors; and (ii) the rainfall combination (amount–duration) responsible for past slope instability within the test site will produce the same effects (i.e. same type of landslides and similar total affected area), each time they occur in the future. When the return period of rainfall triggering events is known, different scenarios can be modelled, each one ascribed to a specific return period. Therefore, landslide hazard is quantitatively assessed on a raster basis, and is expressed as the probability for each pixel (25 m 2 ) to be affected by a future landslide, considering a rainfall triggering scenario with a specific return period. Elements at risk within the test site include 2561 buildings and roads amounting to 169 km. Values attributed to elements at risk were defined considering reconstruction costs, following the guidelines of the Portuguese Insurance Institute. Vulnerability is considered as the degree of loss to a given element resulting from the occurrence of a landslide of a given magnitude. Vulnerability depends not only on structural properties of exposed elements, but also on the type of process, and its magnitude; i.e., vulnerability cannot be defined in absolute terms, but only with respect to a specific process (e.g. vulnerability to shallow translational slides). Therefore, vulnerability was classified for the three landslide groups considered on hazard assessment, taking into account: (i) landslide magnitude (mean depth, volume, velocity); (ii) damage levels produced by past landslide events in the study area; and (iii) literature. Finally, a landslide risk analysis considering direct costs was made in an automatic way crossing the following three layers: (i) Probabilistic hazard map for a landslide type Z , considering a particular rainfall triggering scenario whose return period is known; (ii) Vulnerability map (values from 0 to 1) of the exposed elements to landslide type Z ; and (iii) Value map of the exposed elements, considering reconstruction costs.

Landslides occurred in the Lisbon area during the last 50 years were almost always induced by rainfall and have been used to establish rainfall thresholds for regional landslide activity. In 2006, three new rainfall-triggered landslide events occurred in the study area, namely on the 20 March, the 25–27 October, and the 28 November. Landslide events occurred in March and October 2006 include shallow translational slides and few debris flows, and the corresponding absolute antecedent rainfall was found to be above the threshold for durations ranging from 4 to 10 days. These events also fit the combined threshold of daily precipitation and 5 days calibrated antecedent rainfall values. Likewise the landslide event that took place in late November 2006 includes some slope movements with deeper slip surfaces, when compared with landslides dating from March and October. Moreover, the corresponding absolute antecedent rainfall was also found to be above the 40-day period rainfall threshold. Here we characterize in detail the short and long-term atmospheric circulation conditions that were responsible for the intense rainfall episodes that have triggered the corresponding landslide events. It is shown that the three rainfall episodes correspond to considerably different synoptic atmospheric patterns, with the March episode being associated to an intense cut-off low system while the October and November episodes appear to be related to more typical Atlantic low pressure systems (and associated fronts) travelling eastwards. Finally, we analyse the role played by the North Atlantic Oscillation (NAO) during those months marked by landslide activity. It is shown that the NAO index was consistently negative (usually associated with above average precipitation) for the months prior to the landslide events, i.e. between October 2005 and March 2006, and again between August and October 2006.

A general methodology for the probabilistic evaluation of landslide hazard is applied, taking in account both the landslide susceptibility and the instability triggering factors, mainly rainfall. The method is applied in the Fanhões-Trancão test site (north of Lisbon, Portugal) where 100shallow translational slides were mapped and integrated into a GIS database. For the landslide susceptibility assessment it is assumed that future landslides can be predicted by statistical relationships between past landslides and the spatial data set of the predisposing factors (slope angle, slope aspect, transversal slope profile, lithology, superficial deposits, geomorphology, and land use). Susceptibility is evaluated using algorithms based on statistical/probabilistic analysis (Bayesian model) over unique-condition terrain units in a raster basis. The landslide susceptibility map is prepared by sorting all pixels according to the pixel susceptibility value in descending order. In order to validate the results of the susceptibility ana- lysis, the landslide data set is divided in two parts, using a temporal criterion. The first subset is used for obtaining a prediction image and the second subset is compared with the prediction results for validation. The obtained prediction-rate curve is used for the quantitative interpretation of the initial susceptibility map. Landslides in the study area are triggered by rainfall. The integration of triggering information in hazard assessment includes (i) the definition of thresholds of rainfall (quantity-duration) responsible for past landslide events; (ii) the calculation of the relevant return periods; (iii) the assumption that the same rainfall patterns (quantity/duration) which produced slope instability in the past will produce the same effects in the future (i.e. same types of landslides and same total affected area). The landslide hazard is present as the probability of each pixel to be affected by a slope movement, and results from the coupling between the susceptibility map, the prediction-rate curve, and the return periods of critical rainfall events, on a scenario basis. Using this methodology, different hazard scenarios were assessed, corresponding to different rain paths with different return periods.