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This paper presents a procedure for the application of an index-based vulnerability assessment method to the seismic risk assessment of 292,978 reinforced concrete and 152,916 unreinforced masonry buildings in the Lisbon Metropolitan Area (LMA). A singular innovation of this proposed methodology is that it is tailored to be fed with data from the 2011 national population and housing Census. The vulnerability results are then combined with the seismic hazard component into a GIS tool used to map seismic risk across the LMA. The spatial representation of these results highlights the areas of different levels of vulnerability and risk.

The soils are naturally subjected to erosion, this natural and periodic phenomenon shapes the reliefs, under the combined effect of several drivers, and by the intermediary of certain agents such as the water, wind, etc. The eventual result of the rocks' deterioration and wear is a displacement and deposit where the sediments build up. The Rherhaya basin, Western High Atlas, Morocco, is among the areas most affected by erosion, the structure of its reliefs combined with the hierarchy of its rivers, as well as the lithology of the formations that constitute it play in the presence of other aggravating factors, a preponderant role in determining the rate of erosion in the region. Using GIS, the Revised Universal Soil Loss Equation (RUSLE) model, and the Erosion Potential Method (EPM) model, are applied in this study in order to quantify the annual soil losses in the Rherhaya basin. The results obtained by the RUSLE model are very consistent with the results measured, both in terms of volume, between 2.5 and 6.9 t/ha/yr as soil loss average volume observed versus 4.07 t/ha/yr calculated and 340 t/ha/year as the maximum volume observed versus 317.86 t/ha/year calculated. The maximum soil loss of 542 t/ha/yr and the average soil loss of 103 t/ha/yr are both overestimated by the EPM model, compared to the observed data.

The Lisbon Metropolitan Area (LMA) is a Portuguese administrative region that encompasses 18 municipalities and is characterized by a high risk of landsliding as a consequence of the high susceptibility and exposure of people and assets. Therefore, this work aimed to assess the evolution of exposure levels to landsliding in each municipality of LMA, based on three timesteps (1995, 2011 and 2018), through the following summarized steps: 1) Landslide susceptibility modelling for LMA using an inventory that contains 1268 landslides, mostly rotational and translational slides; 2) Assessment of the relationship between the number of existing buildings and the urban area represented in the official land use map in 2011; 3) Assessment of the population exposed to landslides in 2011 (using Census data) within and outside the urban areas, based on the dasymetric distribution approach; 4) Backward and forward projection of population exposure to landsliding in the years of 1995 and 2018, for which official land use maps are available. Projections are based on relations found in 2) and 3). Overall, the results show that population exposure to landsliding has increased over time in LMA, but differently depending on the municipality considered. The relations found allow to estimate future population and assets exposure based on scenarios of urban expansion and population growth.S.C. Oliveira was financed by the Portuguese Foundation for Science and Technology, I.P., under the framework of the project BeSafeSlide Landslide Early Warning soft technology prototype to improve community resilience and adaptation to environmental change (PTDC/GES-AMB/30052/2017). Ricardo A. C. Garcia was financed by the project Riskcoast - Development of tools to prevent and manage geological risks on the coast linked to climate change (SOE3/P4/EO868, Interreg Sudoe). CEG Research Unit UID/GEO/00295/2019.

On November 18, 1983, a heavy and short-duration rainfall event (164 mm/24 hours ) occurred, particularly, in the northern Lisbon metropolitan area, associated with an atmospheric depression, localised southwest of the Azores islands, which evolved into a cut-off depression. This rainfall event triggered a large number of landslides, with evident regional importance, which remained little explored until now.Event-based landslide inventories identify the location of landslides caused by a single trigger, which is crucial to understand the predisposition factors and to assess landslide susceptibility for different types of landsides occurring in the study area. The purpose of this study is to elaborate a complete event-based landslide inventory for this rainfall-triggered event, which is used to model landslide susceptibility at the regional scale, helping to understand the combined action of the trigger and the landslide predisposing factors.The landslide inventory is built based on the interpretation of high-resolution analogic aerial photographs (1:15,000 scale), obtained after the event, between the 8th and the 13th December 1983. Recent orthophotomaps covering the complete study area were used as the baseline image for the process of geo-referencing the aerial photos. In addition, it was necessary to perform local correction of deformations, resulting from the conic projections of aerial photographs, to improve the geometry of landslide limits. The landslide inventory allows to identify the landslide event spatial extension as well as to characterize the landslide typology, landslide morphometric parameters and event magnitude.The landslide susceptibility is assessed using the event-based landslide inventory and a set of geo-environmental landslide predisposing factors that are modelled with the statistical method of the Information Value. The obtained results are interpreted taking in account the combination of landslide predisposing factors, but also of the spatial distribution of the rainfall that triggered the landslide event. AcknowledgementsThis work is part of the project Riskcoast - Development of tools to prevent and manage geological risks on the coast linked to climate change (SOE3/P4/EO868, Interreg Sudoe). Sérgio C. Oliveira is funded by FCT - Portuguese Foundation for Science and Technology, I.P., through the project BeSafeSlide - Landslide Early Warning soft technology prototype to improve community resilience and adaptation to environmental change (PTDC/GES-AMB/30052/2017) and by the Research Unit UIDB/00295/2020, UIDP/00295/2020.

This work aims to assess the physical vulnerability of buildings (PVB) exposed to landslides that can be triggered by rainfall and earthquake in the Lisbon metropolitan area (LMA).Susceptibility to landslides triggered by rainfall was assessed with a statistical model (Information Value), using seven predisposing factors: slope, aspect, geology, curvature, land use, and topographic wetness and position (TPI) indexes. A landslide inventory containing 4k landslides identified in the Lisbon and Tagus Valley region was used. The ROC curve of this model produced an AUC of 0.92. In this approach, the area defined as most susceptible was selected to assess the PVB for each exposed building to landslides with a slip surface depth of 1 m and an accumulated material height of 0.5 m.Susceptibility to landslides triggered by earthquakes was assessed with an Analytic Hierarchy Process to achieve the relative weights based on the Saaty’s scale of influence using six predisposing factors: slope, curvature, TPI, geology, PGA and distance to faults. The results of this model were compared with a historical inventory of landslides triggered by earthquakes in the LMA obtained from documental sources (Vaz and Zêzere, 2016). The area most susceptible to landslides (8th and 9th deciles) was selected to assess the PVB for each exposed building to landslides with a slip surface depth of 3 m and an accumulated material height of 1 m.In both cases, the PVB assessment considered all exposed buildings with a residential function surveyed in the 2011 Census (Georeferenced Buildings Database - BGE), including the following parameters: construction material, presence of reinforced structure, number of floors, conservation status, and need for repairs in the structure and finishes. Each parameter was divided into a set of building classes obtained from BGE. A score was given to each building class and the respective parameter. Both scores and parameters’ weights are based on expert opinion and dedicated literature (Guillard-Gonçalves et al., 2016; Pereira et al., 2020).The analysis allowed us to observe meaningful regional multi-hazard potential interactions between earthquake and rainfall triggered landslides which can generate, in space and time, a complex level of damages scenarios for residential buildings. Additionally, it contributes to identifying risk hotspots and possible risk adaptation and mitigation measures. AcknowledgmentsTo MIT-RSC - Multi-risk Interactions Towards Resilient and Sustainable Cities (MIT-EXPL/CS/0018/2019), Portuguese Foundation for Science and Technology (FCT I.P.), MIT-Portugal program; RISKCOAST (SOE3/P4/EO868), Interreg-SUDOE program. Pedro Pinto Santos financed through FCT I.P contract CEECIND/00268/2017. CEG Research Unit UID/GEO/00295/2019 References:Guillard-Gonçalves, C., Zêzere, J. L., Pereira, S., & Garcia, R. A. (2016). Assessment of physical vulnerability of buildings and analysis of landslide risk at the municipal scale: application to the Loures municipality, Portugal. Natural Hazards and Earth System Sciences, 16(2), 311-331.Pereira, S., Santos, P. P., Zêzere, J. L., Tavares, A. O., Garcia, R. A. C., & Oliveira, S. C. (2020). A landslide risk index for municipal land use planning in Portugal. Science of the Total Environment, 735, 139463.Vaz, T., & Zêzere, J. L. (2016). Landslides and other geomorphologic and hydrologic effects induced by earthquakes in Portugal. Natural Hazards, 81(1), 71–98.

From the territorial land use planning perspective new urban areas have been safeguarded during the last decades by the Portuguese regulation and practice that consider land use restrictions on landslide hazard prone areas. Nevertheless, the fatalities due to landslides did not reduce in number, mostly due to the occurrence of rapid shallow landslides, affecting people inside buildings and more recently, inside vehicles, as a consequence of the increasing people’s mobility. When the exposure is to deep-seated landslides, structures and infrastructures frequently undergo intense destruction, leading to severe disruption of economic and social activities.The present work intends to evaluate actual exposure of road network to landslides in the context of a Landslide Early Warning System (LEWS) prototype, developed upon both soft and low-cost technology. To achieve this main goal, three specific objectives were defined: (i) to evaluate the road network exposure considering different road types; (ii) to evaluate the re-routing of circulation for users, the loss of access to functions or services, due to travel time increase; and (iii) to evaluate the road network connectivity hierarchy and its contribute to define landslide risk hotspots for evacuation and rescue access in case of disastrous landslide events.The study area corresponds to four municipalities (Alenquer, Arruda dos Vinhos, Sobral de Monte Agraço and Vila Franca de Xira) that are partially included in the Grande da Pipa River (GPR) basin, which is one of the most landslide prone areas in Portugal. The road network hierarchy data is based on available official road network maps; the road segment connectivity role in regional network is based on graph analysis; and the landslide risk hotspots - are classified by combining the different types of road segments, the re-routing travel time scenarios and the road network hierarchy and network connectivity function with the shallow and deep-seated landslide maps produced in the context of the BeSafeSlide project.The final results will be incorporated on the LEWS prototype, which is conceptualized to be people-centred, which means, not specifically focused on hazardous processes, but on reducing exposure and vulnerability, allowing an effective implementation of risk management strategies, contributing for increasing resilience and adaptive capacity building of local communities.Acknowledgments: This work was financed by national funds through FCT (Foundation for Science and Technology, I. P.), in the framework of the project BeSafeSlide – Landslide early warning soft technology prototype to improve community resilience and adaptation to environmental change (PTDC/GES-AMB/30052/2017), and the Research Unit UIDB/00295/2020 and UIDP/00295/2020.

As observed worldwide during the last decades, landslides are one of the deadliest natural hazards in mainland Portugal and Azores archipelago being responsible for significant direct and indirect societal and economic losses, justifying the implementation of a landslide early warning system at the regional scale.The BeSafeSlide project aims to develop and implement a soft technology/low-cost prototype for precipitation-triggered landslide early warning system (LEWS) in Portugal. We plan it to allow be adaptable to a changing climate and a changing land use by working with different climate scenarios. Future changes on regional rainfall patterns due to climate change were evaluated in the LEWS for 2071-2100 period, considering two emission scenarios: RCP 4.5 and RCP 8.5. To evaluate future exposure trends and effects in risk analysis, simulations of changes in land use, by the end of the 21th century, will be carried out. The uncertainty of future projections will be addressed by developing a set of different scenarios.The LEWS prototype for Portugal is sustained on different types of regional rainfall thresholds for landslide occurrence based on daily/hourly rainfall series available for each BeSafeSlide study area. The proposed prototype aims at integrating 3-day rainfall forecasts on rainfall thresholds monitoring and on dynamic physically based susceptibility models, to anticipate changes in hydrological conditions and consequently on the spatio-temporal occurrence of landslides. Special attention is given to two different types of rainfall-triggered landslide events, recognized as responsible for shallow and deep-seated landslides occurrence on natural slopes, which are permanently monitored within the regional early warning system in hotspot risk areas: (i) landslide events associated to intense, short-duration rainfall periods; and (ii) landslide events associated to long-lasting rainfall periods.The LEWS main goals are to provide information to civil protection services to anticipate and manage people’s evacuation from landslide prone areas and to ensure the maintenance and operability of regional transport, energy and communications networks and the safeguarding of people´s lives. Although the LEWS is being developed within the framework of Portugal we expect to be applicable in different settings. The application of the LEWS will define warning communication procedures, assess response capacity of stakeholders and develop social capacity practices, to reduce vulnerability and mitigate risk, providing a reduction of affected people, economic losses and critical infrastructures/basic services disruptions.Acknowledgments: This work was financed by national funds through FCT (Foundation for Science and Technology, I. P.), in the framework of the project BeSafeSlide – Landslide early warning soft technology prototype to improve community resilience and adaptation to environmental change (PTDC/GES-AMB/30052/2017), and the Research Unit UIDB/00295/2020 and UIDP/00295/2020.

It is expected that landslide events will occur more frequently, throughout the century, as a direct consequence of climate change. The main triggering factor, over Portugal mainland, is extreme precipitation. Thus, the aim of this study relied on the assessment of the projected future changes in the extreme precipitation over Portugal mainland and quantifying the correlation between extreme rainfall events and landslide events through Rainfall Triggering Thresholds (RTT). This methodology was applied for two specific locations within two Portuguese areas of great geomorphological interest.To evaluate the possible projected changes in the extreme precipitation, we used the Iberia02 dataset and the EURO-CORDEX models’ runs at a 0.11º spatial resolution. First, it was analyzed the models’ performance to simulate extreme values in the precipitation series. The simulated precipitation relied on RCM-GCM models’ runs, from EURO-CORDEX, and a Multimodel ensemble mean. The extreme precipitation assessment relied on the values associated to the highest percentiles, and to the values associated to the RTTs’ percentiles. To evaluate the possible future changes of the precipitation series, both at the most representative percentiles and RTTs’ percentiles, a comparison was made between the simulated values from EURO-CORDEX historical runs (1971-2000) and the simulated values from EURO-CORDEX future runs (2071-2100), considering two emission scenarios: RCP 4.5 and RCP 8.5. In the models’ performance, the Multimodel ensemble mean appeared to be within the best representing models. As for the projected changes in the extreme precipitation for the end of the century, when following the RCP 4.5 scenario, most models projected an increase in the extreme values, whereas, when following the RCP 8.5 scenario, most models projected a decrease in the extreme values. AcknowledgementsThis work was financed by national funds through FCT–Portuguese Foundation for Science and Technology, I.P., under the framework of the project BeSafeSlide (PTDC/GES-AMB/30052/2017)

Compound weather and climate events are combinations of climate drivers and/or hazards that contribute to societal or environmental risk. Studying compound events often requires a multidisciplinary...

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.

Modeling and understanding the impact of climate change on flooding processes in Mediterranean climate areas, namely in southern Europe, is a complex endeavor that must also consider losses and vulnerability patterns. Understanding disaster risk involves multidimensional and multiscale information, demanding the development of methods that integrate hazard, exposure, capacity, and vulnerability data, strengthening the scientific capacity to support policy makers and practitioners. Assuming that vulnerability plays a relevant role in explaining the degree of loss due to natural hazards and the ability to recover, the present research compares a flood susceptibility index with components of a social vulnerability index and the historical record of flood losses, aggregated at the municipal level. Cross tabulation, cluster classification, and principal components analysis are performed using these three assessment domains in order to identify and interpret their interrelations. The purpose of this research is to understand the contexts of flood disasters and risk for the 278 municipalities of mainland Portugal and to contribute to the strategic allocation of resources for flood risk management.

Compound weather and climate events are combinations of climate drivers and/or hazards that contribute to societal or environmental risk. Studying compound events often requires a multidisciplinary approach combining domain knowledge of the underlying processes with, for example, statistical methods and climate model outputs. Recently, to aid the development of research on compound events, four compound event types were introduced, namely (a) preconditioned, (b) multivariate, (c) temporally compounding, and (d) spatially compounding events. However, guidelines on how to study these types of events are still lacking. Here, we consider four case studies, each associated with a specific event type and a research question, to illustrate how the key elements of compound events (e.g., analytical tools and relevant physical effects) can be identified. These case studies show that (a) impacts on crops from hot and dry summers can be exacerbated by preconditioning effects of dry and bright springs. (b) Assessing compound coastal flooding in Perth (Australia) requires considering the dynamics of a non‐stationary multivariate process. For instance, future mean sea‐level rise will lead to the emergence of concurrent coastal and fluvial extremes, enhancing compound flooding risk. (c) In Portugal, deep‐landslides are often caused by temporal clusters of moderate precipitation events. Finally, (d) crop yield failures in France and Germany are strongly correlated, threatening European food security through spatially compounding effects. These analyses allow for identifying general recommendations for studying compound events. Overall, our insights can serve as a blueprint for compound event analysis across disciplines and sectors., Plain Language Summary: Many societal and environmental impacts from events such as droughts and storms arise from a combination of weather and climate factors referred to as a compound event. Considering the complex nature of these high‐impact events is crucial for an accurate assessment of climate‐related risk, for example to develop adaptation and emergency preparedness strategies. However, compound event research has emerged only recently, therefore our ability to analyze these events is still limited. In practice, studying compound events is a challenging task, which often requires interaction between experts across multiple disciplines. Recently, compound events were divided into four types to aid the framing of research on this topic, but guidelines on how to study these four types are missing. Here, we take a pragmatic approach and—focusing on case studies of different compound event types—illustrate how to address specific research questions that could be of interest to users. The results allow identifying recommendations for compound event analyses. Furthermore, through the case studies, we highlight the relevance that compounding effects have for the occurrence of landslides, flooding, vegetation impacts, and crop failures. The guidelines emerged from this work will assist the development of compound event analysis across disciplines and sectors., Key Points: Using case studies representative of four main compound event types we show how compound event‐related research questions can be tackled. We present user‐friendly guidelines for compound event analysis applicable to different compound event types. We demonstrate that compound events cause vegetation impacts, coastal flooding, landslides, and continental‐scale crop yield failures., European COST action DAMOCLES, NERC, Swiss National Science Foundation, Helmholtz Initiative and Networking Fund, Netherlands Organisation for Scientific Research (NWO), Fundação para a Ciência e a Tecnologia, Scientific Employment Stimulus 2017, Italian Ministry of University and Research, European Union's Horizon 2020 research and innovation programme, AXA Research Fund for support, Portuguese Foundation for Science and Technology

Nowadays it is essential to develop new methodologies to quantify landslide risk, which contribute to the landslide risk management at the municipal level. In this work, a Landslide Risk Index (LRI) is computed for the 278 Portuguese municipalities, which are ranked and characterized according the landslide risk drivers. Landslide risk index was assessed as the product of hazard, exposure and physical vulnerability of buildings scores.The landslide hazard includes the landslide susceptibility evaluated at the national scale using the Information Value method and further validated with prediction-rate curves (Zêzere et al., 2018). Additionally, a weather and climate events index (WCE) was computed using a multicriteria analysis that included the annual frequency of circulation weather types associated to damaging landslides and an extreme precipitation susceptibility index (Santos et al., 2020). Exposure was evaluated for each municipality using the population density (inhabitants/km2) and the road density (km/km2). The physical vulnerability of the buildings was computed using four statistical variables obtained from the official Census: (i) construction technique and construction materials, (ii) reinforced structure, (iii) number of floors and (iv) conservation status. Variable classes were empirically weighted.Exposure is the main driving force of LRI in the metropolitan areas of Lisbon and Porto, whereas the hazard is more relevant in the NW municipalities and the physical vulnerability is the major driving force in the south of the country.For each municipality a landslide risk profile was built, based on the combination of the three driving forces, which can be compared and ranked. Therefore, the landslide risk management strategies at the municipal level must be adjusted to the corresponding dominant drivers in order to reduce landslide impacts.Municipalities with high values of hazard are sensitive to changes on the other risk components, which should draw additional efforts concerning land use management and emergency planning. On the exposure, planning instruments should consider the negative effects on LRI from measures that promote the expansion of people and economic activities towards hazardous zones. On the physical vulnerability, public policies should be aware of the increasing physical vulnerability of buildings in time due to age and lack of maintenance and to public works involving embankments and earthworks.This work contributes to context-oriented strategies of landslide risk management that still lacks in most of the national and regional levels of risk governance processes. Acknowledgements:This work was financed by national funds through FCT—Portuguese Foundation for Science and Technology, I.P., under the framework of the project BeSafeSlide—Landslide Early Warning soft technology prototype to improve community resilience and adaptation to environmental change (PTDC/GES-AMB/30052/2017) and by the Research Unit UIDB/00295/2020. Pedro Pinto Santos is funded by FCT (project reference CEEIND/00268/2017). References:Santos, P.P.; Pereira, S.; Zêzere, J.L.; Tavares, A.O.; Reis, E.; Garcia, R.A.C.; Oliveira, S.C. (2020) A comprehensive approach to understanding flood risk drivers at the municipal level. Journal of Environmental Management (in press).Zêzere, J.L., Oliveira, S.C., Pereira, S., Garcia, R.A.C., Melo, R., Vaz, T., Tavares, A.O., Bateira, C., Santos, P.P., Meneses, B., Quaresma, I. (2018) Construction of a National Landslide Susceptibility Map for Portugal. Geophysical Research Abstracts, Vol. 20, EGU2018-4541.

During the last two centuries, several debris flow events occurred in the upper part of the Zêzere valley, which is located in the Estrela mountain, in Central Portugal. These events were responsible for material damage as well as for the loss of lives. Given the susceptibility of this area to the occurrence of debris flows, a methodology for pedestrian evacuation modelling was implemented, in order to identify buildings at risk and pedestrian travel times to safety areas in a debris flow worst-case scenario. Starting from a dynamic run-out model, developed in previous works, the potential debris flow intensity was estimated (e.g. flow depth, velocity and run-out distance). Sequentially, the buildings potentially affected by the impact of debris flows, as well as the ones where the evacuation would take longer than the debris flows arrival, were identified. In addition, the potentially exposed population was estimated by applying a dasymetric distribution to each residential building. This population distribution took into account the identification of the older residents as the most exposed to debris flows, which is critical to develop reliable pedestrian evacuation travel time scenarios. The pedestrian evacuation modelling was performed using the Pedestrian Evacuation Analyst, a GIS tool developed by the United States Geological Survey. The evacuation modelling was based on an anisotropic approach, which considers the influence of slope direction on travel costs, thus its application is suitable in a mountainous area. The implemented methodology is a critical step towards the implementation of a reliable early warning system to debris flows that can be reproduced elsewhere.Funding information: This work was financed by national funds through FCT—Portuguese Foundation for Science and Technology, I.P., under the framework of the project BeSafeSlide—Landslide Early Warning soft technology prototype to improve community resilience and adaptation to environmental change (PTDC/GES-AMB/30052/2017) and by the Research Unit UIDB/00295/2020. Pedro Pinto Santos is funded by FCT through the project with the reference CEEIND/00268/2017.

This work aims to compute a flood risk index (FRI) for the 278 Portuguese municipalities, designed to rank and characterize the drivers of fluvial flooding-related disasters (Santos et al., 2020). FRI is the product of hazard, exposure and vulnerability scores, where each factor is raised to 1/3, a solution also applied by the INFORM risk index to increase the dispersion of index values.Hazard considers two variables: flood susceptibility (SUSCF), and the weather and climate events index (WCE) translating the frequency of the rainfall events that may generate peak flows. SUSCF is the product of stream flood susceptibility (SFS) (Santos et al., 2019) and the main flood-prone areas (MFPA). SFS considers flow accumulation, slope angle and relative permeability, accounting for the cumulative effect of these factors along the entire basins’ area. MPFA results from overlaying areas with slope angle ≤ 2º and areas with Height Above Nearest Drainage ≤ 2, only when they were topologically connected to streams with SFS > 5.Exposure considers three variables: population density (PD), road density (RD) and the average degree of imperviousness (ADI). PD (inhab./km2) is based on the 2011 Census. RD (km/km2) is calculated from the OpenStreetMap© data. ADI is the municipal average value of the layer “IMD - Imperviousness Degree 2012 – 20 m resolution”, from the Copernicus Land Monitoring Service.Vulnerability (V) is the product of criticality and support capability, where the latter acts by attenuating criticality, according to the methodology presented by Tavares et al. (2018) to assess social vulnerability.The six core variables were scaled to the range [0, 1] following the max-min method. The respective weights were tested and selected according to the scientific literature, correlation and reliability tests.Ward’s clustering classification was used to define seven clusters of municipalities, differing in the scores of hazard, exposure and vulnerability. While it is suggested that municipalities in some clusters would require interventions to reduce hazard, others should invest on medium to long-term measures that address high exposure and vulnerability. The results obtained with this methodological approach contribute to the diversification of flood risk management strategies. Acknowledgements:This work was financed by national funds through FCT—Portuguese Foundation for Science and Technology, I.P., under the framework of the project BeSafeSlide‑Landslide Early Warning soft technology prototype to improve community resilience and adaptation to environmental change (PTDC/GES-AMB/30052/2017) and by the Research Unit UIDB/00295/2020. Pedro Pinto Santos is funded by FCT through the project with the reference CEEIND/00268/2017. References:Santos, P.P., Pereira, S., Zêzere, J.L., Tavares, A.O., Reis, E., Garcia, R.A.C., Oliveira, S.C., 2019. A comprehensive approach to understanding flood risk drivers at the municipal level. J. Environ. Manage. https://doi.org/10.1016/j.jenvman.2020.110127Santos, P.P., Reis, E., Pereira, S., Santos, M., 2019. A flood susceptibility model at the national scale based on multicriteria analysis. Sci. Total Environ. 667, 325–337. https://doi.org/10.1016/j.scitotenv.2019.02.328Tavares, A.O., Barros, J.L., Mendes, J.M., Santos, P.P., Pereira, S., 2018. Decennial comparison of changes in social vulnerability: A municipal analysis in support of risk management. Int. J. Disaster Risk Reduct. 31, 679–690. https://doi.org/10.1016/J.IJDRR.2018.07.009

Landslides, like any natural hazardous process, do not generate risk until some type of interaction with human settlements or activities occur. Consequently, the landslide susceptibility assessment and the quantification of the exposure and potential losses of structures and infrastructures is crucial for informing emergency and spatial planning in areas prone to geomorphological hazards. Thus, the major aim of this work is to identify the current and future buildings’ exposure to landslides, in order to get useful information to support decision planners.The current spatial distribution of buildings and future exposure trends will be assessed based on the Portuguese Census data, which will be used as ancillary information to derive the number and type of buildings at the basic census polygonal unit. The future buildings’ exposure will be determined from a cellular automata simulation model.Four types of buildings are considered: E1 – light structures of wood or metal; E2 – buildings of adobe, rammed earth or loose stone walls; E3 - buildings with brick or stone masonry walls; and E4 - buildings of masonry walls confined with reinforced concrete. The evaluation of buildings’ exposure is made for two landslide event scenarios: one for shallow soil slips (with rupture surfaces depth < 1.5 m) and another one for deep-seated slides (with rupture surfaces depth > 1.5 m). The landslide susceptibility/hazard hotspots for both scenarios are assessed in a study area corresponding to four municipalities located in the northern sector of the Lisbon Metropolitan Area, Portugal. The landslide susceptibility models are based on a bivariate statistical method (Information Value) and on a dataset of eight independent variables assumed as predisposing factors for the occurrence of landslides: lithology, slope, curvature, aspect, slope/contribution area ratio, topographic position index (TPI), soil type and land use. The validation procedures include the computation of ROC curves and the calculation of AUROC. Landslide susceptibility and buildings’ exposure are presented as probabilities at the basic census unit scale. Results combine the probability of occurrence of a landslide with the probability of having a building of a certain type potentially affected by a landslide, for the two landslide event scenarios.Finally, potential losses on buildings are assessed from exposure and damage on buildings caused by landslides in the past.Acknowledgements:This work was financed by national funds through FCT—Portuguese Foundation for Science and Technology, I.P., under the framework of the project BeSafeSlide—Landslide Early Warning soft technology prototype to improve community resilience and adaptation to environmental change (PTDC/GES-AMB/30052/2017) and by the Research Unit UIDB/00295/2020. Pedro Pinto Santos is funded by FCT through the project with the reference CEEIND/00268/2017.

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.

Debris flows are one of the most hazardous types of landslides in mountain regions. In the upper part of the Zêzere valley (Serra da Estrela, Portugal) several debris flows events occurred in the last 200 years, some of them causing loss of lives and material damages. In this work, a methodology for pedestrian evacuation modelling, in a debris flow hazard scenario, was implemented. A dynamic run-out model, developed in previous studies, was used to evaluate the debris flows velocities, thickness of the deposits and extent of the mobilized material. The buildings potentially affected by the impact of debris flows were identified and the potentially exposed population was estimated by applying a dasymetric distribution. The results lead to the conclusion that, in the study area, the elderly are those who are most exposed to debris flows. Furthermore, the time lapse between the debris flows initiation and the arrival at the buildings at risk was estimated, allowing to account for the overall number of buildings where the evacuation time takes longer than the debris flows arrival. Additionally, the safe areas within the study area were identified, and several safe public buildings with the capacity to gather a large number of persons were selected. Considering that the study area is located in a mountain region, characterized by steep slopes, the evacuation modelling was performed based on an anisotropic approach, in order to consider the influence of slope direction on travel costs. At the end, three pedestrian evacuation travel time scenarios, based on different walking speeds to accommodate residents with different ages in safer places, were compared and the results mapped. The implemented methodology is not local dependent, which allows its reproduction elsewhere.

In the last decades, Portugal was affected by several geomorphological hazards that produced high levels of destruction and disruption on human activities, particularly due to the inappropriate occupation of areas where natural hazardous phenomena occur. To cope against the consequences of these hazards, a set of legal instruments has been implemented in the last 30–40 years by national initiative or by transposition to the national law of European Directives within the thematic of risk assessment and management. This chapter broadly presents the planning and emergency management legal framework in Portugal, as well as the specific normative instruments for the major geomorphological hazards that influence land use regulation.

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.

This work proposes a comprehensive methodology to assess rainfall thresholds for landslide initiation, using a centenary landslide database associated with a single centenary daily rainfall dataset. The methodology is applied to the Lisbon region and include the rainfall return period analysis that was used to identify the critical rainfall combination (quantity-duration) related to each landslide event. The spatial representativeness of the reference rain gauge is evaluated and the rainfall thresholds is assessed and validated using the receiver operating characteristic (ROC) metrics. Results show that landslide events located up to 10 km from the rain gauge can be used to calculate the rainfall thresholds in the study area; however, such thresholds may be used with acceptable confidence up to 50 km distance from the rain gauge. The obtained rainfall thresholds using linear and potential regression have a good performance in ROC metrics. However, the intermediate thresholds based on the probability of landslide events, established in the zone between the lower limit threshold and the upper limit threshold are much more informative as they indicate the probability of landslide event occurrence given rainfall exceeding the threshold. This information can be easily included in landslide early warning systems, especially when combined with the probability of rainfall above each threshold.

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.

Floristic and vegetation analysis in seven Mediterranean landslides led to the understanding of the successional processes occurring in different landslide disturbed sectors. Our study showed that in landslides that occurred between 1996 and 2010 there is a clear differentiation between the three main landslide sectors (scarp, main body and foot) concerning floristic composition, vegetation structure, floristic richness, successional processes and plant functional type. Additional differences were found between landslide areas and undisturbed agricultural areas adjacent to landslides. In this study 48 floristic relevés were made using a stratified random sampling design. The main landslide body exhibits the highest floristic richness whereas the landslide scarp has the lowest coverage rate and the highest presence of characteristic species from ruderal and strongly perturbed habitats. Finally, the landslide foot shows a late stage in the succession (maquis or pre-forest stage) with a high dominance of vines. We further discuss the importance of landslides as reservoirs of biodiversity especially for Mediterranean orchids.

A landslide quantitative risk analysis is applied the municipality of Santa Marta de Penagui~ao (N of Portugal) to evaluate the risk to which the buildings are exposed, using a vector data model in GIS. Two landslide subgroups were considered: landslide subgroup 1 (event inventory of landslides occurred on January 200)1; and landslide subgroup 2 (inventoried landslides occurred after the 2001 event until 2010). Seven landslide predisposing factors were weighted and integrated using the Information Value Method. The landslide susceptibility model was independently validated and the model performance was expressed by ROC curves. The probability of landslide size was estimated using a probability density function and the landslide hazard scenario was defined using the same landslide rainfall-triggering event. A vulnerability curve was constructed for each type of building considering its structural properties and the proxy of landslide magnitude. The economic value assigned for each building represents an approximated cadastral value. The landslide risk was computed for each building in vector format based on a rainfall triggering scenario and two landslide magnitudes. The probability of occurrence of small landslides is two orders of magnitude higher than the probability of occurrence for large landslides, which explains the higher risk generated by small landslides, despite of registering.

This research is focused on the susceptibility assessment of shallow slides by modeling the failure and run-out areas separately. The shallow slides failure is evaluated using a statistical method (logistic regression) and for the run-out assessment, a simple cellular automata model is proposed. The existence of shallow slides inventories occurred in distinct time periods allowed the separation of data into two independent groups (modeling and validation) and the adoption of the temporal criterion for the independent validation. The logistic regression model showed a very good predictive capacity (area under the receiver operating characteristic curve of 0.90), although it may be overestimated, as well as the susceptibility scores obtained. The run-out modeling, using a simple cellular automata model developed for this study, provided good results, with an overlap between the simulation and the real cases of 77%. Lastly, a final shallow slide susceptibility map was constructed including both failure and run-out areas. This work accomplished a combination of low-cost methodology with limited input data that allowed a good performance of the landslide susceptibility assessment and can be easily applied to other regions.

This study presents a proposed application of the Time-Weighted Dynamic Time Warping (TWDTW) method for urban sprawl analysis. Four spectral indices were computed from a long time-series of Landsat satellite imagery, corresponding to 48 scenes acquired between 2006 and 2018. The spectral indices were the Normalized Difference Vegetation Index (NDVI), the Normalized Difference Built Index (NDBI), the Normalized Difference Water Index (NDWI), and the Normalized Difference Bareness Index (NDBaI), which when processed resulted in 192 different images. The R package dtwSat was used for image processing, since it represents one of the few open source software programs available for processing large time-series datasets. The method was tested applied in the Alentejo Region of Southern Portugal; traditionally a rural region, where urban sprawl presents risks for the preservation of agricultural systems and for ecosystem sustainability. The sprawl analysis was integrated in a Geographic Information System (GIS), in which we computed an Expansion Index to quantitatively assess the three main urban land expansion types: infill, extension, and leapfrog. The results show that, between 2007 and 2012, the main changes are due to extension (50 ha), but with a significant amount of infill (36 ha) and leapfrog growth (4 ha), with this latter being the worst-case scenario. However, in the subsequent period, 2012-2017, urban growth decreased to about 10 ha, comprising both infill and extension, but notably leapfrog expansion disappeared. Our methodology proved to be flexible for managing irregular sampling and an out-of-phase time-series. The procedure offers a quantitative means of assessing urban sprawl dynamics and represents a potential strategy for defining sustainable urban development.

In Portugal landslides caused 237 fatalities and >1600 displaced people in the period 1865-2015. Spatial distribution and temporal patterns of slope instability can be related with a complex set of natural and human factors responsible for generating damages. It is essential to develop new methodologies to synthetize risk dimensions to contribute to the landslide risk management at the municipal level. This work proposed a municipal landslide risk index (LRI) considering three risk dimensions: hazard, exposure and physical vulnerability of buildings. The hazard dimension includes the landslide susceptibility performed at the national scale, the probability of weather types associated with landslides and an extreme precipitation susceptibility index. The exposure dimension considered the population density and the number of buildings, whereas the average physical vulnerability of the buildings was computed using four statistical variables from the official census: (i) construction technique and construction materials; (ii) reinforced structure; (iii) number of floors; and (iv) conservation status. Each variable includes different classes that were empirically weighted. After evaluating the three risk dimensions and the LRI, a cluster analysis was performed in order to identify the most important landslide risk drivers in each municipality. Exposure is the main driving force of LRI in the metropolitan areas of Lisbon and Porto, while the hazard is more relevant in the NW municipalities and the physical vulnerability is the major driving force in the south of the country. This methodological approach contributes to a comprehensive and synthetized knowledge about the landslide risk driving forces within the 278 Portuguese municipalities. In addition, it contributes to the diversification and context-oriented strategies of landslide risk management that still lacks in most of the national-level risk governance processes. Finally, this methodology can be generalized to other geographical contexts, improving the risk management, land use planning and the disaster risk reduction.

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).

Leishmaniasis is caused by protozoan parasites of the genus Leishmania. In mammalians, these parasites survive and replicate in macrophages and parasite elimination by macrophages is critical for host resistance. Endosomal Toll-like receptors (TLRs) have been shown to be crucial for resistance to Leishmania major in vivo. For example, mice in the resistant C57BL/6 genetic background that are triple-deficient for TLR3, -7, and -9 (Tlr3/7/9−/−) are highly susceptible to L. major infection. Tlr3/7/9−/− mice are as susceptible as mice deficient in MyD88 or UNC93B1, a chaperone required for appropriate localization of endosomal TLRs, but the mechanisms are unknown. Here we found that macrophages infected with L. major undergo autophagy, which effectively accounted for restriction of parasite replication. Signaling via endosomal TLRs was required for autophagy because macrophages deficient for TLR3, -7, and 9, UNC93B1, or MyD88 failed to undergo L. major-induced autophagy. We also confirmed that Myd88−/−, Tlr3/7/9−/−, and Unc93b1−/− cells were highly permissive to L. major replication. Accordingly, shRNA-mediated suppression of Atg5, an E3 ubiquitin ligase essential for autophagosome elongation, in macrophages impaired the restriction of L. major replication in C57BL/6, but did not affect parasite replication in Myd88−/− or Unc93b1−/− macrophages. Rapamycin treatment reduced inflammatory lesions formed in the ears of Leishmania-infected C57BL/6 and Tlr3/7/9−/− mice, indicating that autophagy operates downstream of TLR signaling and is relevant for disease development in vivo. Collectively, our results indicate that autophagy contributes to macrophage resistance to L. major replication, and mechanistically explain the previously described endosomal TLR-mediated resistance to L. major infection.

Landslides are one of the most relevant geomorphological hazards in Portugal, by the high levels of people affected, destruction of assets and disruption of economic and social activities. Regarding the Portuguese territorial land use planning and emergency management, regulation, practice, prevention and risk management have been promoted in different ways. In Portugal, the areas susceptible to landslides are included in the ‘National Ecological Reserve’, which is a public utility restriction legal figure that rules the land use planning at the municipal level. In addition, the Municipal Emergency Plans include landslide susceptibility maps that are combined with the map of the exposed elements, allowing the assessment of exposure to landslides. This study is applied to the Loures municipality located to the north of Lisbon. In this municipality 621 landslides registered in a landslide inventory (rotational slides, deep-seated translational slides and shallow translational slides) that affected 1,469,577 m2 (0.87%) of the Loures territory. The final landslide susceptibility map shows that in Loures municipality 1347 ha are associated to a Very high landslide susceptibility and 2372 ha to High landslide susceptibility, which corresponds both to 22.1% of the entire municipality, and constitutes the larger fraction of the National Ecological Reserve, related to landslides. These areas do not present geomorphological and geotechnical suitability for building structures or infrastructures. From the civil protection and emergency management point of views 34 classes of exposed elements were identified in the municipality, with point, linear and polygonal representations. The elements at risk located in the Very High or High landslide susceptibility classes were summarized and correspond to: high voltage poles; wind turbines; transmission/reception antennas; industrial areas; water tanks; silo; gas station/tank; service area; buildings of educational institutions; worship buildings; buildings of electricity facilities; regular buildings; gas pipeline; motorways; national roads; and municipal roads.

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.