Reference metadata describe statistical concepts and methodologies used for the collection and generation of data. They provide information on data quality and, since they are strongly content-oriented, assist users in interpreting the data. Reference metadata, unlike structural metadata, can be decoupled from the data.
Eurostat, the statistical office of the European Union
1.2. Contact organisation unit
Unit E1: Agriculture and fisheries
1.3. Contact name
Restricted from publication
1.4. Contact person function
Restricted from publication
1.5. Contact mail address
2920 Luxembourg LUXEMBOURG
1.6. Contact email address
Restricted from publication
1.7. Contact phone number
Restricted from publication
1.8. Contact fax number
Restricted from publication
2.1. Metadata last certified
18 December 2019
2.2. Metadata last posted
18 December 2019
2.3. Metadata last update
18 December 2019
3.1. Data description
Data on soil erosion are published under agreement with 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 represents 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 of EU territory per year (t ha-1 yr-1), in EU-28 Member States for NUTS 3 level administrative areas. Note that Eurostat is not the producer of these data, only re-publishes them. For more information please consult the Eurostat Statistics Explained article Agri-environmental indicator – Soil erosion.
3.2. Classification system
Classification in DPSIR (Driving forces, Pressures, State, Impact, Responses): Pressures and benefits, Resource depletion
3.3. Coverage - sector
The coverage area of the indicator refers to several classes of the CORINE Land Cover (CLC) nomenclature. 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.
The following classes are included: 2 Agricultural areas 2.1 Arable land 2.2 Permanent crops 2.3 Pastures 2.4 Heterogeneous agricultural areas 3 Forest and semi natural areas 3.1 Forests 3.2 Scrub and/or herbaceous vegetation associations 3.3 Open spaces with little or no vegetation, but only the following subcategories: 3.3.3 Sparsely vegetated areas 3.3.4 Burnt areas
The following classes are excluded: 1 Artificial surfaces 3 Forest and semi natural areas, but only the following subcategories: 3.3 Open spaces with little or no vegetation 3.3.1 Beaches, dunes, sand plains 3.3.2 Bare rocks 3.3.5 Glaciers and perpetual snow 4 Wetlands 5 Water bodies
This dataset contains a differentiation in the following four CORINE Land Cover classification groups:
CLC2_3X331_332_335: Agricultural areas (2), forest and semi natural areas (3) excluding beaches, dunes, sand plains (3.3.1), bare rock (3.3.2), glaciers and perpetual snow (3.3.5)
Refers to all potentially erosive-prone land (in simplified terms)
CLC2_321: Agricultural areas and natural grassland
Refers only to agricultural land (agricultural cropland as well as grassland in simplified terms)
CLC2X23: Agricultural areas (2) excluding pastures (23)
Refers only to agricultural cropland (in simplified terms)
CLC23_321: Pastures (23) and natural grassland (321)
Refers only to agricultural grassland (in simplified terms)
3.4. Statistical concepts and definitions
Soil erosion (by water and wind) can be defined as the wearing away of the land surface by physical forces such as rainfall, flowing water, wind, ice, temperature change, gravity or other natural or anthropogenic agents that abrade, detach and remove soil or geological material from one point on the earth's surface to be deposited elsewhere. When used in the context of pressures on soil, erosion refers to accelerated loss of soil as a result of anthropogenic activity, in excess of accepted rates of natural soil formation.
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 is the Universal Soil Loss Equation (USLE) and its revised version (RUSLE). RUSLE is the most frequently used model, which was developed to evaluate soil erosion by water at a regional scale.
Erosion rates in this dataset have been estimated with the revised version of empirical model RUSLE 2015 which considers six main factors controlling soil erosion:
the erosivity of the eroding agents (water) – R factor,
the erodibility of the soil (including stoniness) – K factor,
the slope steepness – S factor,
the slope length of the land – L factor,
the land cover and management – C factor,
the human practices designed to control erosion – P factor.
Compared to past approaches, the RUSLE 2015 has the following improvements:
Soil erodibility is based on around 20 000 measured soil profile data from LUCAS 2009 topsoil survey;
Rainfall erosivity has been estimated after an extensive data collection of high temporal resolution data on rainfall;
Cover incorporates the vegetation density and the crop management;
Management takes into account the tillage practices, plant residues and cover crops;
Topography is calculated with the best ever available Digital Elevation Model (DEM);
Support practices have been estimated for the first time at the European scale.
In addition, the best available pan-European databases have been introduced for all input layers:
Stoniness effect taking into account the LUCAS topsoil survey;
First ever Rainfall Erosivity Database at European Scale (REDES);
Copernicus remote sensing datasets on vegetation density;
Eurostat statistical data on crops, tillage practices, plant residues and cover crops;
Digital Elevation Model (DEM) at 25 m resolution;
Good Agricultural and Environmental Conditions (GAEC) database;
LUCAS 2012 earth observations on stone walls and grass margins.
The smallest regional entity presented in this dataset is NUTS 3 regions of EU territory.
3.6. Statistical population
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.
3.7. Reference area
EU Member States
Data are not available for the following NUTS2 and NUTS3 oversea regions:
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
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
3.8. Coverage - Time
2000, 2010 and 2016
3.9. Base period
Not applicable.
Soil erosion rates are estimated on the basis of empirical computer model in tonnes per ha of EU territory per year (t ha-1 yr-1).
This dataset presents the following units:
Tonnes (t yr-1)
Tonnes per hectares (t ha-1 yr-1)
Hectares (ha yr-1)
Square kilometres (km2 yr-1)
Percentages (% yr-1); 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): Tonnes per hectares and hectares.
The values of the following units were computed by Eurostat based on the provided values of the JRC: Tonnes, square kilometres, percentages.
The soil erosion levels are classified in three size categories:
Total (> 0 tonnes per hectare per year)
Moderate or severe (> 5 tonnes per hectare per year)
Moderate (5-10 tonnes per hectare per year)
Severe (> 10 tonnes per hectare per year)
Calendar year
6.1. Institutional Mandate - legal acts and other agreements
Soil erosion is one of the 28 indicators developed on the basis of the Commission Communication COM (2006) 508 - Development of agri-environmental indicators for monitoring the integration of environmental concerns into the common agricultural policy.
Soil erosion by water is also one of the impact indicators for Monitoring and Evaluation Framework for measuring the performance of the Common Agricultural Policy (CAP) based on the Regulation No 1306/2013 of the European Parliament and of the Council on the financing, management and monitoring of the CAP and Commission Implementing Regulation No 834/2014 laying down rules for the application of the common monitoring and evaluation framework of the CAP.
6.2. Institutional Mandate - data sharing
Data are modelled by the Joint Research Centre (JRC) and re-published by Eurostat. Original data are downloadable from European Soil Data Centre (ESDAC).
7.1. Confidentiality - policy
Regulation (EC) No 223/2009 on European statistics (recital 24 and Article 20(4)) of 11 March 2009 (OJ L 87, p. 164), stipulates the need to establish common principles and guidelines ensuring the confidentiality of data used for the production of European statistics and the access to those confidential data with due account for technical developments and the requirements of users in a democratic society.
7.2. Confidentiality - data treatment
Only non-confidential data are published.
8.1. Release calendar
Data are disseminated as soon as they are available.
8.2. Release calendar access
Not applicable
8.3. Release policy - user access
In line with the Community legal framework and the European Statistics Code of Practice Eurostat disseminates European statistics on Eurostat's website (see item 10 - 'Accessibility and clarity') respecting professional independence and in an objective, professional and transparent manner in which all users are treated equitably. The detailed arrangements are governed by the Eurostat protocol on impartial access to Eurostat data for users
On a non-regular basis, as soon as new data become available.
Panagos, P., Borrelli, P., Poesen, J., Ballabio, C., Lugato, E., Meusburger, K., Montanarella, L., Alewell, .C. 2015. The new assessment of soil loss by water erosion in Europe. Environmental Science & Policy. 54: 438-447.
Panagos, P., Ballabio, C., Borrelli, P., Meusburger, K., Klik, A., Rousseva, S., Tadić, M.P., Michaelides, S., Hrabalíková, M., Olsen, P., Aalto, J., Lakatos, M., Rymszewicz, A., Dumitrescu, A., Beguería, S., Alewell, C., 2015a. Rainfall erosivity in Europe. Sci Total Environ, 2015. 511: 801-814.
Panagos, P., Borrelli, P., Meusburger, K. 2015b. A New European Slope Length and Steepness Factor (LS-Factor) for Modeling Soil Erosion by Water. Geosciences, 5: 117-126
Panagos, P., Borrelli, P., Meusburger, K., van der Zanden, E.H., Poesen, J., Alewell, C. 2015c. Modelling the effect of support practices (P-factor) on the reduction of soil erosion by water at European Scale. Environmental Science & Policy 51: 23-34
Panagos, P., Meusburger, K., Ballabio, C., Borrelli, P., Alewell, C. 2014b. Soil erodibility in Europe: A high-resolution dataset based on LUCAS. Science of Total Environment, 2014. 479–480:189–200.
Panagos, P., Borrelli, P., Meusburger, C., Alewell, C., Lugato, E., Montanarella, L., 2015d. Estimating the soil erosion cover-management factor at European scale. Land Use policy journal. 48C, 38-50.
10.7. Quality management - documentation
Not available
11.1. Quality assurance
Validation of scientific methodology (see documentation of methodology).
Validation of individual input layers in peer review publications.
11.2. Quality management - assessment
See 11.1.
12.1. Relevance - User Needs
Regional to European policy makers, land use planners, scientists.
Joint Research Centre (JRC) publishes data on a non-regular basis.
14.2. Punctuality
Not well defined, since data delivery depends on the organisation providing the data.
15.1. Comparability - geographical
Comparability across countries is considered good.
15.2. Comparability - over time
Comparability over time is considered good.
15.3. Coherence - cross domain
Other models are available and these do not give the same results. Examples are Pesera and Eurosem. The journal article 'Evaluation of the EUROSEM Model for Simulating Erosion in Hilly Areas of Central Italy' discusses the relative closeness to actual erosion evidence of Eurosem and Rusle. However, the RUSLE model has been used for its usability and applicability to the whole of Europe.
15.4. Coherence - internal
Not applicable
Input data are mainly derived from existing data sources and reporting requirements. Validation is rather complex.
17.1. Data revision - policy
5 years interval is planned for the future.
17.2. Data revision - practice
Not applicable
18.1. Source data
LUCAS Topsoil 2009;
European Soil Database (ESDB);
Rainfall Erosivity Database at European Scale (REDES);
CORINE Land Cover 2012 (developed based on CORINE Land Cover 2006 + changes of 2006-2012);
COPERNICUS Remote Sensing data;
Eurostat Crop Statistics;
Eurostat data on tillage practices, plant residues, cover crops (2016);
LUCAS Earth Observations 2015;
Good Agricultural Environmental Conditions (GAEC) (2010);
Data on soil erosion are published under agreement with 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 represents 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 of EU territory per year (t ha-1 yr-1), in EU-28 Member States for NUTS 3 level administrative areas. Note that Eurostat is not the producer of these data, only re-publishes them. For more information please consult the Eurostat Statistics Explained article Agri-environmental indicator – Soil erosion.
18 December 2019
Soil erosion (by water and wind) can be defined as the wearing away of the land surface by physical forces such as rainfall, flowing water, wind, ice, temperature change, gravity or other natural or anthropogenic agents that abrade, detach and remove soil or geological material from one point on the earth's surface to be deposited elsewhere. When used in the context of pressures on soil, erosion refers to accelerated loss of soil as a result of anthropogenic activity, in excess of accepted rates of natural soil formation.
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 is the Universal Soil Loss Equation (USLE) and its revised version (RUSLE). RUSLE is the most frequently used model, which was developed to evaluate soil erosion by water at a regional scale.
Erosion rates in this dataset have been estimated with the revised version of empirical model RUSLE 2015 which considers six main factors controlling soil erosion:
the erosivity of the eroding agents (water) – R factor,
the erodibility of the soil (including stoniness) – K factor,
the slope steepness – S factor,
the slope length of the land – L factor,
the land cover and management – C factor,
the human practices designed to control erosion – P factor.
Compared to past approaches, the RUSLE 2015 has the following improvements:
Soil erodibility is based on around 20 000 measured soil profile data from LUCAS 2009 topsoil survey;
Rainfall erosivity has been estimated after an extensive data collection of high temporal resolution data on rainfall;
Cover incorporates the vegetation density and the crop management;
Management takes into account the tillage practices, plant residues and cover crops;
Topography is calculated with the best ever available Digital Elevation Model (DEM);
Support practices have been estimated for the first time at the European scale.
In addition, the best available pan-European databases have been introduced for all input layers:
Stoniness effect taking into account the LUCAS topsoil survey;
First ever Rainfall Erosivity Database at European Scale (REDES);
Copernicus remote sensing datasets on vegetation density;
Eurostat statistical data on crops, tillage practices, plant residues and cover crops;
Digital Elevation Model (DEM) at 25 m resolution;
Good Agricultural and Environmental Conditions (GAEC) database;
LUCAS 2012 earth observations on stone walls and grass margins.
The smallest regional entity presented in this dataset is NUTS 3 regions of EU territory.
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:
Soil erosion rates are estimated on the basis of empirical computer model in tonnes per ha of EU territory per year (t ha-1 yr-1).
This dataset presents the following units:
Tonnes (t yr-1)
Tonnes per hectares (t ha-1 yr-1)
Hectares (ha yr-1)
Square kilometres (km2 yr-1)
Percentages (% yr-1); 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): Tonnes per hectares and hectares.
The values of the following units were computed by Eurostat based on the provided values of the JRC: Tonnes, square kilometres, percentages.
The soil erosion levels are classified in three size categories:
Total (> 0 tonnes per hectare per year)
Moderate or severe (> 5 tonnes per hectare per year)
Moderate (5-10 tonnes per hectare per year)
Severe (> 10 tonnes per hectare per year)
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
LUCAS Topsoil 2009;
European Soil Database (ESDB);
Rainfall Erosivity Database at European Scale (REDES);
CORINE Land Cover 2012 (developed based on CORINE Land Cover 2006 + changes of 2006-2012);
COPERNICUS Remote Sensing data;
Eurostat Crop Statistics;
Eurostat data on tillage practices, plant residues, cover crops (2016);
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.
Joint Research Centre (JRC) publishes data on a non-regular basis.
Comparability across countries is considered good.
Refers to all potentially erosive-prone land (in simplified terms)
Refers only to agricultural land (agricultural cropland as well as grassland in simplified terms)
Refers only to agricultural cropland (in simplified terms)
Refers only to agricultural grassland (in simplified terms)