Investigating the patterns of major geo-hydrological disasters inItaly

This is apreliminary study to better refine Landslide Early Warning Systems effectiveness about very severe events. When issuing an alert at the maximum level possible, missed alarms may result in casualties, increased damages and delayed response, but also false alarms may have consequences that cannot be ovelooked (including economic costs of countermeasures activated in vain, suspended services, and a generalized loss of trust in the system, which undermines the effectiveness of the future warnings). 

We therefore focus on the spatial patterns of major geo-hydrological disasters across Italy (for which national-level emergencies were issued), using an innovative target variable (Months in Emergency State - MES), which captures both the recurrence of disasters and the persistence of their impacts.

As explanatory variables, we initially consider 62 potential predisposing factors from different fields: environmental, territorial planning, soil sealing, and
socio-economic. A three-step feature selection process based on Pearson correlation, multicollinearity analysis, and ReliefF algorithm, was applied to reduce redundancy and identify the most relevant predictors (18), which were used in a CatBoost regression model.
Results highlight that combining parameters from different fields significantly improves model performance. Surprisingly, anthropogenic factors, such as territorial planning and socio-economic indicators, had a greater influence than physical characteristics in driving the recurrence of disasters and the persistence of their impacts. 
A further analysis on the results (by means of Partial Dependence Plots) highlighted very complex and somehow counterintuitive relationships.

The most important driver is the amount of soil sealing in areas classified as “medium hazard” for landslides or floods. This factor is directly and sharply related to MES (more than high-hazard areas), suggesting a need to revise hazard classifications or existing planning regulations. Gross Domestic Product (GDP - a proxy for wealth and productivity) ranks second, showing a mixed effect: while wealthier areas face higher exposure, they also show
stronger resilience. TWI, a hydrological indicator, shows that disasters are more linked to minor watercourses than to large rivers, advising to reconsider the mitigation priorities.

This study provides new insights on hydro-geological disasters and the complex non-linear relationships between physical features, land planning and socioeconomic characteristics. The consequences of urbanization in fragile areas is clearly overlooked and we conclude that it should be better addresses in modern territorial landslide early warning systems. This study has tested and identified some prominent variables that are being intergated into prototypal warning systems under development in the framework of ongoing research programs.