Spatial Distribution, Temporal Behaviour, and Trends of Rainfall Erosivity in Central Italy Using Coarse Data

This study examines the spatio-temporal dynamics of rainfall erosivity, R, in the Umbria region (central Italy), based on a 20-year dataset of 30 min precipitation records from 54 stations. Using the RUSLE2 framework, models of varying complexity were evaluated to estimate the R-factor: the original model (Model A), and models based solely on event rainfall depth he or daily rainfall depth hd. All the models show consistency in the spatial and temporal patterns of the R-factor: higher erosivity is observed in the southern and northwestern areas, while summer contributes the most to annual erosivity due to the high average intensity of rainfall events. Trend analyses indicate stationarity across most stations. Compared to Model A (mean R-factor: 1840 MJ mm ha−1 h−1 y−1), the models based on he underestimate the R-factor by about 15%, whereas the R-factor derived from the hd-dependent model is almost equivalent. The estimate from Model A is also approximately 20% higher than that of a previous study conducted on a more limited dataset. The most likely reason for this difference appears to be the formula used for estimating the R-factor. The study highlights the practicality of simplified models, which offer a viable alternative in contexts where high-resolution precipitation data are unavailable. It also demonstrates the benefits of denser station networks and longer observation periods, particularly in regions characterised by complex terrains.