A drought risk management system for early drought alert and proactive actions in large semi-arid areas

Water supply systems risk collapsing during droughts, which can affect millions of people. To mitigate these risks, we developed a proactive drought management system that integrates climate, hydrological variables, and mathematical modeling. The proposed Integrated Information and Early Warning System for Drought (IIEWSD) includes three main components: monitoring, prediction, and action, which trigger short- and long-term mitigating actions. By analyzing historical and forecasted time series on precipitation, flow, and water volume, the IIEWSD provides a notion of the tendency to drought worsening. The prediction component uses dynamic and statistical methods and artificial neural networks to monitor and predict the drought status of each water system, allowing the estimation of transition probabilities and the anticipation of actions. With predicted information, decision-makers can anticipate actions before the worsening of the drought state. A risk aversion planning matrix was proposed to help decision-makers trigger mitigation actions and responses, avoiding regret in anticipation of actions. This matrix restricts the use of forecasted information to intensify mitigation and response actions while using monitored information to reduce those actions. The IIEWSD was applied to the urban supply system of Fortaleza, Brazil, a 4.1 million metropolitan region whose main water resources are in the semi-arid region. The results revealed that the system effectively estimated the probabilities of future drought states. Our approach enhances proactive drought planning and management by integrating the assessment of current and future drought states.