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Estimated soil erosion by water, by erosion level, land cover and NUTS 3 region (aei_pr_soiler)

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Reference Metadata in Euro SDMX Metadata Structure (ESMS)

Compiling agency: [4D0] European Commission (including Eurostat)

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Data on the risk of soil erosion are published under agreement with the data provider - Joint Research Centre of the European Commission (JRC – Ispra), one of the partners of the Memorandum of Understanding for cooperation on the development of Agri-environmental indicators.

Soil erosion by water is one of the most widespread forms of soil degradation in Europe. Since it is difficult to measure at large scales, soil erosion models are a crucial estimation tool at regional, national and European levels.

This dataset presents the soil erosion rates by water estimated on the basis of the Revised Universal Soil Loss Equation (RUSLE) empirical computer model in tonnes per ha per year, in the EU-27 Member States.

The areas affected are expressed in km2 and as a percentage of the total non-artificial, erodible area in the country.

The soil erosion risk levels are classified in two size categories:

  • Severe risk (> 10 tonnes per hectare per year)
  • Zero Severe risk. Soil erosion may still be occurring in these areas, but at an yearly rate of less than 10 tonnes per hectare.

Note that Eurostat is not the producer of these data, but only re-publishes them. For more information please consult the Eurostat Statistics Explained article Agri-environmental indicator – Soil erosion.

30 October 2026

Soil erosion by water is understood as the removal of soil by rain fall and can take different forms: rain splash, sheet erosion (uniform removal of a thin layer of soil), rill erosion (formation of small channels) or gully erosion (development of larger, permanent channels). Soil erosion by water occurs mainly in areas with a high rainfall intensity, steep topography and limited land cover. Among the main consequences are a loss of cultivable, fertile soil, the pollution of surface water and possibly a destruction of infrastructure. A loss of soil is irreversible.

The main factors affecting the rates of soil erosion by water are precipitation, soil type, topography, land use and land management. The most commonly used erosion model at a regional scale is the Revised Universal Soil Loss Equation (RUSLE).  It estimates erosion by means of an empirical equation including six main factors:

Er = R K L S C P

  • R = rainfall erosivity factor (MJ mm ha-1h-1 yr-1)
  • K = soil erodibility factor (t ha h ha-1 MJ-1 mm-1)
  • L = slope length factor (dimensionless)
  • S = slope steepness factor (dimensionless)
  • C = land cover and management factor (dimensionless)
  • P = human practices aimed at erosion control (dimensionless)

The best available pan-European databases have been introduced for all input layers:

  • Eurostat statistical data on crops, tillage practices, plant residues and cover crops updated with 2023 EU Farm Structure Survey;
  • Stoniness effect taking into account the LUCAS topsoil survey;
  • Rainfall Erosivity Database at European Scale (REDES);
  • Copernicus remote sensing datasets on vegetation density;
  • Digital Elevation Model (DEM) at 25 m resolution;
  • CORINE Land Cover 2018 and 2012
  • Good Agricultural and Environmental Conditions (GAEC) database;
  • LUCAS 2012 earth observations on stone walls and grass margins.

For more information please consult the Eurostat Statistics Explained article Agri-environmental indicator – Soil erosion.

The smallest regional entity presented in this dataset is NUTS 3 regions of EU territory. 2023 data are only available at NUTS 0 level for now.

Areas of the EU territory that refer to specific classes of the CORINE Land Cover (CLC) nomenclature (see 3.3). Generally, artificial, sandy, rocky and icy surfaces as well as wetlands and water bodies are not included in the area on which the indicator is based.

EU Member States

Data are not available for the following NUTS2 and NUTS3 oversea regions:

NUTS 2 code Region
ES64 Ciudad Autónoma de Melilla
ES70 Canarias
FRY1 Guadeloupe
FRY2 Martinique
FRY3 Guyane
FRY4 La Réunion
FRY5 Mayotte
PT20 Região Autónoma dos Açores
PT30 Região Autónoma da Madeira

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

NUTS3 code

Region

ES640

Mellila

ES703 El Hierro
ES704 Fuerteventura
ES705 Gran Canaria
ES706 La Gomera
ES707 La Palma
ES708 Lanzarote
ES709 Tenerife
FRY10 Guadeloupe
FRY20 Martinique
FRY30 Guyane
FRY40 La Réunion
FRY50 Mayotte
PT200 Região Autónoma dos Açores
PT300 Região Autónoma da Madeira

Calendar year

Contact the Joint Research Centre (JRC) at EU Soil Observatory (EUSO) - ESDAC - European Commission.

Soil erosion rates are estimated on the basis of an empirical computer model in tonnes per ha of EU territory per year.

The dataset presents the following units:

  • Tonnes (T)
  • Tonnes per hectare (T_HA)
  • Hectare (HA)
  • Square kilometres (KM2)
  • Percentages (PC); the percentages express the share of a land cover class with a certain soil erosion rate in relation to the total area of the corresponding land cover class (see 3.3 for CLC classes)

The values of the following units were provided by the Joint Research Centre (JRC):

  • ha
  • t/ha

The values of the following units were computed by Eurostat based on the provided values of the JRC:

  • t
  • %
  • km²
  • 2023 EU Farm Structure Survey data on tillage practices, cover crops and plant residues
  • LUCAS Topsoil 2009;
  • European Soil Database (ESDB);
  • Rainfall Erosivity Database at European Scale (REDES);
  • CORINE Land Cover 2018 and 2012;
  • COPERNICUS Remote Sensing data;
  • Eurostat Crop Statistics;
  • LUCAS Earth Observations 2015;
  • Good Agricultural Environmental Conditions (GAEC) (2010);
  • Digital Elevation Model (DEM) 25m

On a non-regular basis, as soon as new data become available. Usually, new data points are disseminated within 3 years after the reference year.

Joint Research Centre (JRC) publishes data on a non-regular basis.

Usually, new data points are disseminated within 3 years after the reference year.

Comparability across countries is considered good.

Comparability over time is considered good.