Soil Erosion Risk Modelling in the Alps – ERKBerg as a Prototype of ERK2 for mountain zones III, IV and summering grazing zones
Project funded by the Federal Office for the Environment (FOEN) - N° N222-0350
Duration: March 2015 – March 2017
Soil Erosion on grassland is generally neglected due to its protective character of dense grass vegetation on soil loss. However, recent studies by Meusburger et al. (2010), Konz et al. (2012) and Alewell et al. (2013) show that large amounts of topsoil are mobilized also on grassland in the alpine areas.
For flat and gently sloped regions of Switzerland, a soil erosion modelling approach was already realized by the Centre for Development and Environment University Bern and Agroscope Reckenholz (ERKII) which is currently to be upgraded. To complement the ERKII-results and to create a nationwide soil erosion risk map, a risk assessment for the formally excluded mountain zones III, IV and summering grazing zones will be realized by geospatial modelling.
According to a comprehensive approach, the model is based on the Revised Universal Soil Loss Equation (RUSLE) by Wischmeier & Smith (1978). The general soil-loss-equation of RUSLE is a function of six factors:
A = R * K * L * S * C * P
whereat A is the mean long-time soil loss in t*ha-1*yr-1, R the rain erosivity factor, K the soil erodibility and the parameters L and S describe the length and slope of the relief. C deals as an index for soil cover and landuse methods, P as a variable of protection and soil conservation.
The main task of the ongoing project is the adaptation of the model parameters which aren’t generally accepted for steep slopes and grassland in alpine areas. Using rainfall data with high temporal and spatial resolution, Meusburger et al. (2012) and Nogler (2012) found out that rain erosivity (R-factor) has a reasonable seasonal variability in Switzerland. Furthermore, detailed information of soil cover could be obtained by remote sensing methods to reflect the seasonal ratios of covering. Considering the seasonal variability of R-factor as well the shift of soil cover (C-factor) will improve the model reliability significantly.
Due to the excellent database of Switzerland, the model could be used as a prototype for risk assessment in the European alpine regions.