Validation of official erosion modelling based on high‐resolution radar rain data by aerial photo erosion classification |
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| Authors: | Franziska Katharina Fischer Michael Kistler Robert Brandhuber Harald Maier Melanie Treisch Karl Auerswald |
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| Institution: | 1. Technische Universit?t München, Lehrstuhl für Grünlandlehre, Freising, Germany;2. Bavarian State Research Centre for Agriculture, Freising, Germany;3. Deutscher Wetterdienst, Au?enstelle Weihenstephan, Freising, Germany |
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| Abstract: | The universal soil loss equation (USLE) is the most frequently applied erosion prediction model and it is also implemented as an official decision‐making instrument for agricultural regulations. The USLE itself has been already validated using different approaches. Additional errors, however, arise from input data and interpolation procedures that become necessary for field‐specific predictions on a national scale for administrative purposes. In this study, predicted event soil loss using the official prediction system in Bavaria (Germany) was validated by comparison with aerial photo erosion classifications of 8100 fields. Values for the USLE factors were mainly taken from the official Bavarian high‐resolution (5 × 5 m2) erosion cadastre. As series of erosion events were examined, the cover and management factor was replaced by the soil loss ratio. The event erosivity factor was calculated from high‐resolution (1 × 1 km2, 5 min), rain gauge‐adjusted radar rain data (RADOLAN). Aerial photo erosion interpretation worked sufficiently well and average erosion predictions and visual classifications correlated closely. This was also true for data broken down to individual factors and different crops. There was no reason to assume a general invalidity of the USLE and the official parametrization procedures. Event predictions mainly suffered from errors in the assumed crop stage period and tillage practices, which do not reflect interannual and farm‐specific variation. In addition, the resolution of radar data (1 km2) did not seem to be sufficient to predict short‐term erosion on individual fields given the strong spatial gradients within individual rains. The quality of the input data clearly determined prediction quality. Differences between USLE predictions and observations are most likely caused by parametrization weaknesses but not by a failure of the model itself. Copyright © 2017 John Wiley & Sons, Ltd. |
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| Keywords: | RUSLE RADOLAN erosion cadastre event soil loss orthorectified photographs |
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