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This study aimed to understand the perception of drought among farmers, in order to support decision-making in the water allocation process. This study was carried out in the Tabuleiro de Russas irrigated perimeter, in northeast Brazil, over the drought period of 2012–2018. Two analyses were conducted: (i) drought characterization, using the Standardized Precipitation Index (SPI) based on drought duration and frequency criteria; and (ii) analysis of farmers’ perceptions of drought via selection of explanatory variables using the Random Forest (RF) and the Decision Tree (DT) methods. The 2012–2018 drought period was defined as a meteorological phenomenon by local farmers; however, an SPI evaluation indicated that the drought was of a hydrological nature. According to the RF analysis, four of the nine study variables were more statistically important than the others in influencing farmers’ perception of drought: number of cultivated land plots, farmer’s age, years of experience in the agriculture sector, and education level. These results were confirmed using DT analysis. Understanding the relationship between these variables and farmers’ perception of drought could aid in the development of an adaptation strategy to water deficit scenarios. Farmers’ perception can be beneficial in reducing conflicts, adopting proactive management practices, and developing a holistic and efficient early warning drought system.

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Associating the dynamic spatial modeling based on the theory of cellular automata with remote sensing and geoprocessing technologies, this article analyzes what would be the per capita consumption behavior of Fortaleza-CE, located in the Northeast of Brazil, in 2017, had there not been a period of water scarcity between 2013 and 2017, and estimates the future urban water demand for the years 2021 and 2025. The weight of evidence method was applied to produce a transition probability map, that shows which areas will be more subject to consumption class change. For that, micro-measured water consumption data from 2009 and 2013 were used. The model was validated by the evaluation of diffuse similarity indices. A high level of similarity was found between the simulated and observed data (0.99). Future scenarios indicated an increase in water demand of 6.45% and 10.16% for 2021 and 2025, respectively, compared to 2017. The simulated annual growth rate was 1.27%. The expected results of urban water consumption for the years 2021 and 2025 are essential for local water resources management professionals and scientists, because, based on our results, these professionals will be able to outline future water resource management strategies.

Drought is widely known as a complex natural hazard, not just by its climatological features but also by human experiences and socio-economical impacts. Drought preparedness is the only way a society can mitigate effects and better cope with droughts. Here we present a methodological approach to guide the implementation of proactive drought plans, specially designed for hydrossystems and cities scales. We highlight strategies to engage local stakeholders in constructing such plans and build a participatory methodology. The preparedness drought plan methodology was developed and applied to two hydrosystems and two cities located in the Piranhas-Açu river basin, a drought-prone area of Brazilian Semi-arid. Our ndings suggest that participatory socio-technical methodologies, built only from the system operators' tacit knowledge, can achieve good results when data and resources are limited. Still, results can be enhanced by hydrologic and hydraulic modeling to assess vulnerability, scenarios and strategies. We illustrate and analyze the process by storytelling to develop a meaningful and convincing narrative that speaks to theory and practice, and we provide recommendations to facilitate this approach.

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