The social and economic impacts caused by floods in urban areas are diverse and increase as the land becomes gradually impervious. Due to the increasing urbanization of cities, it is necessary to implement a better planning process and optimize the urban spaces management and occupation. Thus, the government needs to gather reliable and useful data for the decision-making process. Therefore, the GIS plays an important role among urban planning instruments. Given the current situation in Campina Grande County, Paraiba State, Brazil - an area continually facing disturbances caused by occasional and concentrated rainfalls - the current study aims to map the areas seen as the most susceptible to floods, by using a MCDA GIS-based model (Multi-Criteria Decision Analysis). There are five quantitative criteria considered in the analysis: slope, altitude, roads with drainage infrastructure, distance from water bodies and land use. It is a pixel by pixel analysis based on predetermined assumptions. Fuzzy functions were developed and overlay operations were performed. The results were consistent with historical records and with previous studies about the county, thus adding reliability to the model, which can be considered a potential management instrument for the case study area, as well as for cities facing similar issues.

Since hazards act upon vulnerability and exposure to become disasters, the understanding of societal challenges is key for disaster risk reduction. This condition is even more critical when more than one hazard is in place. Taking the case of flooding and water shortage, this study is built upon the premise that disasters are a social phenomenon; therefore, it is essential to comprehend the social context in which they occur. Particularly, this study aims to evaluate the similarities and differences in risk perception and the coping capacity of residents in the multiple-hazard context. For this, a place-based citizen science approach was developed in this study in Campina Grande, a semiarid region of Brazil, with the collaboration of 199 participants. Risk perception and coping capacity were analysed through the citizens’ participation, while combining subjective and objective methods. The results indicate that even though residents have experienced severe flooding and water shortages in the past, they still have low coping capacity. The findings highlight the need to combine a triad of societal challenges, namely information, trust, and incentives, to improve coping capacity in the future and increase resilience. This study underlines the need to understand multiple hazards according to social, spatial, and temporal scales in a socio-spatial perspective.

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The northeastern Brazilian region has been vulnerable to hydrometeorological extremes, especially droughts, for centuries. A combination of natural climate variability (most of the area is semi-arid) and water governance problems increases extreme events’ impacts, especially in urban areas. Spatial analysis and visualisation of possible land-use change (LUC) zones and trends (urban growth vectors) can be useful for planning actions or decision-making policies for sustainable development. The Global Human Settlement Layer (GHSL) produces global spatial information, evidence-based analytics, and knowledge describing Earth’s human presence. In this work, the GHSL built-up grids for selected Brazilian cities were used to generate urban models using GIS (geographic information system) technologies and cellular automata for spatial pattern simulations of urban growth. In this work, six Brazilian cities were selected to generate urban models using GIS technologies and cellular automata for spatial pattern simulations of urban sprawl. The main goal was to provide predictive scenarios for water management (including simulations) and urban planning in a region highly susceptible to extreme hazards, such as floods and droughts. The northeastern Brazilian cities’ analysis raises more significant challenges because of the lack of land-use change field data. Findings and conclusions show the potential of dynamic modelling to predict scenarios and support water sensitive urban planning, increasing cities’ coping capacity for extreme hazards.

In developing countries, the urbanisation process occurs with empirical urban management, a high increase of impermeable areas, and a lack of connection between water resource management and planning. In Brazil, concentrated rainfall and ineffective urban drainage systems add to this context and may impact the population with flash floods. Although sustainable drainage systems (SuDS) are widely used for flood mitigation, it is still not very well known how those strategies behave in semi-arid regions, where most of the time the weather is very dry. In Brazil, flood mitigation still mostly involves structural measures such as larger pipes or channels, with limited guidance for SuDS use due to the great resistance to change by citizens and managers. This study sought to analyse the efficacy of SuDS in Campina Grande, a semi-arid region of Brazil. A land-use and legislation-based methodology was developed with physical, climate, hydrological and governance data for three catchments and 312 sub-catchments in 30 applications and simulations. Simulations suggest that these strategies would be appropriate for semi-arid regions, with reductions in the flooded area, flooding volume, and impacts. This study is of relevance for cities with a similar climate to reach a sustainable level of urban drainage services, supporting the integration of urban planning and water resources management.