Understanding the spatial patterns of major geo-hydrological disasters in Italy using the CatBoost algorithm

We investigate 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. A total of 62 potential predisposing factors were considered, covering four 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. To better understand the influence of the selected variables, we used Partial Dependence Plots, finding very complex 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. 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; highlighting a generalized oversight on the consequences of urbanization in fragile areas, and an oversight on the secondary impacts that urbanization can cause downstream.