Abstract. The measurement and mapping of transportation network vulnerability constitute subjects of global interest. During a flood, some elements of a transportation network can be reached, causing damages directly (to people, vehicles and roads/streets) and indirect damages (services) with great economic impacts. The Complex Networks approach may offer a valuable perspective considering one type of vulnerability especially related to Disaster Risk Reduction on critical infrastructures: the topological vulnerability. The topological vulnerability index associated to an element in a graph is defined as the damage (variation) on the network’s average efficiency due to the removal of that element. We have performed a topological vulnerability analysis to the highways in the state of Santa Catarina (Brazil), and produced a risk map considering that index and the flood susceptible areas. Our results can represent an important tool for stakeholders from the transportation sector.

The measurement and mapping of transportation network vulnerability to natural hazards constitute subjects of global interest for a sustainable development agenda and as means of adaptation to climate change. During a flood, some elements of a transportation network can be affected, causing the loss of lives. Furthermore, impacts include damage to vehicles, streets/roads, and other logistics services - sometimes with severe economic consequences. The Network Science approach may offer a valuable perspective considering one type of vulnerability related to network-type critical infrastructures: the topological vulnerability. The topological vulnerability index associated with an element is defined as reducing the network’s average efficiency due to removing the set of edges related to that element. In this paper, we present the results of a systematic literature overview and a case study applying the topological vulnerability index for the highways in Santa Catarina (Brazil). We produce a map considering that index and areas susceptible to urban floods and landslides. Risk knowledge, combining hazard and vulnerability, is the first pillar of an Early Warning System and represents an important tool for stakeholders of the transportation sector in a disaster risk reduction agenda.

Cities increasingly face flood risk primarily due to extensive changes of the natural land cover to built‐up areas with impervious surfaces. In urban areas, flood impacts come mainly from road interruption. This article proposes an urban flood risk map from hydrological and mobility data, considering the megacity of São Paulo, Brazil, as a case study. We estimate the flood susceptibility through the Height Above the Nearest Drainage algorithm; and the potential impact through the exposure and vulnerability components. We aggregate all variables into a regular grid and then classify the cells of each component into three classes: Moderate, High, and Very High. All components, except the flood susceptibility, have few cells in the Very High class. The flood susceptibility component reflects the presence of watercourses, and it has a strong influence on the location of those cells classified as Very High.

Since natural disasters may cause big human and material losses, the Brazilian government are specially interested in ways to avoid it. Among these ways, the use of computational technologies are specially interesting for monitoring and warning population about such disasters. At this work we present an approach, developed at the Brazilian National Center for Monitoring and Early Warning of Natural Disasters (CEMADEN), for watershed areas delimitation and characterization, based on digital images and geographical databases, using only open source tools. The proposed approach achieves consistent and useful results on operation environment, providing a significant helping for disasters management. Finally, we present some examples of delimited and characterized watersheds, in different regions of Brazil, including one in the Amazon rainforest area. The presented approach is already operational at the situation room in CEMADEN.

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A estimativa de pessoas que passam por zonas de tráfego, juntamente com informações hidrográficas, serve como base para o estudo de relações entre mobilidade e inundações. A partir de dados de origem e destino, foi desenvolvido um script baseado no Google Maps para obter os caminhos feitos em cada viagem. Para computar a quantidade de pessoas diretamente afetadas na mobilidade, foram selecionadas todas as regiões interceptadas pelos rios. O número total de pessoas indiretamente afetadas foi calculado através da análise de rotas que interceptam os rios, e, com base nesta informação, foram estimadas quantas pessoas têm sua mobilidade potencialmente afetada por inundações em cada rio. Os resultados sugerem que os rios Pavuna e Guandu Mirim devem receber atenção prioritária por tomadores de decisão para mitigar os efeitos de inundações sobre a mobilidade urbana na região metropolitana do Rio de Janeiro.

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