shallow landslides susceptibility assessment in different environments

The spatial distribution of shallow landslides is strongly influenced by different climatic conditions and environmental settings. This makes difficult the implementation of an exhaustive monitoring technique for correctly assessing the landslide susceptibility in different environmental contexts. In this work, a unique methodological strategy, based on the statistical implementation of the generalized additive model (GAM), was performed. This method was used to investigate the shallow landslide predisposition of four sites with different geological, geomorphological and land-use characteristics: the Rio Frate and the Versa catchments (Southern Lombardy) and the Vernazza and the Pogliaschina catchments (Eastern Liguria). A good predictive overall accuracy was evaluated computing by the area under the ROC curve (AUROC), with values ranging from 0.76 to 0.82 and estimating the mean accuracy of the model (0.70–0.75). The method showed a high flexibility, which led to a good identification of the most significant predisposing factors for shallow landslide occurrence in the different investigated areas. In particular, detailed susceptibility maps were obtained, allowing to identify the shallow landslide prone areas. This methodology combined with the use of the rainfall thresholds for triggering shallow landslides may provide an innovative tool useful for the improvement of spatial planning and early warning systems

Regional geomorphic analysis and GIS susceptibility mapping of landslides in the Blue Nile and the Tekeze River Basins of Ethiopia

The Plateau region of Ethiopia lies within a seismically active continental extensional regime, which is being rapidly incised by the Blue Nile and the Tekeze Rivers. Extremely large landslides pose serious hazards in this highly populated region (\u3e27 million), which is in the process of developing its hydrologic resources. This research sought to develop cost-effective methods to compile regional landslide inventory and landslide susceptibility maps, using geomorphic tools and GIS technologies. This work also sought to evaluate the relationships between landslide dams and knickpoints, caused by channel bed incision from those caused by slope failures, by utilizing identified knickpoints along 56 tributary channels across the study area. The study employed the weighted overlay technique to produce regional landslide susceptibility hazard maps, and for the first time, employing wind-driven and integrated rainfall/aspect rasters at various inclination to more realistically model the actual precipitation that is felt by hillsides of varying azimuth, shape, and height. Landslides greater than 500m long were tentatively identified on 1:200,000 topographic maps draped over 30m hill-shade generated ASTER GDEMv2. The mapping revealed different types of landslides, and also revealed a considerable number of old, dormant landslide features. The use of wind-driven rainfall with integrated rainfall and aspect rasters provided a much more detailed and asymmetric distribution of precipitation. Spatial distribution of the very high and high hazard areas, during the Kermit and Belg rainy seasons by a range of 0.38% for an inclination of 40º and 1.7% for inclinations on 60º, as compared to the traditional assumption of 90º vertical rainfall, without integration of a slope aspect raster --Abstract, page iii

Progress in Landslide Research and Technology, Volume 1 Issue 1, 2022

This open access book provides an overview of the progress in landslide research and technology and is part of a book series of the International Consortium on Landslides (ICL). The book provides a common platform for the publication of recent progress in landslide research and technology for practical applications and the benefit for the society contributing to the Kyoto Landslide Commitment 2020, which is expected to continue up to 2030 and even beyond to globally promote the understanding and reduction of landslide disaster risk, as well as to address the 2030 Agenda Sustainable Development Goals

Climate change, water risks and urban responses in the Pearl River Delta, China

Currently, concerns are increasing that climate change may intensify natural disasters, like droughts, floods and storms which pose risks to human society, especially at the coastal urban area. This thesis studies climate change, water shortage and flood risks as well as human response measures in the highly urbanized Pearl River Delta (PRD) area in South China. Analysis on climate change in the PRD area is based on existing datasets and model projections, with an integration of literature results. Findings indicate significant climate change in both the past and future of the area, with a trend of increasing mean temperature, fluctuating precipitation, rising sea level and increasing typhoon intensity as well as the frequency of extreme weather events. In particular, the annual mean temperature in the PRD area is likely to rise by around 3℃ and precipitation to increase slightly but with greater fluctuations by 2100, while the sea level is projected to rise with an annual rate of 0.33cm to 1cm in this century. Climate change is likely to increase rainfall variability, drought intensity and duration, and damages on water-related infrastructure by extreme weather events, which all increasingly threaten the local freshwater availability. The water supply situation is becoming more complicated along with the population growth, economic development and difficulties in response/management. Hence, ensuring sufficient freshwater availability is one of the major water management challenges for all the PRD cities. Taking Hong Kong as a case study, this thesis highlights six interrelated risks within the context of climate change, namely: drought, rainstorm/flood events, sea-level rise, water pollution, social management and policy gaps. It suggests that for a sustainable future, Hong Kong needs to invest in improving water self-sufficiency, diversify water sources and conduct aggressive public awareness to increase individual adaptation to predicted climate change impacts. Flood implications of climate change trends are pronounced in most of the cities in PRD as well. The frequency and intensity of extreme weather and climate events have assumed significant change, together with continuing development in flood-prone areas, which increase both the scale and degree of urban flood risk. Further estimation was made on the flood risk in the 11 cities of PRD area from both aspects of the probability of a flood occurrence and the vulnerability of the cities. The results suggest that the exposure and sensitivity of Hong Kong, Macao, Shenzhen and Guangzhou are very high because of highly exposed populations and assets located in lowland areas. However, the potential vulnerability and risk is low due to high adaptive capacities in both hard and soft flood-control measures. A novel framework on flood responses is proposed to identify vulnerable links and response strategies in different phases of a flood event. It further suggests that the flood risks can be reduced by developing an integrated climate response strategy, releasing accurate early warning and action guidance, sharing flood related information to the public and applying the advantages of social network analysis. Further, an agent-based model is developed as an instrument to simulate the process by which individual households optimize benefits through flood response investment and damage control. The model implements a subjective response framework in which households appraise inundation scenarios according to warnings, and decide whether to invest in mitigation measures to reduce potential inundation damages. Households may have variant flood response preferences and activities but they all require investments which are consequently considered as part of the final flood losses. A case study was carried out in the Ng Tung River basin, an urbanized watershed in Northern Hong Kong. First results underline that in-time, accurate and wide-covered flood warning plays a significant role in reducing flood losses. And earlier investments in responding measures are more efficient than late activities. This dynamic agent-based modeling approach finally demonstrates its capacity to analyze the interactions between flood inundation and households responses. Overall, findings of this study help understand the level of climate change impacts and vulnerability in water domain, which are vital to gauge the cities’ risks and corresponding responses and therefore inform decisions about how best to deal with emerging climate-related water risks like drought and flood

Development and validation of the terrain stability model for assessing landslide instability during heavy rain infiltration

Slope stability is a key topic, not only for engineers but also for politicians, due to the considerable monetary and human losses that landslides can cause every year. In fact, it is estimated that landslides have caused thousands of deaths and economic losses amounting to tens of billions of euros per year around the world. The geological stability of slopes is affected by several factors, such as climate, earthquakes, lithology and rock structures, among others. Climate is one of the main factors, especially when large amounts of rainwater are absorbed in short periods of time. Taking this issue into account, we developed an innovative analytical model using the limit equilibrium method supported by a geographic information system (GIS). This model is especially useful for predicting the risk of landslides in scenarios of heavy unpredictable rainfall. The model, hereafter named terrain stability (or TS) is a 2-D model, is programed in MATLAB and includes a steady-state hydrological term. Many variables measured in the field – topography, precipitation and type of soil – can be added, changed or updated using simple input parameters. To validate the model, we applied it to a real example – that of a landslide which resulted in human and material losses (collapse of a building) at Hundidero, La Viñuela (Málaga), Spain, in February 2010.</p

Enhancing community resilience in arid regions: A smart framework for flash flood risk assessment

This paper presents a novel framework for smart integrated risk management in arid regions. The framework combines flash flood modelling, statistical methods, artificial intelligence (AI), geographic evaluations, risk analysis, and decision-making modules to enhance community resilience. Flash flood is simulated by using Watershed Modelling System (WMS). Statistical methods are also used to trim outlier data from physical systems and climatic data. Furthermore, three AI methods, including Support Vector Machine (SVM), Artificial Neural Network (ANN), and Nearest Neighbours Classification (NNC), are used to predict and classify flash flood occurrences. Geographic Information System (GIS) is also utilised to assess potential risks in vulnerable regions, together with Failure Mode and Effects Analysis (FMEA) and Hazard and Operability Study (HAZOP) methods. The decision-making module employs the Classic Delphi technique to classify the appropriate solutions for flood risk control. The methodology is demonstrated by its application to the real case study of the Khosf region in Iran, which suffers from both drought and severe floods simultaneously, exacerbated by recent climate changes. The results show high Coefficient of determination (R2) scores for the three AI methods, with SVM at 0.88, ANN at 0.79, and NNC at 0.89. FMEA results indicate that over 50% of scenarios are at high flood risk, while HAZOP indicates 30% of scenarios with the same risk rate. Additionally, peak flows of over 24 m3/s are considered flood occurrences that can cause financial damage in all scenarios and risk techniques of the case study. Finally, our research findings indicate a practical decision support system that is compatible with sustainable development concepts and can enhance community resilience in arid regions

Geo-Information Technology and Its Applications

Geo-information technology has been playing an ever more important role in environmental monitoring, land resource quantification and mapping, geo-disaster damage and risk assessment, urban planning and smart city development. This book focuses on the fundamental and applied research in these domains, aiming to promote exchanges and communications, share the research outcomes of scientists worldwide and to put these achievements better social use. This Special Issue collects fourteen high-quality research papers and is expected to provide a useful reference and technical support for graduate students, scientists, civil engineers and experts of governments to valorize scientific research

Earthquake risk assessment using an integrated Fuzzy Analytic Hierarchy Process with Artificial Neural Networks based on GIS: A case study of Sanandaj in Iran

Earthquakes are natural phenomena, which induce natural hazard that seriously threatens urban areas, despite significant advances in retrofitting urban buildings and enhancing the knowledge and ability of experts in natural disaster control. Iran is one of the most seismically active countries in the world. The purpose of this study was to evaluate and analyze the extent of earthquake vulnerability in relation to demographic, environmental, and physical criteria. An earthquake risk assessment (ERA) map was created by using a Fuzzy-Analytic Hierarchy Process coupled with an Artificial Neural Networks (FAHP-ANN) model generating five vulnerability classes. Combining the application of a FAHP-ANN with a geographic information system (GIS) enabled to assign weights to the layers of the earthquake vulnerability criteria. The model was applied to Sanandaj City in Iran, located in the seismically active Sanandaj-Sirjan zone which is frequently affected by devastating earthquakes. The Multilayer Perceptron (MLP) model was implemented in the IDRISI software and 250 points were validated for grades 0 and 1. The validation process revealed that the proposed model can produce an earthquake probability map with an accuracy of 95%. A comparison of the results attained by using a FAHP, AHP and MLP model shows that the hybrid FAHP-ANN model proved flexible and reliable when generating the ERA map. The FAHP-ANN model accurately identified the highest earthquake vulnerability in densely populated areas with dilapidated building infrastructure. The findings of this study are useful for decision makers with a scientific basis to develop earthquake risk management strategies

Indirect impact of landslide hazards on transportation infrastructure

This thesis examines the indirect impact of natural hazards on infrastructure networks. It addresses several key themes and issues for hazard assessment, network modelling and risk assessment using the case study of landslides impacting the national road network in Scotland, United Kingdom. The research follows four distinct stages. First, a landslide susceptibility model is developed using a database of landslide occurrences, spatial data sets and logistic regression. The model outputs indicate the terrain characteristics that are associated with increased landslide potential, including critical slope angles and south westerly aspects associated with increased rates of solar irradiance and precipitation. The results identify the hillslopes and road segments that are most prone to disruption by landslides and these indicate that 40 % (1,700 / 4,300 km) of Scotland s motorways and arterial roads (i.e. strategic road network) are susceptible to landslides and this is above previous assessments. Second, a novel user-equilibrium traffic model is developed using UK Census origin-destination tables. The traffic model calculates the additional travel time and cost (i.e. indirect impacts) caused by network disruptions due to landslide events. The model is applied to calculate the impact of historic scenarios and for sets of plausible landslide events generated using the landslide susceptibility model. Impact assessments for historic scenarios are 29 to 83 % greater than previous, including £1.2 million of indirect impacts over 15 days of disruption at the A83 Rest and Be Thankful landslide October 2007. The model results indicate that the average impact of landslides is £64 k per day of disruption, and up to £130 k per day on the most critical road segments in Scotland. In addition to identifying critical road segments with both high impact and high susceptibility to landslides, the study indicates that the impact of landslides is concentrated away from urban centres to the central and north-west regions of Scotland that are heavily reliant on road and haulage-based industries such as seasonal tourism, agriculture and craft distilling. The third research element is the development of landslide initiation thresholds using weather radar data. The thresholds classify the rainfall conditions that are most commonly associated with landslide occurrence in Scotland, improving knowledge of the physical initiation processes and their likelihood. The thresholds are developed using a novel optimal-point threshold selection technique, high resolution radar and new rain variables that provide spatio-temporally normalised thresholds. The thresholds highlight the role of the 12-day antecedent hydrological condition of soils as a precursory factor in controlling the rain conditions that trigger landslides. The new results also support the observation that landslides occur more frequently in the UK during the early autumn and winter seasons when sequences or clustering of multiple cyclonic-storm systems is common in periods lasting 5 to 15 days. Fourth, the three previous elements are combined to evaluate the landslide hazard of the strategic road segments and a prototype risk assessment model is produced - a catastrophe model. The catastrophe model calculates the annual average loss and aggregated exceedance probability of losses due to the indirect impact of landslides in Scotland. Beyond application to cost-benefit analyses for landslide mitigation efforts, the catastrophe model framework is applicable to the study of other natural hazards (e.g. flooding), combinations of hazards, and other infrastructure networks

The occurrence, impacts and dynamics of debris flows in Brazil

Among the landslide types, debris flows represent a greater hazard to society due to their high destruction potential. In Brazil, debris-flow studies are still incipient when compared to other hydrogeomorphic processes and a good understanding of their dynamics is fundamental to supporting hazard and risk assessment studies. In particular, determining the spatialization of events and the extent of the impacts that the phenomenon represents in the country is crucial to supporting targeted and more in-depth studies. In this context, the main objectives of this thesis are to assess the societal impact of debris flows in Brazil and to propose a methodology that aims at reducing the potential damage that future events can cause in susceptible regions. A detailed post-event characterization of a debris-flow event is also conducted, as it is a fundamental step to understanding the phenomenon’s dynamics and can further support the proposal of the hazard assessment methodology. To determine the societal impact of debris flows, a catalogue of events that have caused fatalities and/or economic losses between 1920 and 2021 was created, which supported the debris-flow Mortality Rate (MR) calculation and the application of the so-called F-N Curves (Frequency of events vs. Number of Fatalities). In total, 45 debris-flow events were documented in the considered period, having caused more than 5,773 fatalities and 5.4 billion USD in economic losses. The city of Cubatão (state of São Paulo) shows the highest number of recorded events in the considered period (9), consolidating the status as the most debris-flow prone region in the country. A multi-step hazard assessment is, then, proposed using Cubatão as the test-site, based on the combination of Logistic Regression (LR) analysis, numerical simulation and rainfall back-analysis. The LR results highlight that rainfall is the main influencing factor in debris-flow initiation in the region and indicate the catchments more susceptible to the phenomenon. The simulation results, performed in the catchments indicated by the LR, show that the average runout distance in the region is 470 m, with an average peak flow height of 5 m and a peak velocity of 23 m s-1, according to the calibration based on two past debris-flow events. These results are comparable to the debris-flow event of February 2017 that occurred in the Pedra Branca catchment (Guaratuba, state of Paraná), in which a detailed post-event geomorphological characterization was conducted to estimate the event’s magnitude. The Guaratuba event was of a large-sized stony debris flow, with a total magnitude of 120,195 m3, a peak flow heigh of 7 m and a peak velocity of 26.5 m s-1. Debris-flow events both in Cubatão and Guaratuba are generally triggered by short duration (200 mm) precipitation, with return periods that vary from 3 to 15 years. Five levels of hazard (very low to very high) are, then, proposed in our hazard assessment method, based mainly on the 48-h accumulated rainfall, flow properties (height, velocity) and the spatial analysis of the elements (infrastructures, houses, etc.) at hazard. In Cubatão, industrial and residential areas in the projected debris-flow route generally exhibit the highest overall hazard levels, as many were developed in the depositional area of the phenomenon and near fluvial courses, where associated floods and flash floods may occur. As pointed out by recent studies, an increase in the frequency of extreme precipitation events is projected in the Serra do Mar region and when the general short return period of the debris-flow triggering rainfall is considered (105 m3) events are likely to occur in the next decade in the portions of the mountain range located in the states of São Paulo and Paraná. This thesis, therefore, is a contribution to better understanding the dynamics of debris flows in Brazil and is a step towards the prevention of future disasters.Unter den Rutschungsarten stellen Murgänge aufgrund ihres hohen Zerstörungspotentials eine größere Gefahr für die Gesellschaft dar. In Brasilien sind Murgangstudien im Vergleich zu anderen hydrogeomorphen Prozessen noch am Anfang und ein gutes Verständnis ihrer Dynamik ist essentiell für die Erstellung von Gefahren- und Risikobewertungsstudien. Insbesondere ist die Bestimmung des Ausmaßes der Auswirkungen, die das Phänomen in einer Region oder einem Land darstellt, von wesentlicher Bedeutungfür gezielte und eingehendere Studien. In diesem Zusammenhang besteht das Hauptziel dieser Arbeit darin, die gesellschaftlichen Auswirkungen von Murgängen in Brasilien zu bewerten und eine Methodik vorzuschlagen, die darauf abzielt, den potenziellen Schaden zu verringern, den zukünftige Ereignisse in anfälligen Regionen verursachen können. Eine detaillierte Nachuntersuchung eines Murgangereignisses wird ebenfalls durchgeführt, da dies ein grundlegender Schritt zum Verständnis der Dynamik des Phänomens ist und den Vorschlag der Gefahrenbewertungsmethodik weiter unterstützen kann. Um die gesellschaftlichen Auswirkungen von Murgängen zu bestimmen, wurde ein Katalog von Ereignissen erstellt, die zwischen 1920 und 2021 Todesopfer und/oder wirtschaftliche Schäden verursacht haben, was die Berechnung der Murgangmortalitätsrate (MR) und die Anwendung der sogenannten F-N unterstützten Kurven (Häufigkeit von Ereignissen vs. Anzahl Todesfälle) ermöglicht. Insgesamt wurden im betrachteten Zeitraum 45 Murgangereignisse dokumentiert, die mehr als 5.773 Todesopfer und 5,4 Milliarden US-Dollar an wirtschaftlichen Schäden verursachten. Die Stadt Cubatão (Bundesstaat São Paulo) weist die meisten Ereignisse auf und festigt damit ihren Status als die am stärksten von Murgängen bedrohte Region des Landes. Daher wird eine mehrstufige Gefährdungsbeurteilung vorgeschlagen und am Beispiel von Cubatão getestet, basierend auf einer Kombination von logistischer Regressionsanalyse (LR), numerischer Simulation und Niederschlagsrückanalyse. Die LR-Ergebnisse verdeutlichen, dass Niederschlag der Haupteinflussfaktor bei der Entstehung von Murgängen in der Region ist und zeigen die Einzugsgebiete, die für das Phänomen in der Region anfälliger sind. Die Simulationsergebnisse von zwei Murgangereignissen, die in diesen Einzugsgebieten durchgeführt wurden, zeigen, dass die durchschnittliche Auslaufstrecke in der Region 470 m beträgt, mit einer durchschnittlichen Fließhöhe von 5 m und einer Spitzengeschwindigkeit von 23 m s-1. Diese Ergebnisse sind vergleichbar mit dem Murgangereignis vom Februar 2017 im Einzugsgebiet von Pedra Branca (Guaratuba, Bundesstaat Paraná), bei dem eine detaillierte geomorphologische Charakterisierung nach dem Ereignis durchgeführt wurde, um das Ausmaß des Ereignisses abzuschätzen. Bei dem Guaratuba-Ereignis handelte es sich um einen großen steinigen Schuttstrom mit einer Gesamtgröße von 120.195 m3, einem Spitzenabfluss von 2.146,7 m3 s-1 und einer Spitzengeschwindigkeit von 26,5 m s-1. Murgangereignisse in Cubatão und Guaratuba wurden durch Niederschläge von kurzer Dauer ( 200 mm) mit Wiederkehrperioden von 3 bis 15 Jahren ausgelöst. Fünf Gefahrenstufen (sehr gering bis sehr hoch) werden dann in unserer Gefahrenbewertungsmethode vorgeschlagen, die hauptsächlich auf den Niederschlägen über 48 Stunden und Strömungseigenschaften basiert. In Cubatão weisen Industrie- und Wohngebiete in der prognostizierten Murgangroute im Allgemeinen die höchsten Gesamtgefahrenstufen auf, da diese sich überwiegend im Ablagerungsgebiet des Phänomens und in der Nähe von Flussläufen befinden, wo damit verbundene Überschwemmungen und Sturzfluten auftreten können. Wie neuere Studien zeigen, wird in der Region Serra do Mar eine Zunahme der Häufigkeit extremer Niederschlagsereignisse prognostiziert; unter Berücksichtigung der allgemein kurzen Wiederkehrperiode ( 105 m3) im nächsten Jahrzehnt in Teilen der Bergkette in den Bundesstaaten São Paulo und Paraná auftreten. Diese Arbeit trägt daher zum besseren Verständnis der Dynamik von Murgängen in Brasilien bei und ist ein Schritt zur Vermeidung zukünftiger Katastrophen.Entre os tipos de movimentos de massa, os fluxos de detritos representam um risco maior à sociedade devido ao seu alto potencial de destruição. No Brasil, os estudos de fluxos de detritos ainda são incipientes quando comparados a outros processos hidrogeomorfológicos e uma melhor compreensão da sua dinâmica é fundamental para subsidiar estudos de avaliação de perigos e riscos. A estimativa da extensão dos impactos que o fenômeno representa no país é, particularmente, fundamental para subsidiar estudos direcionados e mais aprofundados. Nesse contexto, os principais objetivos desta tese são de espacializar os eventos de fluxos de detritos e avaliar o impacto socioeconômico do fenômeno no Brasil, além de propor uma metodologia que tem como objetivo reduzir os danos potenciais que eventos futuros podem causar nas regiões mais suscetíveis. A caracterização detalhada pós-evento de um fluxo de detritos também é conduzida, uma vez que é um passo fundamental na compreensão da dinâmica do fenômeno e dá suporte à proposta de metodologia de avaliação de perigo. Para determinar o impacto socioeconômico dos fluxos de detritos, foi criado um banco de dados dos eventos que causaram fatalidades e/ou perdas econômicas entre 1920 e 2021, que serviu de base para o cálculo da Taxa de Mortalidade (TM) e a aplicação de Curvas F-N (Frequência de eventos vs. Número de Fatalidades). No total, 45 eventos de fluxo de detritos foram documentados no período considerado, causando mais de 5.773 mortes e US$ 5,4 bilhões em perdas econômicas. A cidade de Cubatão (SP) apresenta o maior número de eventos, consolidando-se como a região mais propensa a fluxos de detritos no país. Consequentemente, a proposta de uma metodologia de avaliação de perigo a fluxos de detritos em várias etapas é feita utilizando Cubatão como área piloto, que tem como base a combinação de análise de Regressão Logística (LR), simulação numérica e retro análise de eventos de chuva. Os resultados da LR destacam que a chuva é o principal fator de influência no início do fluxo de detritos na região, além de também indicarem as bacias mais suscetíveis ao fenômeno no local de estudo. Os resultados da simulação de fluxos de detritos nas bacias indicadas pelo LR mostram que a distância média de runout na região é de 470 m, com altura média do pico do fluxo de 5 m e velocidade de pico de 23 m s-1. Esses resultados são comparáveis ao evento de fluxo de detritos de fevereiro de 2017 que ocorreu na bacia hidrográfica de Pedra Branca (Guaratuba, estado do Paraná), no qual uma caracterização geomorfológica pós-evento detalhada foi realizada com o objetivo de estimar a magnitude do evento. O evento de Guaratuba foi um fluxo de detritos “rochoso” (stony debris flow) de grande porte, com magnitude total de 120.195 m3, altura do pico de vazão de 7 m e pico de velocidade de 26,5 m s-1. Os eventos de fluxo de detritos em Cubatão e Guaratuba são, de uma forma geral, desencadeados por precipitação de curta duração (200 mm), com períodos de retorno que variam de 3 a 15 anos. Cinco níveis de risco (muito baixo a muito alto) foram, então, propostos em nosso método de avaliação de perigo, baseado principalmente na chuva acumulada em 48 horas, propriedades cinemáticas do fluxo (altura de vazão, velocidade) e nos elementos no raio de perigo (infraestruturas, casas, etc.). As áreas industriais e residenciais na rota estimada de fluxo de detritos geralmente exibem os mais altos níveis de perigo geral na área piloto, uma vez que se desenvolveram na área de deposição do fenômeno e perto de cursos fluviais, onde podem ocorrer inundações e enxurradas associadas. Conforme apontado por estudos recentes, projeta-se um aumento na frequência de eventos extremos de precipitação na região da Serra do Mar e, quando se considera o curto período geral de retorno das chuvas desencadeadoras do fenômeno ( 105 m3) podem ocorrer na próxima década nas áreas consideradas nesta tese, localizadas na região da Serra do Mar paulista e paranaense. Esta tese, portanto, contribui para a melhor compreensão da dinâmica dos fluxos de detritos no Brasil e para a prevenção de futuros desastres