Beyond Pixels: Soil Erosion Risk Mapping and Its Impact on the Implementation of Regulatory Measures by Farms

Abstract

A series of modelling scenarios were employed to determine the influence of raster resolution on soil erosion risk maps using both the Water and Tillage Erosion Model (WaTEM) and the Revised Universal Soil Loss Equation (RUSLE) in the regions of Flanders (Belgium) and Lower Austria (Austria) using field-specific data from the Integrated Administration and Control System (IACS). The impact of these maps on farms when used as areas for regulatory measures was also investigated. Three different resampling techniques were employed to assess the impact of varying data resolution on the accuracy of soil erosion risk maps. These techniques included (i) resampling input data, (ii) resampling RUSLE factors and (iii) resampling the output erosion risk map. The resampling of input data resulted in the most pronounced discrepancies in erosion values in both regions. The impact analysis, assessing the effect of data resolution and resampling techniques, was conducted with the objective of identifying fields and farms that were most affected by erosion. This was achieved by applying erosion thresholds of 11 and 2 t ha⁻¹ year⁻¹. The results indicate that raster resolution has a significant influence on model accuracy, with lower resolutions resulting in substantial deviations in erosion estimates. The analysis reveals that lower resolution data and certain resampling methods have a disproportionate impact on smaller farms, resulting in high erosion values in regions with a generally high erosion potential. The study highlights the necessity of utilising the best available data and robust modelling techniques to generate reliable soil erosion risk maps. These findings have significant policy implications, suggesting that erosion control measures and agricultural regulations should be informed by accurate, high-resolution data to ensure fair and effective soil conservation practices.