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Land Use Policy 24 (2007) 576–583

www.elsevier.com/locate/landusepol

Modelling the impact of land cover changes in the Czech Republicon sediment delivery

A. Van Rompaeya,�,1, J. Krasab, T. Dostalb

aResearch Group Physical and Regional Geography, KU Leuven, Celestijnenlaan 200E, 3001 Heverlee, BelgiumbDepartment of Irrigation, Drainage and Landscape Engineering, CVUT, Czech Republic

Received 16 March 2005; received in revised form 7 October 2005; accepted 15 October 2005

Abstract

At present large collective fields in the Czech Republic are being split up into smaller spatial units. Moreover, a large number of former

state farms are abandoned, resulting in an increase of the area of set-aside land. Between 1990 and 2000 the area of pasture land in the

Czech Republic increased 150%. The ongoing landscape dynamics has a significant impact on soil erosion and sediment delivery to rivers

and reservoirs. In some cases sedimentation records in retention ponds at the outlet of rural drainage basins show a 75% decrease of the

mean annual sediment export since 1990. It may be expected that the EU enlargement will be a significant driver for future land cover

change in Central and Eastern Europe. In this paper some possible land cover change scenarios for rural areas in the Czech Republic

were considered. Next, these scenarios were used as an input for a spatially distributed sediment delivery model in order to evaluate their

impact on soil erosion and sediment delivery. The results show that the spatial pattern of land cover change seems to be more important

than the percentage of land cover change, which encourages the development and application of spatially explicit land cover change

models.

r 2006 Elsevier Ltd. All rights reserved.

Keywords: Decollectivization; EU enlargement; Soil erosion; Land use

Introduction

Sediment delivery to river channels is probably the mostproblematic off-site consequence of soil erosion. The inputof sediment by erosion processes into rivers, reservoirs andponds results in high sediment deposition rates, frequentdredging operations and an increased risk of flooding.Moreover, in areas with intensive agricultural land use,certain nutrients and pesticides are strongly adsorbed ontosoil particles, which contributes to the pollution of surfacewaters. Not all of the eroded soil material in a drainagebasin is delivered to river channels as a large fraction of theeroded soil material is deposited on the flow path betweensediment source and river channel. The land cover pattern

e front matter r 2006 Elsevier Ltd. All rights reserved.

ndusepol.2005.10.003

ing author. Research Group and Regional Geography,

elestijnenlaan 200E, 3001 Heverlee, Belgium.

6403; fax: +32 1632 2980.

ess: anton.vanrompaey@geo.kuleuven.be

aey).

ientific research—Flanders, Belgium.

determines to a large extent the sediment delivery ratio(SDR) of a drainage basin. Not surprisingly soil erosionand sediment delivery are an important point on theagenda of land arrangement administrations, especially inregions that are characterized by important land coverchange dynamics.In this paper the impact of recent and possible future

land cover changes in the Czech Republic on sedimentdelivery is examined. Landscapes in the Czech Republic arecharacterized by two major changes in the agri-environ-mental policy system since World War II (Zellei et al.,2005). In the first half of the 20th century the average sizeof arable parcels in the Czech Republic was in an order ofmagnitude of a few hectares (Vrana et al., 1998). From1948 onwards the communist government started,under the supervision of the Soviet Union, with acollectivization of the agricultural land. Two types ofagricultural production units were installed: the UnitedAgricultural Cooperatives and the State Farms. TheUnited Agricultural Cooperatives consisted of a union of

ARTICLE IN PRESSA. Van Rompaey et al. / Land Use Policy 24 (2007) 576–583 577

the original former landowners, although individual farm-ers had no influence on the way their land was used. Thestate farms were agricultural enterprises of a few thousandhectares managed by the state. The collectivization processhad a dramatic impact on the landscape structure: thematrix of individual fields disappeared completely. Follow-ing the example of the Soviet Union, individual fields wereput together in order to create fields with a size and shapethat enabled mass production technologies (Fig. 1). Thenew single field size was approximately 50–100 ha, whichled to an enormous acceleration of erosion and sedimenttransport processes on arable land. Moreover, the collecti-vization led to an increase in the area of arable land asmany pastures and meadows were converted. In manycases, land degradation was even more accelerated by theintroduction of crops that were not suited to the localconditions (such as maize on unfertile parcels with steepslopes). The original extensive animal production based on

Fig. 1. Rural village in the southwest of the Czech Republic (left b

Fig. 2. Land use in Kvetonov in the south of the Czech R

grazing was converted into intensive animal production instables, which required the growing of modified feedingmixtures (Bicik et al., 2001).The political changes in 1990 resulted in a second

major change of the agri-environmental policy system.Since 1990 the original landowners or their successors canclaim their original property. Therefore the large parcels ofthe cooperatives and the state farms are split up againresulting in a relatively fragmented land ownership (VanDijk and Kopeva, 2006.) In some cases the land is notclaimed back in which case the arable land is abandonedand converted to extensive rangeland. In some regionsthe abandonment of state farms led to dramatic land-scape changes on a very short term. Fig. 2 shows the landcover pattern in Kvetonov, which is 32 km2 drainage basinin the south of the Czech Republic. After the collapseof state farming more than 50% of the arable land wasset aside.

efore collectivization, 1953, right after collectivization, 1987).

epublic (left situation—1992, right situation—1998).

ARTICLE IN PRESSA. Van Rompaey et al. / Land Use Policy 24 (2007) 576–583578

Decollectivization opened the Czech agriculture tocompetition with European Union (EU)-states and NorthAmerica, which is leading to a more intensive use of fertileland and a gradual conversion of less fertile soils intopermanent grassland or to forests (Bicik et al., 2001). Theaccession of the Czech Republic to the EU in 2004 willprobably enforce the current trend (Bogaerts et al., 2002).

It is obvious that the recent and possible future landcover changes in the Czech Republic had and will have animportant impact on the sediment delivery to rivers.Although land arrangement administrations in the CzechRepublic explicitly recognize sediment delivery and its off-site consequences as a major environmental problem(Krasa et al., 2005) quantitative assessments of futuresediment delivery rates (SDR) in the Czech Republic are atpresent not available.

This paper tries to produce these assessments byanalysing the current spatial variability in erosion andsediment yield and use the results to extrapolate into thefuture. Firstly, a spatially distributed sediment deliverymodel is calibrated and validated using a dataset withmeasured SDR. Secondly, possible future land coverpatterns are defined by extrapolation of the current trend.Finally, the impact of these hypothetical land coverpatterns on the SDR is quantified.

Model calibration and validation

Model structure

WaTEM/SEDEM is a sediment delivery model thatpredicts how much sediment is transported to the riverchannels on a yearly basis. For a detailed description of themodel structure we refer to Van Rompaey et al. (2001a).WaTEM/SEDEM is a spatially distributed model, whichmeans that the landscape is divided in small spatial units orpixels. In each of the pixels a mean annual sedimentproduction by water erosion (A) and a mean annualtransport capacity (TC) is calculated. By means of arouting algorithm, each cell is connected with the river viaa unique flow path. If the local transport capacity exceedsthe incoming sediment volume the sediment is transferredfurther downslope. If the local transport capacity is lowerthan the incoming sediment volume sediment depositionoccurs. Sediment that reaches the river channel isconsidered to leave the drainage basin.

The mean annual sediment production by water (ton/grid cell) is calculated with the RUSLE (Eq. (1), Renard etal., 1997).

A ¼ RK LS CP, (1)

where A is the mean annual soil erosion rate (t ha�1 y�1), R

the rainfall erosivity factor (MJmmha�1 h�1 y�1), K thesoil erodibility factor (t hMJ�1mm�1), LS the topographicfactor (dimensionless), C the crop management factor(dimensionless) and P the erosion control practice factor(dimensionless).

K, C, R and P are assessed using standard RUSLEprocedures (Renard et al., 1997). The topographic factorLS is calculated with a two dimensional routing algorithmin which the 1-D upslope length is replaced by a unitcontributing area. At parcel borders the contributing areais lowered by 50% (Van Oost et al., 2000). This soil erosionassessment accounts for interrill, rill and ephemeral gullyerosion as effects of flow convergence are explicitlyaccounted for (Desmet et al., 1999).The mean annual transport capacity TC depends on

topography and land cover. In WaTEM/SEDEM thetransport capacity is considered to be directly proportionalto the potential for rill erosion (Eq. (2), Van Oost et al.,2000).

TC ¼ KTCEprill, (2)

where TC is the transport capacity (t ha�1m�1), KTC thetransport capacity coefficient (m) and Eprill the potentialfor rill erosion (t ha�1 y�1)

Eprill is assessed using the equation proposed by McCoolet al. (1989). KTC values for different land use types have tobe assessed by means of calibration. Tillage erosion is a soilredistribution process that does not contribute to thesediment delivery of a drainage basin and is therefore notconsidered in this study.

Model calibration

The sediment production component of WaTEM/SEDEM is based on the RUSLE. Calibration of theRUSLE parameters for the Czech Republic was carried outby Dostal et al. (2002). Van Rompaey et al. (2001a)calibrated the KTC of WaTEM/SEDEM for different landuse types in rural areas in central Belgium. For this studythe KTC of WaTEM/SEDEM were recalibrated usingmeasured sediment yield data from Czech drainage basins.Sediment yield data were available for five drainage basinsin the Czech Republic that have a large reservoir at theoutlet (Fig. 3, Table 1).Sediment yields were derived from excavated sediment

volumes or from measured water depths within thereservoirs (Dostal et al., 2002). Brune’s rule (Brune, 1953)was used to assess the trap efficiency of each reservoir. Forthe Kvetonov drainage basin (Fig. 2) sediment yield datawere available for two periods 1989–1993 and 1994–1999.In 1994, 50% of the arable land in the Kvetonov drainagebasin was converted into fallow, which led to a significantlowering of the sediment yield.WATEM/SEDEM was applied to each of these drainage

basins. WaTEM/SEDEM was run with a raster-DEM at a50m resolution derived from 1:25,000 contour maps with acontour interval of 10m (VTOPU Dobruska, CzechMilitary Institute of Cartography). Different land usetypes were derived from CORINE land cover maps 1990(European Environment Agency). Because no data onparcel boundaries were available average parcel sizes of50 ha were simulated using a random allocation algorithm,

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Fig. 3. Location of the drainage basins used for model calibration.

Table 1

Average annual sediment delivery data in the Czech Republic (Dostal et al., 2002)

Drainage basin Size (km2) Average slope (%) % arable land Obs. Period (y) Obs. Method* SD (t y�1)a SSD (t ha�1 y�1)b

Kvetonov (1994) 32 8.6 41.6 5 WD 6400 2.01

Kvetonov (1999) 32 8.6 21.1 4 WD 1600 0.51

Hamry 56 5.3 23.1 32 WD 460 0.82

Nemcice 80 6.7 58.5 16 EX 5900 0.74

Trnavka 339 7.1 58.0 13 EX 7100 0.21

Sedlice 412 7.0 54.1 65 EX 12500 0.30

*Observation method: WD ¼ measurement of water depths in the reservoir,EX ¼ measurement of excavated sediment volumes.aSD ¼ average annual sediment delivery (t y�1).bSSD ¼ average annual area-specific sediment delivery (t ha�1 y�1).

A. Van Rompaey et al. / Land Use Policy 24 (2007) 576–583 579

which is an approximation of the average situation beforethe decollectivization in the Czech Republic (Vrana et al.,1998). RUSLE K factors were derived from the nationalsoil maps at a scale of 1:200,000 (Dostal et al., 2002).

Because of the limited number of sediment yield observa-tions, transport capacity coefficients for only two types ofland use were calibrated: arable land (KTCA) and non-arableland (KTCN), e.g. pastures and forests. For each drainagebasin of the dataset the model was run with KTCA valuesranging from 0 to 100m and KTCN ranging from 0 to 50m.This allowed a comparison of the measured and predictedvalues for each parameter combination. The model effi-ciency coefficient ME as proposed by Nash and Sutcliffe(1970) was used as a measure of likelihood (Eq. (3)).

ME ¼ 1�

PðYobs � YpredÞ

2

PðYobs � YmeanÞ

2, (3)

where ME is the model efficiency, Yobs the observed value,Ypred the predicted value and Ymean the mean observed

value. Values for ME range from �N to 1. The closer ME

approximates 1, the better the model will predict individualvalues.The results of these simulations are plotted in Fig. 4. The

results show maximal ME values for KTCA at 50m and forKTCN at 20m. This means that WaTEM/SEDEM has anoptimal performance when the TC is calculated with theseKTC values.With the optimal parameter values a ME of 0.58 is

obtained. Modelled versus predicted values are plotted inFig. 5. Each dot in Fig. 5 represents one drainage basin.The results show that WaTEM/SEDEM is able to rank thedifferent drainage basins correctly according to theirsediment delivery. The Kvetonov data (white dots inFig. 5) show that the model responds in a logical way to theland cover changes in 1994. Nevertheless, the predictedmean annual sediment delivery for the Kvetonov drainagebasin in the period 1989–1993 is much lower than theobserved sediment delivery in that period. This may be dueto the fact that some exceptional wet years occurred in the

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-1.0

-0.8

-0.6

-0.4

-0.2

0.0

0.2

0.4

0.6

0.8

0 20 40 60 80 100

Ktca (m)

ME

(A)

-1.0

-0.8

-0.6

-0.4

-0.2

0.0

0.2

0.4

0.6

0.8

0 10 20 30 40 50 60

Ktcn (m)

ME

(B)

Fig. 4. Calibration of the WaTEM/SEDEM transport capacity coefficient. A for arable land (KTCA in m) and B for non-arable land (KTCN in m). ME is

model efficiency.

0

5000

10000

15000

0 5000 10000 15000

Observed Sediment Delivery (t/y)

Pre

dict

ed S

edim

ent

Del

iver

y (t

/y)

Fig. 5. Observed versus modelled sediment delivery. Absolute sediment

delivery in A (SD in t y�1) and area specific sediment delivery in B (SD in

t ha�1 y�1). The two SD records for the Kvetonov drainage basin are

visualized with white squares.

A. Van Rompaey et al. / Land Use Policy 24 (2007) 576–583580

short measuring period. Detailed rainfall records thatcould validate this hypothesis are not available.

Scenario analysis at larger scale

After the calibration WaTEM/SEDEM was applied atthe Orlice drainage basin in the northern part of the CzechRepublic (Fig. 2). The Orlice drainage basin of 1960 km2

has an average slope of 8.4%. The average slope of thearable land (43% of the total area) is 6.0% because forestcovers the steepest parts of the drainage basin. Under thepresent circumstances, the mean soil erosion rate in thedrainage basin is assessed at 3.2 t ha�1 y�1 (WaTEM/SEDEM prediction). The average parcel size was assessedat 50 ha. As the arable land is on average close to the riverchannels, without buffer areas of forest, the drainage basin

has a relatively high SDR of 28%. The average yearlysediment delivery was assessed at 174600 t y�1.Starting from the present situation S0 four possible

future land use scenarios S1, S2, S3 and S4 for the Orlicedrainage basin were defined:

S1: splitting up of the collective fields,S2: ad random conversion of arable fields to permanentgrassland,S3: conversion of arable fields to grassland on thesteepest slopes,S4: better crop management.

Scenario 1 corresponds with EU guidelines to split verylarge fields into smaller ones within the framework oflandscape revitalization. Such a scenarios could be realizedin the framework of the new land arrangement projects inwhich former owners can claim a piece of land accordingthe size and quality of the land they owned before thecollectivization. For this analysis hypothetical parcels weregenerated at random using the random allocator of Idrisi32(sIDRISI) with average sizes of 5, 10, 20 and 30 ha.Scenarios 2 and 3 are an extrapolation of the observed landcover changes from 1990 to 2000. The CORINE land covermaps of 1990 and 2000 of the European EnvironmentAgency show an 150% increase of pasture land for thewhole of the Czech Republic over the last 10 years, which isthe result of a shift from crop cultivation to extensivelivestock breeding. If farmers are willing to fight soildegradation the new pastures will appear on steeper slopesin the landscape as simulated in scenario 3. A similaranalysis in central Belgium showed that farmers do take tosome extent the slope gradient into account when arableland is taken out of production but that slope gradient isnot the only determining factor (Van Rompaey et al.,2001b). For both scenario 2 and 3 arable land to pastureconversion volumes of 5%, 10%, 15% and 20% weresimulated. Scenario 4 simulates a decrease of the cropmanagement factor (RUSLE-C). This scenario is realisticwhen agricultural policy makers encourage farmers to

ARTICLE IN PRESSA. Van Rompaey et al. / Land Use Policy 24 (2007) 576–583 581

modify the crop management and to reduce the growing oferosion-prone crops such as maize. A decrease of the Cfactor with 5, 10%, 15% and 20% was simulated.

Results and discussion

The results of all the simulations are listed in Table 2.A possible decrease of the average parcel size (scenario 1)has a significant impact on both soil erosion and sedimentdelivery (Fig. 6). Erosion rates are lower because the lengthof the slopes is reduced. Sediment delivery is decreasedeven further because of a double effect: less sediment isproduced and there are more field boundaries where thesediment can be trapped. The relation between parcel sizeon the one hand and soil erosion and sediment delivery onthe other hand that was found in this study is not a 1:1relation: e.g. a 40% decrease of the average parcel size(from 50 to 30 ha) results in a 12.5% decrease of theaverage soil erosion and a 35% decrease of the sedimentdelivery. Van Oost et al. (2000) came to similar results,which can be explained by the fact that the relationbetween soil erosion and the upslope area is described bymeans of a power function with an exponent smaller than1. The large number of parcels involved in each simulationimplies that the sensitivity to different random allocationsis relatively low because over- and underpredictions of soilloss will compensate each other. Model runs for differentrandom allocations with the same parcel size show a

Table 2

Impact of possible scenarios on soil erosion and sediment delivery in the Orli

Scenario % ar

land

S0 (present situation) 43.1

S1: new parcel structure with an average parcel size of: 30 ha 43.1

20 ha 43.1

10 ha 43.1

5 ha 43.1

S2: Conversion arable fields to grassland at random 5% 40.9

10% 38.8

15% 36.6

20% 34.4

S3: Conversion arable fields to grassland on steepest

slopes

5% 40.9

10% 38.8

15% 36.6

20% 34.4

S4: Modified crop management: decrease of RUSLE C-

factor with:

5% 43.1

10% 43.1

15% 43.1

20% 43.1

*SD ¼ average annual sediment delivery (t y�1).aSSD ¼ average annual area-specific sediment yield (t ha�1 y�1).bSDR ¼ sediment delivery ratio.

variation of less than 1% on the predicted soil erosion andSDR at catchment scale.Fig. 7 shows that the conversion of the steepest arable

land to grassland S3 is much more effective in reducing soilerosion than an ad random conversion of the arable landS2. In scenario 2 (random conversions) a 5% conversion ofthe arable land results in a 15% decrease of the average soilerosion rate. In scenario 3 (conversion of steepest parcels) a5% conversion of the arable land results in a 28% decreaseof the average soil erosion rate. Even in the case of an adrandom conversion the ‘benefit’ in terms of soil erosionreduction is three times higher than what would beexpected based on the percentage arable land that is takenout of production. This can be explained by the fact that ifpastures are introduced in the landscape soil erosion will bereduced on the converted fields but also on neighbouringarable fields that receive much less runoff from upslopefields that are converted to pasture. This effect graduallyfades away when the number of pastures increases. Theimpact of arable land to pasture conversions has an evenstronger impact on the sediment delivery of the Orlicedrainage basin. A 5% conversion of the arable land resultsin a 37% decrease of the sediment delivery in scenario 2and a 50% decrease in scenario 3. This can be explained bythe double impact of the increased percentage of pastureson the sediment delivery: (1) less soil is eroded and (2)the eroded soil has a higher probability of getting trappedby downslope pastures. This result implies that the

ce drainage basin

able Mean annual

erosion rate

(t ha�1 y�1)

SD

(t y�1)*

SSD

(t ha�1 y�1)aSDRb

3.20 17,4600 0.89 0.278

2.80 11,2900 0.58 0.206

2.39 87,600 0.45 0.187

1.86 60,200 0.31 0.165

1.41 38,100 0.19 0.138

2.69 109,500 0.56 0.208

2.56 105,400 0.54 0.210

2.40 101,400 0.52 0.216

2.28 96,800 0.49 0.217

2.30 87,100 0.44 0.193

1.95 70,900 0.36 0.186

1.75 64,300 0.33 0.187

1.50 56,600 0.29 0.193

3.04 168,000 0.86 0.282

2.88 16,1400 0.82 0.286

2.72 15,6200 0.80 0.293

2.56 14,9500 0.76 0.298

ARTICLE IN PRESSA. Van Rompaey et al. / Land Use Policy 24 (2007) 576–583582

introduction of pastures in the landscapes causes a decreaseof the SDR. Fig. 7 also shows that a 10% conversion fromarable land to pasture at erosion-prone locations in thelandscape decreases the average soil erosion and sedimentdelivery much more than when 20% of the arable land isconverted into pasture at random locations. This findingimplies that, with respect to the reduction of soil erosionand sediment delivery, the spatial pattern of land coverchange can be more important than the percentage of landcover change.

A better crop management (scenario 4, Table 2) leads toa linear decrease of the mean soil erosion rate. The model

0

0.2

0.4

0.6

0.8

1

0 10 20 30 40 50

Parcel size (ha)

frac

tion

eros

ion/

sedi

men

t del

iver

y co

mpa

red

to S

0

Impact of parcel sizeon erosion

Impact of parcel sizeon sediment delivery

Fig. 6. Relative impact of parcel size in the Orlice drainage basin on soil

erosion and sediment delivery (S0 ¼ 0%).

0

0.2

0.4

0.6

0.8

1

0 5

Converted ar

frac

tion

eros

ion/

sedi

men

t del

iver

y co

mpa

red

to S

0

Impact of random conversion arable

Impact of planned conversion arable

Impact of ad random conversion ara

Impact of planned coversion arable

Fig. 7. Relative impact of random and planned conversion of arable land to

(S0 ¼ 50 ha).

simulations show a slight increase in the sediment deliveryratio if the RUSLE C factor is lowered. This can beexplained by the fact that at some places in the drainagebasin the sediment flux is transport capacity limited. If thesediment production is lowered, a larger fraction of theavailable sediment will be transported at these places.

Conclusion

Landscapes in the Czech Republic are characterized bysignificant changes in the recent past. In many regions theconversion from collective to private farming systems is notyet fully completed. The recent EU enlargement will be animportant catalyst for new land cover changes. During thelast decade the levels of mean sediment export fromagricultural drainage basins decreased significantly due toland abandonment and the splitting up of collective arableland. It is, however, not guaranteed that this positive trendwill be maintained when the local agricultural production isfully integrated into the European market. Thereforelandscape reorganization will be one of the main issues inthe new EU-member states in the near future. Thedevelopment of a sustainable land management policyrequires the necessary tools to predict the impact ofpossible policy options on socio-economic and environ-mental processes.This paper explored the impact of four possible future

land use change scenarios in the Orlice drainage basin inthe north of the Czech Republic. The results show that areduction of the field size to an average of 30 ha wouldreduce the mean annual sediment delivery by more than30%. Other possible erosion control measures are theconversion from arable land to pasture on the most criticalplaces or modified crop management. The simulations

10 15 20

able land (in %)

land to pasture on erosion

land to pasture on erosion

ble land to pasture on sediment delivery

land to pasture on sediment delivery

pasture in the Orlice drainage basin on soil erosion and sediment delivery

ARTICLE IN PRESSA. Van Rompaey et al. / Land Use Policy 24 (2007) 576–583 583

suggest that modified crop management is more effective tolower mean soil erosion rates than the sediment delivery.Taking the steepest parcels out of production is the mosteffective way to lower the mean annual sediment export.The results show that the spatial pattern of change seems tobe more important than the percentage of change, whichencourages the development and application of spatiallyexplicit land cover change models.

Acknowledgements

Financial support for this research was provided by theFund for Scientific Research—Flanders. The work done bythree referees is greatly acknowledged; their comments andsuggestions significantly improved this manuscript.

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