Rainfall erosivity in Europe

• Published in: The Science of the total environment Vol. 511; pp. 801 - 814
• Main Authors: Panagos, Panos, Ballabio, Cristiano, Borrelli, Pasquale, Meusburger, Katrin, Klik, Andreas, Rousseva, Svetla, Tadić, Melita Perčec, Michaelides, Silas, Hrabalíková, Michaela, Olsen, Preben, Aalto, Juha, Lakatos, Mónika, Rymszewicz, Anna, Dumitrescu, Alexandru, Beguería, Santiago, Alewell, Christine
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 01.04.2015
• Subjects: Density; Erosivity density; Mathematical models; Modelling; Precipitation; R-factor; Rainfall; Rainfall intensity; Rainstorm; Regression; RUSLE; Soil erosion; Stations; Temporal resolution; Time series; MED; Switzerland; Europe, Mediterranean Region; RUSLE; Precipitation; Soil erosion; R-factor; Rainfall intensity; Erosivity density; Modelling; Rainstorm
• ISSN: 0048-9697; 1879-1026
• DOI: 10.1016/j.scitotenv.2015.01.008

Rainfall is one the main drivers of soil erosion. The erosive force of rainfall is expressed as rainfall erosivity. Rainfall erosivity considers the rainfall amount and intensity, and is most commonly expressed as the R-factor in the USLE model and its revised version, RUSLE. At national and continental levels, the scarce availability of data obliges soil erosion modellers to estimate this factor based on rainfall data with only low temporal resolution (daily, monthly, annual averages). The purpose of this study is to assess rainfall erosivity in Europe in the form of the RUSLE R-factor, based on the best available datasets. Data have been collected from 1541 precipitation stations in all European Union (EU) Member States and Switzerland, with temporal resolutions of 5 to 60min. The R-factor values calculated from precipitation data of different temporal resolutions were normalised to R-factor values with temporal resolutions of 30min using linear regression functions. Precipitation time series ranged from a minimum of 5years to a maximum of 40years. The average time series per precipitation station is around 17.1years, the most datasets including the first decade of the 21st century. Gaussian Process Regression (GPR) has been used to interpolate the R-factor station values to a European rainfall erosivity map at 1km resolution. The covariates used for the R-factor interpolation were climatic data (total precipitation, seasonal precipitation, precipitation of driest/wettest months, average temperature), elevation and latitude/longitude. The mean R-factor for the EU plus Switzerland is 722MJmmha−1h−1yr−1, with the highest values (>1000MJmmha−1h−1yr−1) in the Mediterranean and alpine regions and the lowest (<500MJmmha−1h−1yr−1) in the Nordic countries. The erosivity density (erosivity normalised to annual precipitation amounts) was also the highest in Mediterranean regions which implies high risk for erosive events and floods. •Rainfall erosivity in Europe & Switzerland is estimated to 722MJmmha−1h−1yr−1.•Rainfall Erosivity Database at European Scale (REDES) includes 1541 stations.•The highest R-factor is in Mediterranean & Alpine regions and lowest in Scandinavia.•The erosivity density shows high variability of the R-factor per precipitation unit.•High resolution (1km grid cell) dataset of R-factor is available for modelling.