Abstract
The greatest obstacle to soil erosion modelling at larger spatial scales is the lack of data on soil characteristics. One key parameter for modelling soil erosion is the soil erodibility, expressed as the K-factor in the widely used soil erosion model, the Universal Soil Loss Equation (USLE) and its revised version (RUSLE). The K-factor, which expresses the susceptibility of a soil to erode, is related to soil properties such as organic matter content, soil texture, soil structure and permeability. With the Land Use/Cover Area frame Survey (LUCAS) soil survey in 2009 a pan-European soil dataset is available for the first time, consisting of around 20,000 points across 25 Member States of the European Union. The aim of this study is the generation of a harmonised high-resolution soil erodibility map (with a grid cell size of 500m) for the 25 EU Member States. Soil erodibility was calculated for the LUCAS survey points using the nomograph of Wischmeier and Smith (1978). A Cubist regression model was applied to correlate spatial data such as latitude, longitude, remotely sensed and terrain features in order to develop a high-resolution soil erodibility map. The mean K-factor for Europe was estimated at 0.032thahha−1MJ−1mm−1 with a standard deviation of 0.009thahha−1MJ−1mm−1. The yielded soil erodibility dataset compared well with the published local and regional soil erodibility data. However, the incorporation of the protective effect of surface stone cover, which is usually not considered for the soil erodibility calculations, resulted in an average 15% decrease of the K-factor. The exclusion of this effect in K-factor calculations is likely to result in an overestimation of soil erosion, particularly for the Mediterranean countries, where highest percentages of surface stone cover were observed.
Highlights
Soil erosion is the most widespread form of soil degradation worldwide (Bridges and Oldeman, 1999)
The empirical Revised Universal Soil Loss Equation (RUSLE) (Renard et al, 1997), which predicts the average annual soil loss resulting from raindrop splash and runoff from field slopes, is still most frequently used
The mean K-factor for the 25 Member States was calculated as 0.032 t ha h ha−1 MJ−1 mm−1 with a standard deviation of 0.009 t ha h ha−1 MJ−1 mm−1 (Fig. 2)
Summary
Soil erosion is the most widespread form of soil degradation worldwide (Bridges and Oldeman, 1999). Since soil erosion is difficult to measure at large scales, soil erosion models are a crucial estimation tool at regional, national and European levels. The Kfactor is a lumped parameter that represents an integrated annual value of the soil profile reaction to the process of soil detachment and transport by raindrops and surface flow (Renard et al, 1997). As such soil erodibility is best estimated by carrying out direct measurements on field plots (Kinnell, 2010). Since field measurements are expensive and often not transferable in space, researchers investigated the relation between “classical” soil properties and soil erodibility
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