Abstract

The rise of awareness about climate change and its possible consequences has increased the interest in the impact of meteorological stressors on  the sustainability of complex socio-economic systems. Sustainability can have  many facets, ranging from economic to political and societal issues. This work  focuses on political and humanitarian crises in fragile contexts. Specifically, it  aims at assessing the impact of droughts on conflicts and displacements in developing countries. To reach our goal, we proceeded as follows. We first provided  a theoretical model framing the problem and proposing hypotheses on the mutual  relationships among variables. Hypotheses are then tested by estimating the parameters of a multi-variate linear correlation model. Finally, we propose an operational implementation of the model to forecast crises by training a machine  learning model. Empirical tests have provided consistent and encouraging results  supporting the ability of the model to predict conflicts and displacements. We  studied the impact of droughts on both phenomena, highlighting their role as an  exacerbating factor rather than a triggering one. The value of our work lies in the conceptual framework we provided, which is flexible and reusable to account for  other stressors and impacts. Moreover, the system that we developed could be  employed to perform crisis management in a variety of real-world applications.

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