Soil erosion is one of the eight threats in the Soil Thematic Strategy, the main policy instrument dedicated to soil protection in the European Union (EU). During the last decade, soil erosion indicators have been included in monitoring the performance of the Common Agricultural Policy (CAP) and the progress towards the Sustainable Development Goals (SDGs). This study comes five years after the assessment of soil loss by water erosion in the EU [Environmental science & policy 54, 438–447 (2015)], where a soil erosion modelling baseline for 2010 was developed. Here, we present an update of the EU assessment of soil loss by water erosion for the year 2016. The estimated long-term average erosion rate decreased by 0.4% between 2010 and 2016.

1. The European Commission’s science
and knowledge service
Joint Research Centre

2. Mapping and modelling soil erosion in
the European Union
Panos Panagos
European Commission, Joint Research Centre
Symposium on Soil Erosion
Leuven, 5-6 December, 2019

3. Outline
•Soil loss by water erosion
•Main policy needs - drivers
•Other erosion processes
• Gully
• Soil loss due to crop harvesting
• Wind
• Global soil erosion
• What we can do better?

4. Soil Biodiversity loss
Sealing
Erosion
Decline of
Soil Organic Matter
Salinization Compaction
Landslides
Contamination
Soil Threats
Policy: Soil Thematic Strategy(2006)

5. The report ‘The implementation of the Soil Thematic Strategy and on-going
activities’ (Jones et al., 2012) stated that 20% of Europe’s land surface is
subject to erosion rates above 10 t ha-1 yr-1
1990 2012
*
Limitations
• Spatial resolution
• Land planning
• Static land uses
• Crop systems
• Conservation practices (CAP)
• Coupled modelling
WHAT
Erosion in Europe: State-of-the-art 2012

6. Data collection from Member States
 Only 8 countries provided data
 Harmonization problems:
• Different input parameters: CORINE
2000 vs. CORINE 2006
• Different periods covered: Map of
2000 vs. map of 2006
• The case of Italy (9 regions)
 No dynamic layers
 No scenarios, etc
All countries are using (R)USLE model

7. Modelling soil erosion by water
Erosion-prediction technology rests on a set of mathematical
equations that are used to compute soil erosion variables by using
input data such as climate, soil, topography, land use and land
management information.
 Empirical
 Conceptual
 Process-based
(R)USLE-type
Source: Alewell et al. 2019 + a Metanalysis of erosion models (80+ scientists)

8. RUSLE2015 soil erosion model
Panagos et al. (2015) – Environmental Science & Policy

9. Panagos et al. (2014), Science of Tot. Environment.
Soil Erodibility
• Use of LUCAS topsoil database
• Combines the influence of Texture,
Organic carbon, soil structure,
Permeability, coarse fragments and
Stone cover
• Regression interpolation using Terrain
features, Lat/Long, vegetation covariates
• Verified against 21 local, regional and national
datasets from 13 countries
Land use/Land Cover Survey
A soil component in LUCAS
20,000 surveyed points
Physico-chemical properties
Orgiazzi et al., Eur . Journal of Soil Science
Impact of stoniness
in reducing soil
erodibility
Stone cover effect:
15%

10. Rainfall erosivity and data collection
• 1675 Precipitation Stations
• 18,000 monthly values (monthly erosivity)
• >300,000 erosive events
• High temporal resolution rainfall data: 5 min, 10-min, 15 min, 60
min
• Participatory approach: Environmental & Meteorological Services from
all Member States (Mar 2013 – Jun 2014).
• Erosivity factor combines the influence of precipitation duration,
magnitude and intensity
• Calibration and estimation of R-factor at 30-Minutes
• Data: 29,000 years of High Temporal resolution precipitation records,
>300,000 erosive events
• REDES: Rainfall Erosivity Database on the European Scale
Panagos, P., Ballabio, C., Borrelli, P.,.....et 14 others scientists from Member
States……(2015). Science of Total Env.

11. Cover – Management
• Differentiate between Arable lands & Non-Arable lands
• Non arable: Forest – Shrub – sparse vegetation –
Heterogeneous – Permanent crops - pastures/grasslands
• CORINE Land Cover & Vegetation Density
 Calibrate the C-factor from literature: 20 major published
studies
 with Remote Sensing(RS) images from Copernicus
Programme: Vegetation Density layer: RS every 10 days
Example: Pastures C-factor
• Range from literature: 0.05 – 0.15
• Each pixel gets a value in this range depending on its Vegetation Density
(0-100%)
• Pastures (mean) C-factor in Ireland: 0.077
• Pastures (mean) C-factor in Cyprus: 0.125
Panagos et al.(2015) Land Use Policy.

12. Low erosive High erosiveMedium erosive
Crop distribution – Management practices
Reduced
Tillage
Plant
Residues
Cover
Crops
Stone
walls
Grass
margins
Contour
farming
-65% -12% -20% -25% -10-15%(density) -40% - 5%(slope)
Modelled Management practices against erosion
Permanent
Grasslands
Other fodder
areas (Alfa,etc)
Wheat,
Barley
Olives, other
Fruits..
Energy crop,
sunflower
Sugar beets,
Potatoes
Maize,
Tobacco
0.05 0.15 0.20 0.22-0.25 0.30 -0.32 0.35 0.38 0.50

13. Soil Loss by water erosion (2010)
Average EU-28: 2.46 t ha-1 yr-1 (in the erosive prone areas: 91% of
EU)
Data produced for years: 2000 – 2010 – 2016
Mean erosion rate in agricultural areas: 3.2 t ha-1 yr-1
Soil formation rate: 1.0-2.0 t ha-1 yr-1
24% of EU lands have rates >2 t ha-1 yr-1
11% of total area contributes to almost 70% of total Soil Loss
(hotspots)
2000-2010: decrease by 9% in erosion rates
• 1/3 due to increase of forestlands (decrease of croplands)
• 2/3 due to change of management practices (proposed by
GAEC/CAP, Soil Thematic Strategy)
2010-2016: decrease by 0.4% in erosion rates

14. Soil erosion indicators & policy support
UN Sustainable Development Goals
DG AGRI: CAP context Indicator
CAP post 2020
Impact Assessment
European Parliament
Greens group report
DG ENV-
DG ESTAT
DG ESTAT:
Regional stats
DG AGRI: EU
Agricultural
Outlook
UNEP IPBES
Panagos & Katsogiannis 2019. Environmental Research. 470-474

15. 2003 cross-compliance
Farmer received an income
aid, on condition that they
respect strict food safety,
environmental and animal
welfare standards.
Common Agricultural Policy (CAP)
(EC) No 1306/2013
GAEC (Good Agricultural and
Environmental Conditions)

16. Indicators for policy : Common Agricultural Policy (CAP)
Data calculated using RUSLE Model. EU, National and regional data: 2012 (CLC2012).
Corine Land Cover classes: Total agricultural area (12-22 and 26), Arable and permanent crop area (12-17 and 19-22), Permanent
meadows and pasture (18, 26).
Soil erosion by water Agricultural areas at risk of soil erosion by water
2012 2012 2012
Country Tonnes/ha/year
Estimated (ha) agricultural area affected by
moderate to severe water erosion (>11 t/ha/yr)
Estimated (%) agricultural area affected by
moderate to severe water erosion (>11 t/ha/yr)
Total
agricultural
area
Arable and
permanent
crop area
Permanent
meadows
and pasture
Total
agricultural
area
Arable and
permanent
crop area
Permanent
meadows
and pasture
ha % of total area in each category
EU-28 2.40 14137.2 12025.5 2111.8 6.7 7.5 4.2
BE 1.22 6.9 6.5 0.4 0.4 0.5 0.1
BG 2.03 204.7 191.6 13.1 3.3 3.6 1.6
CZ 1.62 65.7 63.2 2.5 1.5 1.7 0.3
DK 0.50 0.1 0.1 0.0 0.0 0.0 0.0
DE 1.18 286.9 242.7 44.2 1.4 1.7 0.7
EE 0.21 0.1 0.1 0.0 0.0 0.0 0.0
IE 1.12 14.7 6.7 8.0 0.3 0.8 0.2
EL 4.19 657.9 607.4 50.5 10.7 12.1 4.4
ES 3.73 2633.1 2381.2 251.9 9.6 10.5 5.3
FR 2.25 973.3 679.5 293.8 2.9 2.8 3.0
HR 3.03 238.7 183.2 55.5 9.4 9.2 10.4
IT 8.35 5574.1 5043.6 530.6 32.7 33.0 29.4
CY 2.94 33.5 33.4 0.1 7.2 7.6 0.4
LV 0.33 0.2 0.2 0.0 0.0 0.0 0.0
LT 0.49 0.6 0.6 0.0 0.0 0.0 0.0
LU 2.08 4.7 4.5 0.2 3.4 4.5 0.5
HU 1.57 166.3 162.4 3.9 2.6 3.0 0.4
MT 6.00 1.5 1.5 0.0 9.6 9.6 0.0
NL 0.27 0.1 0.1 0.0 0.0 0.0 0.0
AT 7.32 690.6 243.7 446.9 21.0 12.2 34.3
PL 0.93 258.0 257.0 1.0 1.4 1.6 0.0
PT 2.21 231.8 229.9 1.9 5.4 5.6 1.1
RO 2.86 1373.2 1248.0 125.2 9.7 11.2 4.1
SI 7.41 306.9 242.4 64.4 42.4 41.2 47.4
SK 2.12 158.9 152.1 6.8 6.8 7.4 2.4
FI 0.05 0.1 0.1 0.0 0.0 0.0 0.0
SE 0.39 13.2 12.3 0.9 0.3 0.3 0.2
UK 2.07 241.2 31.2 210.0 1.6 0.5 2.5

17. Soil erosion indicators & SDGs
UN Sustainable Development Goals
The EU land affected by the risk of severe
soil erosion is decreasing from 6.0% to
5.2% between 2000 and 2012.
The main reason for this decrease is the
mandatory cross-compliance measures in
the EU Common Agricultural Policy
(CAP).
Published
31.1.2019

18. • Article 6 (Specific Objectives)
• The achievement of the general objectives shall be pursued through the following specific objectives:
 a) support viable farm income and resilience across the Union to enhance food security;
 b) enhance market orientation and increase competitiveness, including greater focus on research, …
 c) improve the farmers' position in the value chain;
 d) contribute to climate change mitigation and adaptation, as well as sustainable energy;
 e) foster sustainable development and efficient management of natural
resources such as water, soil and air;
• Article 12
Obligations of Member States relating to Good Agricultural and Environmental Condition (GAEC)
Member States shall ensure that all agricultural areas including land which is no longer used for production
purposes, is maintained in good agricultural and environmental condition. Member States shall define, at
national or regional level, minimum standards for beneficiaries for good agricultural and environmental
condition of land in line with the main objective of the standards……………
• Article 60 (Types of intervention)
(i) soil conservation, including the enhancement of soil carbon;
……………
Soil in the proposal COM(2018) 392
Common Agricultural Policy (CAP) 2021-2027

19. CAP objectives and indicators related to "soil"
1. EU Specific objectives
2. EU Impact indicators (I)
• Foster sustainable development and efficient management of natural
resources such as water, soil and air
• Contribute to climate change mitigation and adaptation
• GAEC 2: Protection of carbon-rich soils (protection of wetland and petland)
• GAEC 3: Maintenance of soil organic matter (ban on burning arable stubble..)
• GAEC 6: Minimum land management (Tillage management reducing the risk of soil degradation including slope consideration)
• GAEC 7: Protection of soils in winter (No bare soil in most sensitive period….cover crops)
• GAEC 8: Preserve soil potential (crop rotation)
• I.13 Reduce soil erosion: "Percentage of land in moderate and
severe soil erosion on agricultural land"
• I.11 Enhance carbon sequestration: "Increase the soil organic carbon"
3. EU Result indicators (R)
• R.18 Improving soils: Share of agricultural land under management
commitments beneficial for soil management
• R.14 Carbon storage in soils and biomass: Share of agricultural land under commitments to
reducing emissions, maintaining and/or enhancing carbon storage (permanent grassland, ..
agricultural land in peatland, forest, etc.)
Good Agricultural and Environmental Condition (GAEC) in CAP2021-27
Monitoring performance of the CAP vs. objectives:
Indicators related to "soil"

20. Scenario analysis (2030) & uncertainties
Two “unknown” factors:
Rainfall intensity is projected
to increase by 18% by 2050
Impact of policies in changing
Agricultural Management practices
• Cover Crops
• Reduced Tillage
• Plant residues
• Grass margins
• Contour farming
• Stone walls
• Agroforestry, etc…..

21. Knowledge gaps & challenges: Towards real observations
From crop statistics at NUTS2 to Farm objects
Combine with Remote Sensing: Phenological changes in Crops
Object-oriented approach
LPIS
databases
Digital land use maps
Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec
• Process-based modelling
• Downscale at Farm level
(Objects)
• Extensive use of
COPERNICUS
• Intra-annual (monthly
changes)
• Scenarios (Climate, land
use change, policy)

22. Soil loss by wind modelled for the
European arable land
• Other erosion processes that are not accounted:
• Wind erosion
• Gully erosion
• Soil loss due to crop harvesting
• etc.
• Gully erosion workshop – 21-23 March 2018
• Forming a working group
• How to model the gully erosion processes at
regional scales?
• Review the existing research on gully erosion in
Europe
• Data collection from Member States
• Draft a Review Paper Gully erosion at regional to
continental scales (Vanmaercke et al in
preparation…)
Soil erosion workshop & follow up

23. Soil loss by wind modelled for the
European arable land
• LUCAS 2018 (20,000 visited points) included additional modules:
• Soil biodiversity
• Bulk density
• Visual assessment of soil soil erosion
• First results on soil erosion erosion:
• Works well for gully erosion (evident geomorphological feature)
• 211 recorded points
• 206 points validated with Google Earth, Photos
• Proposal for including gully erosion assessment in the 2022 LUCAS survey (> 330,000 visited
points)
LUCAS 2018 and gully erosion

24. Soil loss by wind modelled for the
European arable land
Soil loss due to crop harvesting
Data on sugar
beets & potatoes:
1987 – 2016
SLCH is less
intense compared
to water, wind,
tillage and gully
erosion

25. GIS-RWEQ model
The first quantitative assessment at
European level.
Main Factors influencing wind erosion
(included in the model):
Climate: wind velocity & direction,
Rainfall and evapotranspiration
Soil characteristics: sand, silt, clay,
Calcium Carbonate(CaCO3), organic
matter, water-retention capacity and soil
moisture
Land use (vegetation cover): land use
type, percent of vegetation cover and
landscape roughness
----------------------------------------------
Model used: RWEQ
The model scheme is designed to
describe the daily soil loss potential at
regional or larger scale
Borrelli et al., 2017. Land Degradation & Development, 28: 335-344
A pan-European quantitative assessment
of soil loss by wind

26. Borrelli et al., 2017. Land Degradation & Development, 28: 335-344
Soil loss by wind modelled for the
European arable land
• The average annual soil loss predicted by GIS-RWEQ in the
EU arable land totalled 0.53 Mg ha-1 yr-1
• 2nd quantile equal to 0.3 Mg ha-1 yr-1
• 4th quantile equal to 1.9 Mg ha-1 yr-1
• Highest wind erosion rates in arable lands: Denmark,
Netherlands and Bulgaria
• Peak in winter period (December-February): 57% of total
• Noticeable rates in Eastern UK, North France, Belgium,
Czech Republic, Slovakia and Hungary
• In Mediterranean, higher soil loss rates were located in the
Spanish regions of Aragón, Castilla y Leon, the Italian
regions of Apulia, Tuscany and Sardinia, in the Provence in
France and the Greek regions of Central and Eastern
Macedonia and Thrace and Aegean islands.
Data available:
http://esdac.jrc.ec.europa.eu/themes/land-susceptibility-wind-erosion
Soil loss by wind modelled for the
European arable land

27. Status of Global Soil Resources
“…the most likely range of global soil
erosion by water is 20–30 Pg yr-1”
“Over the last decade, the figures published for water
erosion range over an order of magnitude of ca. 20 Pg
yr-1 (billion tones) to over 200 Pg yr-1”
FAO & ITPS. 2015
The FAO and the Intergovernmental Technical Panel on Soils in 2015 have completed the first State of
the World’s Soil Resources Report.
The majority of the world’s soil resources are in only fair, poor or very poor condition
Globally soil erosion was identified as the gravest threat, leading to deteriorating water quality in
developed regions, lowering of crop yields in many developing regions.
The quality of soil information for policy formulation must be improved – the regional assessments in the
State of the World’s Soil Resources Report frequently base their evaluations on studies from the 1990s
based on observations made in the 1980s or earlier.

28. Need of new spatially explicit information: GLASOD approach can be much improved
taking into account today’s technological advances can build upon
- 15 times more literature than 1980
- Quasi-daily satellite information
- Computation capacity
- Exponential increase of digital resources
- Harmonized databases (e.g Land Parcel
Identification System, FAO Statistics, etc)
Sinergise
Spatial Assessment of Soil Erosion. Where do We Stand?

29. Global Soil Erosion
High resolution: 250 x 250 grid
Coverage: 202 countries ≈ 125 106 Km2 (84% of earth surface)
35.9 Pg yr-1 (Billion tons) of soil erosion (2012)
Global Soil Erosion

30. A study which is more than a map or
a model ….
• 4 Million Km2 change land use between 2000-2012
• Increase of total erosion by 2.5% due to decrease in
forestlands
• Africa has the highest increase (8%) followed by
South America and South East Asia
• Focus in croplands: 17−0.7
+1
Pg yr-1
New insights in Earth systems dynamics
A study which is more than a map or a model ….

31. SECRETARIAT
Mark Nearing Panos Panagos Jean Poesen Jae Yang Richard Cruse Michael Märker Nigussie Haregeweyn
Christine Alewell Baoyuan Liu Rui Li Paulo Oliveira Rosa Poch Megan Balks Costanza Calzolari
Participants in the group discussion

32. Synthetic workflow of the multilevel approach
Water
erosion
Wind
erosion
Tillage
erosion
Other
processes
GSERmap
Working group meeting: 16-18 March 2020, Ispra (JRC)

33. Soil Erosion: Summarizing the main policies in EU
Environment
Soil Thematic Strategy
• Stronger integration with
other policies
• Increase awareness raising
• Research to enhance soil
protection
• Legislation?
Agriculture
Common Agricultural Policy (CAP)
• Cross compliance: minimum
standards for soil protection
• Greening: payments for crop
diversification, permanent
grassland, ecological areas. etc.
• Rural Development: practices to
restore degraded land,
conservation agriculture, green
covers, buffer strips, etc.
Water Framework Directive (sediments), Climate policies (Carbon/Erosion)

34. • The new Common Agricultural Policy (post 2020) will have a strong
Environmental Component (including soil erosion)
• Agricultural Management practices are the key driver for reducing soil
erosion
• EU is a front-runner in Sustainable Development Goals (SDGs) and
soil erosion is part of EU SDGs indicator monitoring
• EU Green Deal: Reduce GHG emissions and halt biodiversity loss –
integration of soil erosion to carbon sequestration & biodiversity protection
• Global Challenge: link to UNCCD (Land degradation indicators), IPCC
(Report on climate change & desertification) & IPBES(biodiversity)
Concluding remarks

35. Data available
http://esdac.jrc.ec.europa.eu

36. Thanks
Questions?
panos.panagos@ec.europa.eu
http://esdac.jrc.ec.europa.eu
@PanosPanagos33