Back to Search
Start Over
Validation of official erosion modelling based on high-resolution radar rain data by aerial photo erosion classification
- Source :
- Earth Surface Processes and Landforms. 43:187-194
- Publication Year :
- 2017
- Publisher :
- Wiley, 2017.
-
Abstract
- The Universal Soil Loss Equation (USLE) is the most frequently applied erosion prediction model and it is also implemented as official decision-making instrument for agricultural regulations. The USLE itself was already validated by 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 x 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 x 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 parameterization 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 parameterization weaknesses but not by a failure of the model itself.
- Subjects :
- Hydrology
Erosion prediction
010504 meteorology & atmospheric sciences
Meteorology
0208 environmental biotechnology
Geography, Planning and Development
02 engineering and technology
01 natural sciences
020801 environmental engineering
law.invention
Tillage
Universal Soil Loss Equation
law
Earth and Planetary Sciences (miscellaneous)
Erosion
Environmental science
Stage (hydrology)
Radar
Scale (map)
0105 earth and related environmental sciences
Earth-Surface Processes
Interpolation
Subjects
Details
- ISSN :
- 01979337
- Volume :
- 43
- Database :
- OpenAIRE
- Journal :
- Earth Surface Processes and Landforms
- Accession number :
- edsair.doi...........4168fbdf9f25cf58088edeed447d2da8
- Full Text :
- https://doi.org/10.1002/esp.4216