GeoJournal 57: 203–209, 2002.© 2003 Kluwer Academic Publishers. Printed in the Netherlands.

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Climate change impacts in Romania: Vulnerability and adaptation options

Vasile Cuculeanu1, Paul Tuinea1 & Dan Balteanu2

1National Institute of Meteorology and Hydrology, Sos.Bucuresti-Ploiesti 97, 71552 Bucharest, Romania; 2Institute ofGeography, Str. D. Racovita 12, Sector 2, RO-70307 Bucuresti-20, Romania

Key words: agricultural crops, climate change, forests, impact, water resources

Abstract

Using the output from five climate model experiments (four equilibrium GCMs and one transient GCM) for a double carbondioxide atmospheric concentration, the climate change scenarios in Romania for a time slice up to 2075 were constructed.These scenarios were used to assess the climate change impacts on different resource sectors: agricultural crops, forests,and water resources. The vulnerability of each sector and specific adaptation options were then analysed.

Introduction

Scientific evidence has already established that increases inatmospheric concentrations of greenhouse gases may leadto irreversible changes in the climate (Houghton et al.,1996). Sufficient evidence indicates that climate changecould have a significant impact on agriculture, forests, andwater resources, particularly in regions with high present-day vulnerability and little potential for adaptation (Tegartet al., 1990).

The United Nations Framework Convention on ClimateChange (UNFCCC, UNEP/WMO) calls upon all countriesto assess the impact of climate change on different economicsectors so that the most vulnerable areas can be assessedand adaptation responses for climate change can be de-veloped. The majority of the results presented in this paperhave been collected within the framework of the RomanianCountry Study on Climate Change, which was establishedunder the US Country Studies Program (Cuculeanu, 1997).The basic principles behind the methodology used to assessthe impact of climate change are further explained in thebook Guidance for Vulnerability and Adaptation Assessment(US Country Studies Management Team, 1994). This studycontributes to current estimations of climate change at theregional scale.

Climate change scenarios

General Circulation Models (GCMs) are the most widelyused tools to develop climate change scenarios for impactassessment. The output of four equilibrium GCMs were ana-lyzed in order to select the models that best describe thecurrent climate in Romania. These four GCMs include: theGISS (Godard Institute for Space Studies), the GFDL R-30 (Geophysical Fluid Dynamics Laboratory, referred to asGFD3), the UK (United Kingdom Meteorological Office,

referred to as UK 89), and the CCCM (Canadian ClimateCenter Model, referred to as CCCM) (Hansen et al., 1983;Mitchell et al., 1990; Phillips, 1994). The transient GCMused in this analysis was the GFDL model (referred to asGFD1) (Manabe and Stouffer, 1993).

The model output necessary for impact assessment con-sisted of long-term monthly mean temperature and precipit-ation data derived by assuming the present level of carbondioxide (referred to as 1xCO2) and a doubling of the presentlevel of carbon dioxide (referred to as 2xCO2). Ten-yearstatistics for each month were also included in the transi-ent model runs as well. The baseline climate was definedas the long term (1961–1990) monthly averages of pre-cipitation and surface air temperature from one hundredmeteorological stations uniformly distributed over the Ro-manian territory. In order to select GCMs that best depictthe climate in Romania, the 1xCO2 runs were compared tothe observed climate (monthly mean temperatures and pre-cipitation) over a large area that included Romania, as wellas to the country’s baseline climate.

In regards to temperature, the CCCM and GISS modelsbest reproduce the climate in Romania, but the resolution ofthe GISS model is too low to represent the country’s geo-graphically extensive territory. The UK and GFD3 modelssimulate a much colder climate than the baseline. However,the GFD3 simulates a warmer climate than the baseline forsome warm months of the year.

The annual trends in temperature simulated by GCMs aregenerally similar to the baseline except for the GFD3, whichsimulates August temperatures warmer than July temperat-ures, and the UK 89, which simulates February temperaturescooler than January temperatures. On the whole, all modelssimulate a climate with more continental characteristics thanthe actual observed temperatures reflect.

In regards to precipitation, a more complex situation oc-curred. Certain models better simulate precipitation in some

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months than others. However, the UK89 and the GFD3give the most extreme differences between modeled andobserved precipitation trends. The UK89 most drasticallyoverestimates and the GFD3 most drastically underestim-ates. The annual precipitation trends in Romania are notaccurately simulated by any model. Generally, precipitationis overestimated for the cold months and underestimated forwarm months. CCCM gives the lowest differences betweenmodeled and observed precipitation trends. Therefore, it hasbeen concluded that this model best describes the currentclimate in Romania both for temperature and precipitation.

All climate models show that a doubling of the CO2concentration leads to the same climate signal, namely, in-creased air temperature in Romania. Thus, CCCM and GISSanticipate the increase of temperature ranging between 2.8–4.9 ◦C and 2.4–5.8 ◦C, correspondingly, depending on themonth. With regard to precipitation, CCCM simulates anincrease (20% on average over the country’s territory) duringthe cold season and a decrease (20%) during the warm sea-son. GISS generally shows an increase in precipitation forall months (except for September), the maximum increasebeing in October (40%). The new climate scenarios wereconstructed by adjusting the baseline data by the differences(for temperature) and by using a ratio (for precipitation)between 2xCO2 and 1xCO2 experiments.

Impacts on agricultural crops

In this section the potential impact of climate change onthe development, grain yield, and water balance for the keyagricultural crops are analyzed for 6 typical sites located inone of the most vulnerable zones in Romania – the south-ern region. In addition, the possible adaptation options forcrop management under anticipated climate changes are ex-amined. The vulnerability assessment was focused on winterwheat and maize because of their considerable importancein the agriculture of the area and because of the differencesbetween these crops’ genetic physiological responses to CO2concentration levels (winter wheat being a C3 crop andmaize a C4 crop). According to the climate change scenariosused in this impact assessment, the annual mean temperaturein the southern region of Romania is likely to increase by3.9–4.4 ◦C, with monthly variations of precipitation rangingbetween −47% and +81%. Precipitation will increase dur-ing autumn and winter and will decrease during the summer,depending on the site and crop season.

Crop simulation models

A number of crop growth simulation models (AR-FCWHEAT2, CERES, ACCESS) (Poster, 1993; Rounsevellet al., 1996; Godwin et al., 1989; Ritchie et al., 1989) wereused to estimate the effects of climate change on winterwheat and maize (a late-ripening cultivar). Three levels ofmanagement practices were considered in the assessmentprocess (Cuculeanu et al., 1999): (i) no fertilizer stress, wa-ter and temperature being the only factors affecting the crop

yield; (ii)‘ medium’ technology, allowing nitrogen and phos-phorus to drop to values that are compensated by fertilizeramounts currently applied on most farms in the region ofinterest; (iii)‘ low’ input technology with no applied fer-tilizer. The crop simulation models output were validatedat two reference sites – Fundulea, cambic chernozem, andCraiova, brown reddish soil – where the experimental cropyield data and 30-year climate series were available. In orderto assess the biophysical and economic impacts of climatechange, CERES models (Godwin et al., 1989; Ritchie et al.,1989) linked with the seasonal analysis program included inappropriate software DSSAT v.3.0 (Tsuji et al., 1994) wererun for 30-year baseline and modeled climates.

Impact on agricultural crops

The results of crop simulation models under equilibriumscenarios showed that the climate change impacts on winterwheat and maize development, grain yield, and water bal-ance depend on the local conditions of each site, the severityof climate parameters changes, and direct physiological ef-fects of the double CO2 concentration. Wheat and maizehave different photosynthetic pathways, so their responsesto increased CO2 are different.

Winter wheat could benefit from the combination ofCO2 concentration increases and higher temperatures, whilemaize appears to be vulnerable to these changes, especiallyin the case of a warm dry climate, such as simulated byCCCM. Wheat yields increased at all analyzed sites in twoclimate change scenarios as a result of large direct effects ofCO2 doubling on photosynthesis and water use.

In the case of ‘medium’ agricultural technologies (allow-ing nitrogen and phosphorus stresses to factor up to 50%),the crop models provided the following results for winterwheat:• both experiments (CCCM and GISS) induced grain yieldincreases in about 0.7 t ha−1 and 0.4 t ha−1, correspond-ingly;• no statistical differences were found between the standarddeviation of current yields and climate change projections.Therefore, the yearly variations in the yields under CO2doubling will be more or less the same;• the length of a growing season decreased by about 16–27days;• the water use efficiency increased by 47–57% as comparedto current conditions, mainly because of the increased CO2assimilation rate;• the economic risk analysis gives as dominant a non-irrigated agrotechnology, both for the current and changedclimates;• no significant changes in the yields under climate changeconditions (CCCM and GISS) were noted if the sowing datewas altered by 30 days before or after the present one;• all the selected sites show analogous trends in simulatedparameters.

The impact on maize differs between the two models anddifferent management practices used. Thus, the followingconclusions can be drawn about rain-fed maize:

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• the CCCM scenario resulted in a grain yield increase of1.4–2.1 t ha−1d.m.; the increase according to GISS was 3.5–5.6 t ha−1d.m. These data show that the CO2 assimilationrate reaches its maximum with the GISS projections of cli-mate change ;• the length of growing season decreased by 4–32 days withthe CCCM and by 2–26 days with the GISS models;• compared to the baseline climate, the precipitation sumfor a vegetation period decreased by 2–19% according toCCCM and increased by 1–18% according to the GISS scen-ario;• the total evapotranspiration during the growth periodslightly decreased at all sites for both scenarios (0 to 19%).

The following results were noticed about irrigated maize:• the average grain yield decreased by 4–15% with theCCCM scenario, depending on location. With the GISSscenario, the yield increased up to 18% at three sites andslightly decreased by 2–5% at the other three sites;• the water needs for irrigation increased from 17% to 52%in the CCCM model in locations where climate change in-duced significant water stress in the maize fields especiallyin the grain filling phase. However, the opposite situation oc-curred in the GISS scenario; irrigation efficiency increased.Compared to the baseline climate, use of irrigation waterdecreased at almost every site by an average of 14–29%.

Adaptation options

The above results show that maize productivity might bevulnerable to climate change. To evaluate alterations in theagricultural practices that could reduce the possible negativeeffects of climate change on irrigated maize production, fouradaptation options were analyzed: changes in crop varieties,sowing dates, crop densities, and fertilization levels.

The simulation results and economic risk analysis sug-gest the following dominant adjustment strategy: applicationof irrigation, use of late hybrids, sowing in the last 10 daysof April plant densities of 5 plants per m−2, and the increaseof nitrogen levels up to 120–160 kg ha−1.

The main effects on crop rotation options are:• in general, new climate conditions benefited all crop rota-tions;• the greatest benefits occurred in short crop rotations (singlecrop of wheat, wheat-maize);• use of mineral fertilizer increased by about 15–20% underexpected climate conditions when applied for the same levelof stress factor;• the benefit values for the best rain-fed management sys-tems under expected climate conditions were about the sameas those for the best irrigated technologies under the baselineclimate.

Impact on forests

Forests in Romania are mainly made up of deciduous spe-cies (69.3%). The remaining 30.7% of the forested areasare made up of resinous species. One of the basic principlesfor sustainable silviculture is to ensure continuity of wood–mass production prone to being harvested from exploitable

stands usually more than 100 years old. In view of this, itis desirable to have a normal age class structure with equalforested surfaces of each class.

The present Romanian forest structure includes an excessof the young age classes (1–60 years) and a deficiency inthe middle-age classes (61–80 years), the exploitable stands(over 100 years), and especially in the pre-exploitable standclasses (81–100 years). In order to assess the potential im-pact of climate change on forests, two approaches were used:the first was based on the Holdridge life zone classificationmodel, and the second, was based on a dynamical model thatpredicts the temporal evolution of species composition andproductivity as a function of climate parameters.

Holdridge model

The Holdridge model (Holdridge, 1947) relates in a simpleway to the vegetation pattern of climate change by usinga climate-vegetation classification procedure. By assumingthat the broad-scale patterns of vegetation (e.g., biomass)are at equilibrium in the present climate, the distribution ofmajor vegetation types can be correlated with biologicallyimportant climate features. The Holdridge life zone methodlinks vegetation distribution with such climatic variables asbiotemperature, mean annual precipitation, and the ratio ofpotential evapotranspiration to precipitation. This model issuitable for examining, on the one hand, broad-scale sens-itivity of vegetation to climate and, on the other hand, theinfluence of climate change on the suitability of a region fordifferent vegetation types.

The model does not take into account the specific ve-getation processes and as such it cannot be used to predictthe dynamics of species composition and stand productivity.The maps and associated databases relying on the Holdridgemodels for the current climate and projected climates showthe changes in land area associated with different categoriesof vegetation (e.g., forest).

The Holdridge life zones, derived by applying the modelto the baseline climate of Romania, are quite similar tothe existing forest distribution in the country (Figure 1).The maps corresponding to four equilibrium climate changescenarios are illustrated in Figure 2. The comparison ofmodeled vegetation life zones shows the relative concord-ance of CCCM, GFD3 and GISS models concerning theratio between different types of vegetation. All three scen-arios assign a share close to 50% of the country’s surfaceto the warm temperate thorn steppes. The warm temperatedry forests rank second in surface area, holding between16% (GISS) and about 26% (GFD3) of the country’s sur-face. The UK 89 scenario assigns the largest share of thecountry’s surface (55%) to this zone, while the warm steppe,ranking second, occupies about 38% according to this scen-ario. The cool temperate wet forest ranks third accordingto all scenarios, with percents between 3.7 (UK 89) and 10(other three). Regardless of scenario differences, signific-ant climate change will induce dramatic changes in the lifezones of Romania. Thus, the present life zones existing inthe plain areas will migrate towards higher altitudes and bereplaced by life zones specific to warmer climate conditions,

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Figure 1. Holdridge life zones under the baseline climate conditions.

perhaps like those existing nowadays in the southern BalkanPeninsula or in Asia Minor.

JABOWA model

A more advanced model simulating the temporal dynamicsof forests in response to environmental changes is JABOWAII (Botkin, 1993). For each plot-year of simulation, themodel determines the annual growth increment for each tree,stochastically adding new samplings and deciding whichtrees die out. The model output consists of the time evol-ution of the basal area and total biomass for different forestspecies as the function of both the climate conditions spe-cific to analyzed period, and the plot characteristics. Beinga dynamic JABOWA requires a transient scenario to char-acterize the time evolution of climatic variables. Thus, atransient GFD1 scenario was applied to three points in thecountry: Bistrita (in a hilly area), Predeal (in the mountains),and Bucharest (in the midddle of a plain). The transient cli-matic data for each point were obtained by a downscalingprocedure (Busuioc, 1996).

Beech forests prevail at the Bistrita station, fir forestsat the Predeal station, and oak forests at the Bucharest sta-tion. In order to estimate the effect of climate change onforest composition and productivity, particularly on the basalarea and total biomass, the JABOWA model was run withthe baseline climate parameters, as well as with the transi-ent climatic data for three decades specific to the NCAR-(National Center for Atmospheric Research) supplied data:2001–2010, 2031–2040, and 2061–2070.

If the present climate conditions remain constant in theBistrita area the biomass would display a slight decrease,followed by more obvious growth in the beginning of 2010and a tendency to stabilize around 2040. The same depend-ence was also obtained for the basal area. The simulations in-dicate a progressive growth in total biomass from 6.4 kg/msqto 28.3 kg/msq starting in 1990. Under future climate scen-ario conditions the time-dependence of the parameters offorest productivity is quite similar to that of the current cli-mate, until 2040. However, in the 2050s a severe decreasein both parameters is anticipated. As a result, biomass willdecrease from 27.8 kg/msq in 2040 to 6.6 kg/msq in 2060.Such a sharp fall in the forest ecosystem’s productivity is dueto enhanced aridization of the region caused by temperatureincreases and precipitation decreases, especially during thesummer months.

In the plain region (Bucharest station), the basal area andbiomass dynamics are very similar to the Bistrita zone. Thetransient scenario resulted in maximum values for both thebasal area (48 cmsq/msq) and the biomass (29.9 kg/msq)in 2040, followed by a decrease in the two parameters (by20 cmsq and 14.6 kg/msq, respectively) until 2060, and aslight increase in 2070.

In the mountainous area (Predeal station), small differ-ences occurred in forest productivity between baseline andmodeled climates. The spruce and fir forests of the moun-tainous zones seem to be less affected by climate change.The predominance of these species will be maintained evenuntil 2040. The oak forests in the lowest areas of the Ro-manian Plain near Bucharest as well as the hill area beechforests (e.g., Bistrita) seem to be more sensitive to climate

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Figure 2. Holdridge life zones for different climate scenarios.

change. The vulnerability of these forest ecosystems will in-crease considerably, especially after 2040, as a consequenceof temperature increases and associated water stress. Con-sequently, the productivity and protection capacity of theforest area will decrease.

Adaptation measures

To examine the possibility of transplanting species fromother geographic zones, JABOWA was run for species ofNorth-American flora. The results showed that red maple(Acer rubrum), white pine (Pinus strobus) and red oak(Quercus rubra) seem to have favorable development con-ditions according to the GFD1 scenario.

At present, in order to diminish adverse effects, the fol-lowing measures should be taken: augment the building ofstorage lakes and irrigation canals, create forest shelterbeltsin the low-forested areas, and achieve ecological rehab-ilitation of impaired forests. The application of extendedadaptation measures in the climate change-affected areaswill require huge expenses that exceed the possibilities ofsilviculture.

Impacts on water resources

Application of the model to the pilot basins

In order to estimate the impact of climate change on hy-drologic resources, a rainfall-runoff model was applied tothree pilot basins, representing mountainous, hilly, and plain

zones. The model was applied to two sets of input data: thefirst characterizing the actual climate and the second specificto the climate change scenario based on CCCM output. Theriver flow at the outlets of the pilot basins simulated by themodel for actual climate conditions and the climate changescenario were then transferred to several river sections in theanalyzed basins by an up-scaling procedure.

The VIDRA rainfall runoff model (Serban, 1987) usedfor the simulation of river flow under different climate con-ditions is a lumped type model. Consequently, the inputmeteorological data (precipitation and temperature) and themodel parameters should be considered as average valuesover a basin area. Such a condition may be met providedthat a basin area is sufficiently small–no more than a coupleof hundred square kilometers. Therefore, in order to ap-ply the VIDRA model as a first step in estimating climatechange impacts on hydrological resources, representativesmall basins, named pilot basins, were selected. Three basins(200–350 km2), located in representative mountainous, hilly,and plain areas (Poiana Tapului, Band, and Vartoapele,respectively) were chosen as pilots. The relief categoriesand pilot basins selected for the assessment of water re-source vulnerability and corresponding adaptation measureswere found in the basins of the Siret, Arges, and TarnaveRivers. In order to calibrate the model, the daily flows from1971–1988 were simulated for the pilot basins.

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Transfer of the simulated monthly flow series from the pilotbasins to the runoff-forming basins (reference basins)

The Siret and Arges River basins embrace two main zoneswith different hydrological behaviors: (i) the contributingzone, which supplies most of the total flow of the catchment;the corresponding basin of this zone is mainly hilly or moun-tainous; and (ii) the routing zone, where the contributionof the basin is minor although its area is significant. In theTarnave basin, the runoff is gradually formed over the wholecatchment area. The reference basin is a catchment corres-ponding to a contribution zone. An up-scaling procedure fortransferring the model output from the pilot basin to the ref-erence basin takes into consideration the relief configurationof the latter, which usually shows a quasi-gradual variationwith altitude. For those basins with a complex orography,the mean absolute altitude represents a morphometric char-acteristic that integrates the influence of all climatic andphysiographic factors upon the runoff formation. The riverand the basin slopes, the hydrographic network density, soilpermeability, vegetation, as well as the main climate factors(temperature and precipitation) are characterized by obvi-ous variations with altitude. Thus, the specific multiannualrunoff, defined as the ratio of the multiannual discharge tothe basin area, correlates well with the mean basin altitude.In addition, there is a good correlation between the meanaltitude and the long-term monthly mean specific discharge.By coupling the hypsographic curves with these statisticalrelationships, the monthly mean specific runoff for each re-lief zone of the reference basins were found. Then they wereintegrated to obtain the total runoff.

Impact on the hydrological resources in the referencebasins and in different points of the analyzed basins

It is important to note that the pilot basins are not locatedinside the reference basins and only represent the typicalrelief configurations (mountain, hill, and plain) that are sim-ilar to the landscape of the reference basins. Consequently,it must be assumed that the modeled meteorological inputdata applied to the pilot basins reflect the climate changefor reference basins. Therefore, the baseline temperatureand precipitation data for pilot basins were corrected in thedegree simulated by CCCM for the reference basins. Thecorrections were performed by averaging the values gener-ated by the CCCM model in certain points of each reliefzone.

Based on the pilot basin modeling with the up-scalingprocedure, the monthly discharge hydrographs at the outletsof reference basins were estimated. The main conclusionsthat were reached are as follows:• for the climate change with CO2 doubling, a decrease inrunoff occurs when compared to the present climate. Thiseffect can be explained by a significant increase in evapo-transpiration caused by the increase in air temperature, eventhough higher precipitation is anticipated in this scenario;• with CO2 doubling, a redistribution of the monthly meanrunoff is highlighted, with an increase in the monthly dis-charges’ coefficients of variation, as compared to present

characteristics;• the analysis of the monthly frequency of the discharges thatare above normal revealed that April has the highest decreasein maximum runoff;• the maximum monthly discharges shift from the spring andsummer months to the winter months because of expectedwinter warming that causes snow cover to melt at an earlierphase than the precipitation maximum (generally occurringApril–July );• the minimum monthly mean discharges shift from theOctober–January period to August–October as a result of airtemperature increases (greater evapotranspiration and soilmoisture decreases) and because of the marked precipitationdecrease in September.

Vulnerability and adaptation options

In order to assess the vulnerability of water resources underthe climate change conditions, the series of mean monthlydischarges in several points of the analyzed basins shouldbe tracked. These points refer to the locations of waterreservoirs and diversion and restitution works where the wa-ter resource-demand budgets are estimated. The assessmentof the monthly flows in these points was accomplished bymeans of a correlation between the stations at the outletsof a reference basin and gauging stations in the analyzedbasins. The correlation function was calculated on the basisof 40–50 year records at the gauging stations located in theanalyzed basins. It is assumed that the correlation functionbetween discharges in different points of the analyzed basinsfor the current climate will be valid in a 2xCO2 climate.

Taking into account the monthly flow estimated on thebasis of future demands for agriculture, industry, and wa-ter supplies under climate change conditions, a water bal-ance ‘resource-demand’ model was applied. This model(Amaftiesei, 1988) allowed us to simulate the storage reser-voir exploitation according to pre-established scenarios. Foreach time step the model calculates the balance equation foreach storage reservoir in an upstream-to-downstream cas-cade. Application of this model resulted in the assessment ofvulnerability of three studied basins. Taking into account theexisting water management, the Arges River basin appearsto be the only one sensitive to climate change. Moreover,it is one of the most important water basins from an eco-nomic, social, and environmental point of view. Bucharest,the capital of Romania, with about two million inhabitants,is located in this basin.

The adaptation options considered for the Arges basininclude structural and non-structural measures. To establishstructural measures, 15 combinations of the most econom-ical measures were analyzed for a number of reservoirs andwater diversion works that could be undertaken in the future.Finally, on the basis of economic criteria three sets of com-binations were selected. In regard to structural measures,new operational rules for the strategic Vidraru reservoir wereexamined. Time evolutions of the users’ demands were com-bined with gradual reductions in water losses in the watersupply network.

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Conclusions

The results show that climate change could induce signific-ant effects on different environmental and economic sectorsof Romania. The ones most affected appear to be maizecrops in the southern part of the country, forest species grow-ing in the plains and hilly zones, and water resources wheredemands could exceed their availability, as in the case ofthe Arges River basin. In order to increase the reliabilityof these estimations, it is necessary to apply the outputs ofmore advanced GCMs and to improve models for describ-ing the physical and biophysical processes specific to impactassessment.

Acknowledgements

All GCM outputs were supplied by the US National Centerfor Atmospheric Research. The software DSSAT v3.0 andthe computer codes associated with Holdridge and JABOWAmodels were presented by the US Country Studies Program.We acknowledge the Management Team of this programfor excellent their collaboration. The main part of the res-ults represented in this paper have been obtained withinthe framework of the National Country Study on ClimateChange in Romania, developed under the US Country StudyProgram. We are very grateful to reviewers, particularly, tothose who assisted us in editing the paper in proper English.

References

Amaftiesei R., 1988: ARTIZAN- program for simulating the exploiting ofwater resource systems, ICPGA (Internal Report).

Balteanu D., Ozenda P., Kuhn M., Kerschuner H., Tranquillini W. andBortenschlager S., 1987: Volume G: Impact analysis of climatic changein the Central European mountain ranges, European Workshop on in-terrelated bioclimatic and land use changes, Noordwukerhout, TheNetherlands.

Botkin D.B., 1993: Forest dynamics. An ecological model. Oxford Univer-sity Press.

Busuioc A., 1996: Estimation of the effect of CO2 concentration doub-ling upon winter air temperature in Romania. Romanian Journal ofMeteorology 3(1), 23–33.

Cuculeanu V. (ed.), 1997: Country study on climate change in Romania.Element 2: Vulnerability assessment and adaptation options. FinalReport, August, US Country Studies Program.

Cuculeanu V., Marica A. and Simota C., 1999: Climate change impact onagricultural crops and adaptation options in Romania. Climate Research12, 153–160.

Godwin D.C., Ritchie J.T., Singh U. and Hunt L., 1989: A user’s guideto CERES-Wheat v.2.10. International Fertilizer Development Center,Muscle Shoals, AL.

Hansen, J., Russell G., Rind D., Stone P., Lucis A., Lebedeff S., RuedyR. and Travis L., 1983: Efficient Three-dimensional global models forclimate studies: Model I and II. Monthly Weather Review III: 609–662.

Holdridge L.R., 1947: Determination of world plant formation from simpleclimate data. Science 105: 367–368.

Houghton J.T., Meira Filho L.G., Callander B.A., Harris N., KattenbergA. and Maskell K. (eds), 1995 Climate Change, The Science of ClimateChange, IPCC, Cambridge University Press, Cambridge, U.K.

Mitchell J.F.B., Manabe S., Tokioka T. and Meleshko V., 1990: Equilibriumclimate change and its implications for the future. In: Thoughton J., Jen-kins G.J. and Ephraums J.J. (eds), Climate Change, The IPCC ScientificAssessment, pp. 131–172. Cambridge University Press, Cambridge,U.K.

Phillips T.J., 1994: A summary documentation of the AMIP models, ReportNo. 18, PCMDI. Lawrence Livermore National Laboratory, Livermore,CA, UCRL-ID-116384, 343 pp.

Poster J.R., 1993: ARFCWHEAT 2 – A model of the growth and develop-ment of wheat incorporating responses to water and nitrogen. EuropeanJournal of Agronomy 2(2): 69–82.

Ritchie J.T., Singh U., Godwin D.C. and Hunt L., 1989: A user’s guideto CERES-Maize v.2.10, International Fertilizer Development Center,Muscle Shoals, AL.

Rounsevell M.D.A., Loveland P.J., Mayr T.R., Armstrong A.C., De la RosaD., Legros J.P., Simota C. and Sobczuk H., 1996: ACCESS – A spatiallydistributed soil water and crop development model for climate changeresearch. Aspects of Applied Biology 45.

Serban P., 1987: The VIDRA flood simulation and forecasting model.Meteorology and Hydrology 7(2): 3–43.

Tsuji G.I., Uehara G. and Balas S. (eds), 1994: DSSAT v3.0, Vol.1, 2 and3. University of Hawaii, Honolulu.

UNFCCC-United Nations Framework Convention on Climate ChangePublished by UNEP/WMO Information Unit on Climate Change

U.S. Country Studies Management Team (PO-63), 1994: Guidance for Vul-nerability and Adaptation Assessment, U.S. Country Studies Program,Washington D.C., U.S.A.