Drought is an increasingly severe issue in Italy, exacerbated by climate change and regional variability. Romano et al. (2022) provide evidence of an increase in drought events during the last 20 years, with a rise in extreme events such as heat waves and intense droughts in central Italy.  

Traditional reactive approaches to drought management have led to delays and economic losses, particularly in agriculture and hydroelectric production. Existing policies, which rely on historical precipitation patterns and reactive interventions, have proven insufficient to deal with the increasing unpredictability of drought events. See, e.g., Mishra and Singh (2011) and Fung et al. (2017) for extensive reviews. 

While regional and national water management regulations are currently in place, they lack sufficient integration of predictive modeling and coordinated early warning systems. Academic research has made significant strides in developing statistical models for drought forecasting, from the early empirical studies of Hayes et al. (1999) and Cancelliere et al. (2007) to the more recent work of Modarres and Ouarda (2014). 

However, the implementation of these models into policy remains limited.  The suggested contribution aims to bridge the existing gap by introducing a scientifically grounded framework to stimulate proactive drought risk management. Our research highlights the importance of a multivariate modeling approach to accurately assess regional drought trends and improve decision-making.