soil erosion in europe (boardman/soil erosion in europe) || pan-european soil erosion assessment and...

Risk Assessment and Prediction

Soil Erosion in Europe Edited by J. Boardman and J. Poesen# 2006 John Wiley & Sons, Ltd. ISBN: 0-470-85910-5

2.13

Pan-European Soil ErosionAssessment and Maps

Anne Gobin,1 Gerard Govers1 and Mike Kirkby2

1Physical and Regional Geography Research Group, Katholieke Universiteit Leuven,GEO-Institute, Celestijneulaan 200 E, 3001 Heverlee, Belgium2School of Geography, University of Leeds, Leeds LS2 9JT, UK

2.13.1 INTRODUCTION

Soil erosion is a natural process, occurring over geological time, and most concerns about erosion are related

to accelerated erosion, where the natural rate has been significantly increased by human activity. Soil erosion

poses severe limitations to sustainable agricultural land use, as it reduces on-farm soil productivity and causes

the accumulation of sediments and agro-chemicals in waterways. In Europe, soil erosion is caused mainly by

water and, to a lesser extent, by wind. Rill and inter-rill erosion affects the largest area, but evidence of rills

and inter-rills can easily be hidden by normal tillage. Gully erosion and landslides, on the other hand, often

scar entire landscapes but are relatively localised. Soil losses due to water erosion are high in southern Europe

and moderate in northern Europe.

Factors such as climate, topography, specific soil characteristics, land cover and management have

important effects on both runoff and the process of soil erosion. Depending on these factors, average

human-induced soil erosion rates, due to rill and inter-rill erosion, are typically between 1 and 26 t ha�1yr�1

for Mediterranean arable land (Tropeano, 1983; Kosmas et al., 1997) and between 0.5 and 7.8 t ha�1yr�1 for

arable fields in northern Europe (Bollinne, 1982; Kwaad, 1994; Chambers and Garwood, 2000). On the other

hand, soil formation is a slow process involving the breakdown of rock into small particles and the

accumulation of organic matter. Compared with slow soil formation rates, soil can be regarded as a

nonrenewable resource. These are compelling reasons for assessing and monitoring soil erosion and improving

the way soils are managed.

Soil Erosion in Europe Edited by J. Boardman and J. Poesen# 2006 John Wiley & Sons, Ltd. ISBN: 0-470-85910-5

Both national and international agencies need objective spatial information at low resolutions to compare

levels of environmental risk and focus policies on environmentally sensitive areas. The dynamic relationship

between human activities and the environment requires that environmental processes such as erosion be

quantified to monitor and evaluate the impact of agriculture and land-use policies. Policy-makers need to know

the area affected by soil erosion and an estimate of the magnitude at a regional scale in order to formulate

suitable remediation measures and mitigation strategies (Gobin et al., 2003, 2004).

This chapter deals with methods to present and assess the extent of soil erosion by water at a pan-

European scale. Seven different methods and maps are compared for carrying out pan-European soil

erosion assessment. The GLASOD and HOT SPOTS maps are based on distributed data and expert

judgement. The RIVM/IMAGE, CORINE, ESB/USLE and INRA methods are based on ranked factors and

the empirical (R)USLE model. The PESERA map is the result of a process modelling approach to assess

regional soil erosion risk.

2.13.2 REGIONAL ASSESSMENT METHODS

Regional assessment methods of soil erosion can be distinguished as distributed point data involving expert

judgement, indicator or factorial approaches and process modelling. All of these methods require calibration

and validation, although the type of validation needed is different for each category. There are also differences

in the extent to which the assessment methods identify past erosion and an already degraded soil resource, as

opposed to risks of future erosion, under either present climate or land use, or under scenarios of global

change.

2.13.2.1 Methods Using Distributed Point Data

An important form of erosion assessment is from direct field observations of erosion features and soil profile

truncation. Erosion features consist of rills and gullies, some of these ephemeral, and of associated deposition

in swales and small valleys. Soil profiles may show local loss of upper horizons, or burial by deposition from

upslope.

Measurements of soil erosion represent a second important source of information. However, there are only a

limited number of datasets available from experimental erosion plot sites and catchments in Europe. Most of

these datasets cover periods of short duration, i.e. up to 3 years.

Data may also be collated from remote sensing surveys of erosion features, using aerial photographs or other

earth observation techniques. Satellite images with resolutions of 25–30 m, e.g. LANDSAT, can be used to

detect severe and distinct forms of land degradation and soil erosion. Very high-resolution imagery such as

IKONOS permits the detection of rills and smaller gullies. Aerial photographs at different temporal and/or

spatial scales may serve the same purpose.

Data in the form of measurements, field observations or remote sensing surveys may also be collected from

regional experts in soils or soil erosion. Questionnaire surveys may be administered to the scientific

community and national soil experts to arrive at a regional assessment based solely on expert judgement.

All these distributed data methods require validation to standardise differences in the intensity of study of

different areas and in the clarity of suitable features on different soil types. There are also differences in

methods and traditions between scientists in different areas of Europe. On their own, these methods cannot

provide a complete picture except for small sample areas, and require the use of other methods to interpolate

between areas.

The main advantage of distributed observations or measurements of erosion is that data are unambiguous

where they exist, and give a good indication of the current state of degradation of the soil resource. The main

662 Soil Erosion in Europe

disadvantage of these methods is that they provide little or no information about when erosion occurred, unless

there are supporting data on this point.

2.13.2.2 Indicator or Factorial Approaches

Since many of the processes and factors that influence the rate of erosion are well known, it is possible to rank

individual factors for susceptibility to erosion, providing a series of erosion indicators. For example, soil

indicators reflect the tendency for crusting, the experimental erodibility of soil particles and aggregate stability.

Similar rank indicators can be developed for parent materials. Climatic indices are based on the frequency of

high-intensity precipitation and on the extent of aridity or rainfall seasonality. Topographic indicators

incorporate slope gradient and contributing area, a value corresponding to the catchment area upslope of a

point. Vegetation indicators consist of land cover, vegetation type and roughness. Land management indicators

comprise tillage operations, crop selection, spacing, orientation with the slope and other field practices.

Clearly, a high susceptibility for all factors indicates a high erosion risk and a low susceptibility for all factors

indicates a low erosion risk.

Individual indicators can be mapped separately, but it is more problematic to combine the factors into a

single scale, by adding or multiplying suitably weighted indicators for each individual factor. There are

difficulties both about how to select and justify the individual weightings and about the assumed linearity and

statistical independence of the separate factors. The method should therefore be most effective for identifying

the extremes of high and low erosion, but less satisfactory in identifying the gradation between the extremes.

Despite these theoretical limitations, factor or indicator mapping has the considerable advantage that it can be

widely applied using GIS datasets. For example, raster GIS coverages of topography, soils, land use and

climate are readily available for Europe.

There is a wide spectrum of possibilities to use some or all of the factors of the Universal Soil Loss Equation

(USLE), where soil loss is a simple multiplication of five factors: soil erodibility, rainfall erosivity, slope length

factor, vegetation cover factor and crop management practice. However, all of the approaches remain an

imperfect implementation of the USLE, partly owing to the historical lack of systematic data in Europe.

2.13.2.3 Process Modelling

A third approach towards Europe-wide soil erosion assessment is the application of a process model. A process

model consists of components with an explicit physical basis. Current thinking on soil erosion modelling

recognises the importance of runoff forecasting as a critical control on erosion loss. Runoff models are based

on a runoff threshold or infiltration equation approach, and vary in complexity from the RDI model (Kirkby

et al., 2000) to the USDA WEPP model (Nearing et al., 1989). For application at the regional scale, most

erosion models are severely limited by their high data demand and, in many cases, by a focus on individual

events rather than long-term cumulative impacts.

Process models have the potential to respond explicitly and rationally to changes in climate or land use, and

so have great promise for developing scenarios of change and what-if analyses of policy options. Set against

this advantage, process models generally make no assessment of degradation up to the present time, and can

only incorporate the impact of past erosion where this is recorded in other data, such as soil databases. Models

also generally simplify the set of processes operating, so that they may not be appropriate under particular

local circumstances. Although, prima facie, the modelling approach appears to be the most generally

applicable, there are major problems of validation, and in particular in relating coarse-scale forecasts to

available erosion rate data, much of which is for small erosion plots.

A process model that is suitable for regional soil erosion assessment should represent the state of the art in

current understanding of soil erosion processes, combine sufficient simplicity for application at a European

Pan-European Soil Erosion Assessment and Maps 663

scale and have the potential for downscaling to field scales for purposes of explicit validation. PESERA offers

such a methodology (Gobin et al., 2004).

2.13.3 RESULTS OF PAN-EUROPEAN ASSESSMENT METHODS

2.13.3.1 The GLASOD Approach

The main objective of the worldwide GLASOD (Global Assessment of the Current Status of Human-Induced

Soil Degradation) Project was to strengthen the awareness of decision makers on the risks resulting from

inappropriate land and soil management (Oldeman et al., 1991). On the basis of incomplete existing

knowledge, a scientifically credible global assessment of the geographical distribution and the severity of

human-induced soil degradation was made within a very short time frame. The task was subcontracted to

correlators in 21 regions to prepare, in close cooperation with 300 national soil scientists, regional soil

degradation status maps. All collaborators were provided with guidelines and a base map with loosely defined

physiographic units. The assessment consisted of an expert judgement according to the general guidelines of

degradation status (type, extent, degree, rate and cause) for individual polygons on a national/sub-national

level. The regional maps were compiled, correlated and digitised to provide the GLASOD world map of soil

degradation.

The European part of the GLASOD map has been updated on the basis of questionnaires that were sent to

scientific teams in each European country for comments and additions (van Lynden, 1995; Figure 2.13.1). Not

all countries completed and returned the questionnaires and the degree of detail of the information received

varies greatly. It must also be noted that the scale of the maps (1:10 000 000) limits the detail that can be

Figure 2.13.1 Water erosion of soils in Europe according to the GLASOD approach (modified from Van Lynden, 1995,

� Council of Europe, reproduced with permission)


shown, providing a minimum resolution of approximately 10 km. The representation of the map items causes a

visual exaggeration: each polygon which is not 100 % stable shows a degradation colour, even if only 1–5 % of

the area is actually affected. The GLASOD map identifies areas with a subjectively similar severity of erosion,

irrespective of the conditions, which produced the erosion, and irrespective of its wider impacts.

Despite the limited aims of the project and the subjective approach, GLASOD is the only method that has

been applied at a worldwide scale (Oldeman et al., 1991). Therefore, the GLASOD map and complementary

statistics have been used and cited in numerous scientific journals and policy documents of the World

Resources Institute, the International Food Policy Research Institute, the Food and Agriculture Organization of

the United Nations, the United Nations Environment Programme and many others. However, the dependence

on a set of expert judgements results in very little control or objectivity in comparing the standards applied by

different experts for different areas.

2.13.3.2 The HOT-SPOTS Approach

An analysis and mapping of soil problem areas (hot-spots) in Europe was published in the EEA–UNEP joint

message on soil (EEA and UNEP, 2000). The purpose of the study was to support the joint message on the

need for a pan-European policy on soil, identifying ‘hot-spots’ of degradation in Europe and examining

environmental impacts leading to change and particularly degradation of soil function. The hot-spots map for

soil erosion aims to present a kind of ‘spatial indicator’ that would permit the identification of priorities of

intervention and the visualisation of data gaps.

The temporal and spatial patchiness of soil erosion and the uneven density and quality of local

measurements make a simple mapping of hot-spots futile. Soil erosion in the hot-spots approach is therefore

indicated at a hierarchy of scales (Figure 2.13.2). Three zones are identified for which the nature of erosion is

generally similar: Eastern Europe, the Loess Belt and southern Europe, which primarily represent different

land-use history, parent materials and climate, respectively. Hot-spot areas are then highlighted within each

zone on the basis of two earlier maps (de Ploey, 1989; Favis-Mortlock and Boardman, 1999). The intention is

to identify areas of current erosion risk, under present land use and climate. Hot-spot locations, mostly within

the hot-spot areas, are sites with available measurements of erosion rates, taken from erosion plots, fields and

small catchments.

Worth noting is that the underlying map indicating hot-spots is an extension of the soil erosion risk map of

Western Europe by de Ploey (1989). Various experts were consulted to identify areas where, according to their

judgement, erosion processes are important. A limitation of the de Ploey map is that there are no clear

definitions of the criteria according to which areas were delineated and hence there is no assurance of

objectivity.

2.13.3.3 The IMAGE/RIVM Approach

A baseline assessment of water erosion was prepared for 1990, as part of a major report on strategies for the

European Environment (RIVM, 1992). The assessment of current risk was combined with climate and

economic projections within the framework of the IMAGE 2 model to generate scenario projections for 2010

and 2050. IMAGE 2 is an integrated model designed to simulate the dynamics of the global society–

biosphere–climate system (Alcamo, 1994).

Water erosion represents a module of the IMAGE model adapted from the water erosion model of Batjes

(1996) on a 12

� � 12

�(approximately 50 km) grid (Figure 2.13.3). The water erosion impact module generates a

water erosion risk index based on three main parameters: terrain erodibility, rainfall erosivity and land use.

Terrain erodibility is based on soil type and landform. Landform is classified into types by using the difference

between minimum and maximum altitudes for each grid cell. Soil type is derived from the FAO Soil Map of


the World and is assessed on the basis of soil depth, soil texture and bulk density. Rainfall erosivity is derived

from the monthly maximum rainfall per rain-day. Data on precipitation and number of wet days are derived

from the IIASA climate database. The potential erosion risk derived from terrain erodibility and rainfall

erosivity is converted to actual erosion risk by a land cover factor, representing the degree of protection

afforded by various land covers. Natural vegetation with a closed canopy, e.g. forests, is assumed to provide

optimal protection, i.e. no risk. Natural vegetation with a more open structure, e.g. shrubs, is assumed to

provide sub-optimal protection, i.e. low risk. Highest risks are assigned to arable land, linked to a crop

protection factor. Land cover maps for the IMAGE model are derived from several sources including Olson’s

land cover database and statistical information from FAO.

The IMAGE/RIVM approach has the advantages of making explicit scenario projections and combining

physical and economic elements within a single framework, but the 50-km resolution renders it difficult to

interpret and validate at sub-national scales.

2.13.3.4 The CORINE Approach

The CORINE programme was established in 1985 to help incorporate an environmental dimension into

Community Policies, to ensure optimum use of resources to obtain environmental information and to develop

the methodological base needed to obtain environmental data, which are comparable at Community level. For

one of the priority topics, soil erosion, a new methodology was developed, which provides a factor-based

Figure 2.13.2 The soil erosion hots-pots map (modified after EEA and UNEP, 2000. Assessment and reporting on soil

erosion. Background and workshop report. Technical report nr. 94. European Environment Agency, reproduced with

permission)


assessment of risk. The CORINE soil erosion methodology (CORINE, 1992; Briggs and Giordano, 1995) was

based on a considerable simplification of the USLE.

The CORINE soil erosion risk maps are the result of an overlay analysis of factorial scores to evaluate the

soil erosion risk category (CORINE, 1992; Figure 2.13.4). A relative ranking of soil erosion risk was obtained

through the summation of individual erosion risk scores for each of the parameters soil susceptibility, rainfall,

topography and land cover. Erodibility is estimated from soil texture, depth and stoniness, extracted from the

soil map of the European Communities (CEC, 1985). Erosivity is estimated from the Fournier and Bagnouls–

Gaussen climatic indices. Slope gradient is included, but without a slope length correction, and vegetation and

crop management are collapsed into two categories, protected and not fully protected, using data from the

associated CORINE land cover database. The vegetation and crop management factor is the most poorly

parameterised factor. All the factors are combined to estimate three categories of potential and actual soil

erosion risk. Potential risk excludes vegetation factors, and so identifies land at risk, whereas actual risk

includes the vegetation factor to indicate the protective influence provided by present land cover and the

dangers inherent in land use changes. The resulting maps were produced at a 1-km resolution for southern

Europe, excluding northern Europe. The area of land in this region with a high erosion risk totals 229 000 km2

(about 10 % of the rural land surface).

The static CORINE approach relies heavily on risk assessment by experts, and it remains difficult to evaluate

the effect of changes in land use and/or climate on the erosion risk as no quantitative estimate of soil erosion is

made. For the same reasons, it is not feasible to incorporate more detailed data, nor is it possible to evaluate the

accuracy of the final result.

2.13.3.5 The USLE/ESB Approach

The European Soil Bureau (ESB) initiated a project that aimed to assess erosion risk at a continental level on

the basis of European datasets available. The end result is a set of maps that can help identify regions that are

susceptible to rill and inter-rill erosion (van der Knijff et al., 2000).

Figure 2.13.3 Water erosion vulnerability for 1990 (modified from RIVM Report 481505001. The Environment in

Europe: A Global Perspective. Copyright 1992 RIVM, reproduced by permission of RIVM)


The method uses the USLE in an attempt to produce a comprehensive pan-European soil erosion risk

assessment map at 1-km resolution (Figure 2.13.5). The rainfall erosivity factor was estimated using linear

regression equations for northern and southern Europe, allowing for a smooth transition between the two. The

soil erodibility factor was calculated using an exponential equation based on the geometric mean weight

diameter of the primary soil particles, derived from surface texture composition as presented in the European

Geographical Soil Database for Europe (Heineke et al., 1998). The slope length factor was assumed to be

constant, whereas the slope factor was derived from the slope gradient of a 1-km resolution European-wide

Digital Elevation Model. The land cover factor was estimated using an exponential scaling function linked to

NDVI from NOAA AVHRR. The visual appearance of the map was improved using a filter that replaces the

actual pixel values by the median of all pixel values within a 5-km search radius.

The approach represents an application of the USLE methodology, with the benefit of incorporating

improved and updated data layers once they become available at a pan-European scale. Unlike for the USA,

where there exists a large database, lack of systematic data across the different agro-environments of Europe

will make it very difficult to validate the methodology and resulting map. Moreover, the application of the

method to mountainous regions is Europe is questionable.

2.13.3.6 The INRA Approach

The approach elaborated by INRA (Institut National de la Recherche Agronomique, France) presents a

factorial approach.

Figure 2.13.4 (a) Potential and (b) actual erosion risk as estimated by the CORINE methodology (Figure adapted from

the original maps in Soil Erosion Risk and Important Land Resources in the Southern Regions of the European Community

EUR 13233EN. � European Communities, 1992, reproduced with permission)


The INRA approach uses a hierarchical multi-factorial classification designed to assess average seasonal

erosion risk at a regional scale (Le Bissonnais et al., 2001). The annual soil erosion risk for Europe is based on

empirical rules that combine data on land use from the CORINE Land Cover database, soil crusting

susceptibility, soil erodibility (determined by pedotransfer rules from the European Soil Database at a scale

of 1:1 000 000; Le Bissonnais and Daroussin, 2001), relief (1 km� 1 km resolution) and meteorological data

(Figure 2.13.6).

The INRA approach is simple and versatile, not requiring parameters that are not available at the national scale.

The INRA approach is qualitative with the final information provided on a five-class scale of risk. Since the classes

are not linked to quantitative values of erosion, it is impossible to assess the errors associated with the results.

2.13.3.7 The PESERA Approach

The Pan-European Soil Erosion Risk Assessment (PESERA) Project, an EU-funded 5th framework

project, was initiated to develop and evaluate a physically based and spatially distributed model to

quantify soil erosion in a nested strategy of focusing on environmentally sensitive areas relevant to a

European scale.

Figure 2.13.5 Actual erosion risk as estimated by the ESB/USLE approach (modified from Soil Erosion Risk Assessment

in Europe by Van Der Knijff et al., 2000, EUR 19044 EN, reproduced with permission)


The PESERA model calculates expected mean erosion rates at 1-km resolution for the full range of

environments in Europe (Figure 2.13.7). The model makes use of topography, soil, climate, land use and land

management data to estimate ground cover, surface crusting, runoff and sediment transport and to provide an

estimate of water and sediment delivered to stream channels. The estimates are consistent with finer scale

erosion models for flow strips, evaluated at the slope base, and are integrated across the frequency distribution

of storm magnitudes. The model is based on a partition of daily precipitation into Hortonian and saturation

overland flow, subsurface flow and evapotranspiration. Hortonian overland flow, which is mainly responsible

for soil erosion, is generated with respect to local soil and subsurface moisture characteristics. Some allowance

is also made for snow accumulation and melting. Model forecasts are calibrated against runoff plots and small

catchment data. The model output is also compared with other assessment methods at different resolutions and

across different agro-ecological zones (Gobin and Govers, 2003). Detailed reports on these efforts are

available from the Project’s website.

The major advantage of the PESERA approach towards Europe-wide soil erosion assessment is the

application of a process model that can be used for validation at high resolutions and for Europe-wide

forecasting at a coarse resolution, so that cross-scale reconciliation is as explicit as possible. The PESERA

model produces a quantitative forecast of soil erosion and soil cover, offering great promise for scenario

analysis and impact assessment. It is now being demonstrated that it has the potential to respond explicitly and

rationally to changes in climate or land use.

Figure 2.13.6 Annual soil erosion risk as inferred from soil sensitivity to erosion and rainfall erosivity (Soil Erosion Risk

Assessment in Europe data are owned by the European Commission and were calculated by INRA, according to a

methodology which was developed and is owned by INRA and to which reference can be made by citing the following

publication: Le Bissonnais Y., C. Montier, M. Jamagne, J. Daroussin, D. King (2002). Mapping erosion risk for cultivated

soil in France. Catena, 46, 207–220)


2.13.4 DISCUSSION

Methods based on questionnaire surveys (GLASOD map; Oldeman et al., 1991) or erosion measurement sites

(Hot Spots map; Turner et al., 2001) are inadequate on their own. Estimates of the area affected by actual soil

erosion at regional and national levels are not readily available, because measurements are difficult and usually

expensive to make. Soil erosion often takes place over long periods before the true extent is appreciated and

long-term accurate data are scarce. The temporal and spatial patchiness of soil erosion makes interpolations

between limited available data scientifically not justified. Differences between expert assessments and

measurement methods reduce the comparability between the limited data available even further.

Factorial scoring methods such as the static CORINE approach rely heavily on risk assessment by experts,

and it remains difficult to evaluate the effect of changes in land use and/or climate on the erosion risk as no

quantitative estimate of soil erosion is made. For the same reasons, it is not feasible to incorporate more

detailed data, nor is it possible to evaluate the accuracy of the final result. In addition, the sharp delineation of

Figure 2.13.7 Preliminary results of the PESERA model across Europe (modified from Gobin and Govers, 2003,

reproduced with permission)


source data in both the geographic and attribute space inevitably results in information loss, and the results

depend strongly on the class limits and the number of classes used.

There exists a continuous spectrum between mapping based on ranked indicators and empirical models such

as the (R)USLE. The potential risk calculations are based on climatic, topographic and edaphic conditions,

whereas the actual risk takes into account present land cover and land use. In many ways, these empirical

models are comparable to the factorial scoring methods used for producing the CORINE maps. Adhering

closer to the USLE are the RIVM maps at 50 km� 50 km resolution for Europe (RIVM, 1992) and the USLE/

ESB map at 1 km� 1 km resolution (van der Knijff et al., 2000). Although the USLE has been the most

widely applied model, it is now considered as conceptually flawed. Despite this, the USLE-based methods

have the immediate benefit of transferring distributed data into simple factors. However, any model based on

the USLE will not include gully erosion, which, as Poesen et al. (2003) have shown, can be a major contributor

to total erosion in (at least some parts of) Europe. As part of the ranked indicator methods, the INRA approach

presents a more elaborated method, which was tested at high resolution (50 m) for significant areas and

compared favourably with the PESERA modelling method (Gobin and Govers, 2003). The INRA method

explicitly takes into account land use and the interactions particularly with soil sensitivity to erosion. However,

limitations relate to the qualitative and non-physical nature of the method.

Actual levels of erosion are difficult to measure, so estimates, based on the available physical evidence

provide necessary information on risk, rather than an actual occurrence, of erosion for policy and management

purposes. Process modelling methods such as the PESERA approach offer great scope but may simplify the set

of processes operating and may therefore not be appropriate under particular local circumstances. The explicit

cross-scale reconciliation of the PESERA approach provides a method to test the coarse resolution model

forecasts against finer resolution measurements. The PESERA method is the only approach that explicitly

incorporates the effect of vegetation and ground cover at different steps in the model.

All of the methods presented require calibration and validation, although the type needed is different for

each category. The advantage of quantitative and process modelling methods, such as PESERA, is that coarse-

scale forecasts can be related to measured erosion rates so that explicit calibration and validation can be made

with field monitoring data. Examples of validation and calibration using plot data and of validation using

aggregated measurements (e.g. suspension load, pond sedimentation) or high-resolution maps have been

produced within the framework of the PESERA Project (Gobin and Govers, 2003). However, aggregated

measurements necessitate the use of concatenating different models to arrive at forecasts to be confronted with

measurements (e.g. van Rompaey et al., 2003); this in turn increases error propagation and introduces further

uncertainties in the prediction. Despite the uncertainties involved in European-scale assessments of soil

erosion, policy-makers need to know the area affected by soil erosion and an estimate of the magnitude at a

regional and continental scale in order to formulate suitable remediation measures and mitigation strategies

focussing on environmentally sensitive areas (Gobin et al., 2004).

2.13.5 CONCLUSIONS

In order to formulate a European soil protection policy, pan-European soil erosion assessment methods should

provide information of both the extent and the severity of the problem at the European scale as a first crucial

step in a nested strategy of focusing on environmentally sensitive areas, which may require remedial measures

to be taken (Gobin et al., 2003, 2004). There is a huge difference between measured erosion, actual erosion

risk and potential erosion risk. Certain factors may affect the risk of soil erosion, but they may not affect soil

erosion in itself at present.

Runoff is the most important direct driver of severe soil erosion. Processes that influence runoff must

therefore play an important role in any analysis of soil erosion intensity, and measures that reduce runoff are


critical to effective soil conservation. Any approach that explicitly takes into account the land use and

management factors should be of potential interest to the policy-maker since these are the only factors at hand

to control the erosion problem. It is apparent that the majority of approaches discussed in this chapter do not

pay enough attention to land use and land management factors.

The temporal and spatial patchiness of soil erosion favours a risk analysis approach in order to make

comparisons between regions and to complement field measurements and observations. However, model-

ling efforts should be thoroughly validated against erosion measurements, and a clear distinction should be

made between modelled erosion risk and present-day erosion rates. A programme to monitor soil erosion

across different agro-ecological regions and under different land uses should underpin both field

observation/mapping exercises and regional soil erosion risk assessment methods. Only then is a sound

approach ensured of estimations and mapping features that are directly validated and compared with

measurements. Moreover, measuring campaigns may lead to new insights and therefore to better mapping

and risk assessments.

REFERENCES

Alcamo J (ed.). 1994. IMAGE 2.0: Integrated Modelling of Global Climate Change. Kluwer, Dordrecht.

Batjes NH. 1996. Global Assessment of Land Vulnerability to Water Erosion on a 12

�by 1

2

�Grid. International Soil Reference

Centre, National Institute of Public Health and Environment, and United Nations Environment Programme. Land

Degradation & Development, 7: 353–365.

Bollinne A. 1982. Etude et prevision de l’erosion des sols limoneux cultives en moyenne Belgique. PhD Thesis, Universite de

Liege.

Briggs DJ, Giordano A. 1995. CORINE Soil Erosion Report. European Commission, Brussels.

Chambers BJ, Garwood TWD. 2000. Monitoring of water erosion on arable farms in England and Wales, 1990–94. Soil Use

and Management 16: 93–99.

CORINE, 1992. CORINE Soil Erosion Risk and Important Land Resources in the Southern Regions of the European

Community. Publication EUR13233 EN. European Commission, Luxembourg.

CEC 1985. Soil Map of the European Communities, 1:1,000,000. Office for Official Publications of the European

Communities, Luxembour.

de Ploey J. 1989. A Soil Erosion Map for Western Europe. Catena.

EEA. 2002. Assessment and reporting on soil erosion. Background and workshop report. Technical report nr. 94. European

Environment Agency.

EEA/UNEP, 2000. Down to earth: Soil degradation and sustainable development in Europe. Environmental issues series No.

16. Luxembourg, Office for Publications of the European Commission. (http://reports.eea.eu.int/Environmental_issue_-

series_16,en).

Favis-Mortlock D, Boardman J. 1999. Soil Erosion Hot Spots in Europe. In: Turner, S., Lyons, H. and Favis-Mortlock, D.T.

(2000). Analysis and mapping of soil problem areas (hot spots) in Europe. Final Report to EEA. In Where are the ‘hot-

spots’ of soil degradation in Europe? CD-ROM distributed to EIONET. European Environment Agencey, Copenhagen.

Gobin A, Govers G. 2003. Third Annual Report of the Pan-European Soil Erosion Risk Assessment (PESERA) Project.

Report to the European Commission. http://pesera.jrc.it

Gobin A, Govers G, Kirkby M, Jones R, Kosmas C. 2003. Assessment and Reporting on Soil Erosion. Background and

Workshop Report. Technical report No. 94. European Environment Agency, Copenhagen. http://reports.eea.eu.int/

technical_report_2003_94/en

Gobin A, Jones R, Kirkby M, Campling P, Kosmas C, Govers G, Gentile AR. 2004. Pan-European assessment and

monitoring of soil erosion by water. Journal of Environmental Science and Policy 7: 25–38.

Heineke HJ, Eckelmann W, Thomasson AJ, Jones RJA, Montanarella L, Buckley B (eds). 1998. Land Information Systems –

Developments for Planning the Sustainable Use of Land Resources. European Soil Bureau Research Report No. 4. EUR

17729 EN. Office of the Official Publications of the European Communities, Luxembourg.


Kirkby MJ, Le Bissonais Y, Coulthard TJ, Daroussin J, McMahon MD. 2000. The development of land quality indicators for

soil degradation by water erosion. Agriculture, Ecosystems and Environment 81: 125–136.

Kosmas C, Danalatos N, Cammeraat LH, Chabart M, Diamantopoulos J, Farand R, Gutierrez L, Jacob A, Marques H,

Martinez-Fernandez J, Mizara A, Moustakas N, Nicolau JM, Oliveros C, Pinna G, Puddu R, Puigdefabregas J, Roxo M,

Simao A, Stamou G, Tomasi N, Usai D, Vacca A. 1997. The effect of land use on runoff and soil erosion rates under

Mediterranean conditions. Catena 29: 45–59.

Kwaad FJPM. 1994. Cropping systems of fodder maize to reduce erosion of cultivated loess soils. In Conserving Soil

Resources: European Perspectives, Rickson RJ (ed.). CAB International, Wallingford.

Le Bissonnais Y, Daroussin J. 2001. A Pedotransfer Rule for Estimating Soil Crusting and Its Use in Assessing the Risk of Soil

Erosion. Technical Report. INRA, Orleans.

Le Bissonnais Y, Montier C, Jamagne M, Daroussin J, King D. 2001. Mapping erosion risk for cultivated soil in France.

Catena 46: 207–220.

Le Bissonnais Y, Jamagne M, Lambert J.-J, Le Bas C, Daroussin J, King D, Cerdan O, Leonard J, Bresson L-M, and

Jones R.J.A. 2005 Pan-European soil crusting and erodibility assessment from the European Soil Geographical Database

using pedotransfer rules. Advances in Environmental Monitoring and Modelling, 2(1), 1–15.

Nearing MA, Foster GR, Lane LJ, Finkner SC. 1989. A process-based soil-erosion model for USDA-water erosion prediction

project technology. ASAE Trans. 32: 1587–1593.

Oldeman LR, Hakkeling RTA, Sombroek WG. 1991. GLASOD World Map of the Status of Human-induced Soil

Degradation, (2nd edn.) ISRIC, Wageningen; UNEP, Nairobi.

Poesen J, Nachtergaele J, Verstraeten G, Valentin C. 2003. Gully erosion and environmental change: importance and research

needs. Catena 50: 91–133.

RIVM, 1992. The Environment in Europe: a Global Perspective. Report 481505001. RIVM, Bilthoven.

Tropeano D. 1983. Soil erosion on vineyards in the Tertiary Piedmontese Basin (northwestern Italy): studies on experimental

areas. Catena Supplement 4: 115–127.

van der Knijff JM, Jones RJA, Montanarella L. 2000. Soil Erosion Risk Assessment in Europe. EUR 19044 EN. European

Commission, Brussels.

van Lynden GWJ. 1995. European Soil Resources. Nature and Environment No. 71. Council of Europe Publishing,

Strasbourg.

van Rompaey AJJ, Bazzoffi P, Jones RJA, Montanarella L, Govers G. (2003). Validation of Soil Erosion Risk Assessements in

Italy. European Soil Bureau Research Report No. 12, EUR 20676 EN. Office for Official Publications of the European

Communities, Luxembourg.


soil erosion in europe (boardman/soil erosion in europe) || pan-european soil erosion assessment and...

Documents