Panagos, P.a, Borrelli, P.b, Matthews, F.a, Liakos, L.a, Bezak, N.c, Diodato, N.d, Ballabio, C.a, 2022. Global rainfall erosivity projections for 2050 and 2070. Journal of Hydrology 610, 127865. https://doi.org/10.1016/j.jhydrol.2022.127865
aEuropean Commission, Joint Research Centre (JRC), Ispra, Italy
bDepartment of Earth and Environmental Sciences, University of Pavia, 27100 Pavia, Italy
cUniversity of Ljubljana, Faculty of Civil and Geodetic Engineering, Ljubljana, Slovenia
dMet European Research Observatory – International Affiliates Program of the University Corporation for Atmospheric Research, Benevento, Italy
The erosive force of rainfall (rainfall erosivity) is a major driver of soil, nutrient losses worldwide and an important input for soil erosion assessments models. Here, we present a comprehensive set of future erosivity projections at a 30 arc-second (∼1 km2) spatial scale using 19 downscaled General Circulation Models (GCMs) simulating three Representative Concentration Pathways (RCPs) for the periods 2041–2060 and 2061–2080. The future rainfall erosivity projections were obtained based on a Gaussian Process Regression (GPR) approach relating rainfall depth to rainfall erosivity through a series of (bio)climatic covariates. Compared to the 2010 Global Rainfall erosivity baseline, we estimate a potential average increase in global rainfall erosivity between 26.2 and 28.8% for 2050 and 27–34.3% for 2070. Therefore, climate change and the consequential increase in rainfall erosivity is the main driver of the projected + 30–66% increase in soil erosion rates by 2070.
Our results were successfully compared with 20 regional studies addressing the rainfall erosivity projections. We release the whole dataset of future rainfall erosivity projections composed of 102 simulation scenarios, with the aim to support further research activities on soil erosion, soil conservation and climate change communities. We expect these datasets to address the needs of both the Earth system modeling community and policy makers. In addition, we introduce a modeling approach to estimate future erosivity and make further assessments at global and continental scales.