1,2,3,4,5,5,3- 1Department of Civil Engineering, University of Peloponnese, Patras, Greece
- 2Department of Civil Engineering, University of Patras, Greece
- 3Department of Civil and Environmental Engineering and Architecture, University of Cagliari, Cagliari, Italy
- 4Department of Engineering, University of Palermo, Palermo, Italy
- 5Department of Agricultural Sciences, University of Naples Federico II, Portici, Napoli, Italy
Accurate and robust estimation of soil loss is essential in Mediterranean basins, where sediment transfer rates exhibit pronounced seasonal aspects driven by high-intensity storm events. While the Revised Universal Soil Loss Equation (RUSLE) is the most widely used tool for assessing soil loss, its accuracy is highly dependent on the rainfall erosivity (R-factor). This study evaluates the effect of different R-factor quantification approaches on soil loss estimates within the Tirso River basin, Sardinia’s largest basin (> 3000 km²), which provides water resources for agriculture, hydropower, and domestic supply.
We applied the RUSLE method within a geographic information system (GIS) framework. The key factors for soil erodibility (K), topography (LS), land cover-management (C), and conservation practices (P) were derived from established sources, including the European Soil Data Center, a high-resolution Copernicus DEM, the Copernicus Global Land Service, and local authorities. To estimate the R-factor, we used high-resolution (10-minute resolution) precipitation data from more than 40 rainfall gauges, applying two distinct storm identification approaches: Renard et al. (1997) and the recently developed Serafeim et al. (2025). The soil loss estimates obtained from these high-resolution methods were then compared against results derived from a suite of widely applied empirical erosivity models calibrated in Mediterranean regions. This comparative analysis reveals how relying on generalized erosivity equations can distort soil erosion assessments at the basin level.
Keywords
Soil erosion; RUSLE; rainfall erosivity uncertainty; high-resolution precipitation; sediment yield; watershed management
References
Renard, K.G., Foster, G.R., Weesies, G.A., McCool, D.K., Yoder, D.C., 1997. Predicting Soil Erosion by Water: A Guide to Conservation Planning With the Revised Universal Soil Loss Equation (RUSLE). USA, U.S, Department of Agriculture, Washington, DC.
Serafeim, A.V., R. Deidda, A. Langousis, et al., (2025) A Critical Review of Rainfall Erosivity Estimation Approaches: Comparative Analysis and Temporal Resolution Effects (To be submitted).
How to cite: Serafeim, A., Langousis, A., Viola, F., Pumo, D., Romano, N., Nasta, P., and Deidda, R.: Rainfall Erosivity Estimation Accuracy and Its Impact on Soil Loss Assessments: A Case Study in Southern Italy , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-246, https://doi.org/10.5194/egusphere-egu26-246, 2026.
