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Soil Erosion on grassland – the Swiss soil erosion risk map of grasslands as prototype for European mountain areas

  • October 2018
  • Conference: 10. Marktredwitzer Bodenschutztage
  • At: Marktredwitz, DE
Authors:
Simon Scheper at Dr. Simon Scheper - Research | Consulting | Teaching
Simon Scheper
  • Dr. Simon Scheper - Research | Consulting | Teaching
K. Meusburger at Swiss Federal Institute for Forest, Snow and Landscape Research - WSL
K. Meusburger
  • Swiss Federal Institute for Forest, Snow and Landscape Research - WSL
Panos Panagos at European Commission
Panos Panagos
Cristiano Ballabio at European Commission
Cristiano Ballabio
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Abstract

The monetary loss for agriculture in Europe due to soil erosion is about 1.25 billion Euros per year (Panagos et al., 2018). The costs of soil erosion for the Swiss arable land are approximately estimated to be 45.5 million Euro (Ledermann 2012) and will be even higher if Swiss grasslands are included. According to the new national grassland map of Switzerland, grasslands have a proportion of 28% of the total territorial area. An erosion risk map of grassland was developed to quantify the soil loss rates of Swiss grasslands. The erosion factors of the Revised Universal Soil Loss Equation (RUSLE; R rainfall erosivity, K soil erodibility, C cover and management, LS slope length and steepness, and P protection measures) are adapted to the specific characteristics of Swiss grassland and mountains. The modeling assesses the spatial and temporal dynamics of soil erosion simultaneously as the factors R and C are highly dynamic within a year due to the variability of rainfall and phenology. The rainfall erosivity is modeled with regression-kriging of 10 minutes precipitation data at 87 automated gauging stations and high spatial resolution covariates. Analyses of 199 topsoil samples serve as input for a spatial cubist regression of soil erodibility. Spatial-temporal patterns of soil cover could be derived by the high resolution (0.25 m) Swiss Orthophoto Swissimage and a time series of FCover (fraction of green vegetation cover). The LS-factor was modified for steep slopes. Risky periods of the year and spatial risk zones with relatively high rainfall erosivity and low soil coverage (e.g., after grass cutting and pasturing) can be identified due to the dynamic mapping. The dynamic modeling enables the targeted and cost-efficient introduction of soil protection measures. The map can be seen as a prototype of soil erosion risk modeling of grassland in the European mountain areas due to the high resolution database of Switzerland.
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10. Marktredwitzer Bodentage, Marktredwitz, 2018
Soil Erosion on grassland – the Swiss soil erosion risk map of grasslands as
prototype for European mountain areas
Simon Schmidt1, Katrin Meusburger1,2, Panos Panagos3, Cristiano Ballabio3 &
Christine Alewell1
The monetary loss for agriculture in Europe due to soil erosion is about 1.25 billion
Euros per year (Panagos et al., 2018). The costs of soil erosion for the Swiss arable
land are approximately estimated to be 45.5 million Euro (Ledermann 2012) and will
be even higher if Swiss grasslands are included. According to the new national
grassland map of Switzerland, grasslands have a proportion of 28% of the total
territorial area.
An erosion risk map of grassland was developed to quantify the soil loss rates of
Swiss grasslands. The erosion factors of the Revised Universal Soil Loss Equation
(RUSLE; R rainfall erosivity, K soil erodibility, C cover and management, LS slope
length and steepness, and P protection measures) are adapted to the specific
characteristics of Swiss grassland and mountains. The modeling assesses the spatial
and temporal dynamics of soil erosion simultaneously as the factors R and C are
highly dynamic within a year due to the variability of rainfall and phenology.
The rainfall erosivity is modeled with regression-kriging of 10 minutes precipitation
data at 87 automated gauging stations and high spatial resolution covariates.
Analyses of 199 topsoil samples serve as input for a spatial cubist regression of soil
erodibility. Spatial-temporal patterns of soil cover could be derived by the high
resolution (0.25 m) Swiss Orthophoto Swissimage and a time series of FCover
(fraction of green vegetation cover). The LS-factor was modified for steep slopes.
Risky periods of the year and spatial risk zones with relatively high rainfall erosivity
and low soil coverage (e.g., after grass cutting and pasturing) can be identified due to
the dynamic mapping. The dynamic modeling enables the targeted and cost-efficient
introduction of soil protection measures.
The map can be seen as a prototype of soil erosion risk modeling of grassland in the
European mountain areas due to the high resolution database of Switzerland.
Simon Schmidt1 (simon@simonschmidt.de)
Katrin Meusburger1,2 (katrin.meusburger@wsl.ch)
Panos Panagos3 (panos.panagos@ec.europa.eu)
Cristiano Ballabio3 (cristiano.ballabio@ec.europa.eu)
Christine Alewell1 (christine.alewell@unibas.ch)
10. Marktredwitzer Bodentage, Marktredwitz, 2018
1Environmental Geosciences, University Basel, Bernoullistrasse 30, 4056 Basel,
Switzerland
2Swiss Federal Institute for Forest, Snow and Landscape WSL, Zürcherstrasse 111,
8903 Birmensdorf, Switzerland
3European Commission, Joint Research Centre, Sustainable Resources Directorate,
Via E. Fermi 2749, I-21027 Ispra, Italy
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