Ecological Modelling 154 (2002) 251–262

Calibration and application of FOREST-BGC in aMediterranean area by the use of conventional and remote

sensing data

M. Chiesi a,*, F. Maselli a, M. Bindi b, L. Fibbi c, L. Bonora d, A. Raschi a,R. Tognetti e, J. Cermak f, N. Nadezhdina f

a IATA-CNR, P.le delle Cascine, 18-50144 Firenze, Italyb DISAT-Uni�ersity of Florence, Firenze, Italy

c LaMMA-FMA, Campi Bisenzio, Firenze, Italyd CeSIA-Accademia dei Georgofili, Firenze, Italy

e Dipartimento SAVA, Uni�ersity of Molise, Campobasso, Italyf Institute of Forest Ecology, Mendel Uni�ersity of Agriculture and Forestry, Brno, Czech Republic

Received 3 August 2001; received in revised form 4 January 2002; accepted 4 March 2002

Abstract

The current work deals with the use in a Mediterranean environment of a simulation model of forest ecosystemprocesses which was originally created for temperate areas (FOREST-BGC). The model was calibrated and appliedon two deciduous forest stands in Tuscany (Central Italy) by using conventional and remote sensing data as inputs.First, information on the two stands needed to initialise the model was derived from different sources, whilemeteorological data were extrapolated from a nearby station by an existing procedure (MT-Clim). Temporal profilesof leaf area index (LAI) were then derived both from direct ground measurement and from the processing ofNOAA-AVHRR NDVI data. The model was calibrated using stand transpiration values obtained for 1997 by a sapflow method. Next, its performances were tested against the same transpiration values measured in 1998. The resultsobtained indicate that FOREST-BGC is capable of simulating water fluxes of Mediterranean forests when suitableLAI profiles are considered. Moreover, the derivation of these profiles from NDVI data can improve the modelperformance probably due to an enhanced consideration of the effects of the typical Mediterranean summer waterstress. These results support the final objective of the work, which is the development of a procedure capable ofintegrating conventional and remote sensing data to operationally simulate water and carbon fluxes on a regionalscale. © 2002 Elsevier Science B.V. All rights reserved.

Keywords: FOREST-BGC; Remote sensing; Oak forest; LAI

www.elsevier.com/locate/ecolmodel

* Corresponding author. Tel.: +39-055-354-895; fax: +39-055-350-833.E-mail address: foremms@iata.fi.cnr.it (M. Chiesi).

0304-3800/02/$ - see front matter © 2002 Elsevier Science B.V. All rights reserved.

PII: S0 304 -3800 (02 )00057 -1

M. Chiesi et al. / Ecological Modelling 154 (2002) 251–262252

1. Introduction

During the last decades there has been an in-creasing interest for modelling parameters andprocesses of different ecosystems. This is a newapproach to ecological studies which can be par-ticularly useful to obtain information on widespatial and temporal scales (Waring and Running,1998). The importance of environmental mod-elling is also linked to the necessity of being ableto detect and study the effect of large-scale pertur-bations such as global climate change and airpollution on forest and other terrestrial ecosys-tems. The estimated parameters, and in particularthose related to the main vegetation processessuch as transpiration, photosynthesis and produc-tivity, can be a valid support to all decision-mak-ers dealing with problems of managingenvironmental resources.

Even though modern models of ecosystem pro-cesses have reached high efficiency and accuracy,their applicability to operational cases is oftenlimited by the fundamental drawback of requiringinput parameters which are difficult to collect forlarge vegetated areas. This is especially the casefor the parameters describing forest compositionand structure, such as tree species, density, leafarea index (LAI), which are generally highly vari-able in space and/or time and difficult to measurewith conventional methods (Lacaze et al., 1996).The same parameters are however those which aremore directly linked to the spectral properties ofvegetation, so that remote sensing techniques havebeen recently proposed as a promising source ofinformation for modelling forest ecosystem pro-cesses (Running et al., 1989; Lucas et al., 2000).

The current work builds on these consider-ations and investigates the possibility to apply inMediterranean environments a model of forestecosystem processes (FOREST-BGC) driven byconventional and remote sensing data. FOREST-BGC was chosen for its wide applicability and forits suitability to accept data from differentsources, and specifically from remote sensing im-ages (Running and Coughlan, 1988). The applica-tion of FOREST-BGC in Mediterranean areas ishowever a challenge, since the model was origi-nally proposed and developed for simulating the

main processes of coniferous forests under a rangeof climates (Running and Coughlan, 1988). Somemodifications were therefore needed to adapt themodel to a different climatic situation and forestecosystems composed of deciduous species. Addi-tionally, in order to face the problems related tothe topographic and land use variability of theseenvironments, a new methodology had to be de-veloped for deriving suitable inputs to the modelby the integration of remotely sensed and ancil-lary data.

The current work was carried out in a primarytest site of the EU Projects ‘‘Remote Sensing ofMediterranean Desertification and EnvironmentalStability’’, (RESMEDES) and ‘‘Synthesis ofChange Detection Parameters into a Land-surfaceChange Indicator for Long Term DesertificationStudies in the Mediterranean Area’’(RESYSMED) (Bolle, 1998, 1999). As it will beseen later in more detail, this is a hilly areaaround the Radicondoli village in Tuscany (Cen-tral Italy) mostly covered by deciduous woods.The investigation was focused on two stands cov-ered by two oak species representative for most oflocal tree species. The parameters that are neces-sary to initialise and drive the model were col-lected from forestry literature, the ForestManagement Plan of the area and field measure-ments. In particular, daily meteorological data(minimum and maximum temperature, rainfalland radiation) were extrapolated from an adja-cent station, while monthly LAI profiles weredirectly measured in the two stands. Additionally,LAI estimates of the two stands were obtainedfrom NOAA-AVHRR NDVI data using an inte-gration procedure previously developed (Lacaze etal., 1996; Maselli, 2001). All these data served todrive FOREST-BGC for the growing season of 2years (1997–98) for which ground transpirationmeasurements were available, obtained by a sapflow method (Cermak et al., 1998). More particu-larly, the transpiration values from the first seasonwere used for calibrating the model, while thoseof the second year were used for its testing.

The present work is organised as follows. First,a brief introduction to the functionality ofFOREST-BGC is provided. The next sectiondeals with a description of the study area anddata. The methods to retrieve the input data for

M. Chiesi et al. / Ecological Modelling 154 (2002) 251–262 253

the application of the model to two forest standsare then presented. Next, the calibration and val-idation of the model by comparison to dailymeasured transpiration values are described. Dis-cussion and conclusions finally follow on the po-tential application of the model to monitor waterand carbon fluxes through vegetation over wideMediterranean areas.

2. The model FOREST-BGC

The model FOREST-BGC was developed atthe University of Montana (Running andCoughlan, 1988) where it had been originallyapplied to coniferous forest stands. It works sim-ulating water, carbon and nitrogen fluxes withinhomogeneous forests. The model requires dailyclimate data (minimum and maximum air tem-perature, precipitation, solar radiation and va-pour pressure deficit) and general informationabout the stands (latitude, soil depth, soil watercontent) to which it is applied. In addition tothese variables, it needs about 50 parameters de-scribing the ecophysiological behaviour of thespecies characterising the forest stands (Waringand Running, 1998).

The original model has been recently modifiedto improve its performances when applied to de-ciduous forests. While in fact the original ver-sion, suitable for evergreen forests, uses aconstant value of LAI for the whole year, thenew version can receive daily values of LAIderived from various sources (Maselli et al.,1999). This additional information is expressedas leaf carbon content derived by the LAI andsurface leaf area (one of the ecophysiologicalparameters required as input by the model). Themodification is based on the idea that LAI is themost important parameter describing the struc-tural characters of the canopy (mainly leaf den-sity and biomass) and, indirectly, of all processesconnected with it: evaporation, transpiration,photosynthesis, and so on (Waring and Running,1998; Nemani and Running, 1989). Additionally,LAI, together with climate data, has been indi-cated as one of the most important variablesforcing and driving models of forest ecosystem

processes (Running and Coughlan, 1988; Run-ning and Hunt, 1993). The outputs estimated bythe model are about the most important eco-physiological parameters characterising the car-bon, nitrogen and water fluxes within terrestrialecosystems. In particular, the model estimatesdaily values of transpiration (mm/d), photosyn-thesis (gC/ha) and respiration (gC/ha), which areessential elements to compute land water andcarbon budgets.

3. Study area and data

3.1. Radicondoli area

The Radicondoli area (43°10�–43°18�N lat.,10°58�–11°10�E long.) is situated in the centre ofTuscany, Central Italy (Fig. 1). The terrain ofthe area is mainly hilly, with elevation rangingfrom 300 to 900 m. The climate is Mediterraneansub-humid (Rapetti and Vittorini, 1995), withmean annual rainfall around 800 mm, tempera-ture around 15 °C, mild winters and long drysummers.

The land cover is characterised by the alterna-tion of agricultural fields, pastures and wood-lands. Two main forest areas were present, whichcover about 70% of the land surface. Both areasare dominated by diverse deciduous species, withthe presence of some conifers (mainly pines) ar-tificially introduced to increase land productivity.Among the deciduous species, two Mediter-ranean oaks, Quercus pubescens Willd. and Quer-cus cerris L., are by far the most common, butother broadleaved species can also be found suchas Ostrya carpinifolia Scop., Acer campestre L.and Fraxinus ornus L.. The understorey layer isgenerally characterised by the presence of youngtrees of the main dominant species (especiallynatural regeneration) and shrubs of different spe-cies (i.e. Cornus sanguinea L., Rubus caesius L.,Juniperus communis L. and others).

Our work was carried out in two oak standsselected as representative for the main foresttypes of the area. In particular, the first stand(stand A) is dominated by Q. cerris L. and thesecond (stand B) by Q. pubescens Willd.

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3.2. Ancillary data

Topographic maps (1:25 000) produced by theItalian Military Geographic Institute (IGMI) wereavailable for the whole area. The same Institutealso provided a digital elevation model (DEM) inthe form of raster images with a pixel size of20×20 m, derived from contour lines every 25 m.Land cover information was derived from theland cover classification produced during the EUProject CORINE at a nominal scale of 1:100 000(Annoni and Perdigao, 1997). The CORINEnomenclature is hierarchical and comprises threelevels common to all countries, with five cate-gories for the first level, 15 for the second, and 44for the third (Annoni and Perdigao, 1997). Theclassification provided by the Tuscany RegionalService for Cartography in the form of a vectorfile with a nominal scale of 1:100 000 was used inthe current study.

Additional information for the study forestswas obtained by digitising 1:10 000 scale mapsproduced by DREAM (1994) for the Forest Planof Management of the area. This document con-

tains a brief description of each forest stand in thearea, including terrain and soil conditions, treespecific composition, density, volume, mean treeheight, etc. According to this description, the twostudy stands have the following characteristics:1. Stand A is dominated by the presence of Q.

cerris L. with an average height of 16.0 m anddiameter at breast height (DBH) of 14.4 cm;the estimated age is of 42 years;

2. Stand B is dominated by Q. pubescens Willd.with height of 11.0 m and DBH of 12 cm; theestimated age is of 45 years.

In both cases they are natural high forestsderived from old abandoned coppice.

3.3. Meteorological data

Since no meteorological station has been con-tinuously active within the study area in the lastyears, the main source of meteorological data wasthe station of Larderello (altitude 400 m). Thisstation, belonging to the network of the ItalianNational Hydrological Institute, has been collect-ing daily values of maximum and minimum tem-

Fig. 1. NOAA-AUHRR NDVI image of August 1998, showing the position of the study area (Radicondoli) in Central Italy.

M. Chiesi et al. / Ecological Modelling 154 (2002) 251–262 255

perature, and precipitation since 1951. In addi-tion there are shorter data series collected by aportable station installed at the beginning ofRESMEDES (spring 1996) within the Radicon-doli forest area, at Collitalli (43°15�3�� N lat.–11°03�29�� E long.; altitude 485 m). This stationmeasures a wider series of daily parameters (soiltemperature, wind speed and direction, air tem-perature, air humidity, precipitation and solarradiation), but its activity has not been continu-ous, so that only incomplete data series arepresently available.

3.4. Ground data: measurements of LAI

LAI data were collected monthly during thegrowing seasons from 1996 to 2001 in fourteenforest stands which comprised the two oakstands used in the current study. The LAI mea-surements were carried out using a LAI-2000Plant Canopy Analyser (Li-Cor, NE, USA).Each stand was characterised by taking six opti-cal measurements along linear transects of about50 m. A calibration of the LAI values obtainedby LAI-2000 was preliminarily performed forthe main tree species by collecting the leaves andmeasuring their surface area with a planimeter.A factor was thus obtained for each tree speciesfor the possible correction of the LAI-2000 esti-mates.

3.5. Ground data: measurements of transpiration

Transpiration (actually sap flow) was mea-sured during the growing seasons 1997 and 1998in selected parts (about 1 ha) of the two studystands. Twelve sample trees per stand were cho-sen, which size (DBH) was calculated as repre-sentative on the basis of quantils of total for allspecific diameter classes; in particular, each sam-pled tree had to represent approximately thesame fraction of the stand basal area (Cermakand Kucera, 1990). Sap flow was measured atbreast height (1.3 m) from two opposite sides ofstems in smaller trees and four in larger ones.Two different methods to determine the sap flowrate were used according to the diameter of the

sampled trees: for large ones (DBH more than15 cm, as recommended by the producer) thestem segment heat balance method (THB, Cer-mak et al., 1973, 1982; Kucera et al., 1976) andfor smaller trees (DBH�15 cm) the heat fielddeformation method (HFD, Nadezhdina andCermak, 1998; Nadezhdina et al. 1998). Datawere measured every minute and stored in 15min intervals using the EMS-measuring systems(Ecological Measuring Systems, Brno, Czech Re-public) for large trees and custom built data log-gers for small trees. Integration of data fromindividual measuring points to the whole treeswas done on the basis of the radial pattern offlow measured in all studied stem sections(Nadezhdina et al., 2002), so that the conductingsystem in each stem (cross-section area of sap-wood) was characterised by 24 (or more) points.The sap flow values integrated for the whole treelevel in all sample trees were up-scaled for thestand level according to Cermak and Kucera(1990) and Cermak et al. (1998). Tree sap flowdata were related to their basal area in eachparticular day and from the obtained curve tran-spiration of mean trees of DBH classes werecalculated. These were multiplied by numbers oftrees in classes per 1 ha and summarised.

3.6. Satellite images

The satellite data used in the investigationwere AVHRR images transformed in NDVIform, kindly provided by the University ofBerlin within the RESYSMED Project (Bolle etal., 1999). The original data were 10-day NDVIMaximum Value Composite (MVC) images of 6years (1993–98), mapped in a geographic (Lat/Long) reference system with a 0.01° pixel size(Bolle et al., 1999). The standard procedure forthe production of these data comprised thegeoreferencing of the original images by anearest neighbour algorithm, the radiometric cal-ibration of the first two bands to derive appar-ent reflectances following Bolle et al. (1999), andthe computation of NDVI values to finally ob-tain the MVC on a 10-day basis (Holben, 1986).The final products were therefore 36 10-day

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NDVI MVC images for each of the 6 availableyears, which were used for the current analysis.

4. Data processing

As previously explained, the performances ofdifferent versions of FOREST-BGC were evalu-ated against the sap flow transpiration measure-ments which were available for the two studystands in 1997 and 1998. The model was appliedin both stands using inputs from different sources,with particular attention to the effect of LAIvalues. The measured transpiration data from thefirst year (1997) were used for model calibration,and those from the second year (1998) for modelvalidation. These tests required the preliminarilyprocessing of all ancillary and satellite data, whichare described in the following sections.

4.1. Simulation of meteorological data for theforest test sites

The first step concerned the extrapolation ofthe meteorological data needed for the modelfrom the records of the available station (Larde-rello). This station was actually quite far from thestudy stands and at a different altitude. Thus, thetemperature and rainfall values at these standswere extrapolated by the application of the modelMT-Clim (version 4.3, Thornton and Running,1999). This model was developed to provide mete-orological data for a ‘site station’ that is situatedat a different location with respect to the ‘basestation’, for which all meteorological parametersare known. The model was applied consideringthe different characteristics of the two studystands, and particularly their topographical condi-tions (altitude, slope and aspect) and their annualrainfall averages. The application of the modelwas preceded by a test aimed at evaluating theexpected accuracy of the meteorological data ex-trapolation. The test consisted in the simulationof some daily meteorological data at the Collitalliportable station from those of Larderello and inthe subsequent comparison of the simulatedagainst the actual data using RMSE and determi-nation coefficient (r2) as accuracy statistics.

4.2. Deri�ation of LAI profiles from differentsources

As previously mentioned, a major objective ofthe current research was the evaluation of theeffect of different LAI inputs for the applicationof FOREST-BGC in Mediterranean areas. Testswere therefore carried out to assess the perfor-mance of different model versions when usingfixed, measured or estimated LAI inputs. First,the correction factor found with the planimeter(1.25) was applied to all LAI values measured bythe LAI-2000 instrument. Since the model needsdaily LAI values, the corrected monthly LAI mea-surements were then interpolated by a linearapproximation.

The derivation of LAI values from NDVI datawas performed by a multi-step procedure basedon previous methodological works. First, the 10-day NDVI MVC images were further composedover monthly periods, in order to reduce residualatmospheric disturbances (Holben, 1986). Next,forest NDVI profiles were extracted from theimages and then converted into LAI values after acalibration of the relevant relationship (Maselli,2001; Lacaze et al., 1996). The extraction of forestNDVI values from the monthly images was car-ried out using the locally calibrated multivariatelinear regression methodology proposed byMaselli (2001). This is a method which can esti-mate spatially variable spectral signatures (orNDVI values) of pure class on the basis of theknowledge of the cover fractions of the classeswithin each study pixel. In the current case themethod was applied using the class cover fractionsderived from the CORINE map, obtaining pureforest NDVI monthly images from which profileswere extracted in correspondence of the two studystands.

The conversion of these forest NDVI into LAIprofiles was performed according to a generalBeer’s equation already applied for Mediter-ranean oaks by Lacaze et al. (1996), which is:

LAI= −1/K�ln� NDVIcan−NDVI

NDVIcan−NDVIback�

(1)

As can be seen, this equation uses three coeffi-cients, K, NDVIcan and NDVIback. The last two

M. Chiesi et al. / Ecological Modelling 154 (2002) 251–262 257

were obtained directly from the study NDVI im-ages, considering the minimum and maximumNDVI values of the local forest areas. The Kcoefficient, which is related to the slope of therelationship, was instead considered as dependingon the density of each stand. NDVI is in factclosely related to forest canopy LAI only if thecrown cover is complete. In different cases theeffect of the understorey layer must be considered,since it influences the theoretical relationship be-tween NDVI and canopy LAI (Spanner et al.,1990). While in fact NDVI depends on the spec-tral response of all trees, shrubs and grasseswithin the stand, forest LAI as measured by thePlant Canopy Analyser corresponds only to treecanopies, which is also the layer simulated byFOREST-BGC. The conversion of NDVI intotree canopy LAI must therefore be performedafter specific calibration of the K coefficient foreach study stand with uncompleted crown cover.In practice, the coefficient becomes higher as thecanopy closure is lower and the contribution ofthe understorey increases. In the current, the defi-nition of K for each study stand was obtained byregressing the logarithm right term of Eq. (1) overthe relevant LAI values for the available data of1996, 1997 and 1998.

4.3. Calibration and �alidation of FOREST-BGC

The application of the model was preceded by acalibration and setting-up phase aiming at identi-fying the optimal configuration for the simulationof the two oak ecosystems. For this objective, theparameters describing the study forest stands werefirst retrieved by the Forest Management Plan(DREAM, 1994) and by the digital elevationmodel of the area. Next, ecophysiological parame-ters describing the characters of the species werederived from existing literature, with particularreferences to the works describing the use ofFOREST-BGC (Running and Coughlan, 1988;Running and Gower, 1991; Waring and Running,1998). From this bibliographic investigation it wasfound that the modification of one parametercould be sufficient to adapt the model for theecosystems considered when joint to the use oftemporally variable LAI profiles. This parameter

was ‘maximum canopy average leaf conductance’,which is obviously in strict connection with thetranspiration behaviour of the tree species andcan therefore control their xeric nature.

The identification of the optimal leaf conduc-tance for the two species was carried out by usingthe transpiration measurements of the 1997 grow-ing season, which, though rather incomplete, weredeemed to be sufficient for this aim. In practice,FOREST-BGC was run using the above men-tioned ancillary data with the original configura-tion (Running and Coughlan, 1988) but withmaximum canopy average leaf conductances vary-ing within acceptable ranges as defined by Jones(1992). Since the effect of using different LAIinputs was also to assess, the calibration wasrepeated using the three model versions with dif-ferent LAI inputs, and in particular:1. the original version that considers fixed LAI

values during the growing season;2. the modified version that uses variable daily

LAI values derived by the linear interpolationof the monthly ground measurements;

3. the modified version using daily LAI valuesderived from NDVI profiles by the procedurepreviously described.

The simulated transpiration values were thencompared to the available measured values of1997 in order to find error minima which could beindicative of the optimal model configuration.The configuration found was then used for themodel simulation of the two stands in 1998, withthe transpiration outputs again compared to themeasured values for final validation.

5. Results

5.1. Simulated meteorological data

The results of the comparison between dailymeteorological data measured and simulated byMT-Clim at the Collitalli station are summarisedin Table 1. As can be seen, minimum and maxi-mum temperatures were extrapolated with muchhigher accuracy than rainfall. This can be easilyexplained bearing in mind that the formerparameters are distributed rather homogeneously

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Table 1Results obtained by the application of MT-Clim to the Collitalli station using Larderello as base station

Year 1996 1997 1998

RMSE r2 RMSE r2 RMSEr2

2.47 °C 0.49Max T 3.53 °C0.88 0.83 4.34 °C1.87 °C 0.61 1.71 °CMin T 0.870.91 1.84 °C7.41 mm 0.35 6.57 mm0.15 0.14Precipitation 6.21 mm

All statistics are referred to daily values.

on the land surface, mainly depending on thealtitudinal gradient which is considered in MT-Clim. On the contrary rainfall shows much higherspatial and temporal variability and less cleardependence on altitude, which explains the loweraccuracy obtained by MT-Clim. All parameters,however, were approximated much better whenconsidering longer time periods (1 week ormonth) which are more significant for the modelworking. Thus, it was concluded that the extrapo-lation accuracy was sufficient for our scope, andthe procedure was used for all subsequentsimulations.

5.2. Measured and estimated daily LAI profiles

The LAI profiles measured and derived fromNDVI data by the procedure described are shownin Fig. 2. As can be noted, stand A has generallyhigher LAI than stand B, mainly dependent on itshigher tree density. In this situation, the calibra-tion of Eq. (1) for each stand was clearly neces-sary to approximate the real LAI values fromNDVI data, due to the influence of the under-storey on the NDVI/LAI relationship. In particu-lar, in accordance with the previous discussion, aK value of 0.283 was obtained for the denserstand (A), while a value of 0.417 was obtained forthe other stand. The former K value is slightlyhigher than those reported in the literature forsimilar environments (0.2–0.22, Lacaze et al.,1996), which indicates an almost complete standcanopy closure, while the latter value is muchhigher than these, implying a strong contributionof the stand understorey to the NDVI signal.

The results of using modified K coefficients forthe two stands was a rather accurate estimation of

their real LAI values, even if with an anticipationof the LAI peak from July to June. The reasonsand implications of this last fact for model work-ing will be discussed in the conclusions.

5.3. Calibration of the model

The results of the model calibration are visiblein Fig. 3a–b for the two stands as root meansquare errors (RMSE) of the estimated versus themeasured transpiration data available for 1997.The first graph (stand A) shows that the errorscoming from the use of the model with fixed andvariable measured LAI were generally higher thanthose coming from the model with variable LAIderived from NDVI data. All errors had a ratherclear minimum, which corresponded to slightly

Fig. 2. Averaged LAI values of the 3 study years (1996–98)measured (…) and computed by Eq. (1) (– – – ) in the Quercuscerris and Quercus pubescens stands.

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Fig. 3. Transpiration RMSEs obtained using three differentversions of the model; *, errors with constant LAI during thegrowing season; �, errors with measured LAI; and �, thosewith LAI derived from NDVI. (a) Quercus cerris and (b)Quercus pubescens.

spiration measurements for this stand were actu-ally very few, which limited the accuracy of theerror analysis with respect to the variations ofstomatal conductance. In consideration of thisfact, the same method as before for providingLAI values to the model was assumed to be thebest, and the optimum configuration was againidentified as that with LAI derived from NDVIdata and stomatal conductance equal to 0.0026 ms−1.

5.4. Validation of the model

The simulated daily transpirations obtained for1998 from the model runs with the best configura-tion (variable LAI profiles derived from NDVIand optimum stomatal conductance; i.e. 0.0027m/s for Q. cerris and 0.0026 m/s for Q. pubescens)

Fig. 4. Measured (�) and estimated (�) daily values oftranspiration obtained for the growing season 1998 for the twostudy stands. (a) Quercus cerris and (b) Quercus pubescens.

different stomatal conductance for the three simu-lations. The best model configuration was thatwith LAI derived from NDVI data and stomatalconductance equal to 0.0027 m s−1.

Similar results were obtained for stand B, wheresimilar pattern of error minima was found regard-ing the three LAI inputs (i.e. minimum corre-sponding to higher stomatal conductance forvariable LAI from NDVI). In this case, however,all LAI inputs produced almost the same errorminima, so that the best LAI inputs cannot beclearly determined. As a possible explanation forthis fact it can be mentioned that the daily tran-

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are shown in Fig. 4a–b together with the sap flowmeasurements. As can be seen, the model wasvery efficient in simulating daily evapo-transpira-tion for these stands, obtaining very accurateestimates for the whole study period (r2=0.861,RMSE=0.457 mm/day for stand A and r2=0.875, RMSE=0.264 mm/day for stand B). Theagreement between measured and simulated val-ues was particularly good for Q. cerris, whichshowed a wider range of transpiration valueswhich can be reasonably attributed to its higherLAI and stomatal conductance. The comparisonof the accuracy values currently obtained withthose found in previous works will be carried outin Section 6.

6. Discussion and conclusions

The current study investigated on the applica-tion of a model of forest ecosystem processesintegrated with remote sensing inputs for evaluat-ing transpiration fluxes of Mediterranean forests.From the results obtained the following mainconclusions can be drawn:� MT-Clim can estimate all meteorological

parameters that are necessary to initialiseFOREST-BGC, even if with a certain approxi-mation. The only necessary operations to usethis model are the collection of general envi-ronmental information about the sites forwhich the simulation is required. More accu-rate procedures could however be useful, espe-cially for the extrapolation of rainfall which isa particularly crucial parameter in Mediter-ranean areas.

� The efficient methodology applied to processNOAA-AVHRR NDVI data allowed the ex-traction of the NDVI profiles of the two studystands. These profiles were then converted intoLAI values by stand-specific calibrations of ageneral NDVI/LAI relationship. These calibra-tions were necessary due to the medium-lowdensity of the two stands considered, whichdetermined incomplete closures of the treecanopies. On the contrary, the collection ofground data could be avoided in most cases ofdense forests by using coefficients reported inthe literature (Lacaze et al., 1996).

� In general, it was shown that the modelFOREST-BGC can simulate Mediterraneanforest ecosystems if appropriate eco-physiologi-cal parameters and LAI profiles are used. Thislast parameter, in particular, is determinant incontrolling the main bio-geo-chemical pro-cesses of Mediterranean vegetation, since itforces the model to work with appropriatetranspiring and photosynthesising leaf surfacesalso during the arid season, which would benot the case when using the original modelconfiguration that was conceived for temperateforests.

� The necessary LAI profiles can be derived bothfrom ground measurements and from NDVIdata after suitable calibration. A remark isworthwhile on the latter possibility, since itseems to improve the sensitivity of the modelto the local Mediterranean features, as demon-strated by the generally lower transpirationerrors obtained during the calibration phase bythe use of NDVI-derived LAI profiles. It mustbe recalled, in fact, that LAI derived fromNDVI is actually more related to plant photo-synthetic activity than only to leaf area, in thissense being actually a ‘green’ LAI (Spanner etal., 1990). This causes, in Mediterranean areas,the green LAI to show a typical peak in latespring, followed by a decrease due to summeraridity, which is not visible in the measuredLAI values. In practice, this behaviour canenhance the coupling of the LAI profiles withthe actual transpiration and photosynthesisprocesses, which tends to improve the wholemodel functions during summer aridity. This isalso confirmed by the higher leaf conductancefound as optimal when using LAI from NDVI(see Fig. 3) with respect to the other cases.Indeed, the greater adaptability of the modelwith remote sensing inputs allows generallyhigher transpiration values during the summerseason, which are better in accordance withground measurements.

� By using the optimal model configuration (i.e.with most suitable leaf conductance and LAIprofiles derived from NDVI data), the accuracyobtainable is comparable to those reported inthe literature from similar studies. This com-

M. Chiesi et al. / Ecological Modelling 154 (2002) 251–262 261

parison, however, is generally not easy sincethe methods used to obtain and evaluate waterfluxes are very different and there are fewexamples of model validation against measuredvalues at the stand level (Bosveld and Bouten,2001; Iritz et al., 1999; Meiresonne et al., 1999;Gash et al., 1999; Granier et al., 2000). Amongthese examples, we can mention the work ofGash et al. (1999), who compared daily tran-spirations obtained by eddy covariance tech-niques to transpirations simulated by theRutter model. Their work was carried out in anenvironment dominated by the presence of pinetrees and the comparison gave a determinationcoefficient of 0.90. In a different environment,Meiresonne et al. (1999) compared seasonaltranspiration measured by the sap flow ratemethod and estimated by the WAVE waterbalance model. Their work was carried out in apoplar plantation in Belgium and the resultsshowed a good agreement between total mea-sured and simulated values (simulated transpi-ration of 311 mm against measured of 329mm).

� The possibility of efficiently using LAI dataderived from remotely sensed images is particu-larly attractive from an operational point ofview. This in fact indicates that proper simula-tions could be obtained by running the modelwithin a GIS system which integrates conven-tional and remote sensing data. Thus, the cur-rent findings seem to open the possibility ofimplementing an automatic version of themodel running on a regional scale, which is thefinal direction of our research efforts.

Acknowledgements

The authors wish to thank Piero Battista andLjiljana Petkov for their technical assistance inmeasuring LAI and Valeriy Nadezhdin for hiscare about sap flow instrumentation. This re-search has been supported by the EU ProjectsRemote Sensing of Mediterranean Desertificationand Environmental Stability (RESMEDES) andSynthesis of Change Detection Parameters into aLand-Surface Change Indicator for Long Term

Desertification Studies in the Mediterranean Area(RESYSMED).

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