Comparison of the Spatial Wind Erosion Patterns of Erosion Risk Mapping and Quantitative Modeling in Eastern Austria
Creators
- 1. Dr. Simon Scheper—Research|Consulting|Teaching, Eickhorst 3, 29413 Dähre, Germany
- 2. Federal Research and Training Centre for Forests, Natural Hazards and Landscape, Seckendorff-Gudent Weg 8, 1131 Vienna, Austria
- 3. Federal Agency for Water Management, Institute for Land and Water Management Research, Pollnbergstraße 1, 3252 Petzenkirchen, Austria
- 4. Department of Landscape Planning and Land Consolidation, Slovak University of Agriculture in Nitra, Hospodárska 7, 94976 Nitra, Slovakia
- 5. Department of Environment-UNESCO Chair on Eremology, Ghent University, Coupure Links 653, 9000 Ghent, Belgium
- 6. Ghent University
Description
Various large-scale risk maps show that the eastern part of Austria, in particular the Pannonian Basin, is one of the regions in Europe most vulnerable to wind erosion. However, comprehensive assessments of the severity and the extent of wind erosion risk are still lacking for this region. This study aimed to prove the results of large-scale maps by developing high-resolution maps of wind erosion risk for the target area. For this, we applied a qualitative soil erosion assessment (DIN 19706) with lower data requirements and a more data-demanding revised wind erosion equation (RWEQ) within a GIS application to evaluate the process of assessing wind erosion risk. Both models defined similar risk areas, although the assignment of severity classes differed. Most agricultural fields in the study area were classified as not at risk to wind erosion (DIN 19706), whereas the mean annual soil loss rate modeled by RWEQ was 3.7 t ha−1 yr−1. August was the month with the highest modeled soil loss (average of 0.49 t ha−1 month−1), due to a low percentage of vegetation cover and a relatively high weather factor combining wind speed and soil moisture effects. Based on the results, DIN 19706 is suitable for a general classification of wind erosion-prone areas, while RWEQ can derive additional information such as seasonal distribution and soil loss rates besides the spatial extents of wind erosion.
Open Access
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Publication Details
Journal article
Persistent Identifiers
DOI
10.3390/land10090974
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MAGID
3200121562
Funding
Financial Support
Austrian Climate and Energy fund: Austrian Climate Research Programme (ACRP) 11 — Grant: KR18AC0K14642
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References
001-716-006-025-189
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Jugder . Developing a soil erodibility map across Mongolia, Nat Hazards. 2018; 9...
Read more
Woldemariam, G., Iguala, A., Tekalign, S., and Reddy, R. (2018). Spatial Modelin...
Read more
Pimentel . Soil Erosion Threatens Food Production, Agriculture. 2013; 3 443.
Read more
Panagos . The new assessment of soil loss by water erosion in Europe, Environ. S...
Read more
Showing first 5 of 43 references.