Investigating the event-based rainfall spatial variability for reliable geohazard assessment

Rainfall-induced natural hazards are widespread worldwide and pose significant threats to society and infrastructure. Reliable assessment of these hazards strongly depends on the availability and quality of rainfall information. In regions characterized by complex topography, rainfall patterns are highly heterogeneous, which complicates hazard evaluation. This is particularly evident in the mountainous areas of Campania (southern Italy), where pyroclastic soil deposits are widespread and rainfall-triggered shallow landslides and debris flows frequently occur. In such settings, the spatial variability of rainfall plays a crucial role in controlling the spatio-temporal distribution of landslides, affecting the performance of hazard assessment tools.

This study investigates the spatial variability of rainfall at the event scale in the Partenio Massif and the Sarno Mountains. The study area is characterized by coarse-grained pyroclastic soils, consisting of variable layers of volcanic ash and pumice deposited over densely fractured limestone bedrock. Rainfall records from 23 rain gauges operating between 2002 and 2024 were used to define rainfall event series. Rain events were separated using a minimum inter-event time of 24 hours with rainfall amount lower than 2 mm. The study area was subdivided into zones by grouping rain gauges that share the same probability distribution of rainfall event depth and duration, as identified through Kolmogorov-Smirnov tests.

Within each defined zone, the Pearson correlation coefficient and the spatial variability of rainfall were evaluated for all pairs of rain gauges, considering both rainfall depth and duration of events overlapping for at least one hour. Strong correlations were observed for both depth and duration among closely located rain gauges. However, both the correlation strength and the number of overlapping events progressively decreased with increasing inter-station distance. For each pair of stations, the differences in rainfall depth and duration of overlapping events at two stations were found to be normally distributed around their mean values, with a clear dependence of the standard deviation on the square root of the mean. Moreover, the standard deviation was observed to increase following a power-law relationship with inter-station distance across all zones.

The outcomes of this study provide a quantitative basis for incorporating rainfall spatial uncertainty into hydrometeorological models for rainfall-induced hazard assessment over large areas. Additionally, the results offer valuable insights for optimizing rain gauge network design, contributing to the development of more effective early warning systems.