Data Entry: Please note that the research database will be replaced by UNIverse by the end of October 2023. Please enter your data into the system https://universe-intern.unibas.ch. Thanks
One major controlling factor of water erosion is rainfall erosivity, which is quantified as the product of total storm energy of an erosive rainfall event and a maximum 30 min intensity. Rainfall erosivity is expressed as the R-factor in erosion models like the Universal Soil Loss Equation (USLE) and its revised version (RUSLE). R-factors were modelled on a monthly scale to catch simultaneously the highly spatial as well as temporal variability. The observations of a network with 87 precipitation gauging stations with a 10 min temporal resolution and a mean observation length of 19.5 years were used to calculate long-term monthly mean R-factors. Stepwise generalized linear regression (GLM) and leave-one-out cross-validation (LOOCV) select high resolution covariates which explain the spatial and the temporal patterns of R-factors within a month. The predicted R-factors of the regression equation and the corresponding residues are combined to 12 R-factor maps. The residues itself are interpolated by ordinary-kriging (regression-kriging). As spatial covariates, a variety of precipitation indicator data has been used such as snow depths, radar and ground observations of precipitation (CombiPrecip), daily alpine precipitation (EURO4M-APGD), and monthly precipitation sums (RhiresM). Elevation and slope are derived from a digital elevation model (SwissAlti3D) as explanatory variables. The comparison of the 12 monthly rainfall erosivity maps showed highest rainfall erosivity in summer (June, July, and August). In particular, the southern Alps (Canton Ticino), the alpine area of the northern Alps and parts of the Valley region are affected by high R-factors during that period. The 4 months from June to September have a share of 62% of the total annual R-Factor of Switzerland. The identification of regions and time slots with increased erosivity enables the introduction of selective erosion control and a better knowledge about dynamics of erosion processes within a year.
