Soil erosion by wind

This dataset consists of various elements related to soil erosion by wind: 1) Soil loss by wind erosion in European agricultural soils (2016); 1km resolution, 2) Land susceptibility to wind erosion (2014), 500m resolution, 3) Wind erosion susceptibility of European soils (2014); 500m resolutiomn, and 4) Agriculture Field Parameters data (containing averaged Field Size, Field Orientation, Field Length, Average Number of Images, Percentage of Large Fields and Length to Width Ratios) for the EU 27 Member states and Switzerland, aggregated to NUTS region.
Publisher: 
European Commission, Joint Research Centre (JRC)
Year: 
2016
Language: 

The European Commission - Joint Research Centre (JRC) provides access to results from a new series of studies on wind erosion at Pan-European scale: 

  • Soil erosion by wind in European agricultural soils: A GIS version of the Revised Wind Erosion Equation (RWEQ) was developed in JRC to model at large scale wind erosion. The model is designed to predict the daily soil loss potential by wind erosion at 1km spatial resolution.
  • Land susceptibility to wind erosion: An Index of Land Susceptibility to Wind Erosion (ILSWE) was created by combining spatiotemporal variations of the most influential wind erosion factors (i.e. climatic erosivity, soil erodibility, vegetation cover and landscape roughness). 
  • Wind erosion susceptibility of soils: The wind-erodible fraction of soil (EF) is one of the key parameters for estimating the susceptibility of soil to wind erosion. 
  • Former studies: Agriculture Field Parameters on NUTS-3 regions

Metadata for the 4 datasets:

Title: Soil loss by wind erosion in European agricultural soils (Quantitative assessment)
Description: GIS-RWEQ is  a simplified GIS-based application of the RWEQ model (ARS-USDA). It follows a spatially distributed approach based on a grid structure, running in R and Python scripts. The model scheme is designed to describe the daily soil loss potential at regional or larger scale. A complete description of the methodology and the application in Europe is described in the paper:  
Borrelli, P., Lugato, E., Montanarella, L., & Panagos, P. (2017). A New Assessment of Soil Loss Due to Wind Erosion in European Agricultural Soils Using a Quantitative Spatially Distributed Modelling Approach. Land Degradation & Development, 28: 335–344, DOI: 10.1002/ldr.2588 
Spatial coverage: 28 Member States of the European Union  
Pixel size: c.a 1Km 
Projection: ETRS89 Lambert Azimuthal Equal Area 
Temporal coverage: from January 2001 to December 2010


Title: Land susceptibility to wind erosion

Description: Wind erosion is a complex geomorphic process governed by a large number of variables. Field-scale models such as the Wind Erosion Prediction System (WEPS—Wagner, 1996) employ up to some tens of parameters to predict soil loss. A preliminary pan-European assessment of land susceptibility to wind erosion calls for a simplified and more practical approach. Therefore, a limited number of key parameters which can express the complex interactions between the variables controlling wind erosion should be considered. The ILSWE is based on the combination of the most influential parameters, i.e. climate (wind, rainfall and evaporation), soil characteristics (sand, silt, clay, CaCO3, organic matter, water-retention capacity and soil moisture) and land use (land use, percent of vegetation cover and landscape roughness). The spatial and temporal variability of factors are appropriately defined through Geographic Information System (GIS) analyses. Harmonised dataset and a unified methodology were employed to suit the pan- European scale and avoid generating misleading findings that could result from heterogeneous input data. The selected soil erosion parameters were conceptually divided into three groups, namely (i) Climate Erosivity, (ii) Soil Erodibility and (iii) Vegetation Cover and Landscape Roughness. Sensitivity to the contributing group of factors was calculated using the fuzzy logic technique, which allows the sensitivity range of each factor in Europe to be unambiguously defined. A complete description of the methodology and the application in Europe is described in the paper: 
Borrelli, P., Panagos, P., Ballabio, C., Lugato, E., Weynants, M. Montanarella, L (2014). Towards a pan-European assessment of land susceptibility to wind erosion. Land Degradation & Development, In Press. DOI: 10.1002/ldr.2318 
Spatial coverage: 28 Member States of the European Union and 8 other European States (three European Union candidate countries (Montenegro, Serbia, the Former Yugoslav Republic of Macedonia), three potential European Union candidate countries (i.e. Albania, Bosnia and Herzegovina, and Kosovo), Norway and Switzerland). 
Pixel size: 500m 
Projection: ETRS89 Lambert Azimuthal Equal Area 
Temporal coverage:1981-2010


Title: Wind erosion susceptibility of European soils
Description: The wind-erodible fraction of soil (EF) is one of the key parameters for estimating the susceptibility of soil to wind erosion.The predication of the spatial distribution of the EF and a soil surface crust index drew on a series of related but independent covariates, using a digital soil mapping approach. A complete description of the methodology and the application in Europe is described in the paper: Borrelli, P., Ballabio, C., Panagos, P., Montanarella, L. (2014). Wind erosion susceptibility of European soils. Geoderma, 232, 471-478.
Spatial coverage: 25 Member States of the European Union where data available (All EU member states except Bulgaria, Romania and Croatia). 
Pixel size: 500m 
Projection: ETRS89 Lambert Azimuthal Equal Area 
Temporal coverage:2014


Agriculture Field Parameters data: The dataset contains averaged Field Size, Field Orientation, Field Length, Average Number of Images, Percentage of Large Fields and Length to Width Ratios for the EU 27 Member states and Switzerland, aggregated to NUTS region. The analysis is based on approximately 400 satellite images from the IMAGE2000 archive. Each image was segmented using a fractal net evolution approach, which is a region merging technique (Baatz and Schape, 2000). 
- Field Size Area (ha) : The average field size for the reporting unit for wind erosion fields 
- Field Direction (in degrees) : The average direction of the field – by assuming that usually the longer side of the field is the main working direction
-Length to Witdh Ratio: The average Length to Width Ratio on the agricultural fields
- Field Length (Km): The average Length on the agricultural fields
- Average Number of Images: The average number of images which have been averaged for this reporting unit 
- Percentage Agricultural Wind Erosion Susceptible fields/ non susceptible field : The percentage of agricultural area which could be clearly indentified with the applied method 

 

References - Documentation:

 

By sending these data, you declare that you have read & accept the notification below and that your personal data will be handled by the JRC only for statistical purposes (conformed with privacy statement).

Image CAPTCHA